# document

id: 1690b9c5d5476f405f5b5f374e49a682
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 1182
content:
"In summary, global hydrological models project a  larger fraction \r\nof land areas to be affected by an increase in river floods than by \r\na  decrease in river floods (medium confidence). There is medium \r\nconfidence that river floods will increase in the western Amazon, \r\nthe Andes, and south-eastern and northern Asia. Regional changes \r\nin river floods are more uncertain than changes in pluvial floods \r\nbecause complex hydrological processes and forcings are involved, \r\nincluding land cover change and human water management."


id: 1e887353f4af1d3aab957e28de10c2f
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 2575
content:
"some regions (SREX, Chapter 3; Koster et al., 2011; Gimeno et al., \r\n2012; Taylor et al., 2012; Guillod et al., 2015; Tuttle and Salvucci, \r\n2016; Santanello Jr. et al., 2018; Haslinger et al., 2019; Herrera\u0002Estrada et al., 2019). The sign of the feedbacks can be either positive \r\nor negative, as well as local or non-local (Taylor et al., 2012; Guillod \r\net al., 2015; Tuttle and Salvucci, 2016). Earth system models (ESMs) \r\ntend to underestimate non-local negative soil-moisture-precipitation \r\nfeedbacks (Taylor et al., 2012) and also show high variations in their \r\nrepresentation in some regions (Berg et al., 2017b). Soil-moisture-\r\nprecipitation feedbacks contribute to changes in precipitation \r\nin climate model projections in some regions, but ESMs display \r\nsubstantial uncertainties in their representation, and there is thus \r\nonly low confidence in these contributions (Berg et al., 2017b; Vogel \r\net al., 2017, 2018). "


id: fd8262b482d6e3f3fc5e61577c5a53ed
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 41957
content:
"exclusively on AED metrics overestimate changes in soil moisture and \r\nrunoff deficits. Nevertheless, AED also directly impacts hydrological \r\ndrought, as ET from surface waters is not limited (Wurbs and Ayala, \r\n2014; Friedrich et al., 2018; Hogeboom et al., 2018; K. Xiao et al., 2018), \r\nand this effect increases under climate change projections (W. Wang \r\net al., 2018; Althoff et al., 2020). In addition, high AED increases crop \r\nwater consumptions in irrigated lands (Garcia-Garizabal et al., 2014), \r\ncontributing to intensifying hydrological droughts downstream (Fazel \r\net al., 2017; Vicente-Serrano et al., 2017)."


id: a92f6a743fd8e30ba6c36c7582afe94e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 26990
content:
"The influence of AED on drought depends on the drought type, \r\nbackground climate, the environmental conditions and the moisture \r\navailability (Hobbins et al., 2016, 2017; Vicente-Serrano et al., \r\n2020a). This influence also includes effects not related to increased \r\nET. Under low soil moisture conditions, increased AED increases \r\nplant stress, enhancing the severity of agricultural and ecological \r\ndroughts (Williams et al., 2013; Allen et al., 2015; McDowell et al., \r\n2016; Grossiord et al., 2020). Moreover, high VPD impacts overall \r\nplant physiology; it affects the leaf and xylem safety margins, and \r\ndecreases the sap velocity and plant hydraulic conductance (Fontes \r\net al., 2018). VPD also affects the plant metabolism of carbon and, \r\nif prolonged, it may cause plant mortality via carbon starvation \r\n(Breshears et al., 2013; Hartmann, 2015). Drought projections based "


id: c36e70ee6953e82b56c0e6959cfb327c
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 31657
content:
"Soil moisture directly affects plant water stress and ET. Soil moisture \r\nis the primary factor that controls xylem hydraulic conductance  - \r\nthat is, water uptake in plants (Sperry et al., 2016; Hayat et al., 2019; \r\nX. Chen et al., 2020). For this reason, soil moisture deficits are the \r\nmain driver of xylem embolism, the primary cause of plant mortality "


id: 2d0d932e5ff59895742eaa3677023e1f
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 5202
content:
"exceptions). These demand/supply indices are not intended to be \r\nmetrics of soil moisture, streamflow or vegetation water stress. \r\nBecause of their reliance on precipitation and AED, they are mostly \r\nrelated to the actual water balance in humid regions, in which ET is \r\nnot limited by soil moisture and tends towards AED. In water-limited \r\nregions and in dry  periods everywhere, they constitute an upper \r\nbound for overall  water-balance  deficits  (e.g.,  of surface waters) \r\nbut are also related to  conditions  conducive  to vegetation stress, \r\nparticularly under soil moisture limitation (Section 11.6.1.2). "


id: c78ed40973c1b00e442876fbd0501a89
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 32419
content:
"This Chapter assesses changes in meteorological drought, \r\nagricultural and ecological droughts, and hydrological droughts. \r\nPrecipitation-based indices are used for the estimation of changes \r\nin meteorological droughts, such as the Standardized Precipitation \r\nIndex (SPI) and the number of consecutive dry days (CDD). Changes \r\nin total soil moisture and soil moisture-based drought events are \r\nused for the estimation of changes in agricultural and ecological \r\ndroughts, complemented by changes in surface soil moisture, water\u0002balance estimates (precipitation minus ET), and SPEI-PM and PDSI\u0002PM. For hydrological droughts, changes in low flows are assessed, \r\nsometimes complemented by changes in mean streamflow."


id: 714a73fb515bac6d55a8ac3ae0be1b2b
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 17193
content:
"In summary, different drought types exist and they are associated \r\nwith different impacts and respond differently to increasing \r\ngreenhouse gas concentrations. Precipitation deficits and changes in \r\nevapotranspiration govern net water availability. A lack of sufficient \r\nsoil moisture, sometimes amplified by increased atmospheric \r\nevaporative demand, result in agricultural and ecological drought. Lack \r\nof runoff and surface water result in hydrological drought. Drought \r\nevents are the result of dynamic and/or thermodynamic processes, \r\nwith thermodynamic processes being the main driver of drought \r\nchanges under human-induced climate change (high confidence). "


id: d32ac6fee0c61a5e63bff9dc7f7d0a50
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 34496
content:
"Evidence on observed drought trends was limited at the time of SREX \r\n(Chapter 3) and AR5 (Chapter 2). The SREX concluded: 'There is medium \r\nconfidence that since the 1950s some regions of the world have \r\nexperienced a trend to more intense and longer droughts, in particular \r\nin southern Europe and west Africa, but in some regions droughts have \r\nbecome less frequent, less intense, or shorter, for example, in Central \r\nNorth America and north-western Australia.' The assessment at the \r\ntime did not distinguish between different drought types. This Chapter \r\nincludes numerous updates on observed drought trends, associated \r\nwith extensive new literature and longer datasets since AR5. "


id: ea8ee5ced8b01e7fcf712dd83f4c0992
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 38627
content:
"In several regions, AED increases have intensified recent drought \r\nevents (Williams et al., 2014, 2020; Seager et al., 2015b; Basara \r\net al., 2019; Garcia-Herrera et al., 2019), enhanced vegetation stress \r\n(Allen et al., 2015; Sangines de Carcer et al., 2018; Yuan et al., 2019), \r\nor contributed to the depletion of soil moisture or runoff through \r\nenhanced ET (high confidence) (Teuling et al., 2013; Padron et al., 2020). \r\nTrends in pan evaporation measurements and Penman-Monteith AED "


id: f0a7c1a646aa3553049dffb9089eeb95
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 39713
content:
"Evidence from observed or observations-derived trends in soil \r\nmoisture and precipitation minus ET, are combined with evidence \r\nfrom SPEI and PDSI-PM studies to derive regional assessments of \r\nchanges in agricultural and ecological droughts (Section 11.9). This \r\nassessment is summarized in Section 11.6.2.6."


id: 671589181340a9e71dc45105446ddf7a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
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vector_id: 15406
content:
"Globally, trends in SPEI-PM and PDSI-PM suggest slightly higher \r\nincreases of drought frequency and severity in regions affected by \r\ndrying over the last decades in comparison to the SPI (Dai and Zhao, \r\n2017; Spinoni et al., 2019; Song et al., 2020), mainly in regions of \r\nWestern and Southern Africa, the Mediterranean and East Asia \r\n(Figure 11.17), which is consistent with observed soil moisture trends \r\n(Section 11.6.2.3). These indices suggest that AED has contributed to "


id: 5daca5feeb38bbb5720353790bc2cb1a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 13775
content:
"There is evidence based on streamflow records of increased \r\nhydrological droughts in East Asia (D. Zhang et al., 2018) and \r\nsouthern Africa (Gudmundsson et al., 2019). In areas of Western \r\nand Central Europe and Northern Europe, there is no evidence of \r\nchanges in the severity of hydrological droughts since 1950 based on "


id: ae69e7e909de258122cfd8814ca210b3
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
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index: climate_gpt_v2
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content:
"There is only limited evidence on the evaluation of AED in state\u0002of-the-art ESMs, which is performed on externally computed AED, \r\nbased on model output (Scheff and Frierson, 2015; Liu and Sun, \r\n2016, 2017). An evaluation of average AED in 17 CMIP5 ESMs for \r\n1981-1999 based on potential evaporation show that the models' \r\nspatial patterns resemble the observations, but the magnitude of \r\npotential evaporation displays strong divergence among models \r\nglobally and regionally (Scheff and Frierson, 2015). The evaluation \r\nof AED in 12  CMIP5 ESMs with pan evaporation observations in \r\nEast Asia for 1961-2000 (Liu and Sun, 2016, 2017) show that \r\nthe ESMs capture seasonal cycles well, but that regional AED \r\naverages are underestimated due to biases in the meteorological \r\nvariables controlling the aerodynamic and radiative components \r\nof AED. The CMIP5 ESMs also show a  strong underestimation of \r\natmospheric drying trends compared to reanalysis data (Douville and \r\nPlazzotta, 2017)."


id: e4bff78582dfd04c9899e73704920830
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 37526
content:
"In summary, there is high confidence that AED has increased on \r\naverage on continents, contributing to increased ET and resulting \r\nwater stress during periods with precipitation deficits, in particular \r\nduring dry seasons. There is medium confidence in increases in \r\nprecipitation deficits in a few regions of Africa and South America. \r\nBased on multiple evidence, there is medium confidence that \r\nagricultural and ecological droughts have increased in several \r\nregions on all continents (WAF, CAF, WSAF, ESAF, WCA, ECA, EAS, \r\nSAU, MED, WCE, NES: medium confidence), while there is only \r\nmedium confidence in decreases in one AR6 region (NAU). More \r\nsevere hydrological droughts are found in fewer regions (MED: high \r\nconfidence; WAF, EAS, SAU: medium confidence). "


id: e95f36b0d9641fdd71474b264ea91a2a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
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vector_id: 38415
content:
"The performance of climate models for representing soil moisture \r\ndeficits shows more uncertainty than for precipitation deficits since, \r\nin addition to the uncertainties related to cloud and precipitation \r\nprocesses, there is uncertainty related to the representation of \r\ncomplex soil hydrological and boundary-layer processes (van den \r\nHurk et al., 2011; Lu et al., 2019; Quintana-Segui et al., 2020). "


id: 7ba573d7d1fb66a4bebcb14f4e94b44e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
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content:
"Another limitation is the lack of observations, particularly for soil \r\nmoisture, in most regions (Section  11.6.2.3) and the paucity of \r\nland surface property data to parametrize land surface models, in \r\nparticular soil types, soil properties and depth (Xia et al., 2015). The \r\nspatial resolution of models is an additional limitation since the \r\nrepresentation of some land-atmosphere feedbacks and topographic \r\neffects requires detailed resolution (Nicolai-Shaw et al., 2015; Van \r\nDer Linden et al., 2019). In addition to climate models, land surface \r\nand hydrological models are also used to derive historical and \r\nprojected trends in soil moisture and related land water variables \r\n(Albergel et al., 2013; Cheng et al., 2015; Gu et al., 2019b; Padron \r\net al., 2020; Markonis et al., 2021; Pokhrel et al., 2021). "


id: c072ddd1e3298afe0cf523ee8e89ae84
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 31157
content:
"Cook et al., 2020). There is still limited evidence to assess whether \r\nthere are substantial differences in model performance in the two \r\nensembles, but improvements in modelling aspects relevant for soil \r\nmoisture have been reported for precipitation (Section 11.6.3.2), and \r\na better performance has been found in CMIP6 for the representation \r\nof long-term trends in soil moisture in continental USA (Yuan et al., \r\n2021). Despite the mentioned model limitations, the representation \r\nof soil moisture processes in ESMs uses physical and biological \r\nunderstanding of the underlying processes, which can well represent \r\nthe temporal anomalies associated with temporal variability and \r\ntrends in climate. In summary, there is medium confidence in the \r\nrepresentation of soil moisture deficits in ESMs and related land \r\nsurface and hydrological models. "


id: 9b8e27fbdef20da75d9ad25e1503f3a7
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 24620
content:
"A number of studies have analysed the ability of models to capture \r\ndrought severity and trends based on climatic drought indices. Given \r\nthe limitations of ESMs in reproducing the dynamic of precipitation \r\ndeficits and AED (11.6.3.1, 11.6.3.2), atmospheric-based drought \r\nindices derived from ESM data for these two variables are also \r\naffected by uncertainties and biases. A  comparison of historical \r\ntrends in PDSI-PM for 1950-2014 derived from CMIP3 and CMIP5, \r\nwith respective estimates derived from observations (Dai and \r\nZhao, 2017) show a  similar behaviour at global scale (long-term \r\ndecrease), but low spatial agreement in the trends except in a few \r\nregions (Mediterranean, South Asia, north-western USA). In future \r\nprojections, there is an important spread in PDSI-PM and SPEI-PM \r\namong different models (Cook et al., 2014a). "


id: 293f0eb7ae2e43b23c21c6d6df2c4f58
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
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index: climate_gpt_v2
vector_id: 4469
content:
"For future projections, the spread of soil moisture outputs among \r\ndifferent ESMs is more important than internal variability and \r\nscenario uncertainty, and the bias is strongly related to the sign of \r\nthe projected change (Ukkola et al., 2018; Lu et al., 2019; Selten et al., \r\n2020). The CMIP5 ESMs that project more drying and warming in mid\u0002latitude regions show a substantial bias in soil-moisture-temperature \r\ncoupling (Donat et al., 2018; Vogel et al., 2018). Although CMIP6 and \r\nCMIP5 simulations for soil moisture changes are similar overall, some \r\ndifferences are found in projections in a few regions (Section 11.9; "


id: 8976927a18c46052f92d279da990229
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 21360
content:
"in the attribution of observed short-term changes in meteorological \r\ndroughts in the region (Section 11.9). In North America, the human \r\ninfluence on precipitation deficits is complex (Wehner et al., 2017), \r\nwith low confidence in the attribution of long-term changes in \r\nmeteorological drought in AR6 regions (Section 11.9; Lehner et al., \r\n2018). In Africa there is low confidence that human influence has \r\ncontributed to the observed long-term meteorological drought \r\nincrease in Western Africa (Sections 11.9 and 10.6.2). There is low \r\nconfidence in the attribution of the observed increasing trends in \r\nmeteorological drought in East Southern Africa, but evidence that \r\nhuman-induced climate change has affected recent meteorological \r\ndrought events in the region (Section 11.9). "


id: 935c129a78e063cfc8d3c0529e9978d
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 23131
content:
"The performance of ESMs used to assessed changes in variables \r\nrelated to meteorological droughts, agricultural and ecological \r\ndroughts, and hydrological droughts, shows the presence of biases \r\nand uncertainties compared to observations, but there is medium \r\nconfidence in their overall performance for assessing drought \r\nprojections given process understanding. Given the substantial inter\u0002model spread documented for all related variables, the consideration \r\nof multi-model projections increases the confidence of model-based \r\nassessments, with only low confidence in assessments based on \r\nsingle models. "


id: 61a38ab5f46f751a1d5c77be975bb3c7
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 14464
content:
"In summary, the evaluation of ESMs, land surface and hydrological \r\nmodels for the simulation of droughts is complex, due to the regional \r\nscale of drought trends, their overall low signal-to-noise ratio, and the \r\nlack of observations in several regions, in particular for soil moisture \r\nand streamflow. There is medium confidence in the ability of ESMs \r\nto simulate trends and anomalies in precipitation deficits and AED, \r\nand also medium confidence in the ability of ESMs and hydrological \r\nmodels to simulate trends and anomalies in soil moisture and \r\nstreamflow deficits, on global and regional scales. "


id: f648b139f8e849ca28c552a65b486a1c
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 40694
content:
"some events. For example, anthropogenic warming contributed to \r\nthe 2014 drought in North Eastern Africa by increasing east African \r\nand west Pacific temperatures, and increasing the gradient between \r\nstandardized western and central Pacific SSTs, causing reduced \r\nrainfall (Funk et al., 2015a). As different methodologies, models \r\nand data sources have been used for the attribution of precipitation \r\ndeficits, Angelil et al. (2017) re-examined several events using \r\na  single analytical approach and climate model and observational \r\ndatasets. Their results showed a  disagreement in the original \r\nanthropogenic attribution in a number of precipitation deficit events, \r\nwhich increased uncertainty in the attribution of meteorological \r\ndroughts events. "


id: 2cd7abb68b8f11317c9e2a32a2d8f569
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 5157
content:
"low, mean and high flows, while simulated effects of water and land \r\nmanagement do not suffice to reproduce the observed spatial pattern \r\nof trends (Gudmundsson et al., 2021). Regional studies also suggest \r\nthat climate trends have been dominant compared to land use and \r\nhuman water management for explaining trends in hydrological \r\ndroughts in some regions, for instance in Ethiopia (Fenta et al., 2017), \r\nChina (Xie et al., 2015), and North America for the Missouri and \r\nColorado basins, as well as in California (Shukla et al., 2015; Udall \r\nand Overpeck, 2017; Ficklin et al., 2018; K. Xiao et al., 2018; Glas \r\net al., 2019; Martin et al., 2020; Milly and Dunne, 2020)."


id: b0c6752616bc11bb95136e111fdcf48e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 28329
content:
"It is often difficult to separate the role of climate trends from \r\nchanges in land use, water management and demand for changes \r\nin hydrological deficits, especially on a  regional scale. However, \r\na global study based on a recent multi-model experiment with global \r\nhydrological models and covering several AR6 regions suggests \r\na  dominant role of anthropogenic radiative forcing for trends in "


id: 186faa7cd6f58e6257134c763d94a83a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 1510
content:
"2018). In particular, this effect was identified to be the main driver of \r\nthe intensification of the 2017 drought that affected south-western \r\nEurope, and was attributed to the human forcing (Garcia-Herrera \r\net al., 2019). Nangombe et al. (2020) and L. Zhang et al. (2020) \r\nconcluded from differences between precipitation and AED that \r\nanthropogenic forcing contributed to the 2018 droughts that affected \r\nsouthern Africa and south-eastern China, respectively, principally as \r\nconsequence of the high AED that characterized these two events."


id: 60fd4e3db69b8f8287e0657c4d54cd89
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
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index: climate_gpt_v2
vector_id: 14358
content:
"The SREX (Chapter 3) asssessed with medium confidence projections \r\nof increased drought severity in some regions, including southern \r\nEurope and the Mediterranean, central Europe, central America and \r\nMexico, north-east Brazil, and southern Africa, and low confidence\r\nelsewhere given large inter-model spread. The AR5 (Chapters 11 and \r\n12) also assessed large uncertainties in drought projections at the "


id: 9359700dca00ac5c28cd551796cfc13e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 23129
content:
"In Africa, a  strong increase in the length of dry spells (CDD) is \r\nprojected for 4degC of global warming over most of the continent, with \r\nthe exception of central and eastern Africa (Section 11.9; Sillmann \r\net al., 2013a; Giorgi et al., 2014; Han et al., 2019). In West Africa, \r\na strong reduction of precipitation is projected (Sillmann et al., 2013a; "


id: c97e11e32c4f41784d297950866ab7e4
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 32771
content:
"Diallo et al., 2016; Akinsanola and Zhou, 2019; Han et al., 2019; Todzo \r\net al., 2020) at 4degC of global warming, and CDD would increase with \r\nstronger global warming levels (Klutse et al., 2018). The regions most \r\nstrongly affected are southern Africa (ESAF, WSAF) (Nangombe et al., \r\n2018; Abiodun et al., 2019) and northern Africa (part of the MED \r\nregion), with increases in meteorological droughts already at 1.5degC \r\nof global warming, and further increases with increasing global \r\nwarming (Section  11.9). CDD is projected to increase more in the \r\nsouthern Mediterranean (northern Africa) than in the northern part of \r\nthe Mediterranean region (Lionello and Scarascia, 2020)."


id: 1062c4dea4afec19fe0fa227feae5d19
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 71
content:
"The overall evidence suggests an increase in meteorological drought \r\nat 4degC in the WCE region (medium confidence) (Section 11.9). "


id: a03fa5ff23d9ebdacd07fbd7c6f7fd88
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 25404
content:
"Overall, based on global and regional studies, several hot spot \r\nregions are identified, displaying more frequent and severe \r\nmeteorological droughts with increasing global warming, including \r\nseveral AR6 regions at 1.5degC (WSAF, ESAF, SAU, MED, NES) and \r\n2degC of global warming (WSAF, ESAF, EAU, SAU, MED, NCA, SCA, \r\nNSA, NES) (Section  11.9). At 4degC of global warming, there is also \r\nconfidence in increases in meteorological droughts in further regions \r\n(WAF, WCE, ENA, CAR, NWS, SAM, SWS, SSA; Section 11.9), showing \r\na geographical expansion of meteorological drought with increasing \r\nglobal warming. Only few regions are projected to have less intense \r\nor frequent meteorological droughts (Section 11.9)."


id: 15ac4cef78ffd2abb250baf4f54f9d2a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 1028
content:
"In Asia, most AR6 regions show low confidence in projected changes \r\nin meteorological droughts at 1.5degC and 2degC of global warming, with \r\na few regions displaying a decrease in meteorological droughts at \r\n4degC of global warming (RAR, ESB, RFE, ECA; medium confidence), \r\nalthough there is a  projected increase in meteorological droughts \r\nin South East Asia at 4degC (medium confidence) (Section  11.9). In \r\nSouth East Asia, an increasing frequency of precipitation deficits is \r\nprojected as a consequence of an increasing frequency of extreme \r\nEl Nino (Cai et al., 2014b, 2015, 2018). "


id: 4b61a390d106c1131e139920f49e703b
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 10510
content:
"Effects of AED on droughts in future projections is under debate. \r\nThe CMIP5 models project an increase in AED over the majority of \r\nthe world with increasing global warming, mostly as a consequence \r\nof strong VPD increases (Scheff and Frierson, 2015; Vicente-Serrano \r\net al., 2020a). However, ET is projected to increase less than AED in \r\nmany regions due to plant physiological responses related to: i) CO2\r\neffects on plant photosynthesis; and ii) soil moisture control on ET. "


id: f5560d1280aa7817a1a80e2162412aad
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 40532
content:
"An increase in the frequency, duration and intensity of meteorological \r\ndroughts is projected in south-west, south and east Australia (Kirono \r\net al., 2020; Shi et al., 2020). In Canada and most of the USA, based on \r\nthe SPI, Swain and Hayhoe (2015) identified drier summer conditions \r\nin projections over most of the region, and there is a consistent signal \r\ntoward an increase in duration and intensity of droughts in southern \r\nNorth America (Pascale et al., 2016; Escalante-Sandoval and Nunez\u0002Garcia, 2017). In California, more precipitation variability is projected, \r\ncharacterized by increased frequency of consecutive drought and \r\nhumid periods (Swain et al., 2018). "


id: e7a0ba68c124a0aca6fa75796a76443f
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 38057
content:
"Substantial increases in meteorological drought are projected in \r\nEurope, in particular in the Mediterranean region, already at 1.5degC of \r\nglobal warming (Section 11.9). In southern Europe, model projections \r\ndisplay a consistent drying among models (Russo et al., 2013; Hertig \r\nand Tramblay, 2017; Guerreiro et al., 2018a; Raymond et al., 2019). In \r\nWestern and Central Europe there is some spread in CMIP5 projections, \r\nwith some models projecting very strong drying, and others close to \r\nno trend (Vogel et al., 2018), although CDD is projected to increase \r\nin CMIP5 projections under the RCP 8.5 scenario (Hari et al., 2020). "


id: 8d1962783e0c60e46ecad904bdfb7403
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 22014
content:
"Another mechanism reducing the ET response to increased AED in \r\nprojections is the control of soil moisture limitations on ET, which \r\nleads to reduced stomatal conductance under water stress (Berg and \r\nSheffield, 2018; Stocker et al., 2018; Zhou et al., 2021). This response \r\nmay be further amplified through VPD-induced decreases in stomatal \r\nconductance (Anderegg et al., 2020). However, the decreased \r\nstomatal conductance in response to soil moisture limitation and \r\nenhanced CO2 would further enhance AED (Sherwood and Fu, 2014; \r\nBerg et al., 2016; Teuling, 2018; Miralles et al., 2019), whereby the \r\noverall effects on AED in ESMs are found to be of similar magnitude \r\nfor soil moisture limitation and CO2 physiological effects on stomatal \r\nconductance (Berg et al., 2016). Increased AED is thus both a driver \r\nand a  feedback with respect to changes in ET, complicating the \r\ninterpretation of its role on drought changes with increasing CO2\r\nconcentrations and global warming. "


id: 6c3867a136f815a71549dcdc17e51318
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 16334
content:
"Areas with projected soil moisture decreases do not fully coincide \r\nwith areas that have projected precipitation decreases, although \r\nthere is substantial consistency in the respective patterns (Dirmeyer \r\net al., 2013; Berg and Sheffield, 2018). However, there are more \r\nregions affected by increased soil moisture deficits (Figure 11.19) than \r\nprecipitation deficits (Figures 2a,b,c and Cross-Chapter Box  11.1) \r\nas  a  consequence of enhanced AED and the associated increased \r\nET, as highlighted by some studies (Orlowsky and Seneviratne, 2013; \r\nDai et al., 2018; Section  8.2.2.1). Moisture in the top soil layer is \r\nprojected to decrease more than precipitation at all warming levels "


id: 3e22a32f6ba82dc0ee2677dc3cf2d93b
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 8104
content:
"levels, show contrasting trends (Figure 11.19). In the boreal winter \r\nin the Northern Hemisphere, the areas affected by drying show high \r\nagreement with those characterized by an increase in meteorological \r\ndrought projections (Figures 8.14 and 12.4). On the contrary, in the \r\nboreal summer, the drought frequency increases worldwide in \r\ncomparison to meteorological drought projections, with large areas \r\nof the Northern Hemisphere displaying a high signal-to-noise ratio \r\n(low spead between models). This stresses the dominant influence \r\nof ET (as a result of increased AED) in intensifying agricultural and \r\necological droughts in the warm season in many locations, including \r\nmid- to high latitudes."


id: 925529450e70842f026984ec900e3ed6
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 22965
content:
"4degC global warming (Rhoades et al., 2018). This decline would cause \r\nless predictable hydrological droughts in snowmelt-dominated areas \r\nof North America (Livneh and Badger, 2020). The exact magnitude \r\nof the influence of higher temperatures on snow-related droughts \r\nis, however, difficult to estimate (Mote et al., 2016), since the \r\nstreamflow changes could affect the timing of peak streamflows but \r\nnot necessarily their magnitude. In addition, projected changes in \r\nhydrological droughts downstream of declining glaciers can be very \r\ncomplex to assess (Chapter 9, see also SROCC)."


id: dba9279958c6dda0f9936ba7b79f342b
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 35936
content:
"Increased soil moisture limitation and associated changes in droughts \r\nare projected to lead to increased vegetation stress affecting the \r\nglobal land carbon sink in ESM projections (Green et al., 2019), with \r\nimplications for projected global warming (Cross-Chapter Box  5). \r\nThere is high confidence that the global land sink will become less \r\nefficient due to soil moisture limitations and associated agricultural \r\nand ecological drought conditions in some regions in higher-emissions \r\nscenarios, specially under global warming levels above 4degC; however, \r\nthere is low confidence in how these water cycle feedbacks will play \r\nout in lower-emissions scenarios (at 2degC global warming or lower; \r\nCross-Chapter Box 5.1)."


id: 1656f2af0bd9c30e4896f27f82c75336
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 1148
content:
"Regions dependent on mountainous snowpack as a  temporary \r\nreservoir may be affected by severe hydrological droughts in \r\na  warmer world. In the southern European Alps, both winter and \r\nsummer low flows are projected to be more severe, with a  25% \r\ndecrease in the 2050s (Vidal et al., 2016). In western USA, a 22% \r\nreduction in winter snow water equivalent is projected at around 2degC \r\nof global warming, with a further decrease of a 70% reduction at "


id: 72447f15cfb5ba21483af7f58e7962bb
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 17346
content:
"Global tendencies towards more severe and frequent agricultural and \r\necological drought conditions are identified in future projections when \r\nfocusing on atmospheric-based drought indices such as the PDSI-PM \r\nor the SPEI-PM. They expand the spatial extent of drought conditions \r\ncompared to meteorological drought to most of North America, \r\nEurope, Africa, Central and East Asia and Southern Australia (Cook "


id: 35a4fc654cd7327ecff5c494ba48854c
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 6691
content:
"et al., 2014a; Chen and Sun, 2017a, b; Gao et al., 2017b; Lehner et al., \r\n2017; Zhao and Dai, 2017; Dai et al., 2018; Naumann et al., 2018; \r\nPotopova et al., 2018; Gu et al., 2020; Vicente-Serrano et al., \r\n2020c; Dai, 2021). Projections in PDSI-PM and SPEI-PM are used to \r\ncomplement total soil moisture projections in assessing projected \r\nchanges in agricultural and ecological drought (Section 11.9)."


id: 40ac9acb6203625ae75e5c99d8b8dc2
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 8563
content:
"Extreme storms, such as tropical cyclones (TCs), extratropical cyclones \r\n(ETCs), and severe convective storms often have substantial societal \r\nimpacts. Quantifying the effect of climate change on extreme storms \r\nis challenging, partly because extreme storms are rare, short-lived, \r\nand local, and individual events are largely influenced by stochastic \r\nvariability. The high degree of random variability makes detection and \r\nattribution of extreme storm trends more uncertain than detection \r\nand attribution of trends in other aspects of the environment in \r\nwhich the storms evolve (e.g.,  larger-scale temperature trends). \r\nProjecting changes in extreme storms is also challenging because of \r\nconstraints in the models' ability to accurately represent the small\u0002scale physical processes that can drive these changes. Despite the \r\nchallenges, progress has been made since AR5."


id: 8dbfbc84c2f2589dfb6587e84a563e8f
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 22130
content:
"In summary, more regions are affected by increases in agricultural \r\nand ecological droughts with increasing global warming (high \r\nconfidence). New evidence strengthens the SR1.5 conclusion that \r\neven relatively small incremental increases in global warming \r\n(+0.5degC) cause a  worsening of droughts in some regions (high \r\nconfidence). Some regions are projected to be affected by more \r\nsevere agricultural and ecological droughts at 1.5degC of global \r\nwarming (MED, WSAF, ESAF, SAU, NSA, SAM, SSA, can; medium \r\nconfidence). A larger number of regions are projected to be affected \r\nby more severe agricultural and ecological droughts at 2degC of global \r\nwarming, including MED, WSAF, SAM and SSA (high confidence), \r\nand ESAF, MDG, EAU, SAU, SCA, CAR, NSA, NES, SWS, WCE, NCA, "


id: d72cde354da20715d8a2d131c1450b62
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 35165
content:
"will increase with continued greenhouse gas warming; it is likely that \r\nthe global frequency of TCs will either decrease or remain essentially \r\nunchanged, while it is more likely than not that the frequency of the \r\nmost intense storms will increase substantially in some ocean basins; \r\nthere is low confidence in projections of small-scale phenomena such \r\nas tornadoes and hail storms; and there is medium confidence that \r\nthere will be a reduced frequency and a poleward shift of mid-latitude \r\ncyclones due to future anthropogenic climate change. "


id: a872c8187ef4cb7ad39ff85c2b1034a8
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 26843
content:
"Identifying past trends in TC metrics remains a challenge due to the \r\nheterogeneous character of the historical instrumental data, which \r\nare known as 'best-track' data (Schreck et al., 2014). There is low \r\nconfidence in most reported long-term (multi-decadal to centennial) \r\ntrends in TC frequency- or intensity-based metrics due to changes in \r\nthe technology used to collect the best-track data. This should not be \r\ninterpreted as implying that no physical (real) trends exist, but rather \r\nas indicating that either the quality or the temporal length of the \r\ndata is not adequate to provide robust trend detection statements, \r\nparticularly in the presence of multi-decadal variability. "


id: 25846edf4b0001fa6d8173febcfbd3b0
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 3786
content:
"The SREX, AR5, SROCC, and SR1.5, do not provide assessments of \r\nthe atmospheric rivers, and SROCC and SR1.5 do not assess severe \r\nconvective storms and extreme winds. This section assesses the state \r\nof knowledge on the four phenomena of TCs, ETCs, severe convective \r\nstorms, and extreme winds. Atmospheric rivers are addressed \r\nin Chapter  8. In this respect, this assessment closely mirrors the \r\nSROCC assessment of TCs and ETCs, while updating SREX and AR5 \r\nassessments of severe convective storms and extreme winds."


id: 50be832a57a87fd54cb0786eeeb371ae
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 11480
content:
"The genesis, development, and tracks of TCs depend on conditions \r\nof the larger-scale circulations of the atmosphere and ocean \r\n(Christensen et al., 2013). Large-scale atmospheric circulations, such \r\nas the Hadley and Walker circulations and the monsoon circulations \r\ncan significantly affect TCs, as can internal variability acting on various \r\ntime scales (Annex IV), from intra-seasonal (e.g., the Madden-Julian \r\nand Boreal Summer Intraseasonal oscillations and equatorial waves) "


id: 338239c43fd0ef0835aadb9dcfaa0f7b
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 6312
content:
"A subset of the best-track data corresponding to hurricanes that have \r\ndirectly impacted the USA since 1900 is considered to be reliable, and \r\nshows no trend in the frequency of USA landfall events (Knutson et al., \r\n2019). However, an increasing trend in normalized USA hurricane \r\ndamage, which accounts for temporal changes in exposed wealth \r\n(Grinsted et al., 2019), and a  decreasing trend in TC translation \r\nspeed over the USA (Kossin, 2019) have also been identified in this "


id: c5c3957c9fd193e5e40950eb7464befe
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 32102
content:
"change in TC frequency, or to systematic track shifts (or both). \r\nFrom an impacts perspective, however, these changes over land are \r\nhighly relevant and emphasize that large-scale modifications in TC \r\nbehaviour can have a broad spectrum of impacts on a regional scale."


id: f1fcf3e70901e5417bd98a259e8a4056
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 39966
content:
"TC metrics are used to evaluate how capable models are of simulating \r\npresent-day TC climatologies and variability (e.g., TC frequency, wind \r\nintensity, precipitation, size, tracks, and their seasonal and interannual \r\nchanges) (Walsh et al., 2015; Camargo and Wing, 2016; Knutson et al., \r\n2019, 2020). Other examples of TC climatology/variability metrics are \r\nspatial distributions of TC occurrence and genesis (Walsh et al., 2015), \r\nseasonal cycles and interannual variability of basin-wide activity (Zhao \r\net al., 2009; Shaevitz et al., 2014; Kodama et al., 2015; Murakami et al., \r\n2015; Yamada et al., 2017) or landfalling activity (Lok and Chan, 2018), \r\nas well as newly developed process-diagnostics designed specifically \r\nfor TCs in climate models (D. Kim  et al., 2018; Wing et al., 2019; \r\nMoon et al., 2020). "


id: 53564da5506fff2376f130f71930191
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 11933
content:
"2018; J. Sun et al., 2019; T.-C. Lee et al., 2020; Yamaguchi and Maeda, \r\n2020a; Kubota et al., 2021). "


id: a5812e120aa367edcca231d09a067f0f
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 26349
content:
"In summary, there is mounting evidence that a  variety of TC \r\ncharacteristics have changed over various time periods. It is likely that \r\nthe global proportion of Category 3-5 tropical cyclone instances and \r\nthe frequency of rapid intensification events have increased globally \r\nover the past 40 years. It is very likely that the average location \r\nwhere TCs reach their peak wind intensity has migrated poleward in \r\nthe western North Pacific Ocean since the 1940s. It is likely that TC \r\ntranslation speed has slowed over the USA since 1900. "


id: 468f27559d5cb221ddb5dd2aa202f9f1
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 9621
content:
"Operational forecasting models also reproduce TCs, and their use for \r\nclimate projection studies shows promise. However, there is limited \r\napplication for future projections as they are specifically developed \r\nfor operational purposes, and TC climatology is not necessarily well \r\nevaluated. Intercomparison of operational models indicates that \r\nenhancement of horizontal resolution can provide more credible \r\nprojections of TCs (Nakano et al., 2017). Likewise, high-resolution \r\nclimate models show promise as TC forecast tools (Zarzycki and \r\nJablonowski, 2015; Reed et al., 2020), further narrowing the \r\ncontinuum of weather and climate models, and increasing confidence \r\nin projections of future TC behaviour. However, higher horizontal \r\nresolution does not necessarily lead to an improved TC climatology \r\n(Camargo et al., 2020). "


id: b3c2be85cb9e92686f1944b1b204fb4e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 28869
content:
"In summary, various types of models are useful to study how TCs \r\nchange in response to climate changes, and there is no unique \r\nsolution for choosing a model type. However, higher-resolution models \r\ngenerally capture TC properties more realistically (high confidence). \r\nIn particular, models with horizontal resolutions of 10-60 km are \r\ncapable of reproducing strong TCs with Category 4-5 and those of \r\n1-10 km are capable of the eye wall structure of TCs. Uncertainties in \r\nTC simulations come from details of the model configuration of both \r\ndynamical and physical processes. Models with realistic atmosphere-\r\nocean interactions are generally better than atmosphere-only models \r\nat reproducing realistic TC evolutions (high confidence)."


id: 69adddc53355a05c7ae11751503a7667
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 15861
content:
"Atmosphere-ocean interaction is an important process in TC \r\nevolution. Atmosphere-ocean coupled models are generally better \r\nthan atmosphere-only models at capturing realistic processes related \r\nto TCs (Murakami et al., 2015; Ogata et al., 2015, 2016; Zarzycki, 2016; \r\nKanada et al., 2017b; Scoccimarro et al., 2017). However, the basin\u0002scale SST biases commonly found in atmosphere-ocean models can \r\nintroduce substantial errors in the simulated TC number (Hsu et al., \r\n2019). Higher-resolution ocean models improve the simulation of TCs \r\nby reducing the SST climatology bias (Li and Sriver, 2018; Roberts \r\net al., 2020a). Coarse resolution atmospheric models may degrade \r\ncoupled model performance as well. For example, in a  case study \r\nof Hurricane Harvey, Trenberth et al. (2018) suggested that the lack \r\nof realistic hurricane frequency and intensity within coupled climate \r\nmodels hampers the models' ability to simulate SST and ocean heat \r\ncontent and their changes. "


id: d61ac2f82570fb5629ea74c332a9dd1e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 34987
content:
"Even with higher-resolution atmosphere-ocean coupled models, TC \r\nprojection studies still rely on assumptions in experimental design \r\nthat introduce uncertainties. Computational constraints often limit \r\nthe number of simulations, resulting in relatively small ensemble \r\nsizes and incomplete analyses of possible future SST magnitude \r\nand pattern changes (Zhao and Held, 2011; Knutson et al., 2013). \r\nUncertainties in aerosol forcing also are reflected in TC projection \r\nuncertainty (Wang et al., 2014)."


id: 35a5861bd5fecd43695a4631a0795b09
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 6692
content:
"Regional climate models (RCM) with grid spacing around 15-50 km \r\ncan be used to study the projection of TCs. RCMs are run with \r\nlateral and surface boundary conditions, which are specified by the \r\natmospheric state and SSTs simulated by GCMs. Various combinations \r\nof the lateral and surface boundary conditions can be chosen for RCM \r\nstudies, and uncertainties in the projection can be further examined \r\nin general. They are used for studying changes in TC characteristics \r\nin a specific area, such as Vietnam (Redmond et al., 2015) and the \r\nPhilippines (Gallo et al., 2019)."


id: b6eea64ef235b226818cf083676446e3
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 29390
content:
"The cause of the observed slowdown in TC translation speed is not \r\nyet clear. Yamaguchi et al. (2020) used large ensemble simulations \r\nto argue that part of the slowdown is due to actual latitudinal shifts \r\nof TC tracks, rather than data artefacts, in addition to atmospheric \r\ncirculation changes. G. Zhang et al. (2020) used large ensemble \r\nsimulations to show that anthropogenic forcing can lead to a robust \r\nslowdown, particularly outside of the tropics at higher latitudes. \r\nYamaguchi and Maeda (2020b) found a  significant slowdown in \r\nthe western North Pacific over the past 40 years and attributed the \r\nslowdown to a combination of natural variability and global warming. \r\nThe slowing trend since 1900 over the USA is robust and significant \r\nafter removing multi-decadal variability from the time series "


id: bf533fae8a2b7334e9711f937cfae757
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 30929
content:
"Less computationally expensive downscaling approaches that allow \r\nlarger ensembles and long-term studies are also used in the projection \r\nof TCs (Emanuel et al., 2006; C.Y. Lee et al., 2018). A  statistical-\r\ndynamical TC downscaling method requires assumptions of the \r\nrate of seeding of random initial disturbances, which are generally \r\nassumed to not change with climate change (Emanuel et al., 2008; \r\nEmanuel, 2013). The results with the downscaling approach might "


id: 936a78d02020dd18a75d4df1b1203722
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
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vector_id: 23141
content:
"(Kossin, 2019). Among the hypotheses discussed is the physical \r\nlinkage between warming and slowing circulation (Held and \r\nSoden, 2006; see also Section 8.2.2.2), with expectations of Arctic \r\namplification and weakening circulation patterns through weakening \r\nmeridional temperature gradients (Coumou et al., 2018; see also \r\nCross-Chapter Box  10.1), or through changes in planetary wave \r\ndynamics (Mann et al., 2017). The tropics expansion and the poleward \r\nshift of the mid-latitude westerlies associated with warming is also \r\nsuggested as the reason of the slowdown (G. Zhang et al., 2020). \r\nHowever, the connection of these mechanisms to the slowdown has \r\nnot been robustly shown. Furthermore, slowing trends have not been \r\nunambiguously observed in circulation patterns that steer TCs, such \r\nas the Walker and Hadley circulations (Section  2.3.1.4), although \r\nthese circulations generally slow down in numerical simulations \r\nunder global warming (Sections 4.5.1.6 and 8.4.2.2). "


id: 3f0462fa2588bf696febda6b5feb1d42
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 8273
content:
"The observed poleward trend in western North Pacific TCs remains \r\nsignificant after accounting for the known modes of dominant \r\ninterannual to decadal variability in the region (Kossin et al., 2016a), \r\nand is also found in CMIP5 model-simulated TCs (in the recent \r\nhistorical period 1980-2005), although it is weaker than observed \r\nand is not statistically significant (Kossin et al., 2016a). However, \r\nthe trend is significant in 21st-century CMIP5 projections under the \r\nRCP8.5 scenario, with a similar spatial pattern and magnitude to the \r\npast observed changes in that basin over the period 1945-2016, \r\nsupporting a possible anthropogenic greenhouse gas contribution to \r\nthe observed trends (Kossin et al., 2016a; Knutson et al., 2019). "


id: 1dcd304e9e8d45564a61964f393510e2
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 2431
content:
"Event attribution is used in TC case studies to test whether the \r\nseverities of recent intense TCs are explained without anthropogenic \r\neffects. In a case study of Hurricane Sandy (2012), Lackmann (2015) "


id: cb7990277b1e1ff99bfcb6934bcf30c6
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 33126
content:
"In summary, it is very likely that the recent active TC seasons in \r\nthe North Atlantic, the North Pacific, and Arabian basins cannot be \r\nexplained without an anthropogenic influence. The anthropogenic "


id: 44ecfa79990de2ad3f12c3690bb91e26
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 9356
content:
"influence on these changes is principally associated to aerosol forcing, \r\nwith stronger contributions to the response in the North Atlantic. It \r\nis more likely than not that the slowdown of TC translation speed \r\nover the USA has contributions from anthropogenic forcing. It is \r\nlikely that the poleward migration of TCs in the western North Pacific \r\nand the global increase in TC intensity rates cannot be explained \r\nentirely by natural variability. Event attribution studies of specific \r\nstrong TCs provide limited evidence for anthropogenic effects on TC \r\nintensifications so far, but high confidence for increases in TC heavy \r\nprecipitation. There is high confidence that anthropogenic climate \r\nchange contributed to extreme rainfall amounts during Hurricane \r\nHarvey (2017) and other intense TCs."


id: 9dee3d2394dc15d6219cc950c41ceb9e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 25018
content:
"changes in tropical cyclogenesis (Walsh et al., 2015; Hoogewind \r\net al., 2020). Even within a single model, uncertainty in the pattern of \r\nfuture SST changes leads to large uncertainties (including the sign) \r\nin the projected change in TC frequency in individual ocean basins, \r\nalthough global TCs would appear to be less sensitive (Yoshida et al., \r\n2017; Bacmeister et al., 2018)."


id: eaee8eb13e44601d90efa652ab21f603
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 38694
content:
"A summary of studies on TC projections for the late 21st  century, \r\nparticularly studies since AR5, is given by Knutson et al. (2020), which \r\nis an assessment report mandated by the World Meteorological \r\nOrganization (WMO). Studies subsequent to Knutson et al. (2020) \r\nare generally consistent, and the confidence assessments here \r\nclosely follow theirs (Cha et al., 2020), although there are some \r\ndifferences due to the varying confidence calibrations between the \r\nIPCC and WMO reports. "


id: d851b81cb8ee15301f3b7b83853678c9
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 35362
content:
"due to differences in regional SST warming and warming patterns \r\n(Sugi et al., 2017; Yoshida et al., 2017; Bacmeister et al., 2018). \r\nA  summary of projections of TC characteristics is schematically \r\nshown by Figure 11.20."


id: b3a6eaf6cf1aeddde94470c47369bd03
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 28850
content:
"The increase in global TC maximum surface wind speeds is about 5% \r\nfor a 2degC global warming across a number of high-resolution multi\u0002decadal studies (Knutson et al., 2020). This indicates the deepening \r\nin global TC minimum surface pressure under the global warming \r\nconditions. A regional cloud-permitting model study shows that the \r\nstrongest TC in the western North Pacific can be as strong as 857 hPa \r\nin minimum surface pressure with a wind speed of 88 m s-1 under \r\nwarming conditions in 2074-2087 (Tsuboki et al., 2015). TCs are \r\nalso measured by quantities such as ACE and the power dissipation \r\nindex (PDI), which conflate TC intensity, frequency, and duration \r\n(Murakami et al., 2014). Several TC modelling studies (Yamada et al., \r\n2010; H.S. Kim et al., 2014; Knutson et al., 2015) project little change \r\nor decreases in the globally accumulated value of PDI or ACE, which \r\nis due to the decrease in the total number of TCs. "


id: 2e71cbbae65551667e0e2a6eda113137
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 5452
content:
"The coastal effects of TCs depend on TC intensity, size, track, and \r\ntranslation speed. Projected increases in sea level, average TC \r\nintensity, and TC rainfall rates each generally act to further elevate \r\nfuture storm surge and fresh-water flooding (see Section  9.6.4.2). \r\nChanges in TC frequency could contribute toward increasing or \r\ndecreasing future storm surge risk, depending on the net effects of \r\nchanges in weaker vs stronger storms. Several studies (McInnes et al., \r\n2014, 2016; Little et al., 2015; Garner et al., 2017; Timmermans et al., \r\n2017, 2018) have explored future projections of storm surge in the \r\ncontext of anthropogenic climate change with the influence of both \r\nsea level rise and future TC changes. Garner et al. (2017) investigated \r\nthe near-future changes in the New York City coastal flood hazard, \r\nand suggested a small change in storm-surge height because effects \r\nof TC intensification are compensated by the offshore shifts in TC "


id: 3eaa04f90105c540e1cca86e2fb4a41
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 8214
content:
"section is on individual ETCs that have been identified using some \r\ndetection and tracking algorithms. Mid-latitude atmospheric rivers \r\nare assessed in Section 8.3.2.8."


id: 54e99017270f0205a7c401f03c53bcdd
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 12209
content:
"tracks, but concluded that the overall effect due to the rising sea \r\nlevels would increase the flood hazard. Future projection studies \r\nof storm surge in East Asia, including China, Japan and Korea, also \r\nindicate that storm surges due to TCs become more severe (J.A. Yang \r\net al., 2018; Mori et al., 2019, 2021; J. Chen et al., 2020b). For the \r\nPacific Islands, McInnes et al. (2014) found that the future projected \r\nincrease in storm surge in Fiji is dominated by sea level rise, and \r\nprojected TC changes make only a minor contribution. Among various \r\nstorm surge factors, there is high confidence that sea level rise will \r\nlead to a higher possibility of extreme coastal water levels in most \r\nregions, with all other factors assumed equal. "


id: 58c9f8efb57ad982c659694da16bd75a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 12863
content:
"In summary, average peak TC wind speeds and the proportion of \r\nCategory 4-5 TCs will very likely increase globally with warming. \r\nIt is likely that the frequency of Category 4-5 TCs will increase in \r\nlimited regions over the western North Pacific. It is very likely\r\nthat average TC rain rates will increase with warming, and likely that \r\nthe peak rain rates will increase at rate greater than the Clausius-\r\nClapeyron scaling rate of 7% per 1degC of warming in some regions \r\ndue to increased low-level moisture convergence caused by regional \r\nincreases in TC wind intensity. It is likely that the average location \r\nwhere TCs reach their peak wind intensity will migrate poleward in \r\nthe western North Pacific Ocean as the tropics expand with warming, \r\nand that the global frequency of TCs over all categories will decrease \r\nor remain unchanged. "


id: 1a6fc7830a38befac6d8e59d717dff38
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 1853
content:
"There is high confidence that coarse-resolution climate models \r\n(e.g.,  CMIP5 and CMIP6) underestimate the dynamical intensity \r\nof ETCs, including the strongest ETCs, as measured using a variety of \r\nmetrics, including mean pressure gradient, mean vorticity and near\u0002surface wind speeds, over most regions (Colle et al., 2013; Zappa \r\net al., 2013a; Govekar et al., 2014; Di Luca et al., 2016; Trzeciak \r\net al., 2016; Seiler et al., 2018; Priestley et al., 2020). There is also \r\nhigh confidence that most current climate models underestimate \r\nthe number of explosive systems (i.e., systems showing a decrease \r\nin mean sea level pressure of at least 24 hPa in 24 hours) over \r\nboth hemispheres (Seiler and Zwiers, 2016a; Gao et al., 2020; "


id: 9dbd86a28091a5be11d11ec11a1a9088
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 24984
content:
"This section focuses on extratropical cyclones (ETCs) that are either \r\nclassified as strong or extreme by using some measure of their \r\nintensity, or by being associated with the occurrence of extremes \r\nin variables such as precipitation or near-surface wind speed \r\n(Seneviratne et al., 2012). Since AR5, the high relevance of ETCs for \r\nextreme precipitation events has been well established (Pfahl and \r\nWernli, 2012; Catto and Pfahl, 2013; Utsumi et al., 2017), with 80% \r\nor more of hourly and daily precipitation extremes being associated \r\nwith either ETCs or fronts over oceanic mid-latitude regions, and \r\nsomewhat smaller, but still very large, proportions of events over \r\nmid-latitude land regions (Utsumi et al., 2017). The emphasis in this "


id: b3a704ce5830bf3818254dbd4833fd9e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 28851
content:
"Section  3.3.3.3 concluded that there is low confidence in the \r\nattribution of observed changes in the number of ETCs in the Northern \r\nHemisphere and high confidence that the poleward shift of storm \r\ntracks in the Southern Hemisphere is linked to human activity, mostly \r\ndue to emissions of ozone-depleting substances. Specific studies \r\nattributing changes in the most extreme ETCs are not available. \r\nThe human influence on individual extreme ETC events has been \r\nconsidered only a few times and there is overall low confidence in \r\nthe attribution of these changes (NASEM, 2016; Vautard et al., 2019)."


id: a58b83008958b8113e3b805b0609dfc4
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 26361
content:
"In summary, there is low confidence in past changes in the dynamical \r\nintensity (e.g., maximum wind speeds) of ETCs and medium confidence\r\nthat, in the future, these changes will be small, although changes in \r\nthe location of storm tracks could lead to substantial changes in local \r\nextreme wind speeds. There is high confidence that average and \r\nmaximum ETC precipitation-rates will increase with warming, with the \r\nmagnitude of the increases associated with increases in atmospheric \r\nwater vapour. There is medium confidence that projected changes in \r\nthe intensity of ETCs, including wind speeds and precipitation, depend \r\non the resolution and formulation of climate models."


id: 4cc0ae3c71dad5c6aedbf708c04e4995
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 10772
content:
"There are few studies on relations between changes in severe \r\nconvective storms and those of the large-scale circulation patterns. \r\nTornado outbreaks in the USA are usually associated with ETCs with \r\ntheir frontal systems and TCs (Fuhrmann et al., 2014; Tochimoto and \r\nNiino, 2016). In early June to late July in East Asia, associated with \r\nthe Baiu/Changma/Mei-yu, severe precipitation events are frequently \r\ncaused by MCSs. Severe precipitation events are also caused by \r\nremote effects of TCs, known as predecessor rain events (Galarneau \r\net al., 2010). Atmospheric rivers and other coherent types of \r\nenhanced water vapour flux also have the potential to induce severe \r\nconvective systems (Kamae et al., 2017a; Waliser and Guan, 2017; \r\nRalph et al., 2018; see Section 8.3.2.8.2). Combined with the above \r\ndrivers, topographic effects also enhance the intensity and duration "


id: 4286d44bf36bec252c606e2c2245f2fb
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 8899
content:
"of severe convective systems and the associated precipitation \r\n(Ducrocq et al., 2008; Piaget et al., 2015). However, the changes in \r\nthese drivers are not generally significant, so their relations to severe \r\nconvective storms are unclear."


id: dd67a652907be8e289469edfb7731b7f
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 36221
content:
"particular aspects of MCSs, such as lengthening of active seasons \r\nand dependency on duration. MCSs have increased in occurrence \r\nand precipitation amounts since 1979 (Easterling et al., 2017). Feng \r\net al. (2016) analysed that the observed increases in spring total and \r\nextreme rainfall in the central USA are dominated by MCSs, with \r\nincreased frequency and intensity of long-lasting MCSs. "


id: de7c54e8681d011971f30bcaca7588fe
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 36409
content:
"In summary, severe convective storms are sometimes embedded \r\nin synoptic-scale weather systems, such as TCs, ETCs and fronts, \r\nand modulated by large-scale atmospheric circulation patterns. \r\nThe occurrence of severe convective storms and the associated \r\nsevere events, including tornadoes, hail, and lightning, is affected by \r\nenvironmental conditions of the atmosphere, such as CAPE and vertical \r\nshear. The uncertainty, however, arises from the balance between these \r\nenvironmental factors affecting severe storm occurrence."


id: 330765cde17c75d15dfb63c5facb240a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 6245
content:
"In summary, because the definition of severe convective storms varies \r\ndepending on the literature and the region, it is not straightforward \r\nto make a synthesizing view of observed trends in severe convective \r\nstorms in different regions. In particular, observational trends in \r\ntornadoes, hail, and lightning associated with severe convective \r\nstorms are not robustly detected due to insufficient coverage of the \r\nlong-term observations. There is medium confidence that the mean \r\nannual number of tornadoes in the USA has remained relatively \r\nconstant, but their variability of occurrence has increased since the \r\n1970s, particularly over the 2000s, with a decrease in the number of \r\ndays per year, and an increase in the number of tornadoes on these \r\ndays (high confidence). Detected tornadoes have also increased in \r\nEurope, but the trend depends on the density of observations. "


id: bc2a72e2fbd3571f832c08e12f37e427
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 30346
content:
"For the case of the heavy rain event of July 2018 in Japan (Box 11.4), \r\nKawase et al. (2020) took a  storyline approach to show that the \r\nrainfall during this event in Japan was increased by approximately \r\n7% due to recent rapid warming around Japan. For the case of the \r\nDecember 2015 extreme rainfall event in Chennai, India, the extremity \r\nof the event was equally caused by the warming trend in the Bay of \r\nBengal SSTs and the strong El Nino conditions (van Oldenborgh et al., \r\n2016; Boyaj et al., 2018). For hailstorms, such as those that caused \r\ndisasters in the USA in 2018, detection of the role of climate change \r\nin changing hail storms is more difficult, because hail storms are \r\nnot, in general, directly simulated by convection-permitting models \r\nand not adequately represented by the environmental parameters of \r\ncoarse-resolution GCMs (Mahoney, 2020). "


id: dfacf3bcb91e5ce01e650368721f920a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 36599
content:
"In summary, it is extremely difficult to detect and attribute changes \r\nin severe convective storms. There is limited evidence that extreme \r\nprecipitation associated with severe convective storms has \r\nincreased in some cases."


id: 97836e81d219542e366526d8acef412b
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 23869
content:
"The other modelling approach is the analysis of the environmental \r\nconditions that control characteristics of severe convective storms \r\nusing the typical climate model results in CMIP5/6 (Allen, 2018). \r\nSevere convective storms are generally formed in environments \r\nwith large CAPE and tornadic storms are, in particular, formed with \r\na  combination of large CAPE and strong vertical wind shear. As \r\nthe processes associated with severe convective storms occur over \r\na  wide range of spatial and temporal scales, some of which are \r\npoorly understood and are inadequately sampled by observational \r\nnetworks, the model calibration approaches are generally difficult \r\nand insufficiently validated. Therefore, model simulations and their \r\ninterpretations should be done with much caution. "


id: d8218116d42773e626b69d223a8ebc4c
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 35326
content:
"In summary, there are typically two kinds of modelling approaches \r\nfor studying changes in severe convective storms. One is to use \r\nconvection-permitting models in wider regions or the global domain \r\nin time-sliced downscaling methods to directly simulate severe \r\nconvective storms. The other is the analysis of the environmental \r\nconditions that control characteristics of severe convective \r\nstorms by using coarse-resolution GCMs. Even in finer-resolution \r\nconvection-permitting models, it is difficult to directly simulate \r\ntornadoes, hail storms, and lightning, so modelling studies of these \r\nchanges are limited."


id: c8cd9e666dc23a8ae5e158805eb63319
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 32654
content:
"The other approach is the projection of the environmental conditions \r\nthat control characteristics of severe convective storms by analysing \r\nclimate model results. There is high confidence that CAPE, particularly \r\nsummer mean CAPE and high percentiles of the CAPE in the tropics \r\nand subtropics, increases in response to global warming in an \r\nensemble of climate models including those of CMIP5, mainly from \r\nincreased low-level specific humidity (Sobel and Camargo, 2011; \r\nM.S. Singh et al., 2017; J. Chen et al., 2020a). Convective inhibition "


id: 894a5e0d8ca757f775837ddab229f4d7
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 21322
content:
"It is extremely difficult to detect differences in time and space of \r\nsevere convective storms (Kunkel et al., 2013). Although some \r\ningredients that are favourable for severe thunderstorms have \r\nincreased over the years, others have not; thus, overall, changes in \r\nthe frequency of environments favourable for severe thunderstorms \r\nhave not been statistically significant. Event attribution studies on \r\nsevere convective events have now been undertaken for some cases. "


id: 5154774b30d3f8097ad4f66add54b0c5
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 11587
content:
"becomes stronger over most land areas under global warming, \r\nresulting mainly from reduced low-level relative humidity over land \r\n(J. Chen et al., 2020a). However, there are large differences within \r\nthe CMIP5 ensemble for environmental conditions, which contribute \r\nto some degree of uncertainty (Allen, 2018). Because the relation \r\nbetween simulated environments in models and the occurrence of \r\nsevere convective storms are, in general, insufficiently validated, there \r\nis generally low confidence in the projection of severe convective \r\nstorms with the approach of the environmental conditions. "


id: 1574552de353a8bb93d6655ad5fa5bfc
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 989
content:
"Future changes in severe convection environments show \r\nenhancement of instability with less robust changes in the frequency \r\nof strong vertical wind shear in Europe (Pucik et al., 2017) and \r\nin Japan (Muramatsu et al., 2016). In Japan, the frequency of \r\nconditions favourable for strong tornadoes increases in spring, and \r\npartly in summer. "


id: 30e9a6bc5fe6a7cb9946ffab4db8bdc3
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 5860
content:
"In summary, the average and maximum rain rates associated \r\nwith severe convective storms increase in a  warming world in \r\nsome regions, including the USA (high confidence). There is high \r\nconfidence from climate models that CAPE increases in response \r\nto global warming in the tropics and subtropics, suggesting more \r\nfavourable environments for severe convective storms. The frequency \r\nof severe convective storms in spring is projected to increase in \r\nthe USA, leading to a  lengthening of the severe convective storm \r\nseason (medium confidence); evidence in other regions is limited. \r\nThere is significant uncertainty about projected regional changes in \r\ntornadoes, hail, and lightning due to limited analysis of simulations \r\nusing convection-permitting models (high confidence)."


id: 614a8ba0568510726e268f6029871594
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 14418
content:
"positive wind speed trends over the ocean were larger during winter \r\nseasons than summer seasons."


id: 9f188c938642f36cb1f7da1ccf8d24b9
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 25212
content:
"amplify the impact of the events, or (iii) combinations of events that \r\nare not themselves extremes but lead to an extreme event or impact \r\nwhen combined. "


id: 3ffedf9f065c5a1954b971aaf2ccc3ad
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 8450
content:
"Extreme cyclonic windstorms that share some characteristics with \r\nboth TCs and ETCs occur regularly over the Mediterranean Sea and \r\nare often referred to as 'medicanes' (Ragone et al., 2018; Miglietta \r\nand Rotunno, 2019; Zhang et al., 2021). Medicanes pose substantial \r\nthreats to regional islands and coastal zones. A  growing body \r\nof literature consistently found that the frequency of medicanes \r\ndecreases under warming, while the strongest medicanes become \r\nstronger (Gaertner et al., 2007; Romero and Emanuel, 2013, 2017; \r\nCavicchia et al., 2014; Tous et al., 2016; Romera et al., 2017; \r\nGonzalez-Aleman et al., 2019). This is also consistent with expected \r\nglobal changes in TCs under warming (Section 11.7.1). Based on the \r\nconsistency of these studies, it is likely that medicanes will decrease \r\nin frequency, while the strongest medicanes become stronger under \r\nwarming scenario projections (medium confidence)."


id: b118e468324226137e7c85ee12e5d4f4
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 28384
content:
"In summary, the observed intensity of extreme winds is becoming \r\nless severe in the low to mid-latitudes, while becoming more \r\nsevere in high latitudes poleward of 60 degrees (low confidence). \r\nProjected changes in the frequency and intensity of extreme winds \r\nare associated with projected changes in the frequency and intensity \r\nof TCs and ETCs (medium confidence)."


id: 68e17b75a21e4e6490f3d682a6d818a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 15721
content:
"warming, even between 1.5degC and 2degC of global warming (Box 11.2; \r\nGaupp et al., 2019). Concomitant extreme conditions at different \r\nlocations become more probable as changes in climate extremes \r\nare emerging over an increasing fraction of the land area (Sections \r\n11.2.3, 11.2.4, 11.8.2 and 11.8.3, and Box 11.4). "


id: a983633c6d534bdb54159feaf0c95616
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 27044
content:
"In summary, compound events include the combination of two or \r\nmore  - not necessarily extreme  - weather or climate events that \r\noccur (i) at the same time, (ii) in close succession, or (iii) concurrently \r\nin different regions. The land area affected by concurrent extremes has \r\nincreased (high confidence). Concurrent extreme events at different \r\nlocations, but possibly affecting similar sectors (e.g., breadbaskets) \r\nin different regions, will become more frequent with increasing \r\nglobal warming, in particular above +2degC of global warming \r\n(high confidence). "


id: a8202a999465d7015e2e46c11a634cc
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 26795
content:
"Many coastal areas are also prone to the occurrence of compound \r\nprecipitation and wind extremes, which can cause damage, including \r\nto infrastructure and natural environments. A  high percentage of \r\nco-occurring wind and precipitation extremes are found in coastal \r\nregions and in areas with frequent tropical cyclones. Finally, the \r\ncombination of extreme wave height and duration is also shown to \r\ninfluence coastal erosion processes (Corbella and Stretch, 2012). "


id: 693db69f10c3021580d3690e5ab6fb7b
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 15780
content:
"Coastal and estuarine zones are prone to a number of meteorological \r\nextreme events and also to concurrent extremes (see also \r\nSection 6.8.2 in SROCC). Floods are a major climatic impact-driver in \r\ncoastal regions around the world (Chapter 12), and flood occurrence \r\nmay be influenced by the dependence between storm surge, extreme \r\nrainfall, and river flow, but also by sea level rise, waves and tides, as \r\nwell as groundwater for estuaries. Floods with multiple drivers are \r\noften referred to as 'compound floods' (Wahl et al., 2015; Moftakhari \r\net al., 2017; Bevacqua et al., 2020c). "


id: 9d0fff04d0f0cc65f69aec3063b191bb
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 24871
content:
"At USA coasts, the probability of co-occurring storm surge and heavy \r\nprecipitation is higher for the Atlantic/Gulf coast relative to the Pacific \r\ncoast (Wahl et al., 2015). Furthermore, six studied locations on the \r\nUSA coast with long overlapping time series show an increase in the \r\ndependence between heavy precipitation and storm surge over the \r\nlast century, leading to more frequent co-occurring storm surge and \r\nheavy precipitation events at the present day (Wahl et al., 2015). Storm \r\nsurge and extreme rainfall are also dependent in most locations on the \r\nAustralian coasts (Zheng et al., 2013) and in Europe along the Dutch \r\ncoasts (Ridder et al., 2018), along the Mediterranean Sea, the Atlantic "


id: e10cecf762babfb7fa73132caf654481
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 36857
content:
"projected to lead to more frequent and intense compound coastal \r\nflooding events as sea levels continue to rise. "


id: 62591eeab5f29f62e0d5cecb278fc677
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 14581
content:
"In summary, there is medium confidence that, over the last century, \r\nthe probability of compound flooding has increased in some locations, \r\nincluding along the USA coastline. There is high confidence that the \r\noccurrence and magnitude of compound flooding in coastal regions \r\nwill increase in the future due to both sea level rise and increases in \r\nheavy precipitation."


id: 89faf0c64c36d7a5addb6c4b8686d4c8
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 21443
content:
"Concurrent droughts and heatwaves have a  number of negative \r\nimpacts on human society and natural ecosystems. Studies since \r\nSREX and AR5 show several occurrences of observed combinations \r\nof drought and heatwaves in various regions."


id: d47865d1cce1ffc1977a09ec6b543b76
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 34703
content:
"Over most land regions, temperature and precipitation are strongly \r\nnegatively correlated during summer (Zscheischler and Seneviratne, \r\n2017), mostly due to land-atmosphere feedbacks (Sections 11.1.6 and \r\n11.3.2), but also because synoptic-scale weather systems favourable \r\nfor extreme heat are also unfavourable for rain (Berg et al., 2015). \r\nThis leads to a strong correlation between droughts and heatwaves \r\n(Zscheischler and Seneviratne, 2017). Drought events characterized \r\nby low precipitation and extreme high temperatures have occurred, \r\nfor example, in California (AghaKouchak et al., 2014), inland Eastern \r\nAustralia (King et al., 2014), and large parts of Europe (Orth et al., \r\n2016a). The 2018 growing season was both record-breaking dry and \r\nhot in Germany (Zscheischler and Fischer, 2020)."


id: 96b4a9540c9609648e7949b441780bac
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 23717
content:
"In summary, there is high confidence that concurrent heatwaves and \r\ndroughts have increased in frequency over the last  century at the \r\nglobal scale due to human influence. There is medium confidence\r\nthat weather conditions that promote wildfires (fire weather) have \r\nbecome more probable in southern Europe, northern Eurasia, the \r\nUSA, and Australia over the last century. There is high confidence that \r\ncompound hot and dry conditions become more probable in nearly \r\nall land regions as global mean temperature increases. There is high \r\nconfidence that fire weather conditions will become more frequent at \r\nhigher levels of global warming in some regions."


id: f82f38bb606e375d597d193b819c69e9
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 41039
content:
"Drought and heatwaves are also associated with fire weather, related \r\nthrough high temperatures, low soil moisture, and low humidity. \r\nFire weather refers to weather conditions conducive to triggering \r\nand sustaining wildfires, which generally include temperature, soil \r\nmoisture, humidity, and wind (Chapter 12). Concurrent hot and dry \r\nconditions amplify conditions that promote wildfires (Schubert et al., \r\n2014; Littell et al., 2016; Dowdy, 2018; Hope et al., 2019). Burnt area \r\nextent in western USA forests (Abatzoglou and Williams, 2016) and \r\nparticularly in California (Williams et al., 2019) has been linked to "


id: eb892389cb1357634bfb83560a4fb842
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 38801
content:
"suggested that anthropogenic warming contributed to the 2015 Ethiopian and southern African droughts by increasing SSTs and local \r\nair temperatures (Funk et al., 2016, 2018b; Yuan et al., 2018a). It has also been suggested that the 2015-2016 extreme El Nino affected \r\ncirculation patterns in Europe during the 2015-2016 winter (Geng et al., 2017; Scaife et al., 2017). "


id: 7832702eba9449dc30e377a7e23b80b2
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 18359
content:
"The atmospheric CO2 growth rate was particularly high in 2015, possibly related to some of the mentioned droughts, in particular in \r\nIndonesia and the Amazon region, leading to higher CO2 release in combination with less CO2 uptake from land areas (Humphrey et al., \r\n2018). The impact of the 2015-2016 extreme El Nino on vegetation systems via drought was also shown from satellite data (Kogan \r\nand Guo, 2017). Overall, tropical forests were a carbon source to the atmosphere during the 2015-2016 El Nino-related drought, with \r\nsome estimates suggesting that up to 2.3 PgC were released (Brando et al., 2019)."


id: 68f75ae84466838f1ca5a64f19206836
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 15733
content:
"The 2015-2016 extreme El Nino has induced extreme precipitation in some regions. Severe rainfall events were observed in Chennai \r\ncity in India in Devember 2015, and the Yangtze river region in China in June-July 2016, and it was shown that these rainfall events \r\nare partly attributed to the 2015-2016 extreme El Nino (van Oldenborgh et al., 2016; Boyaj et al., 2018; Sun and Miao, 2018; Yuan \r\net al., 2018b; Zhou et al., 2018). "


id: 4151dd06c5d04478c2f3c2a222f2f2e8
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 8676
content:
"The heavy precipitation event was characterized by unusually widespread and persistent rainfall and locally anomalous total \r\nprecipitation led by band-shaped precipitation systems, which are frequently associated with heavy precipitation events in East \r\nAsia (Section 11.7.3; Kato, 2020). The extreme rainfall in Japan was caused by anomalous moisture transport with a combination \r\nof abnormal jet condition (Takemi and Unuma, 2019; Takemura et al., 2019; Tsuji et al., 2020; Yokoyama et al., 2020), which can be \r\nviewed as an atmospheric river (Sections 8.2.2.8 and 11.7.2; Yatagai et al., 2019) caused by intensified inflow velocity and high SST \r\naround Japan (Sekizawa et al., 2019; Kawase et al., 2020). "


id: 55dd3e5cc904ccf6a66846f1494593f
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 12375
content:
"This precipitation event and the subsequent heatwave are related to abnormal condition of the jet stream and North Pacific Subtropical \r\nHigh in this month (Shimpo et al., 2019; Ren et al., 2020), which caused extreme conditions from Europe, Eurasia, and North America \r\n(Box 11.4, Figure 2; Kornhuber et al., 2019). A combination of the positive anomaly of the North Atlantic Oscillation (NAO, Annex IV.2.1) \r\nand the meandering jets is necessary to explain the pattern of the observed anomalies (Drouard et al., 2019). A role of Atlantic SST \r\nanomaly on the meandering jets and the subtropical high have been suggested (B. Liu et al., 2019). These dynamic and thermodynamic \r\ncomponents generally have substantial influence on extreme rainfall in East Asia (Oh et al., 2018), but it is under investigation whether \r\nthese factors were due to anthropogenic forcing."


id: e8033f7791df57a7c43d296b0f045f39
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 38131
content:
"Regarding the hot extremes that occurred across the Northern Hemisphere in the 2018 boreal May-July period, Vogel et al. (2019) \r\nfound that the event was unprecedented in terms of the total area affected by hot extremes (on average, about 22% of populated \r\nand agricultural areas in the Northern Hemisphere) for that period, but was consistent with a +1degC climate which was the estimated "


id: 8baaebbe45a2d5b5f2cdb6bf185de6ff
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
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vector_id: 21748
content:
"Box 11.4, Figure 2 | Meteorological conditions in July 2018. The colour shading shows the monthly mean near-surface air temperature anomaly with respect \r\nto 1981-2010. Contour lines indicate the geopotential height in m, highlighted are the isolines on 12,000 m and 12,300 m, which indicate the approximate positions \r\nof the polar-front jet and subtropical jet, respectively. The light blue-green ellipse shows the approximate extent of the strong precipitation event that occurred at the \r\nbeginning of July in the region of Japan and Korea. All data is from the global European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5, \r\nHersbach et al., 2020)."


id: 8a0efe66d70e8c6c77e13a37cea66520
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
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vector_id: 21461
content:
"The case studies presented in this Box illustrate the current state of knowledge regarding the contribution of human-induced climate \r\nchange to recent concurrent extremes in the global domain. Recent years have seen a more frequent occurrence of such events. \r\nThe heatwave in Europe in the 2019 boreal summer and its coverage in the global domain is an additional example (Vautard et al., \r\n2020). However, very few studies investigate which types of concurrent extreme events could occur under increasing global warming. \r\nIt has been noted that such events could also be of particular risk for concurrent impacts in the world's breadbaskets (Zampieri et al., \r\n2017; Kornhuber et al., 2020; see also Section 11.8.1)."


id: 94660082c3b8195c0f96927050bc45d
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
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index: climate_gpt_v2
vector_id: 23317
content:
"Sections 11.9.2, 11.9.3 and 11.9.4 provide brief summaries of the \r\nunderlying evidence used to derive the regional assessments for \r\ntemperature extremes, heavy precipitation events, and droughts, \r\nrespectively. The assessments take into account evidence from \r\nstudies based on global datasets (global studies), as well as regional \r\nstudies. Global studies include analyses for all continents and AR6 \r\nregions with sufficient data coverage, and provide an important \r\nbasis for cross-region consistency, as the same data and methods \r\nare used for all regions. However, individual regional studies may \r\ninclude additional information that is missed in global studies, and \r\nthus provide an important regional calibration for the assessment."


id: f0f3c9ff0e10b89dd4c73f7328d14e28
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 39756
content:
"The assessments are presented using the calibrated confidence and \r\nlikelihood language (Box  1.1). Low confidence is assessed when \r\nthere is limited evidence, either because of a lack of available data \r\nin the region and/or a  lack of relevant studies. Low confidence is \r\nalso assessed when there is a  lack of agreement on the evidence \r\nof a change, which may be due to large variability or inconsistent \r\nchanges depending on the considered sub-regions, time frame, \r\nmodels, assessed metrics, or studies. In cases when the evidence is "


id: f17d6f5d67a9d47c20454c8dc49daef8
created_at: 2023-04-19 13:21:40
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vector_id: 39872
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"strongly contradictory, for example, with substantial regional changes \r\nof opposite sign, 'mixed signal' is indicated. With an assessment of \r\nlow confidence, the direction of change is not indicated in the tables. \r\nA  direction of change (increase or decrease) is provided with an \r\nassessment of medium confidence, high confidence, likely, or higher \r\nlikelihood levels. Likelihood assessments are only provided in the \r\ncase of high confidence. In some cases, there may be confidence in \r\na small or no change."


id: dc3712b3816c404302076c29d72343b3
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 36017
content:
"For projections, changes are assessed at three global warming levels \r\n(GWLs; Cross-Chapter Box 11.1): 1.5degC, 2degC and 4degC. The assessments \r\nuse literature based both on GWL projections and scenario-based \r\nprojections. In the case of literature on scenario-based projections, \r\na mapping between scenarios/time frames and GWLs was performed, \r\nas documented in Cross-Chapter Box 11.1. Projections of changes in \r\ntemperature and precipitation extremes are assessed relative to two \r\ndifferent baselines: the recent past (1995-2014) and pre-industrial \r\n(1850-1900). With smaller changes relative to the variability, in \r\nparticular because droughts happen on longer timescales compared \r\nto extremes of daily temperature and precipitation, it is more difficult \r\nto distinguish changes in drought relative to the recent past. As such, \r\nchanges in droughts are assessed relative to the pre-industrial \r\nbaseline, unless indicated otherwise. "


id: 4acaf217dff82729dea0f6809c217363
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 10400
content:
"Tables 11.6, 11.9, 11.12, 11.15, 11.18, and 11.21 provide regional \r\nassessments on past, attributed and projected changes in \r\ndroughts. The assessment is subdivided in three drought categories \r\ncorresponding to four drought types: i) meteorological droughts, \r\nii)  agricultural and ecological droughts, and iii) hydrological \r\ndroughts  (see Section  11.6). A  list of metrics and global studies \r\nused for the assessments is provided below. The evidence from \r\nglobal studies is complemented in each continent with evidence \r\nfrom regional studies. An overview of studies considered for the \r\nassessments in projections is provided in Table 11.3."


id: 55958b4125f2d8e80aff9111369c34c7
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 12326
content:
"Agricultural and ecological droughts are primarily assessed based \r\non observed and projected changes in total column soil moisture, \r\ncomplemented by evidence on changes in surface soil moisture, \r\nwater-balance (precipitation minus evapotranspiration (ET)) and \r\nmetrics driven by precipitation and atmospheric evaporative demand \r\n(AED) such as the SPEI and PDSI (Section 11.6). In the latter, only \r\nstudies including estimates based on the Penman-Monteith equation \r\n(SPEI-PM and PDSI-PM) are considered because of biases associated \r\nwith temperature-only approaches (Section  11.6). Medium to "


id: f6cb76d2189065b74a2f81a1eb5b1106
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
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index: climate_gpt_v2
vector_id: 40786
content:
"high confidence in drying was assigned in the assessment for arid \r\nregions if a  signal was also identifiable in total soil moisture in \r\naddition to surface soil moisture or metrics that combine AED and \r\nprecipitation, which tend to dry more in these regions. For observed \r\nchanges, evidence is drawn from several sources: Padron et al. \r\n(2020) for changes in precipitation minus ET, as well as soil moisture \r\nfrom the multi-model Land Surface Snow and Soil Moisture Model \r\nIntercomparison Project within CMIP6 (11.SM; van Den Hurk et al., \r\n2016); Greve et al. (2014) for changes in precipitation minus ET, and \r\nprecipitation minus AED; Spinoni et al. (2019) for changes in SPEI-PM; \r\nand Dai and Zhao (2017) for changes in PDSI-PM. "


id: 5b9fa39b3065073f192e3aa301cf57dd
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 13374
content:
"of global warming, evidence is mostly drawn from: Cook et al. (2020) \r\n(SSP3-7.0, 2071-2100) and the Chapter 11 Supplementary Material \r\n(11.SM) based on CMIP6 for changes in total column and surface \r\nsoil moisture; and from Vicente-Serrano et al. (2020c) for changes \r\nin SPEI-PM based on CMIP5. No global-scale studies with regional\u0002scale information are available for the attribution of agricultural \r\nand ecological droughts, so this assessment is based on regional \r\ndetection and attribution or event attribution studies."


id: 295bde806f25a220984268ef25d05e10
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
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index: climate_gpt_v2
vector_id: 4493
content:
"Hydrological droughts are assessed based on observed and projected \r\nchanges in low flows, complemented by information on changes in \r\nmean runoff. For observed changes, evidence is drawn from three \r\nstudies (Dai and Zhao, 2017; Gudmundsson et al., 2019, 2021). For \r\nprojected changes at 1.5degC of global warming, evidence is drawn from \r\nTouma et al. (2015) based on analyses of the Standardized Runoff \r\nIndex (SRI) (CMIP5, based on 2010-2054 compared to 1961-2005), \r\ncomplemented with regional studies when available. For projected \r\nchanges at 2degC of global warming, evidence is also drawn from Cook \r\net al. (2020) for changes in runoff in CMIP6 (Scenario SSP1-2.6, 2071-\r\n2100), and from J. Zhai et al. (2020) for changes in low flows based \r\non simulations with a single model. For projected changes at 4degC of \r\nglobal warming, evidence is drawn from: Touma et al. (2015) based on \r\nCMIP5 analyses of SRI; Cook et al. (2020) for changes in surface and "


id: 2312845499d2c668f8bdac6fb7d888b9
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
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index: climate_gpt_v2
vector_id: 3364
content:
"For projections at 1.5degC of global warming, evidence is drawn \r\nfrom: L. Xu et al. (2019), based on CMIP5; 11.SM based on CMIP6 \r\nfor changes in total column and surface soil moisture; and from \r\nNaumann et al. (2018) for changes in SPEI-PM, based on EC-Earth \r\nsimulations driven with SSTs from seven CMIP5 Earth system models. \r\nFor projections at 2degC of global warming, evidence is drawn from \r\nL. Xu et al. (2019) based on CMIP5, and Cook et al. (2020) (SSP1-2.6, \r\n2071-2100 compared to pre-industrial) and the Chapter  11 \r\nSupplementary Material (11.SM) based on CMIP6, for changes in \r\ntotal column and surface soil moisture; evidence is also drawn from \r\nNaumann et al. (2018) for changes in SPEI-PM. For projections at 4degC "


id: d2229dfc54ab3ceca38f058f5137ef46
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content:
" 11.3 | Global analyses considered for the assessments of drought projections. MET refers to meteorological droughts, AGR/ECOL to agricultural and ecological \r\nhts, and HYDR to hydrological droughts."


id: 8d0901b3dda36aaa31af8dafdb5b3695
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updated_at: 2023-04-19 13:21:40
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content:
"a\r\n CMIP5 and CMIP6: Coupled Model Intercomparison Project Phases 5/6; CORDEX: Coordinated Regional Downscaling Experiment; GCMs: global climate models; RCMs: \r\nregional climate models; SST: sea surface temperatures; ISI-MIP: Inter-Sectoral Impact Model Intercomparison Project; GHMs: Global Hydrological Models; CDD: consecutive \r\ndry days index; SPI: Standardized Precipitation Index; SRI: Standardized Runoff Index; SPEI-PM: Penman-Monteith-based Standardized Precipitation Evapotranspiration Index. "


id: 9cfe2faafb7f67ccf36fd708417778b2
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vector_id: 24861
content:
"total runoff based on CMIP6; and Giuntoli et al. (2015) for changes in \r\nlow flows based on the Inter-Sectoral Impact Model Intercomparison \r\nProject (ISI-MIP) based on six Global Hydrological Models (GHMs) and \r\nfive GCMs, including an analysis of inter-model signal-to-noise ratio. \r\nOne global-scale study with regional-scale information is available for \r\nthe attribution of hydrological droughts (Gudmundsson et al., 2021), \r\nbut only in a few AR6 regions. This information was complemented \r\nwith evidence from regional detection and attribution, and event \r\nattribution studies when available."


id: 1b758bff59498bd3930c84ee2df5fda0
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 2010
content:
"Alexis Berg, Tim Brodribb, Jamie Hannaford, Nate McDowell, \r\nJack Scheff, Peter Stott, Lena Tallaksen, Peter Thorne, Francis Zwiers."


id: c99712bd6555fc022acb77565678122e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 32791
content:
"Human-caused climate change alters the frequency and intensity of climate variables (e.g., surface temperature) \r\nand phenomena (e.g., tropical cyclones) in a variety of ways. We now know that the ways in which average and \r\nextreme conditions have changed (and will continue to change) depend on the variable and the phenomenon \r\nbeing considered. Changes in local surface temperature extremes closely follow the corresponding changes in \r\nlocal average surface temperatures. On the contrary, changes in precipitation extremes (heavy precipitation) \r\ngenerally do not follow those in average precipitation, and can even move in the opposite direction (e.g., with \r\naverage precipitation decreasing but extreme precipitation increasing)."


id: 6bba87a418439cf13b3920ee9d216b7a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 16260
content:
"Climate change will manifest very differently depending on which region, season and variable we are interested \r\nin. For example, over some parts of the Arctic, temperatures will warm at rates about three to four times higher \r\nduring winter compared to summer months. And in summer, most of northern Europe will experience larger \r\ntemperatures increases than most places in south-east South America and Australasia, with differences that can \r\nbe larger than 1degC, depending on the level of global warming. In general, differences across regions and seasons \r\narise because the underlying physical processes differ drastically across regions and seasons."


id: 8cff9a2967ad6aae6fe1f2d8cc417afc
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 21990
content:
"In summary, the specific relationship between changes in average and extreme conditions strongly depends on \r\nthe variable or phenomenon being considered. At the local scale, average and extreme surface temperature \r\nchanges are strongly related, while average and extreme precipitation changes are often weakly related. For \r\nboth variables, the changes in average and extreme conditions vary strongly across different places due to the \r\neffect of local and regional processes."


id: dab6f9c0cd893dbea56d7b3b5ae2247b
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 35771
content:
"FAQ 11.1, Figure 1 | Global maps of future changes in surface temperature (top panels) and precipitation (bottom panels) for long-term \r\naverage (left) and extreme conditions (right). All changes were estimated using the Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble \r\nmedian for a scenario with a global warming of 4degC relative to 1850-1900 temperatures. Average surface temperatures refer to the warmest three-month season \r\n(summer in mid- to high latitudes) and extreme temperatures refer to the hottest day in a year. Precipitation changes, which can include both rainfall and snowfall \r\nchanges, are normalized by 1850-1900 values and shown as a percentage; extreme precipitation refers to the largest daily precipitation in a year."


id: cffb99c0da7858ad9feeeb4ff572b461
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 33941
content:
"Climate change has already increased the magnitude and frequency of extreme hot events and decreased \r\nthe magnitude and frequency of extreme cold events, and, in some regions, intensified extreme precipitation \r\nevents. As the climate moves away from its past and current states, we will experience extreme events that \r\nare unprecedented, either in magnitude, frequency, timing or location. The frequency of these unprecedented \r\nextreme events will rise with increasing global warming. Additionally, the combined occurrence of multiple \r\nunprecedented extremes may result in large and unprecedented impacts."


id: 28e36c74e7ca57811dee4f33b5854e7a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 4412
content:
"Unprecedented extremes - that is, events not experienced in the past - will occur in the future in five different ways \r\n(FAQ 11.2, Figure 1). First, events that are considered to be extreme in the current climate will occur in the future \r\nwith unprecedented magnitudes. Second, future extreme events will also occur with unprecedented frequency. \r\nThird, certain types of extremes may occur in regions that have not previously encountered those types of events. \r\nFor example, as the sea level rises, coastal flooding may occur in new locations, and wildfires are already occurring \r\nin areas, such as parts of the Arctic, where the probability of such events was previously low. Fourth, extreme events \r\nmay also be unprecedented in their timing. For example, extremely hot temperatures may occur either earlier or \r\nlater in the year than they have in the past."


id: 8ed0442e0a43921aa1812bd5d356a4e4
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 22311
content:
"Finally, compound events  - where multiple extreme \r\nevents of either different or similar types occur \r\nsimultaneously and/or in succession  - may be more \r\nprobable or severe in the future. These compound \r\nevents can often impact ecosystems and societies more \r\nstrongly than when such events occur in isolation. \r\nFor example, a drought along with extreme heat will \r\nincrease the risk of wildfires and agriculture damages \r\nor losses. As individual extreme events become more \r\nsevere as a  result of climate change, the combined \r\noccurrence of these events will create unprecedented \r\ncompound events. This could exacerbate the intensity \r\nand associated impacts of these extreme events."


id: 10303cb0e3d1b784126a194d940adf85
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 34
content:
"Unprecedented extremes have already occurred in \r\nrecent years, relative to the 20th century climate. Some \r\nrecent extreme hot events would have had very little \r\nchance of occurring without human influence on the \r\nclimate (see FAQ 11.3). In the future, unprecedented \r\nextremes will occur as the climate continues to warm. \r\nThose extremes will happen with larger magnitudes \r\nand at higher frequencies than previously experienced. \r\nExtreme events may also appear in new locations, at \r\nnew times of the year, or as unprecedented compound \r\nevents. Moreover, unprecedented events will become \r\nmore frequent with higher levels of warming, for \r\nexample at 3degC of global warming compared to 2degC of \r\nglobal warming."


id: 9fc258be8ba69e2493742391699a7275
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 25313
content:
"FAQ 11.2, Figure 1 | New types of unprecedented extremes that will \r\noccur as a result of climate change."


id: d8b4a0d906b2155cbe8d37e470f14430
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 35418
content:
"While it is difficult to identify the exact causes of a particular extreme event, the relatively new science of event \r\nattribution is able to quantify the role of climate change in altering the probability and magnitude of some \r\ntypes of weather and climate extremes. There is strong evidence that characteristics of many individual extreme \r\nevents have already changed because of human-driven changes to the climate system. Some types of highly \r\nimpactful extreme weather events have occurred more often and have become more severe due to these human \r\ninfluences. As the climate continues to warm, the observed changes in the probability and/or magnitude of some \r\nextreme weather events will continue as the human influences on these events increase. "


id: f7372519cda48fbea96a87956409a363
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 40870
content:
"Attributable increases in probability and magnitude \r\nhave been identified consistently for many hot \r\nextremes. Attributable increases have also been found \r\nfor some extreme precipitation events, including \r\nhurricane rainfall events, but these results can vary \r\namong events. In some cases, large natural variations \r\nin the climate system prevent attributing changes in \r\nthe probability or magnitude of a specific extreme to \r\nhuman influence. Additionally, attribution of certain \r\nclasses of extreme weather (e.g., tornadoes) is beyond \r\ncurrent modelling and theoretical capabilities. As \r\nthe climate continues to warm, larger changes in "


id: b2ebec861e34322ac4ef68338520c152
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 28715
content:
"probability and magnitude are expected and, as a result, it will be possible to attribute future temperature and \r\nprecipitation extremes in many locations to human influences. Attributable changes may emerge for other types \r\nof extremes as the warming signal increases."


id: 214ca7772d0fd3e49a8adf32553dfa93
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 3076
content:
"In conclusion, human-caused global warming has resulted in changes in a wide variety of recent extreme weather \r\nevents. Strong increases in probability and magnitude, attributable to human influence, have been found for \r\nmany heatwaves and hot extremes around the world."


id: 49a8697095abaaf47ecdd83bc274eafc
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 10189
content:
"Table 11.4 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for temperature \r\nextremes in Africa, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.2 for details. CMIP6: Coupled Model Intercomparison Project Phase 6; TXx: hottest daily \r\nmaximum temperature; TNn: coldest daily minimum temperature; CORDEX: Coordinated Regional Downscaling Experiment; RCM: regional climate model."


id: 863bb7d2dc5b74f073c7c4160819ffb
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 20771
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of \r\nTXx events and a robust \r\ndecrease in the intensity and \r\nfrequency of TNn events (Li \r\net al., 2021; 11.SM). Median \r\nincrease of more than 3.5degC \r\nin the 50-year TXx and TNn \r\nevents compared to the 1degC \r\nwarming level (Li et al., 2021) \r\nand more than 5degC in annual \r\nTXx and TNn compared \r\nto pre-industrial (11.SM)\r\nAdditional evidence from \r\nCMIP5 and RCM simulations \r\nfor an increase in the intensity \r\nand frequency of hot extremes, \r\nand decrease in the intensity and \r\nfrequency of cold extremes (Giorgi \r\net al., 2014; Tomozeiu et al., 2014; \r\nEngelbrecht et al., 2015; Nastos \r\nand Kapsomenakis, 2015; Zollo \r\net al., 2016; Cardoso et al., 2019; \r\nCardell et al., 2020; Driouech \r\net al., 2020; Coppola et al., 2021a)"


id: ad3cfc3464bdf70a5e1cf226b52e7168
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 27717
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency \r\nof TXx events and a robust \r\ndecrease in the intensity and \r\nfrequency of TNn events (Li \r\net al., 2021; 11.SM). Median \r\nincrease of more than 1degC \r\nin the 50-year TXx and TNn \r\nevents compared to the 1degC \r\nwarming level (Li et al., 2021) \r\nand more than 2.5degC in \r\nannual TXx and TNn compred \r\nto pre-industrial (11.SM)"


id: a61bed31ea9bf6afcda637c20af713c6
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 26444
content:
"Additional evidence from \r\nCMIP5 and RCM simulations \r\nfor an increase in the \r\nintensity and frequency of hot \r\nextremes, and decrease in the \r\nintensity and frequency of cold \r\nextremes (Tomozeiu et al., 2014; \r\nNastos and Kapsomenakis, 2015; \r\nZollo et al., 2016; Abaurrea et al., \r\n2018; Weber et al., 2018; Cardoso \r\net al., 2019; Cardell et al., 2020; \r\nCoppola et al., 2021a)"


id: 444ab5e6379a6e437c94e2045367fb3e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 9253
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of \r\nTXx events and a robust \r\ndecrease in the intensity and \r\nfrequency of TNn events (Li \r\net al., 2021; 11.SM). Median \r\nincrease of more than 3degC \r\nin the 50-year TXx and TNn \r\nevents compared to the 1degC \r\nwarming level (Li et al., 2021) \r\nand more than 4.5degC in annual \r\nTXx and TNn compared to \r\npre-industrial (11.SM)"


id: 53c2631052e972610459eaf4bef3d375
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 12005
content:
"Additional evidence from \r\nCMIP5/CMIP3 and CORDEX \r\nsimulations for an increase in \r\nthe intensity and frequency \r\nof hot extremes (Giorgi et al., \r\n2014; Engelbrecht et al., 2015; \r\nCoppola et al., 2021a) "


id: d3b8903f10e55c3f63d2d232aaccd2cb
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 34591
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase \r\nof more than 2.5degC in the \r\n50-year TXx and TNn events \r\ncompared to the 1degC warming \r\nlevel (Li et al., 2021) and \r\nmore than 4degC in annual \r\nTXx and TNn compared to \r\npre-industrial (11.SM)\r\nAdditional evidence from \r\nCMIP5/CMIP3 and CORDEX \r\nsimulations for an increase in \r\nthe intensity and frequency \r\nof hot extremes (Giorgi et al., \r\n2014; Engelbrecht et al., 2015; \r\nCoppola et al., 2021a) "


id: fc6c4bbbcb6ae6d7a0244e4082e3a625
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 41779
content:
"Additional evidence from \r\nCMIP5/CMIP3 and CORDEX \r\nsimulations for an increase in \r\nthe intensity and frequency \r\nof hot extremes (Giorgi et al., \r\n2014; Engelbrecht et al., 2015; \r\nCoppola et al., 2021a)"


id: 5a686991544031e52fd428f0985acd14
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 13162
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of more \r\nthan 2.5degC in the 50-year TXx \r\nand TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 923b0a790801dedf9c8f4be50e38965e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 22949
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of more \r\nthan 2.5degC in the 50-year TXx \r\nand TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 86c4de9697f02d3bd9c283eb17f79b2e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 20877
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 2degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 3.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 3eb6572c4531650b7ef7076c993b3e5f
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 8222
content:
"Table 11.5 |  Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for heavy \r\nprecipitation in Africa, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.3 for details."


id: 10dcbb437ede5841f61a0915e7bb8805
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 157
content:
"CMIP6 models project a robust \r\nincrease in the intensity and \r\nfrequency of heavy precipitation \r\n(Li et al., 2021; 11.SM). Median \r\nincrease of more than 25% in \r\nthe 50-year Rx1day and Rx5day \r\nevents compared to the 1degC \r\nwarming level (Li et al., 2021), \r\nand more than 30% in annual \r\nRx1day and Rx5day, and 15% \r\nin annual Rx30day compared \r\nto pre-industrial (11.SM)"


id: f927ea38803536a3780cfa1a7536ea21
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 41198
content:
"Additional evidence from \r\nCMIP5 and CORDEX simulations \r\nfor an increase in the intensity \r\nof heavy precipitation (Giorgi \r\net al., 2014; Akinsanola and \r\nZhou, 2019; Dosio et al., 2019; \r\nCoppola et al., 2021b)"


id: 5320e4c9a2e8f4516844e89199576e50
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 11896
content:
"Table 11.6 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for meteorological \r\ndroughts (MET), agricultural and ecological droughts (AGR/ECOL), and hydrological droughts (HYDR) in Africa, subdivided by AR6 regions. See Sections \r\n1191 and 1194 for details"


id: 555f4befa0b25a1bdd8a2d5467848722
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 12298
content:
"Table 11.7 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for temperature \r\nextremes in Asia, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.2 for details."


id: 263498bf24a5c3011c1e7ad8961bab3e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 3889
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021). \r\nMedian increase of more \r\nthan 4.5degC in the 50-year TXx \r\nand TNn events compared \r\nto the 1degC warming level \r\n(Li et al., 2021)"


id: abfdd2b5c0505a8d4de17403016acc73
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 27502
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase \r\nof more than 4.5degC in the \r\n50-year TXx and TNn events \r\ncompared to the 1degC warming \r\nlevel (Li et al., 2021) and more \r\nthan 5.5degC in annual TXx \r\nand TNn compared to pre\u0002industrial (11.SM)"


id: d7e0dfe9ca9e4cae1d9044f8214120e0
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 35291
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase \r\nof more than 1.5degC in the \r\n50-year TXx and TNn events \r\ncompared to the 1degC warming \r\nlevel (Li et al., 2021) and \r\nmore than 2.5degC in annual \r\nTXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 983c62a9401b400ffa6418f4be7447b
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 23993
content:
"Additional evidence from \r\nCMIP5 and RCM simulations \r\nfor an increase in the intensity \r\nand frequency of hot extremes \r\nand decrease in the intensity \r\nand frequency of cold extremes \r\n(Xu et al., 2017; Han et al., 2018; \r\nKhlebnikova et al., 2019b)"


id: 660d77b29b9904545af15a9fbc04871a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 15214
content:
"CMIP6 models project \r\na robust increase in the \r\nntensity and frequency of TXx \r\nevents and a robust decrease \r\nn the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase \r\nof more than 3.5degC in the \r\n50-year TXx  and TNn events \r\ncompared to the 1degC warming \r\nevel (Li et al., 2021) and \r\nmore than 5.5degC in annual \r\nTXx and TNn compared \r\nto pre-industrial (11.SM)"


id: b1d1fca808f462791cb50f6ad304e0a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 28506
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 6degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)\r\nAdditional evidence from CMIP5 \r\nsimulations for an increase in \r\nthe intensity and frequency of \r\nhot extremes and decrease in \r\nthe intensity and frequency of \r\ncold extremes (Han et al., 2018)"


id: c5e123cdfc9dfda0235b632e1889f01a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 32122
content:
"CMIP6 models project \r\na robust increase in the \r\nntensity and frequency of TXx \r\nevents and a robust decrease \r\nn the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 4.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 5.5degC \r\nn annual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 48e539f40c4ee3412c4337f124778ac9
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 10046
content:
"Additional evidence from \r\nCMIP5 and RCM simulations for  \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes (Xu \r\net al., 2017; Han et al., 2018; \r\nKhlebnikova et al., 2019b) "


id: 28e1d64514b9366779b61c883785651d
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 4410
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 4.5degC in the 50-year \r\nTXx and TNn events compared \r\nto the 1degC warming level (Li \r\net al., 2021) and more than \r\n5degC in annual TXx and TNn \r\ncompared \r\nto pre-industrial (11.SM)"


id: 83dc37d5bc91d23bc162f74c48ad5f8c
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 20343
content:
"Additional evidence from CMIP5 \r\nand RCM simulations for an \r\nincrease in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Xu et al., 2017; Han et al., 2018; \r\nKhlebnikova et al., 2019b)."


id: 8356e4fe1c20a76711035d860fdcc137
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 20239
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 4degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 5c33bb2929f5a56261e4370085660150
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 13475
content:
"Additional evidence from \r\nCMIP5 and RCM simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Seo et al., 2014; Zhou \r\net al., 2014; Y. Xu et al., 2016; \r\nX.Wang et al., 2017; Y.Wang \r\net al. 2017; Guo et al., 2018; \r\nD. Li et al., 2018; Shi et al., 2018; \r\nSui et al., 2018; Imada et al., \r\n2019; C. Sun et al., 2019)"


id: 18aa3ce78c46ebd7974b3ca031ef5197
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 1554
content:
"Additional evidence from \r\nCMIP5 and RCM simulations \r\nfor an increase in the \r\nintensity and frequency of \r\nhot extremes and decrease in \r\nthe intensity and frequency \r\nof cold extremes (Seo et al., \r\n2014; Zhou et al., 2014; Y. Xu \r\net al., 2016; X. Wang et al., 2017; \r\nY.Wang et al., 2017; Guo et al., \r\n2018; D. Li et al., 2018; Shi et al., \r\n2018; Sui et al., 2018; Imada \r\net al., 2019; C. Sun et al., 2019) "


id: 3f6f5eb1bde4c4162695ed66b9e37ddc
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 8344
content:
"CMIP6 models project \r\na robust increase in the \r\nntensity and frequency of TXx \r\nevents and a robust decrease \r\nn the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 3.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 5.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 658a1cbf7d379d0204bff78aba5500c4
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 15132
content:
"Additional evidence \r\nfrom CMIP5 simulations \r\nfor an increase in the \r\nntensity and frequency of \r\nhot extremes and decrease \r\nn the intensity and \r\nfrequency of cold extremes \r\n(Han et al., 2018)"


id: bd1d0f80c089c49fbe424d28d6162386
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 30523
content:
"Additional evidence from CMIP5 \r\nand RCM simulations for an \r\nincrease in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Zhou et al., 2014; Singh and \r\nGoyal, 2016; W. Zhang et al., \r\n2016b; Xu et al., 2017; Han \r\net al., 2018; C. Li et al., 2018)"


id: f21bc76c011ba56a63bc2c2ce13b8020
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 39985
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 3.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: d0756ee70058b27bdb2492c976bd946b
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 34028
content:
"Additional evidence from CMIP5 \r\nand RCM simulations for an \r\nincrease in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Sillmann et al., 2013b; \r\nMurari et al., 2015; Xu et al., \r\n2017; Han et al., 2018; Kharin \r\net al., 2018; Nasim et al., 2018; \r\nS. Ali et al., 2019)"


id: b1d2e1636eeb14e2c98f65972a95dfe2
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 28508
content:
"Additional evidence \r\nfrom CMIP5 and RCM \r\nsimulations for an increase \r\nin the intensity and frequency \r\nof hot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Sillmann et al., \r\n2013b; Murari et al., 2015; Xu \r\net al., 2017; Han et al., 2018; \r\nKharin et al., 2018; Nasim et al., \r\n2018; S. Ali et al., 2019)"


id: 46b7cdc9c37c7e1f8e2051693456348d
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 9647
content:
"CMIP6 models project \r\na robust increase in the \r\nntensity and frequency of TXx \r\nevents and a robust decrease \r\nn the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 2.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 3cd6fcd195d8ee79bd149dfc1a53587e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 7887
content:
"Additional evidence \r\nfrom CMIP5 simulations \r\nfor an increase in the \r\nintensity and frequency of \r\nhot extremes and decrease in \r\nthe intensity and frequency \r\nof cold extremes (Xu et al., 2017; \r\nKharin et al., 2018)"


id: 36d8a2c61e923b4f8225b608092bc98
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 6879
content:
"Table 11.8 |  Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for heavy \r\nprecipitation in Asia, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.3 for details."


id: 701d7d409fae330d05ddda9778b5762
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 16976
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of heavy \r\nprecipitation (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 15% in the 50-year \r\nRx1day and Rx5day events \r\ncompared to the 1degC warming \r\nlevel (Li et al., 2021) and more \r\nthan 15% in annual Rx1day, \r\nRx5day, and Rx30day compared \r\nto pre-industrial (11.SM)"


id: 87e7d47566e0eb2925aa0f2504e1e464
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 21067
content:
"Additional evidence from \r\nCMIP5 simulations for an \r\nncrease in the intensity of heavy \r\nprecipitation (Sillmann et al., \r\n2013b; Xu et al., 2017; Han \r\net al., 2018; Kharin et al., 2018; \r\nKhlebnikova et al., 2019a)"


id: ce78eaf53f1eac23a8e76746f99f4705
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 33673
content:
"Additional evidence from \r\nCMIP5 simulations for an \r\nincrease in the intensity of heavy \r\nprecipitation (Sillmann et al., \r\n2013b; Xu et al., 2017; Han \r\net al., 2018; Kharin et al., 2018; \r\nKhlebnikova et al., 2019a)"


id: fe554209ff9617fd8f29f4a1b7f7f0ad
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 42118
content:
"Table 11.9 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for meteorological \r\ndroughts (MET), agricultural and ecological droughts (AGR/ECOL), and hydrological droughts (HYDR) in Asia, subdivided by AR6 regions. See Sections 11.9.1 \r\nand 11.9.4 for details."


id: db53bbb005ac5465ad3d45344e245888
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 35855
content:
"CMIP6 models project \r\na robust increase in the \r\nntensity and frequency of TXx \r\nevents and a robust decrease \r\nn the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 3degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 3.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: bcffb2b54da558ba09bd5954b67b9348
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 30495
content:
"Additional evidence \r\nfrom CMIP5 simulations \r\nfor an increase in the \r\nintensity and frequency of \r\nhot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Alexander \r\nand Arblaster, 2017; Herold \r\net al., 2018; Grose et al., 2020; \r\nEvans et al., 2021)"


id: 7d43f09dd6eef0c7c621552fa1957455
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 19216
content:
"Additional evidence \r\nfrom CMIP5 simulations \r\nfor an increase in the \r\nntensity and frequency of \r\nhot extremes and decrease \r\nn the intensity and frequency \r\nof cold extremes (Alexander \r\nand Arblaster, 2017; Herold \r\net al., 2018; Grose et al., 2020; \r\nEvans et al., 2021)"


id: 15b67f31da2fcdc404cc1e1568305321
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 1035
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 2.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 3b77c5011f22f67411921250f99bb4fa
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 7647
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 2.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 3.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 485f131210cc5e9990fecfcba61781d0
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 9946
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 0.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 1degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: a1c2c4977404c99211fd88c2f57c3848
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 25683
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 0.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 1.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 54fa6e30df181d9e5fd7b0bcc300e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 12221
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 2degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 2.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 16f137372378aee01bb16dc4d92abb27
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 1258
content:
"Table 11.11 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for heavy \r\nprecipitation in Australasia, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.3 for details."


id: 86a7663c239d8a7215a0026384786d42
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 20853
content:
"Table 11.12 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for meteorological \r\ndroughts (MET), agricultural and ecological droughts (AGR/ECOL), and hydrological droughts (HYDR) in Australasia, subdivided by AR6 regions.\r\nSee Sections 11.9.1 and 11.9.4 for details."


id: 16dcdd5ad76e74d5ecbf4846886e1577
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 1238
content:
"Table 11.13 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for temperature \r\nextremes in Central and South America, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.2 for details."


id: 49ad10210bf6e76748d2fee6723136a0
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 10192
content:
"Additional evidence from \r\nCMIP5 and RCM simulations \r\nfor an increase in the \r\nintensity and frequency of \r\nhot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Chou et al., \r\n2014a; Angeles-Malaspina et al., \r\n2018; Coppola et al., 2021b)"


id: a14051eaeeda279f8cba3f75b2136439
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 25591
content:
"Additional evidence from \r\nCMIP5 and RCM simulations \r\nfor an increase in the \r\nintensity and frequency of \r\nhot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Hall \r\net al., 2013; Chou et al., 2014a; \r\nAngeles-Malaspina et al., 2018; \r\nCoppola et al., 2021b)"


id: 72562310810f608dca7851cde742e4fc
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 17359
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 2degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 7d746d01543eb66d038e6030ba43a7bb
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 19240
content:
"Additional evidence from \r\nCMIP5/CMIP3 and RCM \r\nsimulations for an increase \r\nin the intensity and frequency \r\nof hot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Chou et al., \r\n2014a; Lopez-Franca et al., 2016; \r\nCoppola et al., 2021b) "


id: 7a1d3c01861aa557bd15be4a7e42bd75
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 18682
content:
"Additional evidence from \r\nCMIP5/CMIP3 and RCM \r\nsimulations for an increase in \r\nthe intensity and frequency \r\nof hot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Chou et al., \r\n2014a; Lopez-Franca et al., 2016; \r\nCoppola et al., 2021b) "


id: 41c292229aad085cdb5554981ea1e54e
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 8763
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 2.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 8ef6eb3d4de4da7a3bff25d6b35bddae
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 22342
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 3degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: d867b35583f1db98202b57deb2eeb6cb
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 35373
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 3.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 3.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 1c35dad094319395e8c1f068c068e7b6
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 2156
content:
"Additional evidence from \r\nCMIP5/CMIP3 and RCM \r\nsimulations for an increase in \r\nthe intensity and frequency \r\nof hot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Chou et al., \r\n2014a; Lopez-Franca et al., 2016; \r\nCoppola et al., 2021b)"


id: da213d984c6b6af1a972888cec02210a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 35672
content:
"Table 11.14 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for heavy \r\nprecipitation in Central and South America, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.3 for details."


id: 187f93535d7cec81fe1dfd84c9bac8c
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 1522
content:
"Table 11.15 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for meteorological \r\ndroughts (MET), agricultural and ecological droughts (AGR/ECOL), and hydrological droughts (HYDR) in Central and South America, subdivided by AR6 \r\nregions. See Sections 11.9.1 and 11.9.4 for details. "


id: 50aa8e32bd1e5d01505fc7885afdbf29
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 11466
content:
"Table 11.16 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for temperature \r\nextremes in Europe, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.2 for details. "


id: e4d9c7ea55185bae03a1e0ce470f377b
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 37544
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021). \r\nMedian increase of more than \r\n5degC in the 50-year TXx and TNn \r\nevents compared to the 1degC \r\nwarming level (Li et al., 2021)"


id: f17079241aa26de56a74266b3f1bb4c5
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 39864
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 1degC in the 50-year \r\nTXx and TNn events compared \r\nto the 1degC warming level (Li \r\net al., 2021) and more than \r\n2.5degC in annual TXx and TNn \r\ncompared \r\nto pre-industrial (11.SM)"


id: 41ae187b3c696a0bf38df8d22f57aba7
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 8744
content:
"Additional evidence from CMIP5 \r\nand CORDEX simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Wehner et al., 2018b; Cardell \r\net al., 2020)"


id: 38a21b7a23f4bb381880f177122b793f
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 7168
content:
"Additional evidence from \r\nCMIP5 and CORDEX \r\nsimulations for an increase in \r\nthe intensity and frequency \r\nof hot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Sillmann et al., \r\n2013b; Cardell et al., 2020)"


id: 761251acb3425dc34a01ee336268c90f
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 17999
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 3.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: b0b3c36e685b67fa6310eefa79f1d0d
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 28316
content:
"Additional evidence from CMIP5 \r\nand RCM simulations for an \r\nincrease in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Giorgi et al., 2014; Tomozeiu \r\net al., 2014; Engelbrecht et al., \r\n2015; Nastos and Kapsomenakis, \r\n2015; Zollo et al., 2016; Cardoso \r\net al., 2019; Cardell et al., 2020; \r\nDriouech et al., 2020; Coppola \r\net al., 2021a)"


id: 8841fa05f966d6d89e25b2437eb4764a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 21126
content:
"Additional evidence from \r\nCMIP5 and RCM simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Tomozeiu et al., 2014; Nastos \r\nand Kapsomenakis, 2015; \r\nZollo et al., 2016; Abaurrea \r\net al., 2018; Weber et al., \r\n2018; Cardoso et al., 2019; \r\nCardell et al., 2020; Coppola \r\net al., 2021a)"


id: cee28c56b888b47f80b5c48e74a2b3f2
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 33741
content:
"CMIP6 models project \r\na robust increase in the \r\nntensity and frequency of TXx \r\nevents and a robust decrease \r\nn the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 5.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 6degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 3a7529cf75c4062074903bb9f8094761
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 7484
content:
"Additional evidence from \r\nCMIP5 and RCM simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes (Lau \r\nand Nath, 2014; Lhotka et al., \r\n2018)"


id: 3a8590f8a844300b7e4e64226825ad52
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 7500
content:
"CMIP6 models project \r\na robust increase in the \r\nntensity and frequency of TXx \r\nevents and a robust decrease \r\nn the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 4.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 5.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: b9c91b80f7b17351449fecf1e635d6f7
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 29897
content:
"Additional evidence from CMIP5 \r\nand CORDEX simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Wehner et al., 2018b; \r\nKhlebnikova et al., 2019b; \r\nCardell et al., 2020)"


id: 5f28f953d25c0bd3ec3cc11ca779b443
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 14044
content:
"Additional evidence from CMIP5 \r\nand CORDEX simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Sillmann et al., 2013b; \r\nKhlebnikova et al., 2019b; \r\nCardell et al., 2020)"


id: 12a75186a08cbbc75ab1ceb4dd61ac7a
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 487
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 4.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: c45220679a8a3032f50e86e0c474cbaf
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 31831
content:
"Additional evidence \r\nfrom CMIP5 simulations \r\nfor an increase in the \r\nintensity and frequency of \r\nhot extremes and decrease in \r\nthe intensity and frequency \r\nof cold extremes (Laliberte et al., \r\n2015; Forzieri et al., 2016; Dosio \r\nand Fischer, 2018; Jacob et al., \r\n2018; Sigmond et al., 2018)"


id: 54837f6bacd20f8dedd07a2897d18d72
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 12145
content:
"Table 11.17 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for heavy \r\nprecipitation in Europe, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.3 for details."


id: 736a8e3c8f1a27d6c26b70adb65e2bbc
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 17561
content:
"High confidence: Increase. \r\nWith high confidence\r\nCMIP5 and CMIP6 (and \r\nEURO-CORDEX) show \r\na decline in winter and \r\nsummer total precipitation \r\nand increase in number of \r\nCDD. Drought intensity and \r\nfrequency increase with high \r\nconfidence, particularly in \r\nthe southern Mediterranean \r\n(11.SM; Interactive Atlas; \r\nSamuels et al., 2018; Cardell \r\net al., 2020; Cook et al., \r\n2020; Driouech et al., 2020; \r\nSpinoni et al., 2020; Coppola \r\net al., 2021a; Li et al., 2021)"


id: 566459c785050ad42499b799816a637d
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 12464
content:
"Based on projections at \r\n+3degC: Large decreasing soil \r\nwater availability during \r\ndrought events compared \r\nto 1971-2000, even when \r\naccounting for adaptation \r\nto mean conditions; \r\nmore than three times \r\nlarger signal compared \r\nto response at +1.5degC \r\n(Samaniego et al., 2018)"


id: 3f6ab1fdc3e7eaae348641affef7fc94
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 8343
content:
"Strong decreases of surface \r\nand total soil moisture, in \r\nspring-summer (AMJJAS) \r\nand autumn-winter \r\n(ONDJFM) half years, with \r\nabout twice larger response \r\ncompared to +2degC (Cook \r\net al., 2020)"


id: 1e54011e115355e2a7093849806dd8bf
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 2531
content:
"Decreases of surface and \r\ntotal soil moisture, in \r\nAMJJAS and ONDJFM half \r\nyears (Cook et al., 2020)"


id: 3628dc42b74c8ed6d438ce9bc2856aa6
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 6778
content:
"Very large decrease in soil \r\nmoisture during drought \r\nevents in CMIP6 models \r\nat +4degC vs pre-industrial \r\nbaseline (11.SM) "


id: eb027b71978f78ab87a98dbfe7823366
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 38705
content:
"Decrease in soil moisture \r\nduring drought events \r\nin CMIP6 models at \r\n+2degC vs pre-industrial \r\nbaseline (11.SM) "


id: 912f5690c8c14375befc5cda957b396f
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 22752
content:
"Giuntoli et al. (2015) (five \r\nCMIP5 models driving six \r\nglobal hydrology models): \r\n50-60% increase in \r\nfrequency of days under \r\nlow flow in 2066-2099 \r\ncompared to 1972-2005. \r\nStrong signal-to-noise ratio \r\nin terms of model agreement, \r\nstrongest hot spot globally"


id: a596dfe9699be9ad9f28abfb1b0e3423
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 26372
content:
"Cook et al. (2020) [13 CMIP6 \r\nmodels and SSP3-7.0. Very \r\nstrong decrease (40-60%) of \r\ntotal runoff in spring-summer \r\nhalf-year in southern Europe. \r\nAlso strong decreases \r\n(>20%) for total runoff in \r\nautumn-winter half-year, and \r\nfor surface runoff in both half \r\nyears (AMJJAS, ONDJFM)"


id: 3555a85cce36bf2f3536296ec048eaf6
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 6633
content:
"Table 11.19 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for temperature \r\nextremes in North America, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.2 for details. "


id: 5cf83b7ef61174f07b1a8f9c0f149d7f
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 13623
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 3.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 32f9f206bf1d6b7452c62fa97065f444
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 6232
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of more \r\nthan 4.5degC in the 50-year TXx \r\nand TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 5.5degC in \r\nannual TXx and TNn compared to \r\npre-industrial (11.SM)"


id: 3d736a738a66eb7eddbfc497321be356
created_at: 2023-04-19 13:21:40
updated_at: 2023-04-19 13:21:40
content_type: text
index: climate_gpt_v2
vector_id: 7986
content:
"Additional evidence from CMIP5 \r\nand RCM simulations for an \r\nincrease in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes (Vose \r\net al., 2017; Wehner et al., 2018b)"


id: 2beeed956d9d58acb4d8412be1638daa
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 4982
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 5.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 3671fb69db3312f0e9ec9e0032ca99ab
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 6814
content:
"Additional evidence from \r\nCMIP5 and RCM simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(G. Li et al., 2018; X. Zhang \r\net al., 2019)"


id: b446be19e8de33c62a2167a41d8b9cb8
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 28949
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 4degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: b21b15341458de70320059b4f9dd175e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 28564
content:
"Additional evidence from \r\nCMIP5 and RCM simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Bennett and Walsh, 2015; \r\nG. Li et al., 2018; X. Zhang \r\net al., 2019)"


id: b92f5154a1ae14e40dc03d77df3b681b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 29783
content:
"Table 11.20 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming \r\nprecipitation in North America, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.3 for details. "


id: 31db22bed46f7be8ec05e74b9c0a7dda
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 6022
content:
"Table 11.21 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for meteorological \r\ndroughts (MET), agricultural and ecological droughts (AGR/ECOL), and hydrological droughts (HYDR) in North America, subdivided by AR6 regions.\r\nSee Sections 11.9.1 and 11.9.4 for details."


id: 5640b2b92780eed1732637164d877959
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 12443
content:
"Table 11.A.1 | Common drought metrics, associated drought types, drought indices, general description and associated references."


id: 7941e5b2a62a43c6fd7b33f3e618dd6d
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 18529
content:
"Roshanka Ranasinghe (The Netherlands/Sri Lanka, Australia), Alex C. Ruane (United States of \r\nAmerica), Robert Vautard (France)"


id: 9ac9c68e09fae2caa782193eb495c0bf
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 24472
content:
"Nigel Arnell (United Kingdom), Erika Coppola (Italy), Faye Abigail Cruz (Philippines), Suraje Dessai \r\n(United Kingdom/Portugal), A.K.M. Saiful Islam (Bangladesh), Mohammad Rahimi (Iran), \r\nDaniel Ruiz Carrascal (United States of America/Colombia), Jana Sillmann (Norway/Germany), \r\nMouhamadou Bamba Sylla (Rwanda/Senegal), Claudia Tebaldi (United States of America), \r\nWen Wang (China), Rashyd Zaaboul (United Arab Emirates/Morocco)"


id: c6d26a6ef34b415e456a360283f06644
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 32291
content:
"(Austria), Francesca Raffaele (Italy), Srivatsan Raghavan (Singapore/India), Christophe F. Randin \r\n(Switzerland/France, Switzerland), Johan Reyns (The  Netherlands/Belgium), Lucas Ruiz \r\n(Argentina), Fahad Saeed (Germany/Pakistan), Jean-Baptiste Sallee (France), Marit  Sandstad \r\n(Norway), Clemens  Schwingshackl (Norway, Germany/Italy), Sonia  I. Seneviratne (Switzerland), \r\nAimee B.A. Slangen (The Netherlands), Tannecia S. Stephenson (Jamaica), Anna Steynor (South \r\nAfrica), Markus Stoffel (Switzerland), Benjamin Sultan (France), William V. Sweet (United States \r\nof America), Sophie Szopa (France), Izuru Takayabu (Japan), Moustapha Tall (Rwanda/Senegal), \r\nN'Datchoh Evelyne Toure N'Datchoh (Cote d'Ivoire), Bart van den Hurk (The Netherlands), \r\nSergio M. Vicente-Serrano (Spain), Michalis Vousdoukas (Italy, Greece/Greece), Morgan Wairiu \r\n(Fiji), Prodromos Zanis (Greece), Xuebin Zhang (Canada)"


id: 261b204f4a09062d60840beb0f02b9c2
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 3875
content:
"Ranasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz \r\nCarrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional \r\nImpact and for Risk Assessment. In Climate Change 2021: The Physical Science Basis. Contribution of Working \r\nGroup I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. \r\nZhai, A.  Pirani, S.L.  Connors, C. Pean, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. \r\nLonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekci, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, \r\nCambridge, United Kingdom and New York, NY, USA, pp. 1767-1926, doi:10.1017/9781009157896.014."


id: 29c5ddfc8dfe5e538104dc51c7dd3ad6
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 4576
content:
"Hemisphere (high confidence). Decreasing precipitation will emerge \r\nin a very few regions (Mediterranean, Southern Africa, south-western \r\nAustralia) (medium confidence) by mid-century (medium confidence). \r\nThe anthropogenic forced signal in near-coast relative sea level rise \r\nwill emerge by mid-century RCP8.5 in all regions with coasts, except \r\nin the West Antarctic region where emergence is projected to occur \r\nbefore 2100 (medium confidence). The signal of ocean acidification in \r\nthe surface ocean is projected to emerge before 2050 in every ocean \r\nbasin (high confidence). However, there is limited evidence of drought \r\ntrends emerging above natural variability in the 21st century. {12.5}"


id: 107aff3d9fb556af2da22501726044c9
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 86
content:
"The climatic impact-driver (CID) framework adopted in \r\nChapter 12 allows for assessment of changing climate conditions \r\nthat are relevant for regional impacts and risk assessment. CIDs \r\nare physical climate system conditions (e.g., means, events, extremes) \r\nthat affect an element of society or ecosystems and are thus a priority \r\nfor climate information provision. Depending on system tolerance, \r\nCIDs and their changes can be detrimental, beneficial, neutral or \r\na  mixture of each across interacting system elements, regions and \r\nsociety sectors. Each sector is affected by multiple CIDs and each CID \r\naffects multiple sectors. A CID can be measured by indices to represent \r\nrelated tolerance thresholds. {12.1-12.3}"


id: eee0579125449cfde7378cde1dd06b11
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 39399
content:
"Several impact-relevant changes have not yet emerged \r\nfrom the natural variability but will emerge sooner or later \r\nin this century depending on the emissions scenario (high \r\nconfidence). Increasing precipitation is projected to emerge before \r\nthe middle of the century in the high latitudes of the Northern "


id: 194814df882cc8d702627d6cbf58927
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 1659
content:
"A wide range of region-specific CID changes relative to recent \r\npast are expected with high or medium confidence, by 2050 and \r\nbeyond.Most of these changes concern CIDs related to the water cycle "


id: dcb5d657667ce4790ad76e9b3c771058
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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content:
"occurs multiple times per year under RCP8.5, while under RCP4.5 \r\nit is projected to become a one-in-five-year event, representing at \r\nleast a five fold increase from RCP4.5 to RCP8.5. {12.4, 12.5}"


id: 787527c7cb2963ac580687d054d4feec
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 18396
content:
"There is low confidence in past and future changes of several \r\nCIDs. In nearly all regions there is low confidence in changes in \r\nhail, ice storms, severe storms, dust storms, heavy snowfall and \r\navalanches, although this does not indicate that these CIDs will not \r\nbe affected by climate change. For such CIDs, observations are short \r\nterm or lack homogeneity, and models often do not have sufficient \r\nresolution or accurate parametrization to adequately simulate them \r\nover climate change time scales. {12.4}"


id: 48444d711f8b5613933ea900d6eb52ad
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 9929
content:
"Since AR5, climate change information produced in climate \r\nservice contexts has increased significantly due to scientific, \r\ntechnological advancements and growing user demand (very \r\nhigh confidence). Climate services involve the provision of climate \r\ninformation in such a way as to assist decision-making. These services \r\ninclude appropriate engagement from users and providers, are based \r\non scientifically credible information and expertise, have an effective \r\naccess mechanism, and respond to user needs. Climate services are \r\nbeing developed across regions, sectors, time scales and target users. \r\n{12.6}"


id: c980541850aded9d3377aae0b3cebb53
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 32776
content:
"Climate services are growing rapidly and are highly diverse \r\nin their practices and products (very high confidence). The \r\ndecision-making context, level of user engagement and co-production \r\nbetween scientists, practitioners and intended users are important \r\ndeterminants of the type of climate service developed and its utility \r\nsupporting adaptation, mitigation and risk management decisions. \r\nUser needs and decision-making contexts are very diverse and there \r\nis no universal approach to climate services. {12.6}"


id: 910622322d81acd314b62742b519e1d4
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 22717
content:
"Realization of the full potential of climate services is often \r\nhindered by limited resources for the co-design and co-production \r\nprocess, including sustained engagement between scientists, \r\nservice providers and users (high confidence). Further challenges \r\nrelate to climate services development, provision of climate services, \r\ngeneration of climate service products, communication with users, and \r\nevaluation of the quality and socio-economic value of climate services. \r\nThe development of climate services often uncovers and presents new \r\nresearch challenges to the scientific community. {12.6}"


id: b1e8e31e9adf9ebfa8138c030dc23ef5
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
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content:
"This chapter follows the terminology associated with the framing \r\nintroduced in Chapter  1 (Cross-Chapter Box  1.2) and as found in \r\nAnnex VII: Glossary. The highlighted terms below are introduced and \r\nused extensively in this chapter:"


id: ef3d68992c23a65a2e760bc9a4b15ba3
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
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content:
"Climate change is already resulting in significant societal and \r\nenvironmental impacts and will induce major socio-economic damages \r\nin the future (AR5 WGII). The society, at large, benefits from information \r\nrelated to climate change risks, which enables the development of \r\noptions to protect lives, preserve nature, build resilience and prevent \r\navoidable loss and damage. Climate change can also lead to beneficial \r\nconditions that can be taken into account in adaptation strategies."


id: 7c88a1c1897a2445e3d6a60c4e88c51d
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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vector_id: 19105
content:
"This chapter assesses climate change information relevant for \r\nregional impact and for risk assessment. It complements other \r\nWGI chapters that focus on the physical processes determining \r\nchanges in the climate system and on methods for estimating \r\nregional changes."


id: 4359e3e07a94330e147c9b7a0714de41
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 9066
content:
"In some cases, risk assessments may require climate information \r\nbeyond the CIDs identified in this chapter, with further impacts or \r\nrisk modelling often driven by historical climate forcing datasets \r\n(e.g.,  Ruane et  al., 2021) and full climate scenario time series \r\n(e.g., Lange, 2019) produced using methods described in Chapter 10. \r\nChapter 12 focuses on the assessment of a finite number of drivers \r\nand how they are projected to evolve with climate change, in order \r\nto inform impact and risk assessments."


id: 72e966cdd73c06354ff325389343d2db
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 17464
content:
"The chapter adopts a  regional perspective (continental regions as \r\ndefined in Chapter 1 and used in WGII; see Figure 1.18) on climatic \r\nimpact-drivers to support decision-making across a  wide audience \r\nof global and regional stakeholders in addition to governments \r\n(e.g., civil society organizations, public and private sectors, academia). \r\nWhile the focus here is on future changes, it also describes current \r\nlevels and observed trends of CIDs as an important point of reference \r\nfor informing adaptation strategies."


id: 832f6f4536e92232fc0adae36acd56df
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 20207
content:
"Figure 12.1 summarizes the rationale behind Chapter 12 as the linkage \r\n(also referred to as a 'handshake') between WGI and WGII, illustrating \r\nhow the changing profile of risk may be informed by an assessment \r\nof climatic impact-drivers, aligning WGI findings on physical climate \r\nchange with WGII needs. The implementation of mitigation policy \r\nshifts may modulate hazard probability changes (i.e.,  by reducing \r\nemissions to limit global warming) as well as regional vulnerability and \r\nexposure. The assessment herein is organized around regional climatic \r\nimpact-drivers, but also relates key indices and thresholds to increasing "


id: 26db96c1c79b8d4cf747fd87a3e56024
created_at: 2023-04-19 13:21:41
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vector_id: 3996
content:
"global drivers (such as mean surface warming) as a contribution to the \r\nassessment of 'Reasons for Concern' in WGII (O'Neill et al., 2017)."


id: 2efab86a7eb82b496bb3a7d56883cea2
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 5539
content:
"This section details the methodological approach followed in \r\nChapter 12 and discusses the underlying rationale for the assessments \r\npresented herein. Scientific literature on vulnerability, impacts, and \r\nadaptation (as typically asssessed in IPCC WGII) is examined to identify \r\nrelevant climatic impact-drivers (CIDs) that contribute to sectoral risks \r\nand opportunities. Projected changes in corresponding CID indices are \r\nthen derived from existing literature on changes in the physical climate \r\nsystem, results of other AR6 WGI chapters, and direct calculations \r\nbased on climate projections from several model ensembles."


id: 1dc6563329ed51f6ab778ec5f74777c2
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 2424
content:
"The classification of climatic impact-drivers, the ways that they \r\nchange (e.g.,  their magnitude or intensity, duration, frequency, \r\ntiming and spatial extent) is described in this section. It is \r\nemphasized that this chapter assesses literature relating only \r\nto physical climatic impact-drivers, not their impacts on human \r\nsystems or the environment. Thus, here we do not consider indicators \r\nincluding exposure or vulnerability as assessed by WGII, although \r\nthe selection of climatic impact-drivers is informed by literature \r\nfeeding into WGII."


id: be5bb619ce7071302e3d8f35eb864789
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index: climate_gpt_v2
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content:
"The chapter includes two Cross-Chapter Boxes. Cross-Chapter Box 12.1 \r\nconnects climatic impact-drivers to global climate drivers and levels \r\nof warming as an element of the 'Reasons for Concern' framework \r\n(AR6 WGII Chapter 16). An additional Cross-Chapter Box, including \r\nthree case studies from Europe, Asia and Africa, describes how climate \r\nservices draw upon and apply regional climate information to support \r\nstakeholder decisions (Cross-Chapter Box 12.2)."


id: fea418319845fd1dce63e750f33be25c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 42185
content:
"can be changes in impacts associated with earthquakes that interact \r\nwith climate variables and climate change, such as liquefaction \r\n(e.g.,  Yasuhara et  al., 2012) during earthquakes, or earthquakes \r\ncaused by snow and water changes (Amos et  al., 2014; Johnson \r\net  al., 2017), which are secondary effects on geophysical hazards \r\nthat are not further assessed in this chapter. The characteristics and \r\nphysical description of the climate phenomena or essential climate \r\nvariables associated with each of these CID categories are assessed \r\nand described in previous Chapters 2-11 or Chapter 12 directly as \r\nindicated in Table 12.1. The CID categories are further mapped on to \r\ndifferent sectors in Section 12.3 (Table 12.2)."


id: 992cf76b7ea2f4f3fd6cdc7d9ac57fe6
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content:
"Many of these sectors also include assets affected by climate change \r\nthat are important for recreation and tourism, including elements \r\nof ecosystems services, health and well-being, communities, \r\nlivelihoods and sustainable development (see also Chapter  1 on \r\nthe Intergovernmental Science-Policy Platform on Biodiversity \r\nand Ecosystem Services (IPBES), and the IPCC Special Report on \r\nclimate change, desertification, land degradation, sustainable land \r\nmanagement, food security, and greenhouse gas fluxes in terrestrial \r\necosystems (SRCCL; Hurlbert et al., 2019; IPCC, 2019c))."


id: c5fb0305e47a009ed2292fbc111adad3
created_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
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content:
"Potential changes in the seasonality of CIDs or the length and \r\ncharacteristics of seasons (e.g., changes in growing season length or \r\npollen season) are also important as they may shift the timing of many \r\nCIDs with broad implications for sectors and regional stakeholders \r\n(Wanders and Wada, 2015; Cassou and Cattiaux, 2016; Hansen and \r\nSato, 2016; Bronnimann et al., 2018; Marelle et al., 2018; Unterberger \r\net al., 2018; Kuriqi et al., 2020). Episodic CIDs characterize impact\u0002relevant conditions persisting from short to long time frames but \r\neventually returning to normal conditions."


id: cc73981be3f1fc1999e53e6bcbebc4fe
created_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
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content:
"CIDs can be captured in seven main types: heat and cold; wet and \r\ndry; wind; snow and ice; coastal; oceanic and other. Table  12.1 \r\nprovides an overview of the seven CID types and the CID categories \r\nassociated with each type. The type 'Other' comprises additional CIDs \r\nthat are not encompassed within the other six CID types, including \r\nair pollution weather (e.g.,  meteorological conditions that favour \r\nhigh concentrations of surface ozone, particulate matter or other air \r\npollutants), near-surface atmospheric CO2 concentrations, and mean \r\nradiation forcing at the surface (which are, for example, relevant for \r\nplant growth). Icebergs, fog and lightning are also noted in this chapter \r\nbut are not broadly assessed across all subsections. In addition, there "


id: 6980d51173924edf68fc259009c51f72
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index: climate_gpt_v2
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content:
"In some situations, phenomena causing severe impacts go well \r\nbeyond a single extreme event or a single climate variable, and can \r\ninclude interaction of climatic conditions, such as sea level rise and \r\nstorm surge (Wahl et  al., 2015), precipitation in combination with \r\nstrong winds (Martius et al., 2016) or flooding quickly followed by \r\na heatwave (S.S.-Y. Wang et al., 2019; see also Section 10.5.2.4). Such "


id: 296106b2a4ef07d648b3734d01f288f9
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content:
"Table 12.1 | Overview of the main climatic impact-driver (CID) types and related CID categories with a short description and their link to other chapters \r\nwhere the underlying climatic phenomenon and its associated essential climate variables are assessed and described."


id: 2ad7ac1c426175d92179d0e0a68e0c1e
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content:
"compound events, particularly in the context of climate extremes, \r\nare assessed in Section 11.8. A combination of non-extreme climatic \r\nimpact-drivers in time or space can also lead to severe impacts \r\n(Cutter, 2018)."


id: ab3457c8c539329d387d490f24b623d9
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
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content:
"Climate change becomes relevant for regional impact management \r\nand for risk assessment when changes in mean conditions or episodic \r\nevents affect natural and societal assets (system components with \r\nsocio-economic, cultural or intrinsic value) positively or negatively \r\n(Table  12.2). Decision makers, policymakers, risk managers and \r\nengineers therefore benefit from climate information that tracks key \r\ntrends and exceedance of thresholds that represent crucial challenges \r\nfor natural and human systems. While useful indices can vary widely \r\nfor a given sector and precise tolerance threshold values are often \r\nunknown, common metrics, categories and progressions of threshold \r\nlevels allow experts to recognize coherent messages concerning \r\naltered regional impacts and risk profiles under climate change."


id: 7bc219db558f392b247d94f27a28ca4a
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 18981
content:
"A global perspective on climatic impact-drivers is provided in \r\nSection 12.5.1. Section 12.5.2 focuses on assessing evidence for the \r\nemergence (Section  1.4.2.2) of an anthropogenic climate change \r\nsignal on the change in CIDs beyond natural climate variability, based \r\non the literature assessed in other chapters and additional literature, \r\nat both global and regional scales. The process of generating \r\nuser-relevant regional climate information in the context of co\u0002production and climate services is assessed in Sections 10.5, 12.6, \r\nBox 10.2 and Cross-Chapter Boxes 10.3 and 12.2. Cross-Chapter Box \r\n12.1 provides a global perspective on climatic impact-drivers related \r\nto their evolution for different GWLs (Section 1.6)."


id: 142f642207c43a8de68bfc2b022e1c9b
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index: climate_gpt_v2
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content:
"suitability of future climate zones and climate velocity challenges for \r\na given asset potentially drawing from multiple CIDs and associated \r\nsystem tolerance thresholds (Hamann et  al., 2015). Some broad \r\nconnections indicated as low confidence may be under-represented \r\nin the literature or could be acute under specific circumstances."


id: 9c57ff67a2c13e8b49c96905ff4eba5e
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content:
"determine plant sprouting (Grotjahn, 2021). A number of indices have \r\nbeen developed to represent the length of the viable local growing \r\nseason, including a count of days where Tmax >5degC (Mueller et al., 2015) \r\nor the period between a year's first and last set of five consecutive days \r\nwith a weighted Tmean >=10degC (G. Li et al., 2018). Warmer conditions \r\nand altered seasonality modify the range and metabolism of some \r\npollinators, pests, diseases and weeds (Wolfe et al., 2008; Bebber, 2015; \r\nAljaryian and Kumar, 2016; IPBES, 2016; Ramesh et al., 2017; Deutsch \r\net al., 2018; Nyangiwe et al., 2018) and may reduce the effectiveness \r\nof winter storage for farmers and caching species (Sutton et al., 2016)."


id: fe62bb954642c65b20599a1e80c5be90
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 42129
content:
"Warming raises accumulated seasonal heat indices used in livestock \r\nproduction, especially when humidity is high (Key et al., 2014; Lallo \r\net al., 2018), determines aquaculture suitability and is important for \r\nwild fish species migration (Tripathi et al., 2016; Brander et al., 2017). \r\nAgricultural planners may also calculate how overall warming trends \r\nalter the accumulation of vernalization units or chilling hours for \r\nagricultural or horticultural crops (often accumulated temperature \r\ndeficit below a given daily or hourly threshold; Dennis and Peacock, \r\n2009; Luedeling, 2012; Tripathi et  al., 2016; Grotjahn, 2021). \r\nWarming in the post-harvest is also important for the determination \r\nof spoilage and waste (Stathers et al., 2013) as well as food-borne \r\ndiseases (Kovats et al., 2004; Mbow et al., 2019)."


id: d2d61e54fd021a18782cd36f8375a1c5
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vector_id: 34446
content:
"Warming affects road degradation rates (Chinowsky and Arndt, 2012; \r\nEspinet et al., 2016) and warming rates inform designs for long-term \r\nenergy efficiency of buildings (Kalvelage et al., 2014). Mean temperature \r\ndrives seasonal energy demand, often expressed using winter heating \r\ndegree days (the accumulated deficit of daily temperatures below \r\na  'comfortable' indoor temperature, e.g.,  15.5degC) and summer \r\ncooling degree days (the accumulated excess of temperature above \r\na 'comfortable' level, e.g., 18degC; Spinoni et al., 2015; Arnell et al., 2019). \r\nEnergy resources may also need information on warming trends to \r\ndetermine suitable zones and overall productivity for biofuels and solar \r\npanels, the efficiency of which decreases with higher temperatures \r\n(Schaeffer et al., 2012; Wild et al., 2015; Solaun and Cerda, 2019)."


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vector_id: 10144
content:
"Health impacts and risk studies compare seasonal temperature \r\nconditions to limiting thresholds to understand range shifts and \r\nincubation rates for pathogens, disease vectors and zoonotic hosts \r\n(e.g.,  mosquitoes, ticks; Caminade et  al., 2012, 2014; Eisen and \r\nMoore, 2013; Lima et al., 2016; Ogden, 2017; Monaghan et al., 2018) \r\nand warming of surface ocean and lake waters conducive to bacterial \r\noutbreaks (Baker-Austin et  al., 2013; Jacobs et  al., 2015; Vezzulli \r\net al., 2015). Warmer conditions can also affect tourism (Kovacs et al., \r\n2017) and impact human health by lengthening the allergy season \r\nand increasing pollen concentration (Hamaoui-Laguel et  al., 2015; \r\nKinney et al., 2015a; Lake et al., 2017; Upperman et al., 2017; Sapkota \r\net al., 2019; Ziska et al., 2019)."


id: e0ebcf81b954bb7f8dae539ca513e698
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 36835
content:
"Impacts and risk assessments utilize a  large variety of indices and \r\napproaches tailored to evaluate heat impacts on human health \r\n(Sanderson et al., 2017; C. Gao et al., 2018; McGregor and Vanos, 2018; \r\nStaiger et  al., 2019; J. Zhu et  al., 2019; Schwingshackl et  al., 2021). \r\nA mixture of simple and complex heat stress indices often combine "


id: 89ebc4bd5ce8df9519551f3879c0ad32
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 21437
content:
"weight restrictions (Coffel et  al., 2017; Palko, 2017; T. Zhou et  al., \r\n2018). Heat extremes increase peak cooling demand and challenge \r\ntransmission and transformer capacity (Sathaye et al., 2013; Russo \r\net al., 2016; Craig et al., 2018; X. Gao et al., 2018) and may cause \r\ntransmission lines to sag or fail (Gupta et  al., 2012). Thermal and \r\nnuclear electricity plants may be challenged when using warmer river \r\nwaters for cooling or when mixing waste waters back into waterways \r\nwithout causing ecosystem impacts (Kopytko and Perkins, 2011; van \r\nVliet et al., 2016; Tobin et al., 2018). Extreme temperature can also \r\nreduce photovoltaic panel efficiency (Jerez et al., 2015)."


id: c8d06420ed801fa446b661467fca5c27
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 32655
content:
"The magnitude and timing (relative to developmental stages) of cold \r\nextremes (such as the typical coldest day of the year) set limits in \r\nthe range of species habitat for ecosystems as well as for agricultural \r\nand forest pests (Osland et al., 2013; Cavanaugh et al., 2014; Parker \r\nand Abatzoglou, 2016; Brunner et  al., 2018; Unterberger et  al., \r\n2018). Cold air outbreaks can lead to chilling injuries for crops (even \r\nabove 0degC) and may kill outdoor livestock (particularly young animals; \r\nMader et al., 2010; Liu et al., 2013; Grotjahn, 2021), but are often \r\nnecessary for crop chill requirements (Dennis and Peacock, 2009)."


id: e941f0d685369528368ff3e25a7a9ff5
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 38397
content:
"Increases in human mortality can occur on exceptionally cold days \r\n(e.g., <1st percentile of temperatures in winter) although thresholds \r\nand human-perceived temperatures linked to wind speed (i.e., 'wind \r\nchill') vary geographically due to acclimatization (Li et  al., 2013; \r\nGao et al., 2015; J. Li et al., 2018; J. Zhu et al., 2019). The timing of \r\n'unseasonal' cold spells also affect human health (Kinney et al., 2015b). \r\nExtreme cold can increase heat and electricity demand (Stuivenvolt\u0002Allen and Wang, 2019), cause water pipes to burst, and mechanically \r\nalter roads, railroads and buildings (Underwood et al., 2017)."


id: 19ecb26525f885668c06011fa39d41e5
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 1762
content:
"Heat extremes factor in mortality, morbidity and the range of some \r\nthermally sensitive ecosystem species (Smith and Nagy, 2015; \r\nRatnayake et al., 2019; Thomsen et al., 2019). Combined heat and \r\ndrought stress can reduce forest and grassland primary productivity \r\n(Ciais et al., 2005; De Boeck et al., 2018) and even cause tree mortality \r\nat higher extremes (Teskey et al., 2015)."


id: 99796e1e904821261712d9fff2768d51
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 24230
content:
"Extreme heat events raise temperatures in buildings and cities already \r\nwarmed by the urban heat island effect (Gaffin et al., 2012; Oleson \r\net al., 2018; Zhao et al., 2018; Mauree et al., 2019; Box 10.3) and \r\ncan induce disruptions in critical infrastructure networks (Chapman \r\net  al., 2013). Heat affects transportation infrastructure by warping \r\nroads and airport runways (Chinowsky and Arndt, 2012) or buckling \r\nrailways (Dobney et al., 2010; Depoues, 2017; Chinowsky et al., 2019), \r\nand high temperatures reduce air density leading to aircraft take-off "


id: 829ba925b84f4ebd67d5da2d19a6953e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 20106
content:
"Regional information about the spring and autumn seasonal periods in \r\nwhich freeze-thaw cycles are common (such as the dates of first spring \r\nthaw and last spring frost, or the number of days where Tmax >0degC and \r\nTmin <0degC) are particularly useful in estimating the rate of potential road \r\nand building damage or determining seasonal truck weight restrictions \r\n(Kvande and Liso, 2009; Chinowsky and Arndt, 2012; Palko, 2017; \r\nDaniel et al., 2018). The altitude of the freezing level also identifies \r\nportions of mountain slopes where freeze/thaw transitions or changes \r\nin snowpack condition can influence landslide and snow avalanche \r\nhazards (Coe et al., 2018). The geographical distribution of frost is also \r\na determining factor in the range of vectors for human diseases such \r\nas malaria (X. Zhao et al., 2016; Smith et al., 2020)."


id: 8562f582ecf1efb523b1bc1f23d7eedf
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 20603
content:
"Figure  12.3 illustrates how successive heat and cold hazards can \r\npotentially affect important natural and human systems, with climatic \r\npressures reaching new sectoral assets or becoming increasingly \r\nsevere as conditions become more extreme. While the precise value \r\nof any CID threshold may depend strongly on local environmental \r\nand system characteristics, there are common patterns and \r\ninterdependencies in the types of thresholds encountered. Changes \r\nin the regional profile of CIDs can thus substantially alter threshold \r\nexceedance likelihoods."


id: f9ce5c93f01b51e70a16fff343ed8511
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 41306
content:
"Changes in mean precipitation alter total water resources and \r\nlong-term surface, snowpack and groundwater reservoirs (Schewe \r\net al., 2014). Annual and seasonal wet trends can alter the suitable \r\ngeographic range of species, with implications for biodiversity and \r\nvector-borne diseases (Knouft and Ficklin, 2017; Smith et al., 2020). \r\nThe rate at which higher total streamflow increases river erosion \r\nand changes sediment loading is relevant for fish breeding (Scheurer \r\net al., 2009), the location of riverine salt fronts that affect coastal \r\nagriculture and ecosystems (Chun et  al., 2018; Vu et  al., 2018), \r\ncoastal  freshwater stratification (Baker-Austin et  al., 2013; Bell \r\net al., 2013), and the accretion of sediment in estuaries and beaches \r\n(Syvitski and Milliman, 2007). Wetter conditions may shift tourist \r\nappeal (Kovacs et al., 2017) and alter the pace of degradation for \r\npaved and especially unpaved roads (Chinowsky and Arndt, 2012)."


id: a0ec1ee10b1290ad11505b53455cf53d
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 25536
content:
"Many agricultural systems require minimum rainfall totals or rely \r\nupon irrigation (Mbow et al., 2019). The length of the wet season \r\nhelps determine the potential for multiple cropping seasons, but \r\ninconsistency of wet season arrival times poses challenges for farm \r\nmanagement (Waha et al., 2020). Wetter growing season conditions \r\nincrease the chance of waterlogging, which can delay planting or \r\ndamage planted seeds (Rosenzweig et  al., 2002; Ben-Ari et  al., \r\n2018; Makinen et al., 2018; Wolfe et al., 2018; Kolberg et al., 2019; \r\nGrotjahn, 2021). Tomasek et  al. (2017) calculated 'workable days' \r\nfor agricultural machinery around planting and harvest time set in \r\npart by limits in soil moisture saturation below which farmers can \r\nutilize critical machinery with less rutting or soil compaction. Wetter \r\nconditions may also increase canopy moisture that is conducive to \r\ncrop pathogens (Garrett et al., 2006; Kilroy, 2015; Grotjahn, 2021)."


id: ed597f7cd17a8fd0426234383e7cf48c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 39130
content:
"thresholds related to antecedent wet periods and extreme rainfall \r\nintensities (Alvioli et al., 2018; Monsieurs et al., 2019). Landslides and \r\nrockfalls may also be exacerbated by permafrost thaw and receding \r\nglaciers in polar and mountain areas (Cook et  al., 2016; Haeberli \r\net al., 2017; Patton et al., 2019)."


id: 222fc1e84503f14c7b3a9fbb948f4406
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 3234
content:
"Water managers often utilize a  variety of hydrological drought \r\nindices and hydrological models to characterize water resources, low \r\nflow conditions and the potential for irrigation (Wanders and Wada, \r\n2015; Mukherjee et al., 2018). Low flow volume and intermittency \r\nthresholds can indicate reductions in dissolved oxygen, more \r\nconcentrated pollutants, and higher stream temperatures relevant for \r\necosystems, water resource quality and thermal power plant cooling \r\n(Feeley et al., 2008; Doll and Schmied, 2012; Schaeffer et al., 2012; \r\nPrudhomme et  al., 2014; van Vliet et  al., 2016). Low water levels \r\nmay also restrict waterway navigation for commerce and recreation \r\n(Forzieri et al., 2018)."


id: ccd533d2cc219ea7db3a6b24747abfa3
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 33367
content:
"Landslides, mudslides, rockfalls and other mass movements can lead \r\nto fatalities, destroy infrastructure and housing stock, and block \r\ncritical transportation routes. Climate models cannot resolve these \r\ncomplex slope failure processes (nor triggering mechanisms such as \r\nearthquakes), so most studies rely on proxies or conditions conducive \r\nto slope failure (Gariano and Guzzetti, 2016; Ho et al., 2017). Common \r\nindices include precipitation intensity-duration thresholds (Brunetti \r\net  al., 2010; Khan et  al., 2012; Melchiorre and Frattini, 2012) and "


id: f402a822ad843c15d730b7482ba2cbef
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 40303
content:
"of high wind speed and low humidity (even for just a portion of the \r\nday) can also inform studies examining fruit desiccation and rice \r\ncracking (Grotjahn, 2021). Drought also raises disease infection rates \r\nfor West Nile virus (Paull et al., 2017), and the alternation of dry and \r\nwet spells induces swelling and shrinkage of clay soils that can lead to \r\nsinkholes and destabilize buildings (Hadji et al., 2014)."


id: fb47c7584c8ce5c5007a7bc725ec19da
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 41584
content:
"ground, with tolerance thresholds depending on crop species and \r\ndevelopmental stage (Seidl et  al., 2017; Lai, 2018; Elsner et  al., \r\n2019; Grotjahn, 2021). Severe storms particularly threaten energy \r\ninfrastructure, with maximum wind speed associated with treefall \r\nand breaking of above-ground electrical transmission lines (Ward, \r\n2013; Nik et al., 2020). The profile of heavy wind gusts is also required \r\nin the design of skyscrapers (C.-H. Wang et al., 2013) and bridges \r\n(Mondoro et al., 2018). Severe storms are difficult to simulate at the \r\nrelatively coarse spatial scales of Earth system models, thus scientists \r\noften project changes by noting areas with increased convective \r\navailable potential energy (CAPE) and strong low-level wind shear as \r\nthese are conducive to tornado formation (Diffenbaugh et al., 2013; \r\nTippett et al., 2016; Glazer et al., 2021)."


id: 6499841f27215532b53cdf4333cf852c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 14975
content:
"Tropical cyclones and severe coastal storms can deliver wind, water \r\nand coastal hazards with the potential for widespread mortality and \r\ndamages to cities, housing, transportation and energy infrastructure, \r\necosystems and agricultural lands (Burkett, 2011; NASEM, 2012; Bell \r\net al., 2013; Wehof et al., 2014; Ward et al., 2016; Cheal et al., 2017; \r\nGodoi et al., 2018; Koks et al., 2019; Pinnegar et al., 2019). Storm \r\nplanning is often tied to the Saffir-Simpson scale related to peak \r\nsustained wind speed (Izaguirre et  al., 2021), with several indices \r\nfocusing on storms' overall power and energy, size and translation \r\nspeed to anticipate destructive potential (Knutson et al., 2015; Wang \r\nand Toumi, 2016; Parker et al., 2018; Hassanzadeh et al., 2020)."


id: 939a5b2ca9b9a83004f58a22f8d27cdd
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 23173
content:
"Cryospheric changes are a focus of Chapter 9 and were central to \r\nthe recent IPCC Special Report on the Ocean and Cryosphere in \r\na  Changing Climate (SROCC; IPCC, 2019b). Here we focus on the \r\nways that scientists use snow and ice CIDs to understand current and \r\nfuture societal impacts and risks."


id: 1e02f3576911aae5c2cf0b703a660c40
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 2479
content:
"Heavy snowfall is a substantial concern for cities, settlements and \r\nkey transportation and energy infrastructure (Ward, 2013; Palko, \r\n2017; Janoski et al., 2018; Collins et al., 2019). Heavy snowfall can \r\ninterfere with transportation (Herring et al., 2018) and cause a loss \r\nof both work and school days depending on local snow removal \r\ninfrastructure. Freezing rain and ice storms can be treacherous for \r\nroad and air travel (Tamerius et al., 2016), and can knock down power \r\nand telecommunication lines if ice accumulation is high (Degelia \r\net  al., 2016). Rain-on-snow events can create a  solid barrier that \r\nhinders wildlife and livestock grazing that is important to indigenous \r\ncommunities (Forbes et al., 2016). Shifts in the frequency, seasonal \r\ntiming and regions susceptible to ice storms alter risks for agriculture \r\nand infrastructure (Lambert and Hansen, 2011; Klima and Morgan, \r\n2015; Ning and Bradley, 2015; Groisman et al., 2016)."


id: 2c682e0e0d4e2573856b6cc5cc3e54d3
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 5078
content:
"Change in ice sheet and glacier spatial extent and surface mass \r\nbalance is relevant for polar and high mountain ecosystems and \r\ndownstream assets that rely on glacial water resources (J.R. Lee et al., \r\n2017; Milner et al., 2017; Huss and Hock, 2018; Schaefli et al., 2019). \r\nThe loss of glaciers reduces the thermal consistency of cold streams \r\nsuitable for some freshwater species (Giersch et  al., 2017), and \r\nparks and recreation areas may lose appeal as glaciers and seasonal \r\nsnow cover retreat (Gonzalez et al., 2018; Wang and Zhou, 2019). \r\nRapid glacial retreat can lead to glacial lakes and outburst floods \r\nthat endanger downstream communities (Carrivick and Tweed, 2016; \r\nCook et al., 2016; Harrison et al., 2018)."


id: 2bc11494ac4adcc25edd79b5dc34571f
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 4959
content:
"Information on the changing frequency and size distribution of hail can \r\nhelp stakeholders build resilience for agriculture, vehicles, transportation \r\ninfrastructure and buildings, solar panels and wild species that see \r\ncritical damage at particular hail size thresholds (Dessens et al., 2007; \r\nWebb et al., 2009; Patt et al., 2013; Fiss et al., 2019). Most climate \r\nmodels do not directly resolve hail and therefore studies often examine \r\nproxies associated with severe mesoscale storms (Tippett et al., 2015; \r\nPrein and Holland, 2018), although some regional studies now utilize \r\nhail-resolving models (Mahoney et al., 2012; Brimelow et al., 2017)."


id: 8cdbce1b18d4aa3b8f6153610c258f4e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 21969
content:
"Changes in permafrost temperature, extent and active layer thickness \r\nare metrics that track how permafrost thaw below, for example, roads, \r\nairstrips, rails and building foundations in high-latitude and mountain \r\nregions may destabilize settlements and critical infrastructure \r\n(Pendakur, 2016; Derksen et al., 2018; Duvillard et al., 2019; Olsson \r\net  al., 2019; Streletskiy et  al., 2019). Warmer conditions can also \r\naffect ecosystems, built infrastructure and water resources through \r\nthawing of especially ice-rich permafrost (>=20% ice content) and by \r\nthawing of ice wedges (Shiklomanov et al., 2017; Hjort et al., 2018), \r\ncreation of thermokarst ponds and increased subsurface drainage \r\nfor polar and high-mountain wetlands (Walvoord and Kurylyk, 2016; \r\nFarquharson et al., 2019) and the release of water pollutants such as \r\nmercury (Burkett, 2011; Schaeffer et al., 2012; Schuster et al., 2018)."


id: 51369713a15381bea407c90823bff537
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 11570
content:
"Information about the changing frequency and seasonal timing of \r\nsnow avalanches is important to assess threats to transportation \r\nroutes, infrastructure, recreational skiing and people living in alpine \r\ncommunities (Lazar and Williams, 2008; Mock et al., 2017; Ballesteros\u0002Canovas et  al., 2018; Hock et  al., 2019). Like landslides and other \r\nmass movements, snow avalanches are not directly resolved by "


id: ca1e496ff7a0208f486e8e1c0708cfd6
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 32895
content:
"of floods that overtop coastal protection, due to extreme coastal \r\nwater levels (ECWL), is important for port and harbour operations \r\nand coastal energy infrastructure thresholds (Bilskie et  al., 2016; \r\nCamus et  al., 2017). Frequent inundation by salt water can also \r\nhave significant impacts on water resources, crops, aquaculture and \r\ntransportation systems due to corrosion and undercutting of coastal \r\nroads, bridges and rails (Zimmerman and Faris, 2010; N. Ahmed et al., \r\n2019; Gopalakrishnan et al., 2019)."


id: a4bf603cd511fc73734e2f8380ee39e2
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 26208
content:
"climate models and are thus tracked using proxy climate information \r\ndescribing snow avalanche susceptibility, particularly the snow water \r\nequivalent, and triggering mechanisms such as warm spells, high \r\nwinds, rain-on-snow and heavy precipitation (Hock et al., 2019). The \r\nquality of snow also provides insight into avalanche hazards (Mock \r\net al., 2017), with the seasonal altitude of wet snowpack (>0.5% liquid \r\nwater by volume) particularly important in determining characteristics \r\nof potential avalanches (Castebrunet et al., 2014)."


id: 6811df8cc93ad389f15e3936a2b0cecf
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 15577
content:
"The SROCC included in-depth discussions of threats facing the world's \r\ncoastlines (IPCC, 2019b) and Section 9.6 provides further discussion \r\non coastal processes. Here we note major connections between \r\ncoastal CIDs and ecosystem and societal assets near coastlines."


id: 36e526b5c091c6161f2d00c057c4b999
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 6884
content:
"Oceanic changes and impacts were a  substantial focus of SROCC \r\n(IPCC, 2019b). Chapter 9 of this Report assesses changes in ocean \r\nprocesses, and here we note major connections used by scientists to \r\nunderstand how oceanic CIDs affect ecosystems and society."


id: ee72fa5f2c1773c468fbe9f3162e0e63
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 39327
content:
"Shifts in thermal zones affect the suitability of fisheries and marine \r\nand coastal species habitat and migration routes (Hoegh-Guldberg \r\nand Bruno, 2010; Doney et al., 2012; Burrows et al., 2014; Urban, 2015; \r\nHixson and Arts, 2016; Tripathi et al., 2016; N. Ahmed et al., 2019; \r\nBindoff et al., 2019). Intertidal species are particularly dependent on \r\nsuitable conditions for both air and sea surface temperatures (Monaco \r\nand McQuaid, 2019). The structure of ocean warming also affects the \r\nintensity of upper-ocean stratification and the timing and strength of \r\ncoastal upwelling (driven also by mean wind changes), which alters \r\nthe vertical transport of oxygen- and nutrient-rich waters affecting \r\nfishery and marine ecosystem productivity (D. Wang et al., 2015)."


id: 29de7a41330eb70d7207c5dc5054d85d
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 4590
content:
"Episodic coastal flooding of coastal communities, farmland, buildings, \r\ntransportation routes, industry and other infrastructure is caused \r\nby extreme total water levels (ETWL), which is the combination \r\nof RSL, tides, storm surge and high wave setup at the shoreline \r\n(Vitousek et al., 2017; Melet et al., 2018; Vousdoukas et al., 2018, \r\n2020a; Koks et al., 2019; Kirezci et al., 2020). Coastal settlement and \r\ninfrastructure design often uses coastal flooding metrics such as the \r\nETWL frequency distribution or the 100-year average return interval \r\nstorm tide (storm surge + high tide) level (McInnes et al., 2016; Mills \r\net al., 2016; Walsh et al., 2016b; Zheng et al., 2017). The duration "


id: 439b143ec729b2ad02afb0b9251c8d2b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 9118
content:
"Uptake of atmospheric CO2 and subsequent increases in dissolved \r\nCO2 lowers ocean pH and can reduce carbonate ion concentrations \r\nbelow critical calcium carbonate saturation thresholds for marine \r\nand aquatic organisms growth, reproduction and/or survival, with \r\nextended implications for marine ecosystems including fisheries (Bell \r\net al., 2013; Kroeker et al., 2013; Barange et al., 2014; Dutkiewicz \r\net al., 2015; Ekstrom et al., 2015; Gattuso et al., 2015; Mathis et al., \r\n2015a; Nagelkerken and Connell, 2015; Behrenfeld et  al., 2016; \r\nNagelkerken and Munday, 2016; Tripathi et  al., 2016; Jiang et  al., \r\n2018; Weiss et al., 2018; N. Ahmed et al., 2019; Bindoff et al., 2019). \r\nLower pH may provide more favourable conditions for toxic algal \r\nblooms (Riebesell et al., 2018) and can interact with hypoxic zones \r\nto impact ecosystems (Gobler and Baumann, 2016; Cai et al., 2017)."


id: b8951e5b0210c2be2dd8e2cc90eaf06c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 29682
content:
"Changes in currents, sea ice brine rejection and net freshwater flux \r\nin the ocean can alter salinity with effects on mixed layer structure, \r\ndensity stratification and the vertical movement of nutrients and \r\nmarine organisms (Freeland, 2013; Haumann et al., 2016)."


id: 8bf000404c0bee997c367d8ba32079a1
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 21785
content:
"Ocean warming and increased stratification decrease the oxygen \r\ncontent of the ocean (Griffiths et al., 2017; Schmidtko et al., 2017; \r\nBindoff et al., 2019), lead to an expansion of oxygen minimum zones \r\nin the open ocean (Stramma et  al., 2012; Zhang et  al., 2013) and \r\nexacerbate the creation of anoxic 'dead zones' in the coastal oceans \r\n(Breitburg et al., 2018). Such a decline (characterized by successive \r\ndissolved oxygen concentration thresholds) could affect a wide range \r\nof marine organisms and reduce marine habitats (Chan et al., 2008; \r\nVaquer-Sunyer and Duarte, 2008; Hoegh-Guldberg and Bruno, 2010; \r\nAltieri and Gedan, 2015; Breitburg et al., 2018) and can also lead to \r\nfurther local acidification (Zhang and Gao, 2016; Laurent et al., 2017)."


id: 750ed85ccab0ba729e92e7650f6fdaf1
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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vector_id: 17832
content:
"Changes in surface solar and longwave radiation fluxes alter \r\nphotosynthesis rates and potential evapotranspiration for natural \r\necosystems and food, fibre and energy crops (Makinen et al., 2018); "


id: ddc53bf6e8fd64f3219935b9a993a060
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 36279
content:
"changes in radiation fluxes can also shift solar energy resources \r\n(Schaeffer et al., 2012; Jerez et al., 2015; Wild et al., 2015; Fant et al., \r\n2016; Craig et  al., 2018). Plants and aquatic systems particularly \r\nrespond to changes in photosynthetically active radiation (PAR) and the \r\nfraction of diffuse radiation (Proctor et al., 2018; Ren et al., 2018; Ryu \r\net al., 2018). Increases in ultraviolet radiation can also detrimentally \r\naffect ecosystems and human health (Barnes et al., 2019)."


id: a2ec26992ef9637e9c737abe9fcfebb1
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 25881
content:
"described in Figure  1.18a. The section is organised by continents \r\n(Sections 12.4.1-12.4.6) with a specific assessment for Small Islands \r\n(Section 12.4.7), open and deep ocean (Section 12.4.8), and polar regions \r\n(Section 12.4.9) as defined in Chapter 1 (Figure 1.18c). In addition, CID \r\nindices and thresholds relevant to 'specific zones', as defined in AR6 \r\nWGII Cross-Chapter Papers, are assessed in Section 12.4.10 except for \r\nthe Mediterranean, which is addressed both under Africa and Europe \r\n(Sections 12.4.1 and 12.4.5) and is a focus in Section 10.6.4."


id: d84b62116bf74b2691c1ef60be60e41c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 35358
content:
"Additional CIDs may be relevant for regional studies but are not the \r\nfocus of assessment in this Report. For example, information about \r\nchanges in the frequency and seasonal timing of fog helps anticipate \r\nairport delays and cool beach days, and is also important for water \r\ndelivery and retention in coastal ecological and agricultural systems \r\n(Torregrosa et al., 2014)."


id: ba4dc988f722de9ba06fb1d98df1961e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 29996
content:
"Recent literature defines CID indices to represent trends \r\nand thresholds that influence sectoral assets, albeit with \r\nconsiderable variation owing to the unique characteristics of \r\nregional and sectoral assets. Indices include direct information \r\nabout the CID's profile (magnitude, frequency, duration, timing, \r\nspatial extent) or utilize atmospheric conditions as a proxy for \r\nCIDs that are more difficult to directly observe or simulate. \r\nEach sector is affected by multiple CIDs, and each CID affects \r\nmultiple sectors. Assets within the same sector may require \r\ndifferent or tailored indices even for the same CID. These indices \r\nmay be defined to capture graduated thresholds associated \r\nwith tipping points or inflection points in a particular sectoral \r\nvulnerability, with commonalities in the types of processes \r\nthese thresholds represent even as their precise magnitude \r\nmay vary by specific sectoral system and asset."


id: 511b2e1f14192efb701f24082a524893
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 11551
content:
"This section describes the historical and projected changes in commonly \r\nused indices and thresholds associated with the main climatic \r\nimpact-drivers (Sections 12.2 and 12.3) at the scale of AR6 regions "


id: 7e9f54bbf42a08b3fa6795734922afb1
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 19433
content:
"or projected emergence of the CID change signal from the natural \r\ninterannual variability if assessed with at least medium confidence\r\nin Section 12.5.2, using as a basis a criterion of S/N > 1, noise being \r\ndefined as the interannual variability. The time of emergence (ToE) \r\nis given as either: (i) already emerged in the historical period, or \r\n(ii) emerging by 2050 at least for RCP8.5/SSP5-8.5, or (iii) emerging \r\nafter 2050 but before 2100 at least for scenarios RCP8.5 or SSP5-8.5. \r\nTable cells that do not include emergence information are indicative \r\nof 'low confidence of emergence in the 21st century', which includes \r\nsituations where assessment indicates emergence will not occur \r\nbefore 2100 or that evidence is not available or insufficient for \r\na confidence assessment of time of emergence."


id: 5cae7590f5e0493263eba0c1efe45868
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 13571
content:
"Figures: The assessment of changes in CIDs is based on literature, \r\nphysical understanding (Chapters 2-11), and global and regional \r\nclimate projections of indices and thresholds presented in the \r\nAtlas, as well as in the global and regional figures in Section 12.4 \r\n(Figures 12.4-12.10) showing the future evolution of nine key CID \r\nindices/thresholds used in this assessment (see also Cross-Chapter \r\nBox  10.3). The figure indices and impact-relevant thresholds are \r\ndescribed in Annex VI: Climatic Impact-drivers and Extreme Indices."


id: 887e621c7b2c1a3858cf422c649148fb
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 21177
content:
"Figure  12.4 shows changes in six CID indices. These global maps \r\nare derived from Coupled Model Intercomparison Project Phase 6 \r\n(CMIP6) simulations for different time periods and scenarios (except \r\nfor extreme total water level where CMIP Phase 5 (CMIP5) is used). \r\nThe uncertainty due to climate models, time, scenarios and regional \r\ndownscaling is illustrated in Supplementary Material SM.12.1 to \r\nSM.12.6, which show the distribution of the spatial average of the \r\nindex among models over each land region for CMIP5, CMIP6 and \r\nCoordinated Regional Climate Downscaling Experiment (CORDEX) \r\nensembles for the recent past, mid- and end-21st century, and for \r\nGWLs of +1.5degC, +2degC and +4degC. The hatching in the figure covers \r\nareas where less than 80% of models agree on the sign of change."


id: c587af6a231d5055e313a0308162329d
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 32058
content:
"Further regional detail is provided for the remaining indices in each \r\ncontinental section in the form of continental maps accompanied \r\nby regional box plots displaying changes calculated for AR6 region \r\naverages, and the associated regionally averaged uncertainty."


id: f2bef1d21258571e09901ad8e85bb681
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 40108
content:
"Climatic impact-drivers changing in a globally coherent way:\r\nFor the sake of conciseness, assessments pertaining to ocean acidity \r\nand the 'Other' CID type in Sections 12.2 and 12.3 are not provided \r\nper region in Sections 12.4.1-12.4.9 but are summarized here, given \r\nthe globally coherent way in which they change."


id: eefebf64bae2443ba09612894dfabb2f
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 39417
content:
"(WAF), Central Africa (CAF), North Eastern Africa (NEAF), South \r\nEastern Africa (SEAF), West Southern Africa (WSAF), East Southern \r\nAfrica (ESAF) and Madagascar (MDG) - are the official AR6 regions \r\n(Figure Atlas.2) and one - North Africa - is used in this assessment to \r\nindicate the African portion of the Mediterranean region."


id: df32526641dd2f17635bedb7926e36cd
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 36521
content:
"Quite a large body of new literature is now available for the African \r\nclimate as a result of regionally downscaled CORDEX Africa outputs, \r\nin particular, providing projections of both the mean climate (Mariotti \r\net al., 2014; Nikulin et al., 2018; Dosio et al., 2019; Teichmann et al., \r\n2021) and extreme climate phenomena (Giorgi et al., 2014; Nikulin \r\net al., 2018; Dosio et al., 2019; Coppola et al., 2021b). CORDEX Africa \r\nsimulations are assessed in the Atlas, which finds reasonable skill in \r\nmean temperature and precipitation as well as important features \r\nof regional climate (e.g.,  timing of monsoon onset in West Africa) \r\nalthough lower performance in Central Africa."


id: fe4f69610667f0f625058c33d27c09c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 42110
content:
"Mean air temperature: The African continent has experienced \r\nincreased warming since the beginning of the 20th century in regions \r\nwhere measurements allow a  sufficient homogeneous observation \r\ncoverage to estimate trends (high confidence) (Figure Atlas.11). This \r\nwarming is very likely attributable to human influence (Chapter  3 \r\nand Atlas.4.2) at continental scale. Mean annual temperatures \r\nhave increased at a high rate since the mid-20th century, reaching \r\n0.2degC-0.5degC per decade in some regions such as north, north\u0002eastern, west and south-western Africa (high confidence) (Atlas.4.2 \r\nand Figure Atlas.11)."


id: b7d668044aed0cc679a1929ca1f7b3de
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 29566
content:
"It is very likely that temperatures will increase in all future emissions \r\nscenarios and all regions of Africa (Atlas.4.4). By the end of the \r\ncentury under RCP8.5 or SSP5-8.5, all African regions will very likely\r\nexperience a warming larger than 3degC except Central Africa, where \r\nwarming is very likely expected above 2.5degC, while under RCP2.6 \r\nor SSP1-2.6, the warming remains very likely limited to below 2degC \r\n(Figure Atlas.12). A very likely warming with ranges between 0.5degC \r\nand 2.5degC is projected by the mid-century for all scenarios depending \r\non the region (high confidence). Mean temperatures for all regions \r\nare projected to increase with increasing global warming (virtually \r\ncertain) (Figure Atlas.12)."


id: 5479d4efaa1148c73faa8d4a41e143
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 12136
content:
"Extreme heat: Warm extremes have increased in most of the regions \r\n(high confidence), NEAF, SEAF and MDG (medium confidence) and \r\nwith low confidence in CAF (Table 11.4). Despite the increasing mean \r\ntemperature, there is low confidence (limited evidence) that Africa \r\nhas experienced increased extreme heat stress trend for agriculture \r\nor human health in the last two decades of the 20th century in a few \r\nregions such as West Africa, South Africa and North Africa considering \r\nthe period from 1973 to 2012 (Knutson and Ploshay, 2016)."


id: 135815152ff16ae6acff77f3e28251b5
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 615
content:
"A substantial increase in heatwave magnitude and frequency over \r\nmost of the Africa domain is projected for even 2degC global warming \r\n(high confidence) (Sections 11.3 and 11.9, and Table  11.4), with \r\npotential effects on health and agriculture. The number of days \r\nwith maximum temperature exceeding 35degC is projected to increase \r\n(Coppola et al., 2021b) in the range of 50-100 days by 2050 under "


id: d082fc8f6995f4a2ce9a71e89146c294
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 34034
content:
"Previous IPCC assessments results are summarized in Atlas.4.1.1 \r\nFor the purpose of this assessment the Africa region has been divided \r\nin nine sub-regions of which eight - Sahara (SAH), Western Africa "


id: 10c3a530c174d985a5a512440d127b2b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 132
content:
"SSP5-8.5 in WAF, ESAF and WSAF and NEAF (high confidence) \r\n(Figure  12.4b). Under SSP1-2.6, the change in the number of \r\nexceedance days remains limited to about 40-50 days per year at \r\nthe end of the century in these regions, while it increases by 150 days \r\nor more in WAF, CAF for SSP5-8.5 (Figure 12.4a,c; Figure 12.SM.1)."


id: 4159b9ab4aa96a97b625d8a6bbbc17c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 8682
content:
"Mean precipitation: Since the mid-20th  century, precipitation \r\ntrends have varied in Africa but notable drying trends are found in \r\neastern, central and north-eastern parts of Southern Africa, Central \r\nAfrica and in the Horn of Africa (Atlas.4.2)."


id: a63ceea055403213a647a4dacbff8afb
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 26463
content:
"There is high confidence in projected mean precipitation decreases \r\nin North Africa and West Southern Africa and medium confidence\r\nin East Southern Africa by the end of the 21st century (Dosio et al., \r\n2019; Gebrechorkos et al., 2019; Teichmann et al., 2021; Atlas.4.5). \r\nThe Western Africa region features a gradient in which precipitation \r\ndecreases in the west and increases in the east and increase is also \r\nprojected over Eastern Africa (medium confidence) (Atlas.4.5), with \r\ntrends in Western Africa affecting the boreal summer monsoon (Chen \r\net al., 2020). Increasing precipitation for 1.5degC and 2degC GWLs are \r\nfound in central and eastern Sahel with low confidence and the \r\nwet signal is getting stronger and more extended for a 3degC and 4degC \r\nwarmer world (Atlas.4.4)."


id: 821e3c36b64dfae76ad613d13cf47a80
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 20013
content:
"A change in monsoon seasonality is also reported in Western Africa \r\nand Sahel (low confidence) with a forward shift in time (later onset and \r\nend; Section 8.2; Mariotti et al., 2011; Seth et al., 2013; Ashfaq et al., \r\n2021). This shift has been associated with a  precipitation decrease \r\nduring the monsoon season attributed to a decrease of African easterly \r\nwave activity in the 6-9-day regime (Mariotti et al., 2014) and a soil \r\nprecipitation feedback reported in Mariotti et al. (2011)."


id: 5340ab22a24dca5ad8847f995929a376
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 11917
content:
"Cold spell and frost: Africa experiences cold events and frost days \r\nthat can affect agriculture, infrastructure, health and ecosystems, \r\nespecially in Southern and North Africa, which have marked cold \r\nseasons and mountainous areas. Cold spells have likely decreased in \r\nfrequency over subtropical areas. In particular, in North and Southern \r\nAfrica, the frequency of cold events has likely decreased in the last few \r\ndecades (Sections 11.3 and 11.9). There is a high confidence that cold \r\nspells and low target temperatures will decrease in future climates \r\nunder all scenarios in West, Central and East Africa. Heating degree \r\ndays will have a substantial decrease by the end of the century for up \r\nto about one month under RCP8.5 in North and Southern Africa (high \r\nconfidence) (Coppola et al., 2021b)."


id: ef984c0420b9ca6035cdbc8745c0aa55
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 39534
content:
"River flood: Generally in Africa from 1990 through 2014, annual \r\nflood frequencies have fluctuated and there is medium confidence\r\nin an upward trend in flood events occurrences (C.-J. Li et al., 2016). \r\nIn  particular, over Western Africa, upward trends in hydrological \r\nextremes such as maximum peak discharge have likely occurred \r\nduring the last few decades (i.e.,  after 1980) and have caused \r\nincreased flood events in riparian countries of rivers such as Niger, \r\nSenegal and Volta (high confidence) (Nka et  al., 2015; Aich et  al., \r\n2016a; Wilcox et al., 2018; Tramblay et al., 2020). In Southern Africa, \r\ntrends in flood occurrences were decreasing prior to 1980 and \r\nincreasing afterwards (medium confidence) (Tramblay et al., 2020)."


id: b527b1ed88b7495036497b5a511edced
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 29109
content:
"There is high confidence that extreme heat has increased in \r\nfrequency and intensity in most African regions. Heatwaves \r\nand deadly heat stress and the frequency of exceedance of hot \r\ntemperature thresholds (e.g., 35degC) will drastically increase by \r\nthe end of the century (high confidence) under SSP5-8.5, but \r\nlimited increases are expected in SSP1-2.6. Dangerous heat \r\nstress thresholds (HI > 41degC) are projected to be crossed more \r\nthan 200 days more in West and Central Africa under SSP5-8.5, \r\nwhile this increase remains limited to a few tens of days more \r\nfor SSP1-2.6. Cold spells and frost days are projected to occur \r\nless frequently in all scenarios."


id: e258d35db10c65c455dbe7db0f60c864
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 37113
content:
"Under future climate scenarios, the extreme river discharge as \r\ncharacterized by the 30-year return period of 5-day average peak flow \r\nis projected to increase by the end of the century for RCP8.5 (more \r\nthan 10% relative to the 1971-2000 period) for most of the tropical \r\nAfrican river basins (Dankers et al., 2014) and a consistent increase \r\nof flood magnitude is projected across humid tropical Africa by 2050 "


id: c817fdcc0a08735720e609471d1ae2eb
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 32518
content:
"Gan, 2017). A growing number of studies provide further regional \r\ncontext on expanding aridity in several places in East and West Africa, \r\nrespectively (Sylla et al., 2016a; Liu et al., 2018b; Haile et al., 2020)."


id: 88e5ac950aaa38c6b651b2dade76b588
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 21249
content:
"Hydrological drought: Section 11.9 noted observed decreases in \r\nhydrological drought over the Mediterranean (high confidence) and \r\ndiminished summer river flows in West Africa (medium confidence). \r\nRecent regional modelling studies project substantial increases in \r\nhydrological drought affecting major West African river basins under \r\n1.5degC and 2degC GWLs and RCP4.5 and RCP8.5 scenarios (Oguntunde \r\net al. 2018, 2020; Sylla et al., 2018b); however, there remains low \r\nconfidence in future projections given disagreement with global \r\nmodel runoff projections (e.g., B.I. Cook et al., 2020). There is high \r\nconfidence that a 2degC GWL would see an increase in hydrological \r\ndroughts in the Mediterranean region, and medium confidence in \r\nincreasing hydrological drought conditions in the Southern Africa \r\nregions (Section 11.9)."


id: 66e0ca15a9bebaa3abe5ba9ed65c907d
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
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content:
"Heavy precipitation and pluvial flood: Chapter  11 found that \r\nheavy precipitation intensity and frequency has likely increased \r\nover West and East Southern Africa but there is no evidence due to \r\na lack of studies that any significant trend is observed in any other \r\nregion. In addition, East Africa has experienced strong precipitation \r\nvariability and intense wet spells leading to widespread pluvial \r\nflooding events hitting most countries including Ethiopia, Somalia, \r\nKenya and Tanzania (medium confidence). Finally, with respect \r\nto Southern Africa, heavy precipitations events have increased in \r\nfrequency (medium confidence)."


id: fd7881140493d0140e104a7a1b2b76ae
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 41948
content:
"In West Africa and Central Africa, there is high confidence that the \r\nintensity of extreme precipitation will increase in a  future climate \r\nunder both RCP4.5 and RCP8.5 scenarios and 1.5degC and 2degC GWLs \r\nthreatening widespread flood occurrences before, during and after \r\nthe mature monsoon season (Chapter  11). Extreme precipitation \r\nintensity is also increasing in several other regions, such as SAH, \r\nNEAF, SEAF, ESAF and MDG (high confidence) for 2degC GWL and \r\nhigher (Chapter 11)."


id: de78b25eb40edc1299aea8b3ba98168f
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 36408
content:
"Landslides: There is an increase in reported landslides in WAF, CAF, \r\nNEAF and SEAF in the past decades but with limited evidence of \r\nsignificant trends (Gariano and Guzzetti, 2016; Haque et al., 2019). \r\nThere is low confidence (limited evidence) of a  future increase in \r\nlandslides in central-eastern Africa, and literature is largely missing \r\nto assess this important hazard (Gariano and Guzzetti, 2016)."


id: 5b984deee79dda74b3f91472dfdbee96
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 13363
content:
"Fire weather: There is low confidence (low agreement) in recent \r\nreductions in fire activity given soil moisture increases in some \r\nregions and substantial land use changes (Andela et al., 2017; Forkel \r\net  al., 2019; Zubkova et  al., 2019). Days prone to fire conditions \r\nare going to increase in all extratropical Africa until the end of the \r\ncentury and fire weather indices are projected to largely increase \r\nin North and Southern Africa, where increasing aridity trends occur \r\n(high confidence), with an emerging signal well before the middle \r\nof the century where drought and heat increase will combine \r\n(Chapter 11; Engelbrecht et al., 2015; Abatzoglou et al., 2019). There \r\nis low confidence (limited evidence) of fire weather changes for other \r\nAfrican regions."


id: 9a34338b92f51641b51dd235f33bd6ef
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 24369
content:
"Aridity: Section 11.9 assesses medium confidence in observed \r\nlong-term declines of soil moisture and aridity indices in several \r\nAfrican regions (NAF, WAF). Trends in East Africa are not definitive \r\ngiven uncertain balances between precipitation and potential \r\nevaporation (Kew et  al., 2021). Projected declines in precipitation \r\nand soil moisture trends indicate high confidence in increased aridity \r\nover the 21st century in NAF, WSAF and ESAF but low confidence\r\nelsewhere in Africa (Section 11.9; see also Figure 12.4j-l; Gizaw and "


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vector_id: 25582
content:
"Total precipitation is projected to decrease in the northernmost \r\n(high confidence) and southernmost regions of Africa \r\n(medium confidence), with West and East Africa regions each \r\nhaving a  west-to-east pattern of decreasing-to-increasing \r\nprecipitation (medium confidence). Most African regions will \r\nundergo an increase in heavy precipitation that can lead \r\nto pluvial floods (high confidence), even as increasing dry \r\nclimatic impact-drivers (aridity, hydrological, agricultural and \r\necological droughts, fire weather) are generally projected in \r\nthe North Africa and Southern African regions (high confidence) \r\nand western portions of West Africa (medium confidence)."


id: 12ca62a6690d1cc95440ef0afaa1538c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 509
content:
"Sand and dust storm: North Africa and the Sahel, and to a lesser extent \r\nSouthern Africa, are prone to dust storms, having consequences on \r\nhealth (Querol et al., 2019), transmission of infectious diseases (Agier \r\net al., 2013; Wu et al., 2016), and solar power generation and related \r\nmaintenance costs. There is limited evidence and low agreement\r\nof secular 20th  century trends in wind speeds or dust emissions \r\n(limited length of data records, large variability). Dust variations are \r\ncontrolled by changes in surface winds, precipitation and vegetation, \r\nwhich in turn are modulated at multiple time scales by dominant \r\nmodes of internal climate variability (Chapter  10). In North Africa, \r\nwind variability explains both the observed high concentrations \r\nbetween the 1970s and 1980s and lower concentrations thereafter \r\n(Ridley et al., 2014; Evan et al., 2016). Yet, the effect of vegetation \r\nchanges may not be negligible (Pu and Ginoux, 2017, 2018)."


id: b761bf4834de18344b02a41f83f72f15
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 29475
content:
"Mean wind speed: Decreasing trends in wind speeds have \r\noccurred in many parts of Africa (low confidence due to observations \r\nwith limited homogeneity) (McVicar et al., 2012; AR5 WGI). There \r\nis high confidence in climate change-induced future decreasing \r\nmean wind, wind energy potential and strong winds in North Africa \r\nand Mediterranean regions as a  consequence of the poleward \r\nshift of the Hadley cell (Karnauskas et al., 2018a; Kjellstrom et al., \r\n2018; Sivakumar and Lucio, 2018; Tobin et  al., 2018; Jung and \r\nSchindler, 2019) in the RCP4.5 and RCP8.5 scenarios by the middle \r\nof the century or beyond, and for a  GWL of 2degC or higher. Over \r\nWestern Africa and Southern Africa a  future significant increase \r\nin wind speeds and wind energy potential is expected (medium \r\nconfidence) (Figure 12.4m-o; Karnauskas et al., 2018a; Jung and \r\nSchindler, 2019)."


id: 2ca9de52a5c8a1a2f28d1c801930765f
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 5120
content:
"Changes to the frequency and intensity of dust storms also remain largely \r\nuncertain due to uncertainty in future regional wind and precipitation \r\nas the climate warms, CO2 fertilization effects on vegetation (Huang \r\net al., 2017), and anthropogenic land use and land-cover change due \r\nto land management and invasive species (Ginoux et al., 2012; Webb \r\nand Pierre, 2018). Dust loadings and related air pollution hazards (from \r\nfine particles that affect health) are projected to generally decrease \r\nin many regions of the Sahara and Sahel due to the changing winds \r\n(Evan et al., 2016) and slightly increase over the Guinea coast and West \r\nAfrica (low confidence) (Ji et al., 2018)."


id: dd249b0e2567ebb8a967802e0dba33b8
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 36169
content:
"In summary, there is high confidence of a decrease in mean \r\nwind speed and wind energy potential in North Africa and \r\nmedium confidence of an increase in Southern and Western \r\nAfrica, by the middle of the century regardless of climate \r\nscenario or global warming level equal or superior to 2degC, high \r\nconfidence of a decrease in frequency of cyclones landing in \r\nSEAF, ESAF and MDG, and low confidence of a general increase \r\nin wind storms in most African regions located south of the \r\nSahel. The evolution of dust storms remains largely uncertain."


id: 80f14b2ff1252a57ba58471aba72282e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 19822
content:
"Tropical cyclone: In the South Indian Ocean, an increase in Category 5 \r\ncyclones has been observed in recent decades (Fitchett, 2018) as in \r\nother basins (Section 11.7). However, there is a projected decrease \r\nin the frequency of tropical cyclones making landfall over Madagascar, \r\nSouth Eastern Africa and East Southern Africa in a 1degC, 2degC and 3degC \r\nwarmer world (medium confidence) (Malherbe et al., 2013; Roberts \r\net al., 2015, 2020; Muthige et al., 2018; Knutson et al., 2020). There \r\nis medium confidence in general increasing intensities for cyclones in \r\nsuch studies for African regions."


id: b95619057806cf0699e223726c001287
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 29819
content:
"In conclusion, there is high confidence that African snow and \r\nglaciers have very significantly decreased in the last decades \r\nand that this trend will continue over the 21st century."


id: 68192e1928c105a898f29102573c850f
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 15581
content:
"was found to be retreating while 21% was found to be stable or \r\nprograding over the period 1974-1996 (Addo and Addo, 2016)."


id: 806082027567992fe493a811888b9c62
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 19716
content:
"Relative sea level: Around Africa, from 1900 to 2018, a new tide \r\ngauge-based reconstruction finds a  regional mean RSL change of \r\n2.07 [1.36 to 2.77] mm yr -1 in the South Atlantic and 1.33 [0.80 to \r\n1.86] mm yr-1 in the Indian Ocean (Frederikse et al., 2020), compared \r\nto a  GMSL change of around 1.7  mm yr -1 (Section  2.3.3.3 and \r\nTable  9.5). For the period 1993-2018, these RSLR rates, based on \r\nsatellite altimetry, increased to 3.45 [3.04 to 3.86]  mm yr-1 and \r\n3.65  [3.23 to 4.08]  mm yr-1 respectively (Frederikse et  al., 2020), \r\ncompared to a GMSL change of 3.25 mm yr -1 (Section 2.3.3.3 and \r\nTable 9.5)."


id: fe43e2dcb229819f64dbf294314adf9
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 42104
content:
"Relative sea level rise is virtually certain to continue in the oceans \r\naround Africa. Regional mean RSLR projections for the oceans around \r\nAfrica range from 0.4-0.5 m under SSP1-2.6 to 0.8-0.9 m under \r\nSSP5-8.5 for 2081-2100 relative to 1995-2014 (median values), \r\nwhich is within the range of projected GMSL change (Section 9.6.3.3). \r\nThese RSLR projections may, however, be underestimated due \r\nto potential partial representation of land subsidence in their \r\nassessment (Section 9.6.3.2)."


id: 4ac2d60f42cc0e248c398eeda9b31d24
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 10398
content:
"Marine heatwave (MHW): From 1982 to 2016, the coastal oceans \r\nof Africa have experienced on average 2-3 MHWs per year, with the \r\ncoastal oceans around the southern half of the continent experiencing \r\non average 2.5-3 MHWs per year. The average duration was between \r\n5 and 15 days (Oliver et al., 2018). Changes over the 20th century, \r\nderived from MHW proxies, show an increase in frequency between \r\n0.5 and 2 MHWs per decade over the region, especially off the Horn \r\nof Africa; an increase in intensity per event around Southern Africa; \r\nand an increase in MHW duration along the North African coastlines \r\n(Oliver et al., 2018)."


id: d2ff323ce735ab4842b65c3ca9dd1497
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 34466
content:
"Coastal flood: The present-day 1-in-100-year extreme total water \r\nlevel is between 0.1 and 1.2 m around Africa, with values around 1 m \r\nor above along the south-west, south-east and central east coasts \r\n(Vousdoukas et al., 2018)."


id: a4ff8826af2c47bb9fe9e6eb82e131b5
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 26251
content:
"There is high confidence that MHWs will increase around Africa. \r\nMean SST, a common proxy for MHWs, is projected to increase by \r\n1degC (2degC) around Africa by 2100, with a  hotspot of around 2degC \r\n(5degC) along the coastlines of South Africa under RCP4.5 (RCP8.5; \r\nInteractive Atlas). Under global warming conditions, MHW intensity \r\nand duration will increase in the coastal zones of all sub-regions of \r\nAfrica (Frolicher et al., 2018). Projections for SSP1-2.6 and SSP5-8.5 \r\nboth show an increase in MHWs around Australasia by 2081-2100, \r\nrelative to 1985-2014 (Box 9.2, Figure 1)."


id: 29256bd96494f4470226128b1fa220da
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 4450
content:
"In general, there is high confidence that most coastal\u0002and ocean-related hazards in Africa will increase over the \r\n21st  century. Relative sea level rise is virtually certain to \r\ncontinue around Africa, contributing to increased coastal \r\nflooding in low-lying areas (high confidence) and shoreline \r\nretreat along most sandy coasts (high confidence). Marine \r\nheatwaves are also expected to increase around the region \r\nover the 21st century (high confidence)."


id: 8e5101556d72d156917aefa783afb71c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 22227
content:
"Coastal erosion: Shoreline retreat rates up to 1 m yr -1 have been \r\nobserved around the continent during 1984-2015, except in ESAF, \r\nwhich has experienced a shoreline progradation rate of 0.1 m/r over \r\nthe same period (Luijendijk et  al., 2018; Mentaschi et  al., 2018). \r\nMentaschi et  al. (2018) report a  coastal area losses of 160 km2\r\nand 460 km2 over a 30-year period (1984-2015) along the Atlantic \r\nand  Indian Ocean coasts of the continent. At the more regional \r\nlevel, in Ghana along the Gulf of Guinea about 79% of the shoreline "


id: 8e13ace543803420afcb24aa563e301a
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 22190
content:
"The assessed direction of change in CIDs for Africa and associated \r\nconfidence levels are illustrated in Table 12.3. No relevant literature \r\ncould be found for permafrost and hail, although these phenomena \r\nmay be relevant in parts of the continent."


id: f092c98a3c6f4b556d072979625d64fa
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 39700
content:
"Chapter  11) due to the effects of anthropogenic global warming, \r\nEl Nino and urbanization (Luo and Lau, 2017; Thirumalai et al., 2017; \r\nImada et al., 2019; Y. Sun et al., 2019; Zhou et al., 2019). But there \r\nis medium confidence of heat extremes increasing in frequency in \r\nmany parts of India (Rohini et al., 2016; Mazdiyasni et al., 2017; van \r\nOldenborgh et al., 2018; Sen Roy, 2019; Kumar et al., 2020) partly \r\ndue to the alleviation of anthropogenic warming by increased air \r\npollution with aerosols and expanding irrigation (van Oldenborgh \r\net al., 2018; Thiery et al., 2020)."


id: c535a932b0f361806d44dc22ab66d4
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 32000
content:
"According to the region definitions given in Chapter 1, Asia is divided \r\ninto 11 regions: the Arabian Peninsula (ARP), Western Central Asia \r\n(WCA), West Siberia (WSB), East Siberia (ESB), the Russian Far East \r\n(RFE), East Asia (EAS), East Central Asia (ECA), the Tibetan Plateau \r\n(TIB), South Asia (SAS), South East Asia (SEA) and the Russian Arctic \r\nRegion (RAR). CID changes in RAR are assessed in the Polar Region \r\nsection (Section 12.4.9). As assessed in previous IPCC Reports, major \r\nconcerns in Asia are associated particularly with droughts and floods \r\nin all regions, heat extremes in SAS and EAS, sand-dust storms in \r\nWCA, tropical cyclones in SEA and EAS, snow cover and glacier \r\nchanges in ECA and the Hindu Kush Himalaya (HKH) region, and sea \r\nice and permafrost thawing in northern Asia."


id: 5d93a99eebbc64cfd625b22b6576b5a6
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 13749
content:
"Since AR5, a large body of new literature is now available relevant \r\nto climate change in Asia, which includes projections of both mean \r\nclimate and extreme climate phenomena from global and regional \r\nensembles of climate simulations such as CMIP6 and CORDEX \r\n(Chapter 10 and the Atlas). Literature has also considerably grown on \r\nseveral climate topics relevant to Asia such as the mountain climate \r\n(Chapter  3 of the SROCC), and the novel regional assessments \r\nsuch as the Hindu Kush Himalaya Assessment (Wester et al., 2019). \r\nFigure 12.6 shows the regional changes in indices related to floods, \r\nand coastal erosion over Asia, which are assessed on a regional basis \r\nalong with other climatic impact-driver indices below."


id: 2239ac0976a262ccf3dece15d23f4051
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 3243
content:
"Mean air temperature: A  long-term warming trend in annual \r\nmean surface temperature has been observed across Asia during \r\n1960-2015, and the warming accelerated after the 1970s (high \r\nconfidence) (Davi et al., 2015; Aich et al., 2017; Cheong et al., 2018; \r\nS. Dong et al., 2018; IPCC, 2018; Krishnan et al., 2019; M. Zhang et al., \r\n2019). Records also indicate a higher rate of warming in minimum \r\ntemperatures than maximum temperatures in Asia, leading to more \r\nfrequent warm nights and warm days, and less frequent cold days \r\nand cold nights (high confidence) (Supari et al., 2017; Akperov et al., \r\n2018; Cheong et al., 2018; Rahimi et al., 2018; Khan et al., 2019a; L. Li \r\net al., 2019; M. Zhang et al., 2019)."


id: df49e734fc62e1704bbfd46174d1b9c0
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
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content:
"Cold spell and frost: Cold spells intensity and frequency, as well as \r\nthe number of frost days, in most Asian regions have been decreasing \r\nsince the beginning of the 20th century (high confidence) (Chapter 11; \r\nSheikh et al., 2015; Donat et al., 2016; Erlat and Turkes, 2016; S. Dong \r\net al., 2018; Liao et al., 2018, 2020; Lu et al., 2018; van Oldenborgh \r\net al., 2019), except for the central Eurasian regions, where there was \r\na  cooling trend during 1995-2014, which is linked to sea ice loss \r\nin the Barents-Kara Seas (medium confidence) (Atlas.5.2; Wegmann \r\net al., 2018; Blackport et al., 2019; Mori et al., 2019)."


id: 864e49b673a4da2a1dddb7842b0758e6
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
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content:
"Projections show continued warming over Asia in the future with \r\ncontrasted regional patterns across the continent (high confidence) \r\n(Figure 4.19). For RCP8.5/SSP5-8.5 at the end of the century, the mean \r\nestimated warming exceeds 5degC in WSB, ESB and RFE and 7degC in \r\nsome parts (high confidence). In most areas of ARP and WCA, 5degC is \r\nexceeded (Ozturk et al., 2017), but EAS, SAS and SEA have a lower \r\nprojected warming of less than 5degC (Basha et al., 2017; C. Lu et al., \r\n2019; Almazroui et al., 2020; Atlas.5). Under SSP1-2.6, the warming \r\nremains limited to 2degC in most areas except Arctic regions, where it \r\nexceeds 2degC (Figure 4.19)."


id: 2330c726865a964aec4e186cc9435e43
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
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content:
"It is very likely that cold spells will have a decreasing frequency in all \r\nfuture scenarios across Asian regions (J. Guo et al., 2018; Sui et al., \r\n2018; L. Li et al., 2019), as well as frost days (L. Wang et al., 2017; \r\nFallah-Ghalhari et al., 2019) except in tropical Asia (Chapter 11)."


id: fb856bae515e78c4237673c6e2ddf33e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 41624
content:
"In Asia, temperatures have warmed during the last  century \r\n(high confidence). Extreme heat episodes have become more \r\nfrequent in most regions (high confidence), and are very likely\r\nto increase in all regions of Asia under all warming scenarios \r\nduring this century. Dangerous heat stress thresholds such \r\nas HI  > 41degC will be crossed much more often (typically \r\n50-150  days per year more than the recent past) in many \r\nsouthern Asia regions at the end of the century under SSP5-8.5 "


id: b860f7e66e7e0e1a900bb558efb21107
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 29653
content:
"Extreme heat: There is increased evidence and high confidence of \r\nmore frequent heat extremes in the recent decades than in previous \r\nones in most of Asia (Acar Deniz and Gonencgil, 2015; Rohini et al., \r\n2016; Mishra et al., 2017; You et al., 2017; Imada et al., 2018; Khan \r\net al., 2019b; Krishnan et al., 2019; Rahimi et al., 2019; Yin et al., 2019; "


id: 5cce190fe8a49dfa8a2b162c250f0372
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 13592
content:
"while these numbers should remain limited to a few tens under \r\nSSP1-2.6 (high confidence). It is very likely that cold spells and \r\nfrost days will decrease in frequency in all future scenarios \r\nacross Asian regions during the century."


id: 590e698f47a139431aa915c8aee40c12
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 12912
content:
"precipitation vary considerably by region (Chapter  11). Heavy \r\nprecipitation is very likely to become more intense and frequent in all \r\nareas of Asia except in ARP (medium confidence) for a 2degC GWL or \r\nhigher (Chapter 11)."


id: 575afc306fd2143f86b3a6370828e0c0
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 12630
content:
"Mean precipitation: The most prominent features about changes in \r\nprecipitation over Asia (1901-2010) are the increasing precipitation \r\ntrends across higher latitudes, along with some scattered smaller \r\nregions of detectable increases and decreases (Knutson and Zeng, \r\n2018); however, spatial variability remains high (W. Wang et  al., \r\n2015; Limsakul and Singhruck, 2016; Supari et  al., 2017; Rahimi \r\net al., 2018, 2019; Sein et al., 2018; Kumar et al., 2019; H. Wang et al., \r\n2019; see Atlas.5) (medium confidence)."


id: ad1ef0a666c721961d5bc8b33175ccaa
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 27698
content:
"Mean precipitation is likely to increase in most areas of northern \r\n(WSB, ESB, RFE), southern (ECA, TIB, SAS) and East Asia (EAS) in \r\ndifferent scenarios (high confidence) (Huang et al., 2014; Xu et al., \r\n2017; Kusunoki, 2018; Mandapaka and Lo, 2018; Luo et  al., 2019; \r\nWu et  al., 2019; X. Zhu et  al., 2019; Almazroui et  al., 2020; Jiang \r\net al., 2020; Rai et al., 2020; see Atlas.5). Monsoon circulation will \r\nalso increase seasonal contrasts, with SAS seeing wetter wet seasons \r\nand drier dry seasons (Atlas.5.3). Higher uncertainty between CMIP5 \r\nand CMIP6 as well as spatial differences lend low confidence to \r\nmodel projections in ARP and WCA (Atlas.5.5), with large seasonal \r\ndifferences (Zhu et al., 2020) and some models projecting decreases \r\nin precipitation in Central Asia (Ozturk et al., 2017), Pakistan (Nabeel \r\nand Athar, 2020) and SEA (Supari et al., 2020)."


id: 7dd4e1b88f74ef1d2afc384ec5c9695b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 19311
content:
"River flood: Flood risk has grown in many places in China from \r\n1961 to 2017 (Kundzewicz et  al., 2019) (low confidence). In SAS, \r\nthe numbers of flood events and human fatalities have increased \r\nin India during 1978-2006 (Singh and Kumar, 2013), whereas the \r\naverage country-wide inundation depth has been decreasing during \r\n2002-2010 in Bangladesh, attributed to improved flood management \r\n(low confidence) (Sciance and Nooner, 2018)."


id: c625cf27339aa43b9de6857b29023e4e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 32170
content:
"The counteracting factors of projected increases in precipitation and \r\ntemperature across most of Asia (Section  11.9 and Atlas.5) leads \r\nto low confidence (limited evidence, inconsistent trends) for broad, \r\nlong-term aridity changes with medium confidence only for aridity \r\nincreases in West Central Asia and East Asia. A  growing number \r\nof studies highlight the potential for more localized aridity trends, \r\nincluding projection ensembles indicating significant increase in \r\naridity and more frequent and intense droughts in most parts of "


id: da64593cd73c02290a52d20505d29a2c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 35721
content:
"Heavy precipitation and pluvial flood: Pluvial floods are driven \r\nby extreme precipitation and land use. Observed changes in extreme "


id: 8aa6b68e09102b0643384f6911280b40
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 21566
content:
"confidence) (Q. Sun et al., 2019). Abatzoglou et al. (2019) found that \r\nhigher fire weather conditions due to climate change emerge in the \r\nfirst part of the 21st century in South China, WCA as well as in boreal \r\nareas of Siberia and RFE. The potential burned areas in five Central \r\nAsian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan and \r\nTurkmenistan) will increase by 2-8% in the 2030s and 3-13% in the \r\n2080s compared with the baseline (medium confidence) (1971-2000; \r\nZong et al., 2020)."


id: 4bf09f28fdaab5f7a5336e1ee5744afe
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 10625
content:
"China (Y. Li et al., 2019; Yao et al., 2020) and India under RCP4.5 and \r\nRCP8.5 for the 2020-2100 period (Gupta and Jain, 2018; Bisht et al., \r\n2019; Preethi et al., 2019)."


id: 431b4a2800f14e991d2c6e6ef4f0e1a
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 9012
content:
"In conclusion, there is medium confidence that extreme \r\nprecipitation, mean precipitation and river floods will increase \r\nacross most Asian regions. There is low confidence for projected \r\nchanges in aridity and drought given overall increases in \r\nprecipitation and regional inconsistencies, with medium \r\nincreases for West Central Asia and East Asia especially beyond \r\nthe middle of the century and global warming levels beyond 2degC. \r\nFire weather seasons are projected to lengthen and intensify \r\nparticularly in the northern regions (medium confidence)."


id: 8993879259c0495c560aac2739939df2
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 21378
content:
"Mean wind speed: There is high confidence of the slowdown in \r\nterrestrial near-surface wind speed (SWS) in Asia by approximately \r\n-0.1 m s-1 per decade since the 1950s based on observations and \r\nreanalysis data, with the significant decreases in Central Asia among \r\nthe highest in the world followed by EAS and SAS (J. Wu et al., 2018; \r\nTian et al., 2019; R. Zhang et al., 2019). But a short-term strengthening \r\nin SWS was observed during the winter since 2000 in eastern China \r\n(medium confidence) (Zeng et al., 2019; Zha et al., 2019). "


id: 9336900095749d119f9d0c02731a63fe
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 23100
content:
"Agricultural and ecological drought: Section 11.9 assesses medium \r\nconfidence in observed increases to agricultural and ecological \r\ndroughts in West Central Asia, East Central Asia, and East Asia. \r\nPersistent droughts were the main factor for grassland degradation \r\nand desertification in Central Asia in the early 21st century (G. Zhang \r\net al., 2018; Emadodin et al., 2019). Compound meteorological drought \r\nand heat events, which lead to water stress conditions for agricultural \r\nand ecological systems, have become more frequent, widespread \r\nand persistent in China especially since the late 1990s (Yu and Zhai, \r\n2020). There were more agricultural droughts in northern China than \r\nin southern China, and the intensity of agricultural drought increased \r\nduring 1951-2018 (Zhao et al., 2021)."


id: 64ede034a5d3bb37e6f16e733349a1c2
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 15029
content:
"There is medium confidence of future declining mean SWS in Asia, \r\nexcept in SAS and SEA, as global projections indicate a decreasing \r\ntrend in all climate scenarios for most of northern Asia, TIB and \r\nEast Asia by the mid-century (Karnauskas et  al., 2018a; Fedotova, \r\n2019; Jung and Schindler, 2019; Ohba, 2019; J. Wu et  al., 2020; \r\nZha et  al., 2020; Figure  12.4m-o), with negative effects on wind \r\nenergy potential. Decreases in North Asia are generally modest, not \r\nexceeding 10% for the mid-century and 20% for the end of century \r\nfor the RCP8.5 and RCP4.5 scenarios (Figure 12.4m-o)."


id: fc8e73fbe6172e6eb70790530d410b3
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 41801
content:
"Severe wind storms: Consistent with the general mean decreasing \r\nsurface winds, there is medium confidence that strong winds declined \r\nfaster than weak winds in the past few decades in Asia in general \r\n(Vautard et al., 2010; Tian et al., 2019), but evidence is lacking for \r\nspatial patterns. There is low confidence that extra-tropical cyclones \r\nwill decline in number in future climate scenarios over WCA, TIB, \r\nWSB and ESB, and intensify over the Arctic regions as a result of the \r\npoleward shift of storm tracks (Basu et al., 2018; Chapter 11). There is \r\nlimited evidence for projection of changes in severe winds occurring \r\nin convective storms in Asia."


id: e3caa7b0dcf2e12c1001bdc63d47d14e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 37363
content:
"Studies examining a 2degC GWL give low confidence for projected broad \r\nchanges to agricultural and ecological drought across all Asia regions, \r\nalthough at 4degC GWL agricultural and ecological drought increases are \r\nprojected for West Central Asia and East Asia along with a decrease in \r\nSouth Asia (medium confidence) (Section 11.9). Summer temperature \r\nincrease will enhance evapotranspiration, facilitating ecological and \r\nagricultural drought over Central Asia towards the latter half of this \r\ncentury (Chapter  11; see also Figure  12.4 for soil moisture and DF \r\nindices; Ozturk et al., 2017; Reyer et al., 2017b; Senatore et al., 2019). \r\nHowever, broader changes in droughts could not be determined in \r\nAsia due to the mixture of total precipitation signals together with \r\ntemperature increase patterns (Section 11.9 and Atlas.5)."


id: 1f30128a908ddb2b19fa42e1e7c914db
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 2697
content:
"Tropical cyclone: There was an increase in the number and \r\nintensification rate of intense tropical cyclones (TC), such as \r\nCategory 4-5 (wind speeds >58 m s-1), in the Western North Pacific \r\n(WNP) and Bay of Bengal since the mid-1980s (medium confidence) \r\n(Section  11.7; Kim et  al., 2016; Mei and Xie, 2016; Walsh et  al., \r\n2016a; Knutson et  al., 2019). There is medium confidence that "


id: 1b77faf719a8f179115149ca413063b0
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 2015
content:
"there has been a significant north-westward shift in TC tracks and \r\na poleward shift in the average latitude where TCs reach their peak \r\nintensity in the WNP since the 1980s (Knutson et al., 2019; J. Sun \r\net al., 2019; Lee et al., 2020), increasing exposure to TC passage and \r\nmore destructive landfall over eastern China, Japan, and Korea in the \r\nlast few decades (Kossin et al., 2016; Li et al., 2017; Altman et al., \r\n2018; Liu and Chan, 2019), and decreasing exposure in the region \r\nof SAS and southern China (Cinco et al., 2016; Kossin et al., 2016; \r\nsee Chapter 11). However, while the analysis shows fewer typhoons, \r\nmore extreme TCs have affected the Philippines (low confidence) \r\n(Takagi and Esteban, 2016). The frequency and duration of tropical \r\ncyclones has significantly increased over time over the Arabian \r\nSea and insignificantly decreased over the Bay of Bengal during \r\n1977-2018 (low confidence) (Fan et al., 2020)."


id: 91896bae79f6127024ccdbc6909b969
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 22824
content:
"Observations do show significant changes in the seasonal timing of \r\nEurasian snow cover extent (especially for earlier spring snowmelt) \r\nsince the 1970s, with seasonal changes expected to continue in the \r\nfuture (high confidence) (Yeo et al., 2017; Zhong et al., 2021). By 2100, \r\nsnowline elevations are projected to rise between 400  and 900 m \r\n(4.4  to 10.0 m yr-1) in the Indus, Ganges and Brahmaputra basins \r\nunder the RCP8.5 scenario (Viste and Sorteberg, 2015)."


id: c7e15f37ac0ba2ad27ba5805b98813
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 32474
content:
"Glacier: Observation and future projection of glacier mass changes \r\nin Asia are assessed in Section 9.5.1 grouped in three main regions: \r\nnorthern Asia, High Mountains of Asia, and Caucuses and Middle \r\nEast. All regions show continuing decline in glacier mass and area \r\nin the coming century (high confidence). Under RCP2.6 the pace of \r\nglacier loss slows, but glacier losses increase in RCP8.5 and peak \r\nin the mid to late 21st century. GlacierMIP projections indicate that \r\nglaciers in the High Mountains of Asia lose 42+-25%, 56+-24% and \r\n71+-21% of their 2015 mass by the end of the century for RCP2.6, \r\nRCP4.5 and RCP8.5 scenarios respectively. Under the same scenarios, \r\nglaciers in North Asia would lose 57+-40%, 72+-38% and 85+-30% \r\nof their mass, and glaciers in the Caucuses and the Middle East \r\nwould lose 68+-32%, 83+-19% and 94+-13% of their mass (see also \r\nKraaijenbrink et al., 2017; Rounce et al., 2020)."


id: 1af5a38297ec87c2e2f7a5d4eb6a832e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 1939
content:
"There is medium confidence that future TC numbers will decrease but \r\nthe maximum TC wind intensities will increase in the western Pacific as \r\nelsewhere (Chapter 11, see Figure 11.24; Choi et al., 2019; Cha et al., \r\n2020; Knutson et al., 2020). The simulations for the late 21st century \r\nfor the RCP8.5 scenario yield considerably more TCs in the WNP that \r\nexceed 49.4 m s-1 (Category 3) intensity (Mclay et al., 2019). There is \r\nmedium confidence that the average location of the maximum wind \r\nwill migrate poleward (see Chapter 11), and TC translation speeds \r\nat the higher latitudes would decrease (Yamaguchi et al., 2020). As \r\na consequence, the intensity of TCs affecting the Japan Islands would \r\nincrease in the future under the RCP8.5 scenario (Yoshida et  al., \r\n2017), whereas the frequency of TCs affecting the Philippine region \r\nand Vietnam is projected to decrease (Kieu-Thi et al., 2016; C. Wang \r\net al., 2017; Gallo et al., 2019) (medium confidence)."


id: f1138002918b21c882d9e858194775ca
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 39791
content:
"Although enhanced meltwater from snow and glaciers largely offsets \r\nhydrological drought-like conditions (Pritchard, 2019), this effect is \r\nunsustainable and may reverse as these cryospheric buffers disappear \r\n(medium confidence) (Gan et al., 2015; W. Dong et al., 2018; Huss and \r\nHock, 2018). In the Himalayas and the TIB region higher temperatures \r\nwill lead to higher glacier melt rates and significant glacier shrinkage \r\nand a  summer runoff decrease (medium confidence) (Sorg et  al., \r\n2014). Glacier runoff in the Asian high mountains will increase up \r\nto mid-century, and after that runoff might decrease due to the loss \r\nof glacier storage (medium confidence) (Lutz et al., 2014; Huss and \r\nHock, 2018; Rounce et al., 2020)."


id: f9dfb60ffb55ca131cb12d40ffa62ee2
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 41324
content:
"Sand and dust storm: The Asia-Pacific region contributes \r\n26.8 per cent to global dust emissions as of 2012 (UNESCAP, 2018). \r\nIn West Asia, the frequency of dust events has increased markedly \r\nin some areas (east and north-east of Saudi Arabia, north-west of \r\nIraq and east of Syria) from 1980 to the present (Nabavi et al., 2016; \r\nAlobaidi et al., 2017). This marked dust increase has been associated \r\nwith drought conditions in the Fertile Crescent (Notaro et al., 2015; Yu \r\net al., 2015), likely amplified by anthropogenic warming (Kelley et al., \r\n2015; Chapter 10). Dust storm frequency in most regions of northern \r\nChina show a decreasing trend since the 1960s due to the decrease in \r\nsurface wind speed (medium confidence) (Guan et al., 2017)."


id: b4756587e48420c5f7071584dc3284d
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 28988
content:
"Compared with the 1990s, the number of lakes in TIB in the 2010s \r\ndecreased by 2%, whereas total lake area expanded by 25% (S. Wang \r\net al., 2020) due to the joint effect of precipitation increase and glacier \r\nretreat. Many new lakes are predicted to form as a  consequence \r\nof continued glacier retreat in the Himalaya-Karakoram region \r\n(Linsbauer et al., 2016). As many of these lakes will develop at the \r\nimmediate foot of steep icy peaks with degrading permafrost and \r\ndecreasing slope stability, the risk of glacier lake outburst floods \r\nand floods from landslides into moraine-dammed lakes is increasing \r\nin Asian high mountains (high confidence) (Haeberli et  al., 2017; \r\nKapitsa et al., 2017; Bajracharya et al., 2018; Narama et al., 2018; \r\nS. Wang et al., 2020)."


id: a21e6711fc3fbadfb68c27d746e7db8e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 25755
content:
"While dust activity has decreased greatly over EAS, current climate \r\nmodels are unable to reproduce the trends (Guan et al., 2015, 2017; \r\nZha et al., 2017; C. Wu et al., 2018). Thus, there is limited evidence for \r\nfuture trends of sand and dust storms in Asia."


id: d335a66398da394a494715ac3878b730
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 34506
content:
"In conclusion, surface wind speeds have been decreasing in \r\nAsia (high confidence), but there is a large uncertainty in future \r\ntrends. There is medium confidence that mean wind speeds will \r\ndecrease in Central and northern Asia, and that tropical cyclones \r\nwill have decreasing frequency and increasing intensity overall."


id: 3e14acffab183be1b977df4ebca0209d
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 8087
content:
"Permafrost: Permafrost is thawing in Asia (high confidence). \r\nTemperatures in the cold continuous permafrost of north-eastern \r\nEast Siberia rose from the 1980s up to 2017, and the active layer \r\nthicknesses in Siberia and Russian Far East generally increased \r\nfrom late 1990s to 2017 (Romanovsky et  al., 2018). The change \r\nin mean annual ground temperature for northern Siberia is about \r\n+0.1 to +0.3degC per decade since 2000 (Romanovsky et al., 2018). \r\nGround temperature in the permafrost regions of TIB (taking 40% \r\nof TIB currently) increased (0.02-0.26degC per decade for different "


id: a371a4afbb1afe748115dbc477728470
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 25963
content:
"Snow: There is no significant interannual trend of total snow cover \r\nfrom 2000 to 2016 over Eurasia (X. Wang et al., 2017a; Sun et al., 2020). "


id: 256868eeff0fb8bb45d41def3e46301e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 3766
content:
"In summary, snowpack and glaciers are projected to continue \r\ndecreasing and permafrost to continue thawing in Asia (high \r\nconfidence). There is medium confidence of increasing heavy \r\nsnowfall in some regions, but limited evidence on future \r\nchanges in hail and snow avalanches."


id: 8266ae96689422e37db8832e7712e729
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 20068
content:
"boreholes) during 1980 to 2018, and the active layer thickened at \r\na  rate of 19.5  cm per decade (L. Zhao et  al., 2020). There is high \r\nconfidence that permafrost in Asian high mountains will continue to \r\nthaw and the active layer thickness will increase (Bolch et al., 2019). \r\nThe permafrost area is projected to decline by 13.4-27.7% and \r\n60-90% in TIB (L. Zhao et al., 2020) and 32%+-11% and 76%+-12% \r\nin Russia (Guo and Wang, 2016) by the end of the 21st century under \r\nthe RCP2.6 and RCP8.5 scenarios respectively (high confidence)."


id: 12f20c82eb49dcd25fc1822cbfc70e1c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 540
content:
"Lake and river ice: Lake ice cover duration got shorter in many lakes \r\nin TIB (Yao et al., 2016; Cai et al., 2019; Guo et al., 2020) and some \r\nother areas such as north-west China (Cai et al., 2020) and north-east \r\nChina (Yang et al., 2019) in the last two decades (high confidence). \r\nRiver ice cover extent decreased in TIB as well (H. Li et  al., 2020; \r\nYang et  al., 2020a). Climate warming also leads to a  significant \r\nreduction in the period with ice phenomena and the decrement \r\nof ice regime hazard in Russian lowland rivers (Agafonova et  al., \r\n2017), and the Inner Mongolia reach of the Yellow River in northern \r\nChina (Wan et  al., 2020) (high confidence). Lake ice and river ice \r\nin Asia are expected to decline with projected increases in surface \r\nair temperature towards the end of this century (high confidence) \r\n(Guo et al., 2020; Yang et al., 2020a)."


id: 775a7f593d11e8ded4ca7b975e1bd463
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
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content:
"Relative sea level rise is very likely to continue in the oceans around \r\nAsia. Regional mean RSLR projections for the oceans around Asia \r\nrange from 0.3-0.5 m under SSP1-2.6 to 0.7-0.8 m under SSP5-8.5 \r\nfor 2081-2100 relative to 1995-2014 (median values), which is \r\nwithin the range of projected GMSL change (Section 9.6.3.3). These \r\nRSLR projections may, however, be underestimated due to potential \r\npartial representation of land subsidence in their assessment \r\n(Section 9.6.3.2)."


id: e333913fc8b33460c65fadf139564430
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 37272
content:
"Coastal flood: The present-day 1-in-100-year ETWL is between \r\n0.5-8 m around Asia, with values above 2.5 m or above common \r\nalong the coasts of Central and north-eastern Asia (Vousdoukas et al., \r\n2018; Kirezci et  al., 2020). Sea level rise and land subsidence will \r\njointly lead to more flooding in delta areas in Asia (high confidence) \r\n(Takagi et al., 2016; J. Wang et al., 2018)."


id: bde22238e83a9f34125c28403f1cbf1b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 30667
content:
"Hail: The hailstorm in the Asian region shows a decreasing trend in \r\nseveral regions (low confidence, limited evidence). In China severe \r\nweather days including thunderstorms, hail and/or damaging wind \r\nhave decreased by 50% from 1961 to 2010 (M. Li et  al., 2016; \r\nZhang et al., 2017), and the hail size decreased since 1980 (Ni et al., \r\n2017). A  rate of decrease of 0.214 hail days per decade has also \r\nbeen reported for Mongolia between 1984-2013, where the annual \r\nnumber of hail days averaged is 0.74 (Lkhamjav et al., 2017)."


id: d7c0b84bb38b5acfc6cacf1dbcd57f95
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 35265
content:
"Extreme total water level magnitude and occurrence frequency \r\nare expected to increase throughout the region (high confidence) \r\n(Figure  12.4p-r and Figure  12.SM.6). Across the region, the 5-95th \r\npercentile range of the 1-in-100-year ETWL is projected to increase \r\n(relative to 1980-2014) by 7-44 cm and by 10-52 cm by 2050 under \r\nRCP4.5 and RCP8.5 respectively. By 2100, this range is projected to \r\nbe 11-91 cm and 28-187 cm under RCP4.5 and RCP8.5 respectively "


id: ab9a5d7917e4086bf195ea0991a79432
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 27428
content:
"Snow avalanche: There is as yet limited evidence for the evolution of \r\navalanches in Asia. Tree-ring-based snow avalanche reconstructions in \r\nthe Indian Himalayas show an increase in avalanche occurrence and \r\nrunout distances in recent decades (Ballesteros-Canovas et al., 2018)."


id: bd0fccf7d451e55ef706ec84a6dcb956
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 30509
content:
"In general, there is high confidence that most coastal/ocean\u0002related climatic impact-drivers in Asia will increase over the \r\n21st century. Relative sea level rise is very likely to continue \r\naround Asia, contributing to increased coastal flooding in low\u0002lying areas (high confidence) and shoreline retreat along most \r\nsandy coasts (high confidence). Marine heatwaves are also \r\nexpected to increase around the region over the 21st century \r\n(high confidence)."


id: 632182659bdd1b490af306c53cd59523
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 14735
content:
"(Vousdoukas et al., 2018; Kirezci et al., 2020). Furthermore, the present\u0002day 1-in-100-year ETWL is projected to have median return periods \r\nof around 1-in-50-years by 2050 and 1-in-10-years by 2100 under \r\nRCP4.5 in most of Asia, except SEA and ARP, in which the present-day \r\n1-in-100-year ETWL is projected occur once per year or more, both by \r\n2050 and 2100 (Vousdoukas et al., 2018). The present-day 1-in-50-year \r\nETWL is projected to occur around three times a year by 2100 with \r\na SLR of 1 m across Asia (Vitousek et al., 2017). Compound impacts \r\nof precipitation change, land subsidence, sea level rise, upstream \r\nhydropower development, and local water infrastructure development \r\nmay lead to larger flood extent and prolonged inundation in the \r\nVietnamese Mekong Delta (Triet et al., 2020)."


id: 584ca04d5e7b99d61d78690565e44748
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 12792
content:
"The assessed direction of change in climatic impact-drivers for Asia \r\nand associated confidence levels are illustrated in Table 12.4."


id: cf60df6f4fed334016eaeede685c063b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 33836
content:
"Coastal erosion: Over the past 30 years, South, South East and East \r\nAsia exhibit the most pronounced delta changes globally due to strong \r\nhuman-induced changes to the fluvial sediment flux (Nienhuis et al., \r\n2020). Satellite derived shoreline change estimates over 1984-2015 \r\nindicate shoreline retreat rates between 0.5  m  yr -1 and 1  m yr -1\r\nalong the coasts of WCA and ARP, increasing to 3 m yr-1 in SAS. Over \r\nthe same period, shoreline progradation has been observed along \r\nthe coasts of RFE (0.2 m yr-1), SEA (0.1 m yr-1) and EAS (0.5 m yr-1) \r\n(Luijendijk et  al., 2018; Mentaschi et  al., 2018). Meanwhile, there \r\nhas been a gross coastal area loss of 3,590 km2 in South Asia, and \r\na loss of 2,350 km2 in Pacific Asia, over a 30-year period (1984-2015) \r\n(Mentaschi et al., 2018)."


id: a18c664923ff93558da9b06f51105ce2
created_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 25635
content:
"For the purpose of this assessment, Australasia is divided into five \r\nsub-regions as defined in Section  1.4.5: Northern Australia (NAU), \r\nCentral Australia (CAU), Eastern Australia (EAU), Southern Australia \r\n(SAU) and New Zealand (NZ)."


id: d8e2852882b7a5141813024121a15e43
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 35449
content:
"A detailed national scale climate change assessment of observed \r\nand projected climate change, based on over 40 CMIP5 models and \r\nhigh resolution downscaling (CSIRO and BOM, 2015), and biannual \r\nshort updates thereafter are available for Australia (CSIRO and BOM, \r\n2016, 2018, 2020). Similar national assessments for New Zealand are \r\nalso available (MfE and Stats NZ, 2017, 2020; MfE, 2018). The severe \r\nextreme events such as heatwaves and river floods that have occurred \r\nin Australasia, especially over the last decade, have enabled a number \r\nof attribution studies, improving the understanding of regional climate \r\nchange mechanisms that drive such extreme events (Chapter 11)."


id: e016a2845ae84dbc6cb76d576c7a7d3
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 36671
content:
"Marine heatwave: There have been frequent marine heatwaves \r\n(MHW) in the coastal oceans of Asia, connected to the increase \r\nbetween 0.25degC and 1degC in mean SST of the coastal oceans since \r\n1982-1998 (Oliver et al., 2018). There is high confidence that MHWs \r\nwill increase around most of Asia. Mean SST is projected to increase \r\nby 1degC (2degC) around Asia by 2100, with a  hotspot of around 2degC \r\n(5degC) along the coastlines of the Sea of Japan and the RFE under \r\nRCP4.5 (RCP8.5; Interactive Atlas). Under global warming conditions, \r\nMHW intensity and duration are projected to increase in the coastal \r\nzones of all sub-regions of Asia, but most notably in SEA and SAS \r\n(Frolicher et al., 2018). Projections for SSP1-2.6 and SSP5-8.5 both \r\nshow an increase in MHWs around Asia by 2081-2100, relative to \r\n1985-2014 (Box 9.2, Figure 1)."


id: f74d347b2550de6bb3fc378411b6bb0b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 40886
content:
"Figure  12.7 illustrates projected changes in two selected climatic \r\nimpact-driver indices for Australasia."


id: bbafb7086687fcf62d1c36c50b4dada7
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 30248
content:
"Mean air temperature: Across Australia mean temperatures have \r\nincreased by 1.44degC +- 0.24degC during the period 1910-2019, with \r\nmost of the warming occurring since 1950 (Atlas.6.2; CSIRO and \r\nBOM, 2020; Trewin et al., 2020). In New Zealand, an increase of 1.1degC \r\nhas been measured from 1909-2016 (Atlas.6.2; MfE and Stats NZ, "


id: b813d4cb75d0330f6da3191dda37a60e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 29604
content:
"35degC under SSP5-8.5, which are consistent with the above assessed \r\nliterature and across the two CMIP generations, and indicate a strong \r\ndifference depending on the mitigation scenario (e.g., over 100 days \r\nmore per  year under  SSP5-8.5 in NAU, but, in general, less than \r\n60 days more per year under SSP1-2.6 in NAU; Figure 12.SM.1)."


id: 613fa1249ef6794627bf8a9f62aab13b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 14408
content:
"2020). In the period 1980-2014 a rate of increase of 0.1degC-0.3degC per \r\ndecade has been observed (Atlas.11 and Atlas.20)."


id: 300f489439b3b663a1758c3f0230d3e1
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 5719
content:
"The projected frequency of exceeding dangerous humid heat \r\nthresholds is increasing in Australia, with a  strong increase in \r\nNorthern Australia for RCP8.5 (high confidence) (Zhao et al., 2015; \r\nMora et  al., 2017; Brouillet and Joussaume, 2019), consistently \r\nacross CMIP5, CMIP6 and CORDEX simulations (Figure 12.4d-f and \r\nFigure  12.SM.2). Using the HI index, by end-century, the average \r\nnumber of days exceeding 41degC is projected to increase in NAU by \r\nabout 100 days and by about 25 days under SSP5-8.5 and SSP1-2.6, \r\nrespectively. The projections for New Zealand indicate no appreciable \r\nincrease in the number of days with HI > 41degC across SSPs, time \r\nperiods and CMIP generations (Figure 12.4d-f and Figure 12.SM.2)."


id: a9aeea2bb9612cd8bd56cb10f570259e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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content:
"Cold spell and frost: Excepting parts of Southern Australia, the \r\nAustralasian region has a significant trend of decreasing frequency \r\nin cold extremes since the 1950s (high confidence) (Table  11.10) \r\nand there is high confidence that such trends are attributable \r\nto anthropogenic influence (Table  11.10). The number of frost \r\ndays per  year in Australia has on average declined at a  rate of \r\n0.15 days/decade in the past century (Alexander and Arblaster, 2017), \r\nexcept in some regions of Southern Australia, where an increase in \r\nboth number and season length has been reported (Dittus et  al., \r\n2014; Crimp et al., 2016b). The number of frost days has decreased \r\nat 12 of 30 monitoring sites around New Zealand over the period \r\n1972-2019 (MfE and Stats NZ, 2020)."


id: 9b1bc0d1c23eb9f3ddb592f7a78248ca
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 24540
content:
"Less frequent cold extremes are virtually certain in Australasia \r\n(Table 11.10) while a decrease of frost days is projected with high \r\nconfidence for the region. Projections, relative to 1986-2005, for \r\nthe number of frost days per year in Australia indicate declines of \r\n0.9 days by mid-century and 1.1 days by end-century for RCP4.5, \r\nwhile for RCP8.5, the projected declines are 1.0 days and 1.3 days \r\nby mid- and end-century respectively (Alexander and Arblaster, 2017; \r\nHerold et al., 2018). Projections for New Zealand indicate that the \r\nnumber of frost days will decrease by 30% (RCP2.6) to 50% (RCP8.5) \r\nby 2040, relative to 1986-2005. By 2090, the decrease ranges from \r\n30% (RCP2.6) to 90% (RCP8.5) (MfE and Stats NZ, 2017)."


id: cad9f070ab79cbd50f3b12abd9e66913
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 33030
content:
"In general, there is high confidence that most heat hazards in \r\nAustralasia will increase and that cold hazards will decrease \r\nover the 21st century. The mean temperature in Australasia is \r\nvirtually certain to continue to rise through the 21st century, \r\naccompanied by less frequent cold extremes (virtually \r\ncertain) and frost days (high confidence), and more frequent \r\nhot extremes (virtually certain). Heat stress is projected to \r\nincrease in Australia (high confidence)."


id: 713c14048050e2342e1241bcf33cc02e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 17179
content:
"Mean precipitation: Here, only increases in precipitation (under \r\n'Wet') are addressed, with decreases (under 'Dry') addressed in \r\n'Aridity' below."


id: ae7316c0e7e8d8334f7eb67378eda79f
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 27924
content:
"In terms of wet climatic impact-drivers, detectable anthropogenic \r\nincreases in precipitation in Australia have been reported particularly \r\nfor north-central Australia for the period 1901-2010 (Knutson \r\nand Zeng, 2018). Figure Atlas.11 indicates no significant trend in \r\nprecipitation over the region during the baseline period 1960-2015, \r\nexcept for the Global Precipitation Climatology Project (GPCP) \r\ndataset, which shows an increasing trend in north-central Australia. \r\nIn New Zealand, increases in annual rainfall have been observed \r\nbetween 1960-2019 in the south and west of the South Island and \r\neast of the North Island. Note however, for the most part, the above \r\nreported trends in New Zealand have been classified as statistically \r\nnot significant (Figure Atlas.20)."


id: ac7adae4073d75d78099bb32fcbd1e7a
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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content:
"and 1-in-100-year flood peaks for rivers in many parts of the \r\ncountry may increase by 5 to 10% by 2050 and more by 2100 \r\n(with large variation between models and emissions scenarios), with \r\na  corresponding decrease in return periods for specific flood levels \r\n(Gray et al., 2005; Carey-Smith et al., 2010; McMillan et al., 2010, 2012; \r\nBallinger et al., 2011)."


id: f75765bdebd47ad3a19fc810a69d9e2f
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 40895
content:
"Heavy precipitation and pluvial flood: Rainfall extremes have \r\nbeen detected to increase in Australasia, with low confidence\r\n(Table 11.10). There is high confidence that R x 1 day and R x 5 day \r\nprecipitation extremes will increase for 2degC or lower warming for the \r\nregion as a whole, but on a sub-regional basis there is only medium \r\nconfidence of increases in NAU and CAU and low confidence of \r\nincreases on EAU, SAU and NZ. For warming levels exceeding 2degC, \r\nthese extremes are very likely to increase in NAU and CAU and they \r\nare likely to increase elsewhere in the region (Section 11.9)."


id: 744a8859e1af66ea7f1cc78b1b7ee1ea
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 17694
content:
"Annual mean precipitation is projected to increase in Central and \r\nnorth-east Australia (low confidence) and in the south and west \r\nof New Zealand (medium confidence) (Atlas.6.4). Liu et al. (2018a) \r\nshow that under 1.5degC warming, Central and north-east Australia \r\nwill become wetter. Projected patterns in annual precipitation exhibit \r\nincreases in the west and south of New Zealand (Atlas.6.4; Liu et al., \r\n2018a) and project that the South Island will be wetter under both \r\n1.5degC and 2degC warming. However, there is limited model agreement \r\nfor projected rainfall changes in Australasia as shown in the Atlas."


id: 41ffede81e5d4658d1c069a0f0400a78
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 8808
content:
"Landslide: Based on local slope characteristics, lithology and seismic \r\nactivity, the South Island and the eastern half of the North Island of \r\nNew Zealand are vulnerable to landslide occurrence (Broeckx et al., \r\n2020). The potential for land and rockslides increases with, amongst \r\nother factors, total precipitation rates, precipitation intensity, \r\nmountain permafrost thaw rates, glacier retreat and air temperature \r\n(Crozier, 2010; Allen and Huggel, 2013; Gariano and Guzzetti, 2016; \r\nIPCC, 2019a). Given the increase of the magnitude of these physical \r\nvariables in areas that are already highly susceptible to mass \r\nmovements (MfE, 2018), there is low confidence that the occurrence \r\nof landslides will increase under future climate conditions."


id: 3e75b28db44b33a24ea3e144f70a846f
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 8171
content:
"River flood: Streamflow observations in Australia have shown that \r\nnegative trends dominate in annual maximum flow and that stations \r\nwith significant negative trends were mostly located in the south-east \r\nand south-west (Gu et  al., 2020). The observed peak flow trend in \r\nSouthern Australia is attributed to the decrease of soil moisture, \r\nalthough an increase of flood magnitude is possible for very rare \r\nevents. For the more frequent flood events, the increase of extreme \r\nprecipitation is balanced by the decrease of soil moisture. (Wasko and \r\nNathan, 2019)."


id: a695bc4dc1abdc9e45761206a8bf62f7
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 26522
content:
"Aridity: In terms of dry climatic impact-drivers, a substantial decrease \r\nin precipitation has been observed across Southern Australia during \r\nthe cool season (April-October) (medium confidence). The drying \r\ntrend has been particularly strong over south-west Western Australia \r\nbetween May and July, with rainfall since 1970 being around \r\n20% less than the 1900-1969 average (CSIRO and BOM, 2020). \r\nDetectable decreases in mean precipitation, attributable at least \r\nin part to anthropogenic forcing, have been reported for parts of \r\nsouth-west Australia (Delworth and Zeng, 2014; Knutson and Zeng, \r\n2018), south-east Australia, and Tasmania (Knutson and Zeng, 2018). \r\nIn New Zealand, the north-east of the South Island and western and \r\nthe northern parts of the North Island show decreasing precipitation \r\ntrends during 1960-2019 (MfE and Stats NZ, 2020)."


id: cc705fcb3ddcf76f582ece8c523daf40
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 33286
content:
"There is medium confidence that river flooding will increase in New \r\nZealand. Projections for New Zealand indicate that the 1-in-50-year "


id: fba9a8df5c95d3961b82e13631e4516f
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 41645
content:
"become drier (mainly in Southern Australia) under RCP8.5. Liu et al. \r\n(2018b) project that the North Island of New Zealand will be drier \r\nunder both 1.5degC and 2degC warming."


id: 7cc583a1042787c0748ab172859613f6
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 19150
content:
"increased at two monitored sites (MfE and Stats NZ, 2020). Due to \r\nthe intensification and the shift of the austral storm track by the \r\nend of the century (Yin, 2005), increases in extreme wind speed in \r\nNew Zealand are projected over the South Island and the southern \r\npart of the North Island by mid- and end-century for all RCPs (low \r\nconfidence) (MfE, 2018)."


id: 5d5d5d323fc786ab6c4bb16a5f8d7034
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 13713
content:
"Tropical cyclone: In Australia, the number of TCs has generally \r\ndeclined since 1982, and the frequency of intense TCs that make \r\nlandfall in north-eastern Australia has declined significantly since the \r\n19th century (medium confidence) (Kuleshov et al., 2010; Callaghan \r\nand Power, 2011; Holland and Bruyere, 2014; Knutson et al., 2019; \r\nCSIRO and BOM, 2020). There is high confidence that cyclones making \r\nlandfall along north-eastern and northern Australian coastlines will \r\ndecrease in number and low confidence of an increase in their \r\nintensities for 2degC of global warming as well as for the mid-century \r\nperiod with scenarios RCP4.5 and above (Roberts et al., 2015, 2020; \r\nBacmeister et al., 2018; Knutson et al., 2020), with the amplitude of \r\nchanges increasing from RCP4.5 to RCP8.5 (Bacmeister et al., 2018). \r\nDecreases in frequency are projected for 'east coast lows' (Walsh \r\net al., 2016b; Dowdy et al., 2019a)."


id: 249b34d9552f5a0a5a945df998beb239
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 3631
content:
"Sand and dust storm: Australia is recognized to be the largest dust \r\nsource in the Southern Hemisphere (Zheng et  al., 2016). Land-use \r\nand land-cover change have increased dust emissions in Australia \r\nin the past 200 years (Marx et al., 2014). While projections suggest \r\na decrease in severe winds in Central and Southern Australia, changes \r\nin vegetation due to increased aridity and hydrological drought could \r\nbe expected to result in increased wind erosion and dust emission \r\nacross the country (medium confidence) (Webb et al., 2020)."


id: 3669dbba9a05c52193c1716f559a54b9
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 6811
content:
"Mean wind speed: There is low confidence of a mean wind speed \r\ntrend in the last decades (low agreement) (McVicar et  al., 2012; \r\nTroccoli et al., 2012; Azorin-Molina et al., 2018; J. Wu et al., 2018), as \r\nlong-term measurements are not homogeneous."


id: a5a1c52706bbe2f02ef4bcaa73c1d34b
created_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 26373
content:
"In future climate scenarios wind speed trends in Australia exhibit \r\ngenerally weak amplitudes with low agreement among models \r\n(Figure 12.4m-o and Figure 12.SM.5) with uncertain consequences \r\non wind power potential (CSIRO and BOM, 2015; Karnauskas \r\net al., 2018a; Jung and Schindler, 2019). However, there is medium \r\nconfidence that, by the end of the century, annual mean wind power \r\nwill significantly increase in north-eastern Australia under RCP8.5, but \r\nthere is low confidence of an increase by end-century under RCP4.5, \r\nand for any scenario by mid-century (Karnauskas et al., 2018a). In \r\nNew Zealand, mean wind patterns are projected to become more \r\nnorth-easterly in summer, and westerlies to become more intense in \r\nwinter (low confidence), in agreement with the strengthening of the \r\nSouthern Hemisphere storm tracks (Section 4.5.1)."


id: 360fa4b11bcd9a7b0d362c98fc7346b8
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 6762
content:
"In Australasia, there is low confidence in projected mean wind \r\nspeeds and wind power potential, with a medium confidence\r\nincrease projected only in north-eastern Australia under high \r\nemissions scenarios and by the end of the 21st century. Tropical \r\ncyclones in north-eastern and North Australia are projected to \r\ndecrease in number (high confidence) while their intensity is \r\nprojected to increase (low confidence)."


id: 4c0fa130e9ecd8a87db8e48cb6f6b95e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 10642
content:
"Snow: The snow season length in Australia has decreased by 5% \r\nduring 2000-2013 relative to 1954-1999, especially in spring \r\n(Pepler et al., 2015). A shift in the date of peak snowfall has also \r\nbeen observed with an 11-day advance over the same period (Pepler \r\net al., 2015). A decreasing trend in maximum snow depth has been \r\nobserved for Australian alpine regions since the late 1950s, with \r\nthe largest declines during spring and at lower altitudes. Maximum \r\nsnow depth is highly variable and is strongly influenced by rare heavy \r\nsnowfall days, which have no observed trends in frequency (CSIRO \r\nand BOM, 2020). "


id: 20518f280c3051931f15dbf2dc877d5
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 2904
content:
"Severe wind storm: There is generally low confidence in observed \r\nchanges in extreme winds and extratropical storms in Australasia \r\n(Section 11.7.2). CMIP5 projections of severe winds indicate a general \r\nincrease in north-eastern Australia, and decreases in some parts \r\nin Southern and Central Australia (medium confidence) by the end \r\nof the century under RCP8.5 (CSIRO and BOM, 2015; Kumar et al., \r\n2015; Jung and Schindler, 2019). Elsewhere trends are diverse and \r\nvary across simulations with low agreement. Projections of changes \r\nin the 1-in-25-year return period winds (based on annual maxima) \r\nfor 2074-2100 relative to 1979-2005 for RCP8.5 show an increase in \r\ntropical areas of Northern Australia (Kumar et al., 2015)."


id: baae1f51b877a2f33dbb3ac20e673450
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 30061
content:
"Projections for Southern Australia and New Zealand show a continuing \r\nreduction in snowfall during the 21st  century (high confidence). \r\nThe magnitude of decrease varies with the altitude of the region and \r\nthe emissions scenario. At elevations lower than 1500 m, years without \r\nsnowfall are projected from 2030 in some models. By 2090, and under "


id: 850a6792e544aae2b48069636e8d39e1
created_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 20549
content:
"under RCP4.5 and RCP8.5 respectively (Figure  12.4q). By 2100 \r\n(Figure 12.4p,r), this range is projected to be 25-80 cm and 50-190 cm \r\nunder RCP4.5 and RCP8.5 respectively (Vousdoukas et  al., 2018; \r\nKirezci et al., 2020). Furthermore, the present-day 1-in-100-year ETWL \r\nis projected to have median return periods of around 1-in-20-years by \r\n2050 and 1-in-1-year by 2100 in SAU and NZ and return periods of \r\naround 1-in-50-years by 2050 and 1-in-20-years by 2100 in NAU under \r\nRCP4.5 (Vousdoukas et al., 2018), while the present-day 1-in-50-year \r\nETWL is projected to occur around three times a year by 2100 with \r\na SLR of 1 m around Australasia (Vitousek et al., 2017)."


id: 705135b261d3016a9c607b96a8d48ed3
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index: climate_gpt_v2
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content:
"RCP8.5, such years are projected to become common (CSIRO and BOM, \r\n2015). The number of annual snow days in New Zealand is projected \r\nto decrease under all RCPs, by up to 30 days or more by 2090 under \r\nRCP8.5, relative to 1986-2005 (MfE, 2018)."


id: 70b61395c7fea0a978278087dcbb075e
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updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 17088
content:
"Glacier: Glacier mass and areal extent in New Zealand is projected \r\nto continue to decease over the 21st  century (high confidence) \r\n(Section 9.5.1.3). Glacier ice volume from 1977-2018 in New Zealand \r\nhas decreased from 26.6 to 17.9 km3 (a loss of 33%; Salinger et al., \r\n2019). Relative to 2015, glaciers in New Zealand are projected to \r\nlose 36+-44%, 53+-33% and 77+-27% of their mass by the end of \r\nthe century under RCP2.6, RCP4.5 and RCP8.5 respectively, with the \r\nloss rates decreasing over time under RCP2.6 and increasing under \r\nRCP8.5 (Marzeion et al., 2020)."


id: efb2d59d72b2601f49499c5638f65ee4
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 39550
content:
"Coastal erosion: Satellite derived shoreline retreat rates for \r\nthe period between 1984-2015 show retreat rates between \r\n0.5 and 1 m yr-1 around the region, except in SAU where a shoreline \r\nprogradation rate of 0.1 m yr-1 has been observed (Luijendijk et al., \r\n2018; Mentaschi et al., 2018). Mentaschi et al. (2018) report a coastal \r\narea loss of 350 km2 over the same period in Western Australia from \r\nsatellite observations."


id: 1a42f51915dcfed79d8b506edf03e621
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 1816
content:
"In summary, snowfall is expected to decrease throughout the \r\nregion at high altitudes in both Australia (high confidence) \r\nand New Zealand (medium confidence). In New Zealand, \r\nglacier ice mass and extent are expected to decrease over the \r\n21st century for all scenarios (high confidence)."


id: 9cfcddf7436d7926d312b8638f25f84b
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vector_id: 24858
content:
"Relative sea level: Around Australasia, from 1900-2018, a  new \r\ntide gauge-based reconstruction finds a regional mean RSL change \r\nof 1.33 [0.80 to 1.86]  mm yr -1 in the Indian Ocean-South Pacific \r\nregion (Frederikse et  al., 2020), compared to a  GMSL change of \r\naround 1.7 mm yr-1 (Section 2.3.3.3 and Table 9.5). For the period \r\n1993-2018, the RSLR rates, based on satellite altimetry, increased \r\nto 3.65 [3.23 to 4.08] mm yr -1 (Frederikse et al., 2020), compared to \r\na GMSL change of 3.25 mm yr-1 (Section 2.3.3.3 and Table 9.5)."


id: 3281b3f62f8f8907beaf789d142538e5
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 6141
content:
"Relative sea level is virtually certain to increase throughout the region \r\nover the 21st century (Section 9.6.3, Figure 9.28). Regional mean RSLR \r\nprojections for the oceans around Australasia range from 0.4-0.5 m \r\nunder SSP1-2.6 to 0.7-0.9 m under SSP5-8.5 for 2081-2100 relative to \r\n1995-2014 (median values), which means local RSL change falls within \r\nthe range of mean projected GMSL change (Section 9.6.3.1). However \r\nthese RSLR projections may be underestimated due to potential partial \r\nrepresentation of land subsidence (Section 9.6.3.2)."


id: fc69b6fada356b1287ff32a246d5a110
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 41776
content:
"Distinct from long-term coastline recession, storms and storm surges \r\nalso result in episodic coastal erosion. In general, the historically \r\nmeasured maximum episodic coastal erosion (either eroded volume \r\nor coastline retreat distance) or that due to a 1-in-100-year return \r\nperiod storm wave height is used as a design criterion for coastal \r\nzone management and planning in Australia (Wainwright et  al., \r\n2014; Mortlock et al., 2017)."


id: f2598c869d3a8006b0c471a9dd66d012
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 40033
content:
"Coastal flood: The most commonly used index for episodic coastal \r\ninundation in Australia is the summation of a  high end SLR and \r\nthe 1-in-100-year storm tide level (the combined sea level due to \r\nstorm surge and tide) (CSIRO and BOM, 2016; McInnes et al., 2016). \r\nHowever, episodic coastal flooding is caused by extreme total water \r\nlevels (ETWL), which is the combination of SLR, tides, surge and \r\nwave setup (Section 12.3.5.2). The present-day 1-in-100-year ETWL \r\nis between 0.5-2.5 m around most of Australia, except the north\u0002western coast where 1-in-100-year ETWL can be as large as 6-7 m \r\n(Vousdoukas et al., 2018; O'Grady et al., 2019; Kirezci et al., 2020)."


id: 64919f6111f099bd9ccf4afcd6876535
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 14967
content:
"While there is wide recognition in Australia that the combined \r\neffect of SLR, changing storm surge and wave climates will directly \r\naffect  future episodic coastal erosion (McInnes et  al., 2016; \r\nRanasinghe, 2016; Harley et al., 2017) only a few projections of how \r\nthis hazard may evolve are available for Australia. In one such study, \r\nJongejan et al. (2016) provide projections of how the full exceedance \r\nprobability curve of the maximum erosion per year may evolve over \r\nthe 21st century (due to the combined action of SLR, storm surge \r\nand storm waves). Their results show that, for example, the 0.01 \r\nexceedance probability maximum coastline retreat in 2025 will have \r\nan exceedance probability of 0.015 by 2050 and 0.07 by 2100."


id: edc1c04c336e36ff5dc096cbc9b6357a
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 39185
content:
"Extreme total water level magnitude and occurrence frequency \r\nare expected to increase throughout the region (high confidence) \r\n(Figure 12.4p-r and Figure 12.SM.6). Across the region, the 5-95th \r\npercentile range of the 1-in-100-year ETWL is projected increase \r\n(relative to 1980-2014) by 5-35 cm and by 10-40 cm by 2050 "


id: 5d40b0ac75b75b2fb682ac449ce698a3
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 13681
content:
"Central America (SCA), North-Western South America (NWS), Northern \r\nSouth America (NSA), South American Monsoon (SAM), North-Eastern \r\nSouth America (NES), South-Western South America (SWS), South\u0002Eastern South America (SES) and Southern South America (SSA). \r\nThe Caribbean is placed under the Small Islands section (12.4.7) of \r\nthis chapter."


id: 365cc0db7e578e90d6c2a4d935d91ca1
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 6797
content:
"New literature is now available for the regional climate as a result \r\nof observational research and coordinated modelling outputs of \r\nCORDEX South America (Solman, 2013; Sanchez et  al., 2015) and \r\nCORDEX-CORE (Giorgi et al., 2018; Coppola et al., 2021b; Teichmann \r\net al., 2021). Of particular interest are the new projections of both \r\nmean climate and extremes. This new regional climate information is \r\nkey to main sectors sensitive to climate change in Central and South \r\nAmerica such as water resources, infrastructure, agriculture, livestock, \r\nforestry, silviculture and fisheries (Magrin, 2015; Lopez Feldman \r\nand Hernandez Cortes, 2016), human health (changes in morbidity \r\nand mortality, and emergence of diseases in previously non-endemic \r\nareas; Nunez et  al., 2016) and biodiversity (Uribe Botero, 2015), \r\nurban planning, navigation and tourism."


id: 14810285255f77246aaafbbbaca4719b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 834
content:
"In general, there is high confidence that most coastal/ocean\u0002related hazards in Australasia will increase over the 21st century. \r\nRelative sea level rise is virtually certain to continue in the \r\noceans around Australasia, contributing to increased coastal \r\nflooding in low-lying areas (high confidence) and shoreline \r\nretreat along most sandy coasts (high confidence). Marine \r\nheatwaves are also expected to increase around the region \r\nover the 21st century (high confidence)."


id: 3ded9e0c42a4a41f17f9f1a11e5febfd
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 8066
content:
"The assessed direction of change in climatic impact-drivers for \r\nAustralasia and associated confidence levels are illustrated in \r\nTable 12.5, together with emergence time information (Section 12.5.2). \r\nNo assessable literature could be found for hail and snow avalanches, \r\nalthough these phenomena may be relevant in parts of the region."


id: f987b9910462350d2843ad263e3f65a5
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 41271
content:
"(high confidence) (Atlas.7.2.5) and the well-known dipole for \r\nSouth America, meaning increasing precipitation over subtropical \r\nregions like the Rio de La  Plata basin (SES) (high confidence) and \r\ndecreasing precipitation in the Amazon (NSA) (medium confidence) \r\n(Chou et al., 2014; Llopart et al., 2014; Reboita et al., 2014; Sanchez \r\net al., 2015; Teichmann et al., 2021). These features are consistent \r\nwith observations (Sena et al., 2018) and are evident in regional and \r\nglobal model projections by mid- and end-of-century for both RCP4.5 \r\nand RCP8.5 (Jones and Carvalho, 2013)."


id: 4a974527d85b80fb657dd492bb56b108
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 10362
content:
"Cold spell and frost: A decreasing frequency of cold days and nights \r\nhas been observed in many sub-regions (Table 11.13). There is medium \r\nconfidence (limited agreement) of a decrease in frost days in SWS, SES \r\nand SSA. Projections consistently suggest a  general decrease in the \r\nfrequency of cold spells and frost days in the region as indicated by \r\nseveral indices based on minimum temperature (Chou et  al., 2014; \r\nLopez-Franca et al., 2016; C. Li et al., 2021). Heating degree days are \r\nconsistently projected to decrease by 5 degree days per year in the \r\nAmazon region, and up to 20-30 degree days per year in NWS, SWS \r\nand SES, under RCP8.5/SSP5-8.5 by mid century (Coppola et al., 2021b)."


id: acf7d787d7e1487db886eb3b2021c16e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 27669
content:
"In conclusion, it is virtually certain that warming will continue \r\neverywhere in Central and South America and there is high \r\nconfidence that by the end of the century most regions will \r\nundergo extreme heat stress conditions much more often than \r\nin recent past (e.g., increase of dangerous heat with HI > 41degC, \r\nor Tx > 35degC) with more than 200 additional days per year \r\nunder SSP5-8.5, while such conditions will be met typically \r\n50-100 more days per year under SSP1-2.6 over the same \r\nregions. Cold spells and frost days will have a decreasing trend \r\n(high confidence)."


id: 50614e9945e1400c3c66a6b3f86beae2
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 11422
content:
"Available projections for the region show increases in river floods in \r\nSES and SAM (medium confidence). Projections indicate that SES and \r\nthe coasts of Ecuador and Peru will experience a tendency towards \r\nwetter conditions that can be a proxy for longer periods of flooding \r\nand enhanced river discharges (Zaninelli et al., 2019). CORDEX models \r\nproject the strongest changes for the peak flow with a return period \r\nof 100 years in SES by mid-century and under RCP8.5 (Figure 12.8). At \r\nthe continental scale, on the contrary, Alfieri et al. (2017) suggest that \r\n100-year river floods will decrease under RCP8.5. Regional projections \r\nof river floods have high uncertainty, however, owing to differences in "


id: dd5166715c0098f55f96c7dc1c2fd2b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 36200
content:
"Mean precipitation: The Atlas documents diverse historical \r\nprecipitation trends in the region, including a  small but not \r\nsignificant increasing trend in SCA, a  decreasing trend in south\u0002eastern and north-eastern Brazil, and an increasing trend in SSA. \r\nProjections indicate a  drying signal for SCA (medium confidence) \r\n(Coppola et  al., 2014a; Nakaegawa et  al., 2014), NES and SWS "


id: 358f92a1c109ec0b4e3b80017cd69820
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 6678
content:
"hydrological models (low confidence) (Reyer et al., 2017a). Fabrega \r\net al. (2013) projected increases in surface runoff for Panama, while \r\nZulkafli et al. (2016) identified increases in 100-year floods of 7.5 and \r\n12.0% in projections for the Peruvian Amazon wet season under RCPs \r\n4.5 and 8.5 respectively. Wetter conditions and +-20% variations in \r\nannual mean streamflow are also projected for the Rio de La Plata \r\nunder the warming levels of 1.5degC, 2degC and 3degC above pre-industrial \r\nconditions (Montroull et al., 2018). In central Chile, 50-year peak flows \r\nare expected to be greater by mid-century than 100-year peak flows \r\nobserved over the reference period (Bozkurt et al., 2018)."


id: 31c6c7e7670c968e91988a2af12f0d9a
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 6002
content:
"Llopart et  al., 2014; Atlas.7). Seasonal changes are also projected \r\nby end century under RCP 8.5, with decreases in June-July-August \r\n(JJA) rainfall projected for NSA, the coastal region of SES, SAM and \r\nthe southern portion of SWS (Marengo et  al., 2016). Decreases in \r\nDecember -January-February (DJF) rainfall are projected for the \r\ncentral part of South America in the near term (Kitoh et al., 2011; \r\nChou et al., 2014; Cabre et al., 2016). Regional projections for Central \r\nand South America also indicate an increase in dryness in SCA and \r\nNES by mid- to end-century (medium confidence) (Chou et al., 2014; \r\nMarengo and Bernasconi, 2015)."


id: 4822be19846e54c88d621554dd595844
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 9908
content:
"Heavy precipitation and pluvial flood: Table  11.14 indicated \r\nthat there is low confidence due to limited evidence of extreme \r\nprecipitation trends in almost all Central and South America, except \r\nin SES where increases in the magnitude and frequency of heavy \r\nprecipitation have been observed (high confidence). In general, \r\ndata scarcity persists for a  representative continental assessment. \r\nChapter 11 projections indicate low confidence of increase, compared \r\nto the modern period, in the intensity and frequency of heavy \r\nprecipitation in SCA and SWS for all GWLs, and medium confidence\r\nof increase in NSA, NES, SSA, SAM and SES for GWL of 4degC. In NWS, \r\na wide range of changes is projected (low confidence)."


id: f9fbabb138bd2c44e37826046de42437
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 41345
content:
"Hydrological drought: Chapter 11 assessed mostly low confidence\r\nin observed changes in hydrological droughts given a lack of studies \r\nand clear evidence, with medium confidence only for a streamflow \r\ndecrease in sub-regions of SWS (Table 11.15). Some trends are \r\nbecoming more clear, such as the ones reported for Colombia (NWS) \r\nby Carmona and Poveda (2014), who indicated that 62% of the 25- \r\nto 50-year-long monthly average streamflow time series exhibited \r\nsignificant decreasing trends. However, studies of discharge changes \r\nindicate that uncertainty is still large, as argued by Pabon-Caicedo \r\net al. (2020) for the full extent of the Andes."


id: af8a638e4eb6f6292e7dd9c04af7fe91
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 28117
content:
"A number of studies project decreases in runoff and river discharge \r\nfor SCA, Colombia, Brazil and the southern part of South America \r\nby the end of this century (Nakaegawa and Vergara, 2010; Arnell \r\nand Gosling, 2013; van Vliet et al., 2013). Section 11.9 assessed high \r\nconfidence in projections of increases in hydrological droughts in \r\nNSA, SAM, SWS, and SSA under for 4degC GWL, medium confidence\r\nin SCA, and low confidence in the rest of the sub-regions given \r\ninsufficient evidence, lack of signal or mixed signals among the \r\navailable studies. Signals are much more uncertain for the middle of \r\nthe century (or for a 2degC GWL)."


id: 5ca05823d58d6450d05e4b0e550ee672
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 13556
content:
"Landslide: Several regions in Central America, as well as Colombia \r\nand south-eastern Brazil, are considered areas of high incidence of \r\nobserved fatal landslides. In these areas, El Nino-Southern Oscillation \r\n(ENSO)-driven fluctuations in rainfall amounts (Sepulveda and Petley, \r\n2015) and climate change (Nehren et  al., 2019) seem to be key \r\nfactors. Rockfalls, ice- and rock-ice avalanches, lahars and landslides \r\nhave been reported frequently in the southern, extratropical Andes \r\nin the last decades (Gariano and Guzzetti, 2016). A large number of \r\nice- and moraine-dammed lakes have consequently failed, causing \r\nfloods that rank amongst the largest events ever recorded (Iribarren \r\nAnacona et al., 2015). However, published literature is largely missing \r\nfor a reliable assessment of past and future trends of such hazards."


id: 1efb4500ecf60814c48f25d23f38eab0
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 2654
content:
"Agricultural and ecological drought: Section  11.9 assessed low \r\nconfidence in observed changes in agricultural and ecological drought \r\nacross Central and South America due to regional heterogeneity \r\nand differences depending on the drought metrics used, except \r\nin NES, which has seen a  dominant increase in drought severity \r\n(medium confidence)."


id: d2307827c85e0a24acd92f776ce3e83a
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 34334
content:
"Aridity: Several regional studies suggest increasing trends in the \r\nfrequency and length of droughts in the region, such as: over NWS \r\n(Dominguez-Castro et al., 2018), NSA (Marengo and Espinoza, 2016; \r\nCunha et al., 2019) and NES (Marengo and Bernasconi, 2015), over \r\nsouthern Amazonia (Fu et al., 2013; Boisier et al., 2015), in the Sao \r\nFrancisco River basin and the capital city Distrito Federal in Brazil \r\n(Borges et  al., 2018; Bezerra et  al., 2019), in the southern Andes \r\n(Vera and Diaz, 2015), in central southern Chile (Boisier et al., 2018), \r\nin SES (Rivera and Penalba, 2014) and, during recent years, in SSA \r\n(Rivera and Penalba, 2014). Chapter 8 indicated medium confidence\r\nof anthropogenic forcing on observed drying trends in central Chile. \r\nAdditional discussion on droughts and aridity trends in South America \r\nis presented in Sections 8.3.1.6, 8.4.1.6 and 8.6.2.1."


id: a837db7c1d4335d958242445d1d1d049
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 26811
content:
"Sections 8.3.2.4 and 8.4.1.6 point to two important drying hotspots in \r\nSouth America with long-term soil moisture decline and precipitation \r\ndeclines: the Amazon basin (SAM and NSA) and SWS (medium \r\nconfidence) (Figure  12.4). End-of-century RCP8.5 projections \r\nshow a  longer dry season in the central part of South America \r\nand decreased precipitation over the Amazon and central Brazil \r\n(Teichmann et al., 2013; Coppola et al., 2014a; Giorgi et al., 2014; "


id: a2ec09061c0b78407195a3021cef7f28
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 25880
content:
"Severe wind storm: Similar observational limitations inhibit an \r\nassessment of long-term extreme wind trends. However, Pes et  al. \r\n(2017) found extreme wind increases in most of Brazil over the past \r\ndecades. Future projections indicate a slight decrease in the number \r\nof extratropical cyclones in mid-latitudes (limited evidence, low \r\nconfidence) (Reboita et al., 2018), and an increase of extreme winds in \r\ntropical areas (limited evidence, low confidence) (Kumar et al., 2015). \r\nClimate models project a shift and an intensification of southern storm \r\ntracks, with most effects offshore over the Southern Ocean (Chapter 4), \r\nwith low confidence (low agreement) of significant extreme wind \r\nchanges over land and coastal areas across the 21st century (Chang, \r\n2017; Augusto Sanabria and Carril, 2018; Reboita et al., 2021)."


id: a4c87e05bccac5702059da1359baf251
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 26217
content:
"occurrence of extended droughts, such as the recently experienced \r\n2010-2015 megadrought (which is still driving impacts), is projected \r\nto increase from one to up to five events per 100 years under RCP8.5 \r\n(Bozkurt et al., 2018). Section 11.9 highlights change in confidence \r\nin increases in drought severity in SCA, NSA, NES, SAM, SWS, and \r\nSSA from low to high under the three GWLs of 1.5degC, 2degC and 4degC. \r\nNES and SES change from low confidence to medium confidence\r\nincreases in agricultural and ecological drought severity by 4degC GWL \r\nwith different metrics and high agreement between studies. Only \r\nSAM and SSA have projections of agricultural and ecological drought \r\nincreasing with high confidence for the middle of the century, or for \r\na 2degC GWL, and NSA, NES and SCA are projected to increase with \r\nmedium confidence."


id: 358d9eeeb3b96d2a9408fca3a41794f5
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 6675
content:
"Tropical cyclone: CMIP5 and CMIP6 simulations, including the \r\nnew High Resolution Model Intercomparison Project (HighResMIP), \r\nproject a decrease in the frequency of tropical cyclones in the Atlantic \r\nand Pacific coasts of Central America for the mid-century or under \r\na  2degC GWL, accompanied with an increased frequency of intense \r\ncyclones (medium confidence) (Section 11.7.1.5; Diro et  al., 2014; \r\nKnutson et al., 2020; Roberts et al., 2020)."


id: 9f9b85862dec0c4ab71bb7fa7b5c261f
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 25291
content:
"In summary, there is limited evidence of current trends in \r\nobserved wind speed and wind storms in Central and South \r\nAmerica. Climate projections indicate a decrease in frequency \r\nof tropical cyclones in Central America accompanied with an \r\nincreased frequency of intense cyclones, and an increase in \r\nmean wind speed and wind power potential in most parts of \r\nCentral and South America (medium confidence)."


id: a3fe79d92aea0ecf8ae74effd8f3dd7
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 26041
content:
"Mean precipitation is projected to change in a dipole pattern \r\nwith increases in NWS and SES and decreases in NES and \r\nSWS (high confidence) with further decreases in NSA \r\nand SCA (medium confidence). There is medium confidence\r\nof an increase in river floods in SAM and SES. There is high \r\nconfidence of an increase in drought duration in NES, an in \r\nthe number of dry days and drought frequency in NSA and \r\nSAM. Dry climatic impact-drivers are projected to increase \r\nat the regional level with higher global warming levels. \r\nThe strongest signal of future increase in agricultural and \r\necological drought, aridity and fire weather is over the \r\nAmazon region (high confidence). "


id: 354d7e1c3383948a71796335193531e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 6626
content:
"Mean wind speed: Due to the lack of long-term homogeneous \r\nrecords or limited observations in the region, past wind speed trends \r\nare difficult to establish. Global climate models project an increase \r\nin wind speeds, under all future scenarios, augmenting wind power \r\npotential in most parts of Central and South America, especially in \r\nNES, where changes lie in the range 0-20% by 2050 under RCP8.5 \r\nand 0-40% under RCP8.5 (medium confidence) (Karnauskas \r\net  al., 2018a; Reboita et  al., 2018; Jung and Schindler, 2019). In \r\nPatagonia, wind speeds are projected to decrease. For RCP4.5 \r\nchanges remain marginal and have low confidence (low agreement) \r\n(Figure 12.4m-o)."


id: 2fc11bfcf3813fd3cb1c7c13e8e5fa7a
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 5657
content:
"Glacier: Observation and future projection of Central and South \r\nAmerica glacier mass changes are assessed in Section 9.5.1, grouped \r\nin two main regions: Low Latitude region (98% of which is glaciers in \r\nthe Andes) and the Southern Andes region. An increase in the number \r\nand areal extent of glacial lakes in the Southern Andes was reported \r\nfor the period 1986-2016 (Wilson et al., 2018). Similar changes are \r\nbeing observed in the central Andes (Colonia et al., 2017). Since 1800 \r\nat least 15 ice-dammed lakes and 16 moraine-dammed lakes have \r\nfailed in the extratropical Andes, causing high-magnitude glacial lake "


id: 615242b1560d7b36e430ce7c94fe42d8
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 14424
content:
"outburst floods (Rojas et al., 2014; Cook et al., 2016; Wilson et al., \r\n2018; Drenkhan et al., 2019). Partially due to glacier shrinkage and \r\nlake growth, the frequency of outburst floods has increased in the \r\nlast 30-40 years (Carey et al., 2012; Iribarren Anacona et al., 2015)."


id: 35d481e0b9af2593c263a6aa465b0e99
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 6720
content:
"be underestimated due to potential partial representation of land \r\nsubsidence in their assessment (Section 9.6.3.2)."


id: f70d97bd6b2d3bdc98be1d0394719849
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 40837
content:
"Glaciers across South America are expected to continue to lose \r\nmass and glacier area in the coming century (high confidence) \r\n(Section  9.5). In terms of their mass, glaciers in the Low Latitude \r\nregion are projected by GlacierMIP to lose 67 +- 42%, 86 +- 24% and \r\n94 +- 13%, of their 2015 baseline mass by the end of the century \r\nunder RCP2.6, RCP4.5 and RCP8.5 respectively (Marzeion et  al., \r\n2020). Glaciers in the Southern Andes show decreasing mass loss \r\nrates for RCP2.6, and increasing rates for RCP8.5, which peak in the \r\nmid to late 21st century. Glaciers in the Southern Andes are projected \r\nto lose 26+-27%, 33+-26% and 47+-26% of their 2015 mass by the \r\nend of the century under RCP2.6, RCP4.5 and RCP8.5 respectively \r\n(Section 9.5.1.3)."


id: 91c36bea77bfed941e12aa398207174c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 22870
content:
"The central Andes will experience the highest disturbance to the thermal \r\nregime of the 21st  century. As a  consequence, in the Argentinean \r\nAndes up to 95% of rock glaciers in the southern desert Andes and \r\nin the central Andes will rest in areas above 0degC under the worst case \r\nscenario of warming (the freezing level might move up more than twice \r\nas much as during the entire Holocene; Drewes et al., 2018)"


id: 78eb3c61bc3eb097193ea1b776dedfbf
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 18464
content:
"Coastal erosion: According to satellite data, shoreline retreat rates \r\nof around 1 m yr-1 have been observed along the sandy coasts \r\nof SCA, SES and SSA over the period 1984-2015, while shoreline \r\nprogradation rates of around 0.25 m yr-1 has been observed in \r\nNWS and NSA. The sandy shorelines in NES and SWS have remained \r\nmore or less stable over the same period (Luijendijk et  al., 2018; \r\nMentaschi et  al., 2018). Using satellite observations, Mentaschi \r\net al. (2018) report a coastal area loss of 250 km2 over a 30-year \r\nperiod (1984-2015) along the Pacific coast of South America, and of \r\n780 km2 along the Atlantic coastlines."


id: 9712333fcab05e83a7f1571ae7c9299c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 23771
content:
"Permafrost: There is limited information on the ongoing changes \r\nand projections of permafrost conditions in the region. Based on \r\nmodel projections under the IPCC A1B scenario, permafrost areas in \r\nthe Bolivian Andes will eventually be lost, but this could take years \r\nto decades or longer depending on permafrost thickness (Rangecroft \r\net al., 2016). "


id: 113d7f63fbdbf86cd550f86bbf22772d
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 227
content:
"In conclusion, glacier volume loss and permafrost thawing will \r\ncontinue in the Andes Cordillera under all climate scenarios \r\n(high confidence), causing important reductions in river flow \r\nand potentially high-magnitude glacial lake outburst floods."


id: 622254b68fbccdba521a84753e8fe0c5
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 14539
content:
"Relative sea level: Around Central and South America, over \r\n1900-2018, a new tide gauge-based reconstruction finds a regional \r\nmean relative sea level (RSL) change of 2.07 [1.36 to 2.77] mm yr-1 in \r\nthe South Atlantic, 2.49 [1.89 to 3.06] mm yr-1 in the subtropical North \r\nAtlantic and 1.20 [0.76 to 1.62] mm yr-1 in the East Pacific (Frederikse \r\net al., 2020), compared to a global mean sea level (GMSL) change of \r\naround 1.7 mm yr-1 (Section 2.3.3.3 and Table 9.5). For the period \r\n1993-2018, these RSLR rates, based on satellite altimetry, increased \r\nto 3.45 [3.04 to 3.86)] mm yr-1, 4.04 [2.77 to 5.24] mm yr-1 and 2.35 \r\n[0.70 to 4.06] mm yr-1 respectively (Frederikse et al., 2020), compared \r\nto a GMSL change of 3.25 mm yr-1 (Section 2.3.3.3 and Table 9.5)."


id: 996978bfa9df00ac74229c30d1863e04
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 24213
content:
"Relative sea level rise is extremely likely to continue in the oceans \r\naround Central and South America. Regional mean RSLR projections \r\nfor the oceans around Central and South America range from 0.3-0.5 \r\nm under SSP1-2.6 to 0.5-0.9 m under SSP5-8.5 for 2081-2100 relative \r\nto 1995-2014 (median values), which is around the projected GMSL \r\nchange (Section  9.6.3.3). These RSLR projections may, however, "


id: 3aafcef738330b8f19628772ac3e4cfa
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 7529
content:
"Marine heatwave: The mean sea surface temperature (SST) of the \r\nAtlantic Ocean and the Caribbean around Central and South America \r\nincreased from 0.25degC to 1degC over the period 1982-1998 (Oliver \r\net al., 2018). This mean ocean surface warming is connected to longer "


id: 54ed9b6d678990a39be0fc2f418c37bf
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 12213
content:
"et al., 2018; Vautard et al., 2020; Coppola et al., 2021a) to assess \r\nsignals of climate change in Europe has emerged. These scenario\u0002based simulations have been the basis of a number of impact studies \r\n(e.g.,  Jacob et  al., 2014, 2018; Somot et  al., 2018; Faggian and \r\nDecimi, 2019) highlighting the use of the climatic impact-drivers. The \r\ndevelopment of the science of attribution of weather events (Stott \r\net al., 2016) has provided evidence of links between climate change \r\nand hazard changes such as the 2017 Mediterranean heatwave (Kew \r\net al., 2019) and many others (Chapter 11)."


id: cd952197a5957056ec2015d97ec6e42
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 33504
content:
"The ability of global and regional models to reproduce the observed \r\nchanges in mean and extreme temperature and precipitation \r\nin Europe is assessed in the literature (Atlas.8.3). In summary, \r\nboth GCMs and RCMs have their limitations but, in general, the \r\nincreased resolution of RCMs is shown to clearly add value in terms \r\nof resolving spatial patterns and seasonal cycles of precipitation \r\nand precipitation extremes in many European regions, especially in \r\nregions of complex topography such as the Alps and for quantities \r\nsuch as snowmelt-driven runoff, regional winds and Mediterranean \r\nhurricanes (Medicanes)."


id: 4c409c988fbe5157f04de5e5c07a29a3
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 10679
content:
"There is high confidence that MHWs will increase around Central \r\nand South America. Mean SST is projected to increase by 1degC (2degC) \r\nby 2100, with a  hotspot of about 2degC (4degC) along the coast of \r\nSouth-Eastern South America and North-Western South America \r\nunder RCP4.5 (RCP8.5; Interactive Atlas). More frequent MHWs \r\nare projected around the region for GWLs of 1.5degC, 2degC and 3.5degC \r\nrelative to the modelled reference value for 1861-1880 (Frolicher \r\net  al., 2018). Projections for SSP1-2.6 and SSP5-8.5 both show an \r\nincrease in MHWs around Central and South America by 2081-2100, \r\nrelative to 1985-2014 (Box 9.2, Figure 1)."


id: d051cd5a0b8ebf660705aecf4342fd69
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 34009
content:
"Examples of projected climatic impact-driver thresholds are illustrated \r\nin Figures 12.4 and 12.9 based on the most recently updated EURO\u0002CORDEX RCM projections, CMIP5 and CMIP6 GCMs for comparison. \r\nFor a more comprehensive representation of other climatic impact\u0002driver index trends assessed in this section the reader is referred to \r\nthe interactive Atlas."


id: bdaa520f83b6b1aecdb35b2704fa812b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 30630
content:
"Mean air temperature: Since AR5, studies have confirmed that the \r\nmean warming trend in Europe is increasing (Atlas.8.2). The observed \r\nwarming trend patterns are largely consistent with those simulated by \r\nglobal and regional climate models and it is very likely that such trends \r\nare, in large part, due to human influence on climate (Section 3.3.1)."


id: 8a3f883fd342c6d2c857c8a6b09810b6
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 21501
content:
"In summary, relative sea level rise is extremely likely to continue \r\nin the oceans around Central and South America, contributing to \r\nincreased coastal flooding in low-lying areas (high confidence) \r\nand shoreline retreat along most sandy coasts (high confidence). \r\nMarine heatwaves are also expected to increase around the \r\nregion over the 21st century (high confidence)."


id: ce1a3b056dd4bcdbd891f120e883ef66
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 33589
content:
"All temperature trends are very likely to continue for a  global \r\nwarming of 1.5degC or 2degC and 3degC (Atlas.8.4). Future warming leads \r\nto the exceedance of different temperature thresholds relevant for \r\nvector-borne diseases (medium confidence) (Caminade et al., 2012; \r\nMedlock et  al., 2013), invasive allergens (medium confidence) \r\n(Storkey et al., 2014; Hamaoui-Laguel et al., 2015), SST thresholds in \r\nthe Mediterranean (likely to exceed 20degC), or relevant for the Vibrio\r\nbacteria development (Vezzulli et al., 2015). Future warming is also \r\nprojected to lead to the exceedance of cooling degree day index \r\n(>22degC) thresholds, characterizing a  potential increase in energy \r\ndemand for cooling in southern Europe with increases likely exceeding \r\n40% in some areas (Spinoni et al., 2015) by 2050 under RCP8.5 (high \r\nconfidence) (Section 12.3 and Atlas.8; Coppola et al., 2021a)."


id: 9d5ca137f1960352336805512bf84aa7
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 24915
content:
"The assessed direction of change in climatic impact-drivers for Central \r\nand South America and associated confidence levels are illustrated in \r\nTable 12.6. No assessable literature could be found for sand and dust \r\nstorm, lake and sea ice, heavy snowfall and ice storms, hail and snow \r\navalanches, although these phenomena may be relevant in parts of \r\nthe region."


id: da9bcd9caf63f8ea101a122a62593728
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 35755
content:
"The regional European climate and main hazards have been previously \r\nassessed in SREX, AR5 WGII, SR1.5, SROCC and SRCCL and a summary \r\nof key findings can be found in the Europe section of Atlas.8.1. For the \r\npurpose of this assessment Europe is divided into four climatic regions: \r\nNorthern Europe (NEU), Western and Central Europe (WCE), Eastern \r\nEurope (EEU) and Mediterranean (MED) (Figure Atlas.24)."


id: 223787f0e026631a9a45aadd64a39c02
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 3239
content:
"Extreme heat: The frequency of heatwaves observed in Europe \r\nhas very likely increased in recent decades due to human-induced \r\nchange in atmospheric composition (Section 11.3) and a detectable \r\nanthropogenic increase in a  summer heat stress index over all \r\nregions of Europe has been identified based on WBGT index trends \r\nfor 1973-2012 (medium confidence, limited evidence) (Knutson and \r\nPloshay, 2016)."


id: c74bf3b0370fced5ec88cf6e26390351
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 32381
content:
"Since AR5 and SR1.5, a  large body of literature that uses the \r\nEURO-CORDEX and MED-CORDEX ensembles of high-resolution \r\nsimulations (Jacob et  al., 2014; Ruti et  al., 2016; Kjellstrom "


id: 823b36a7d5ece175d32e02b711047862
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 20042
content:
"It is very likely that the frequency of heatwaves will increase during \r\nthe 21st  century regardless of the emissions scenario in each \r\nEuropean region, and for 1.5degC and 2degC GWLs (Section  11.3.5). \r\nHeat stress due to both high temperature and humidity, affecting \r\nmorbidity, mortality and labour capacity (Section 12.3) is projected to \r\nincrease under all emissions scenarios and GWLs by the middle of the \r\ncentury (Figure 12.4a-f). Under RCP8.5, the expected number of days \r\nwith WBGT higher than 31degC is about 25, 30 and 40 days per year, \r\nas projected by EURO-CORDEX, CMIP5 and CMIP6 respectively on \r\naverage over the Mediterranean region, and around 30, 40 and 60 days \r\nper year in low coastal plain areas such as the Po Valley, the Italian, \r\nGreek and Spanish coasts, and the Mediterranean islands (Coppola "


id: 8183fe3455cd0448bf73c367ca2d57c3
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 19913
content:
"et al., 2021a). An average increase of a few days per year of maximum \r\ndaily temperature exceeding 35degC, a typical critical threshold for crop \r\nproductivity, is expected by the mid-century in central Europe, and \r\nan increase of 10-20 days is expected for the Mediterranean areas \r\n(Figure 12.4b; Coppola et al., 2021a). By contrast, under SSP1-2.6, the \r\nincrease in this number of days remains limited to less than about \r\n10 days, and confined to the Mediterranean regions. Mitigation is \r\nexpected to have a strong effect, with the dangerous heat threshold \r\nof HI > 41degC projected to be crossed 5-10 days more per year in the \r\nMediterranean regions and a few days per year more in WCE and EEU \r\nunder SSP5-8.5, while such increases would be virtually absent under \r\nSSP1-2.6 (Figure 12.4d-f)."


id: 83b8a69ef36a55f8e2b1786afc25cc70
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 20318
content:
"Cold spell and frost: Temperature observations for winter cold spells \r\nin Europe show a  long-term decreasing frequency (Brunner et  al., \r\n2018), with their probability of occurrence projected to decrease \r\nin the future (high confidence) and virtually disappear by the end \r\nof the century (Section 11.3). The frequency of frost days will very \r\nlikely decrease for all scenarios and all time horizons (Lindner et al., \r\n2014; Coppola et al., 2021a) with consequences for agriculture and \r\nforests. A  simple heating degree day index, characterizing heating \r\ndemand, shows a large observed decreasing trend for winter heating \r\nenergy demand in Europe (Spinoni et  al., 2015). This trend is very \r\nlikely to continue through the 21st  century, with decreases in the \r\nrange of 20-30% for Northern Europe, about 20% for central Europe \r\nand 35% for southern Europe, by mid-century under RCP8.5 (Spinoni \r\net al., 2018b; Coppola et al., 2021a; Interactive Atlas)."


id: a1db610f704f03e175f7dc29c9755b69
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 25696
content:
"high flow does not show uniform trends for the entire region (Hall et al., \r\n2014; Mediero et al., 2015) or specific regions (Mudersbach et al., 2017; \r\nVicente-Serrano et al., 2017; Tramblay et al., 2019), regional patterns \r\nof significant flood trends do exist. Based on the most extended river \r\nflow database spanning the period 1960-2010, an increase in floods \r\nfrequency in north-western Europe, decreasing in medium and large \r\ncatchments in southern Europe and decreasing floods in Eastern Europe \r\nhas been detected (Bloschl et al., 2019) in line with Mediero et al. (2014), \r\nArheimer and Lindstrom (2015), Gudmundsson et al. (2017), Krysanova \r\net al. (2017), Kundzewicz et al. (2018) and Mangini et al. (2018)."


id: fb3a052fd3b4dea38615c0c9dd005933
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 41572
content:
"There is high confidence of river floods increasing in Western and \r\nCentral Europe (WCE) and medium confidence of a  decrease in \r\nNorthern (NEU), Eastern (EEU) and southern Europe (MED) for mid\u0002and end-century under RCP8.5 and low confidence under RCP2.6. The \r\nprojected increase in WCE is roughly 10% (18% by end of century) \r\nand the projected decrease in NEU is 5% (11% by end of century) for \r\nthe peak flow with a return period of 100 years for mid-century, under \r\nRCP8.5 (Di Sante et al., 2021; Figure 12.9a for mid-century (Q100) \r\nprojections of flood discharges per unit catchment area (Bloschl \r\net al., 2019) based on EURO-CORDEX models)."


id: dcf36f91fcf754694058cef662f656df
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 36138
content:
"In summary, irrespective of the scenario, it is virtually certain\r\nthat warming will continue in Europe, and there is high \r\nconfidence that the observed increase in heat extremes is \r\ndue to human activities. It is very likely that the frequency \r\nof heat extremes will increase over the 21st century with an \r\nincreasing gradient toward the southern regions. Extreme \r\nheat will exceed critical thresholds for health, agriculture and \r\nother sectors more frequently (high confidence), with strong \r\ndifferences between mitigation scenarios. It is very likely that \r\nthe frequency of cold spells and frost days will keep decreasing \r\nover the course of this century and it is likely that cold spells \r\nwill virtually disappear towards the end of the century."


id: 43cdced162bf8f9fbe1ad523b72e5613
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 9158
content:
"Mean precipitation: Precipitation has generally increased in northern \r\nEurope and decreased in southern Europe, especially in  winter \r\n(Fischer and Knutti, 2016; Knutson and Zeng, 2018) but in the latter, \r\nprecipitation trends are strongly dependent on the examined period \r\n(Atlas.8). These trends in precipitation increases in the north and \r\ndecreases in the south are also represented by global and regional \r\nclimate simulations (Jacob et  al., 2014; Rajczak and Schar, 2017; \r\nLionello and Scarascia, 2018; Coppola et  al., 2021a; Atlas.8.2) and \r\nhave been attributed to climate change (Sections 3.3.2, 8.3.1)."


id: 6fbd2e719a9f2f08373169e844ac781d
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 16914
content:
"Heavy precipitation and pluvial flood: Heavy precipitation \r\nfrequency trends have been detected in Europe with high confidence\r\nfor the NEU and Alpine regions and with medium confidence in \r\nWCE, and also attributed to climate change with high confidence in \r\nNEU (Section 11.9). Guerreiro et al. (2017), based on observations, \r\nshowed that 20% of city areas in WCE and MED regions are affected \r\nby pluvial flooding and less than 10% of city areas in the northern \r\nand western coastal cities."


id: e0002395b442973490603bb81eacbe5a
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 36652
content:
"Studies since AR5, together with EURO-CORDEX and MED-CORDEX \r\nexperiments and the latest CMIP6 ensemble, have increased \r\nconfidence in regional projections of mean and extreme precipitation \r\n(Prein et al., 2016) despite their wet bias, and show that it is very \r\nlikely that precipitation will increase in Northern Europe in DJF and \r\ndecrease in the Mediterranean in JJA under all climate scenarios \r\nexcept RCP2.6/SSP1-2.6 and for both mid- and end-century periods \r\n(Coppola et al., 2021a; Atlas.8.5)."


id: 59f4870ebdf76adc200bb953108d51ad
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 13072
content:
"Projections based on multiple lines of evidence from global to \r\nconvective permitting model scales show high confidence in \r\nextreme precipitation increase in the northern, central and eastern \r\nEuropean regions (NEU, WCE, EEU) and in the Alpine area. Increases \r\nwith medium confidence are projected for the Mediterranean basin \r\n(with a negative gradient towards the south) for mid- and end-century \r\nunder RCP4.5, RCP8.5 and SSP5-8.5 and for 2degC GWL and higher \r\n(Section 11.9; MedECC, 2020)."


id: facc1af91506a0e03c381ef8eda98ae
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 41498
content:
"River flood: There is high confidence of an observed increasing \r\ntrend of river floods in Western and Central Europe (WCE) and \r\nmedium confidence of a decrease in Northern (NEU) and southern \r\nEurope (MED)."


id: c557f31ff9a625001d3a1f8d16bef3d5
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 32026
content:
"The SR1.5 shows evidence of an increase in reported floods in the UK \r\nover the period 1884-2013, and increasing trends in annual maximum \r\ndaily streamflow data over 1966-2005 in parts of Europe. Although "


id: 5d3e53d14bf5097a00611c5ea3d4663b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 13679
content:
"A reduction of drought length and magnitude is projected for NEU \r\nand EEU (Roudier et  al., 2016). In the southern Alps, both winter \r\nand summer low flows are projected to be more severe, with a 25% \r\ndecrease in the 2050s (Vidal et al., 2016)."


id: aaf739421e76bbd9e9846453a0c64949
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 27304
content:
"Agricultural and ecological drought: There is medium confidence\r\nthat agricultural and ecological droughts have increased in \r\nWestern and Central Europe and in the Mediterranean region, and \r\nmedium confidence that anthropogenic drivers contributed to the \r\nMediterranean increase (Sections 8.3.1.6 and 11.9)."


id: 8f6e9657e339e277d1b6af3a0b5e8fd0
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 22447
content:
"Chapter  11 assesses that agricultural and ecological droughts will \r\nincrease in the Mediterranean regions (high confidence) and Western \r\nand Central Europe (medium confidence) by mid-century and with \r\nhigh confidence by the end of the century for the MED for 2degC GWL \r\nand higher and all scenarios except RCP2.6/SSP1-2.6 (Section 11.9.4). \r\nLow confidence in direction of change is assessed for EEU and NEU \r\nunder all scenarios and global warming levels (Figure 12.4k)."


id: a02ddbc7fbb4aea0a602058d4f2dafb1
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 25394
content:
"Aridity: The Mediterranean region shows evidence of large-scale \r\ndecreasing precipitation trends over 1901-2010, which are at least \r\npartly attributable to anthropogenic forcing according to CMIP5 \r\nmodels (Knutson and Zeng, 2018). Nevertheless, there is low \r\nagreement among studies on observed precipitation trend in the \r\nMediterranean region (Section 11.9.4 and Atlas.8.2)."


id: eba843e50c0ba9ef237db7874d5ea85c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 38823
content:
"Precipitation is projected to decrease by mid- and end-century for the \r\nRCP8.5 and SSP5-8.5 with strong agreement among CMIP5, CMIP6 and \r\nCORDEX regional climate ensemble models on the direction of change. \r\nWith both temperature increase and precipitation decrease there is high \r\nconfidence on increased aridity in the MED region (Sections 8.4.1.6 \r\nand 11.9.4 and Atlas.8.2; Coppola et al., 2021a). In NEU there is high \r\nconfidence of decrease in aridity linked to mean precipitation increase \r\n(Section 8.4.1.6, Atlas 8.2) and meteorological drought decrease based \r\non indicators like Standardized Precipitation Index and consecutive dry \r\ndays (Section 11.9.4, Figure 12.4, Coppola et al,, 2021a)."


id: c183429e66bd701ad370784cf9eab883
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 31351
content:
"Hydrological drought: There is high confidence that hydrological \r\ndroughts have increased in the Mediterranean basin with medium \r\nconfidence in anthropogenic attribution of the signal, and high \r\nconfidence that they will continue to increase through the 21st century \r\nfor 2degC GWL and higher and all scenarios except RCP2.6/SSP1-2.6. \r\n(Sections 8.3.1.6, 8,4.1.6, and 11.9.4). There is medium confidence\r\nin hydrological drought increase in WCE and low confidence in \r\ndirection of change for EEU and NEU from mid-century onwards and \r\nfor 2degC GWL and higher and all scenarios except RCP2.6/SSP1-2.6 \r\n(Section 11.9 and Figure 12.4g-i)."


id: 29328dfb9f4a6629c6dd3b5669b83218
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 4461
content:
"Streamflow droughts are projected to become more severe and \r\npersistent in the Mediterranean and western Europe (current \r\n100-year events could occur approximately every 2-5 years by 2080; \r\nForzieri et al., 2016). "


id: 4b62be29454b22791b99308bf3544c7
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 10512
content:
"The opposite tendency is projected in Northern, Eastern and central \r\nEurope where higher precipitation that outweighs the effects of \r\nincreased evapotranspiration is expected to result in a decrease in \r\nstreamflow drought frequency (Forzieri et al., 2014). For a 2degC GWL \r\ndroughts will become more intense in the MED and in France and \r\nlonger mainly due to less rainfall and higher evapotranspiration. "


id: bad3832424f2ee1a57f0feb32733b466
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 30081
content:
"In summary, there is high confidence that river floods will \r\nincrease in central and Western Europe and medium confidence\r\nthat they will decrease in Northern, Eastern and southern \r\nEurope, for mid- and end of century under RCP8.5 and  with \r\nlow confidence under RCP2.6. There is high confidence that \r\naridity will increase by mid- and end-century under the RCP8.5 \r\nand SSP5-8.5, and high confidence that agricultural, ecological \r\nand hydrological droughts will increase in the Mediterranean \r\nregion by mid- and far end of century under all RCPs except \r\nRCP2.6/SSP1-2.6 and also for 2degC and higher GWLs. There is high \r\nconfidence in fire weather increase in the Mediterranean region."


id: ea045b400144b9918a09c4f2b791bb9c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 38521
content:
"Severe wind storm: There are large uncertainties in past evolutions \r\nof windstorms and extreme winds in Europe. Extreme near-surface \r\nwinds have been decreasing in the past decades (Smits et al., 2005; \r\nTian et  al., 2019; Vautard et  al., 2019) according to near-surface \r\nobservations. Significant negative trends of cyclone frequency in spring \r\nand positive trends in summer have been found in the Mediterranean \r\nbasin for the period 1979-2008 (Lionello et  al., 2016). By contrast \r\nincreasing trends have been found in Arctic Ocean areas (Wickstrom \r\net al., 2020). These trends are not associated with significant trends in \r\nextratropical cyclones (Sections 8.3.2.8 and 11.7.2)."


id: b5829b78863ca55eddaa43d4eccfa6e
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 29157
content:
"There is high confidence that mean wind speeds will decrease \r\nin Mediterranean areas and medium confidence of such \r\ndecreases in Northern Europe for global warming levels of \r\n2degC or more and beyond the middle of the century. A slightly \r\nincreased frequency and amplitude of extratropical cyclones, \r\nstrong winds and extratropical storms is projected for northern, \r\ncentral and western Europe by the middle of the century and \r\nbeyond and for global warming levels of 2degC or higher (medium "


id: 4a386f002203f95a788986b1ae3156bc
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 10300
content:
"confidence). The frequency of Medicanes is projected to \r\ndecrease (medium confidence), but their intensity is projected \r\nto increase by mid century and beyond and for global warming \r\nlevels of 2degC or more. Proxies of intense convection indicate \r\nthat the large-scale conditions conducive to severe convection \r\nwill tend to increase in the future climate (low confidence)."


id: a066f13e5ce3c51cfbd1582322ce90a4
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 25432
content:
"day (2017) ice volume is projected to be lost by 2100. In contrast, \r\nunder the strong warming of RCP8.5, glaciers in the European Alps \r\nare projected to largely disappear by 2100 (94 +- 4% volume loss \r\ncompared to 2017; Zekollari et al., 2019)."


id: 28707c8984ba11ff751479db412703a1
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 4319
content:
"Permafrost: In Europe, permafrost is found in high mountains and in \r\nScandinavia, as well as in Arctic Islands (e.g., Iceland, Novaya Zemlia or \r\nSvalbard). In recent decades permafrost has been lost (Section 9.5.2) \r\nand accelerated warming at high altitudes and latitudes has favoured \r\nan increase of permafrost temperatures of the order of 0.2 +- 0.1degC \r\nbetween 2007 and 2016 (Romanovsky et  al., 2018; Noetzli et  al., \r\n2019). Over the 21st  century, permafrost is very likely to undergo \r\nincreasing thaw and degradation under all scenarios (Hock et  al., \r\n2019) and it is virtually certain that permafrost extent and volume will \r\ndecrease with increase of global warming (Section 9.5.2)."


id: e8a992edfe089ff87bbe51be940093e6
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 38277
content:
"Permafrost thawing is projected to affect the frequency and \r\nmagnitude of high-mountain mass wasting processes (Stoffel \r\nand Huggel, 2012). The temporal frequency of periglacial debris flows \r\nin the Alps is unlikely to change significantly by the mid-21st century \r\nbut is likely to decrease during the second part of the century under \r\nthe A1B scenario, especially in summer (Stoffel et al., 2011, 2014). \r\nThere is medium confidence that most of the Northern Europe \r\nperiglacial processes will disappear by the end of the century, even \r\nin the RCP2.6 scenario (Aalto et al., 2017). The magnitude of debris \r\nflow events might increase (Lugon and Stoffel, 2010) and the debris\u0002flow season may last longer under the A1B scenario (Stoffel and \r\nCorona, 2018). Quantitative data for the European Alps is highly site \r\ndependent (Haeberli, 2013)."


id: d3c4b5b63c33baa0b8ae2df4aa72d590
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 34602
content:
"Heavy snowfall, ice storms and hail: There is low confidence that \r\nclimate change will affect ice and snow-related episodic hazards \r\n(limited evidence). The change in snowpack in the Alps is expected \r\nto lead to a possible reduction in overall avalanche activity by end of \r\nthe century (low confidence), except possibly in winter and at high \r\naltitudes (Castebrunet et al., 2014)."


id: 9e2a5d11c23f60a1fb852a7caf8782b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 25060
content:
"For ice storms, or freezing rainstorms, there is also limited evidence\r\ndue to a limited number of studies. Heavy snowfalls have decreased \r\nin frequency in the past decades and this is expected to continue in \r\nthe future climate (low confidence) (Beniston et al., 2018). Freezing \r\nrain is projected to increase in western, central and southern Europe \r\nby the end of the century under RCP4.5 and RCP8.5 (low confidence) \r\n(Kamarainen et  al., 2018). Rain-on-snow events, are decreasing in \r\nnorthern regions (Pall et al., 2019) and by 48% on average in southern \r\nScandinavia (Poschlod et al., 2020) due to decreases in snowfall."


id: cb833786088536201c9b4d0f2df4a17a
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 33133
content:
"In summary, future snow cover extent and seasonal duration \r\nwill reduce (high confidence) and it is virtually certain that \r\nglaciers will continue to shrink. A  reduction of glacier ice \r\nvolume is projected in the European Alps and Scandinavia \r\n(high confidence). There is high confidence that permafrost \r\nwill undergo increasing thaw and degradation over the \r\n21st  century. Most of the Northern Europe periglacial will \r\ndisappear by the end of the century even for a lower emissions \r\nscenario (medium confidence) and the debris-flow season may \r\nlast longer in a warming climate (medium confidence)."


id: eba84c0c089b20ffb8e8cfd97843ca7b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 38824
content:
"(Luijendijk  et  al., 2018; Mentaschi et  al., 2018). Mentaschi et  al. \r\n(2018) report a coastal area loss of 270 km2 over a 30-year period \r\n(1984-2015) along the Atlantic coastlines of Europe."


id: d1aae3bcb95b44b5dc675c5d174a18e1
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 34238
content:
"Relative sea level: Around Europe, over 1900-2018, a  new tide \r\ngauge-based reconstruction finds a  regional mean RSL change of \r\n1.08 [0.79 to 1.38] mm yr -1 in the subpolar North Atlantic (Frederikse \r\net al., 2020), compared to a GMSL change of around 1.7 mm yr -1\r\n(Section 2.3.3.3 and Table 9.5). For the period 1993-2018, the RSLR \r\nrates around Europe, based on satellite altimetry, increased to 2.17 \r\n[1.66 to 2.66] mm yr-1 (Frederikse et al., 2020), compared to a GMSL \r\nchange of 3.25 mm yr-1 (Section 2.3.3.3 and Table 9.5)."


id: 9a607c33861c626502108917188f0fa2
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 24402
content:
"Relative sea level rise is extremely likely to continue in the oceans \r\naround Europe. Regional mean RSLR projections for the oceans around \r\nEurope range from 0.4-0.5 m under SSP1-2.6 to 0.7-0.8 m under \r\nSSP5-8.5 for 2081-2100 relative to 1995-2014 (median values), \r\nwhich means that there are locally large deviations from the projected \r\nGMSL change (Section 9.6.3.3). These RSLR projections may however \r\nbe underestimated due to potential partial representation of land \r\nsubsidence in their assessment (Section 9.6.3.2). The signal is strongest \r\nfor the North Sea and Atlantic coasts, followed by the Black Sea. The \r\nBaltic Sea, on the contrary, shows the lowest increase due to land \r\nuplift (Vousdoukas et al., 2017). The model agreement is higher for the \r\nMediterranean and in line with previous findings by Gualdi et al. (2013)."


id: 79516c71d500e4d3e2725fc487e49af7
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 18539
content:
"Local assessments of both long term shoreline retreat and episodic \r\ncoastal erosion are given by Li et  al. (2014b), Toimil et  al. (2017), \r\nBon de Sousa et al. (2018) and Le Cozannet et al. (2019). In terms \r\nof episodic coastal erosion, 31-88% of all Aegean beaches are \r\nprojected to experience complete erosion, with a RCP4.5 sea level \r\nrise of 0.5 m and a surge of 0.6 m, but with substantial uncertainty \r\n(Monioudi et al., 2017)."


id: a4ec213c3105890dcfc8165f5281788c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 26236
content:
"Coastal flood: The present-day 1-in-100-year ETWL is between 0.5 \r\nand 1.5 m in the MED basin and 2.5 and 5.0 m in the western Atlantic \r\nEuropean coasts, around the UK and along the North Sea coast, and \r\nlower at 1.5-2.5 m along the Baltic Sea coast (Kirezci et al., 2020). \r\nSimilar values are reported by Vousdoukas et al. (2018)."


id: dd9144ef21b707e964854d183cae3a89
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 36246
content:
"Marine heatwave: The mean SST of the Atlantic Ocean and \r\nthe Mediterranean has increased between 0.25degC and 1degC since \r\n1982-1998. This mean ocean surface warming is correlated to longer \r\nand more frequent marine heatwaves in the region (Oliver et al., 2018). \r\nOver the period 1982-2016, the coastlines of Europe experienced on \r\naverage more than 2.0 MHW yr-1, with the eastern Mediterranean \r\nand Scandinavia experiencing 2.5-3 MHWs yr-1. The average duration \r\nwas between 10 and 15 days. Changes over the 20th century, derived \r\nfrom MHW proxies, show an increase in frequency of between 1.0 and \r\n2.0 MHWs per decade in Europe, although the trend is not statistically \r\nsignificant; with an increase in intensity per event in the North Atlantic \r\nand the Mediterranean, and a decrease in the Atlantic off the British \r\nIsles. The total number of MHW days per decade has increased in the \r\nMediterranean (Oliver et al., 2018)."


id: cc5ab6ec520f2251b99449c7db1d4ef4
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 33271
content:
"Mean SST is projected to increase by 1degC-3degC around Europe by \r\n2100, with a hotspot of around 4degC-5degC along the Arctic coastline \r\nof Europe under RCP4.5 and RCP8.5 scenarios (see Interactive Atlas), \r\nleading to a continued increase in MHW frequency, magnitude and \r\nduration (Oliver et al., 2018; MedECC, 2020). Projections for SSP1-2.6 \r\nand SSP5-8.5 both show an increase in MHWs around Europe by \r\n2081-2100, relative to 1985-2014 (Box  9.2, Figure  1). Darmaraki \r\net al. (2019) project that, by the end of the 21st century and under \r\nRCP8.5, there will be one MHW occurring every year in the northern \r\nMediterranean sea, and that these MHWs would be three months \r\nlonger, four times more intense, and 42 times more severe than \r\npresent day MHWs in the region. Frolicher et al. (2018) show that, \r\nin Europe, the change in the probability for the number of days of "


id: b6fc478cbcb51cfa77185954e78d3915
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 29406
content:
"Coastal erosion: Satellite-derived shoreline change estimates over \r\n1984-2015 indicate shoreline retreat rates of around 0.5  m  yr-1\r\nalong the sandy coasts of WCE and MED, around 4 m yr-1 in EEU \r\n(Caspian Sea region) and more or less stable shorelines in NEU "


id: 55e0133c2513ee362d34c92ec77e89
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 12377
content:
"MHWs exceeding the 99th percentile of the pre-industrial level is \r\n4%, 15% and 30% for global warming levels of 1degC, 2degC and 3.5degC, \r\nrespectively. MHW increase in the Mediterranean will impact on \r\nmany species that live in shallow waters and have reduced motility, \r\nwith consequences for related economic activities (Galli et al., 2017)."


id: 612415fc9d96f9f33b68c79c77f5e77
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 14386
content:
"on connections to warming levels provided by SR1.5 (IPCC, 2018), \r\nand climate information related to land degradation and land-use \r\nsuitability in SRCCL (IPCC, 2019c), and ocean and coastal hazards in \r\nthe SROCC (IPCC, 2019b). Recent national assessments in the USA \r\n(USGCRP, 2017, 2018) and Canada (Bush and Lemmen, 2019) enhance \r\nthe local perspective and assessments across a number of CIDs and \r\ntheir sectoral connections. For the purpose of this assessment, North \r\nAmerica is sub-divided into six sub-regions, as defined in Chapter 1: \r\nNorth Central America (NCA), Western North America (WNA), Central \r\nNorth America (CNA), Eastern North America (ENA), North-Eastern \r\nNorth America (NEN), and North-Western North America (NWN). \r\nGreenland and Arctic regions of North-Eastern and North-Western \r\nNorth America are further assessed in Section  12.4.9, and the \r\nCaribbean and Hawaiian Islands are assessed in Section 12.4.7."


id: a36db200c16899705882e2b501237b6d
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 25961
content:
"In general, there is high confidence that most coastal/ocean\u0002related climatic impact-drivers in Europe will increase over the \r\n21st century for all scenarios and time horizons. Relative sea \r\nlevel rise is extremely likely to continue around Europe (except \r\nin the northern Baltic Sea), contributing to increased coastal \r\nflooding in low-lying areas and shoreline retreat along most \r\nsandy coasts (high confidence). Marine heatwaves are also \r\nexpected to increase around the region over the 21st century \r\n(high confidence)."


id: b026e74eb849d2a73d013894ab10b915
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 28230
content:
"Compound events: One typical compound event that is observed in \r\nthe European area is compound flooding due to the combination of \r\nextreme sea level events and extreme precipitation events associated \r\nwith high levels of runoff. In the present climate, the Mediterranean \r\ncoasts are exposed to a higher probability of this type of compound \r\nflooding event (Bevacqua et al., 2019). Under RCP8.5, the probability \r\nof these events is projected to increase along northern European \r\ncoasts (west coast of UK, northern France, the east and south coast \r\nof the North Sea, and the eastern half of the Black Sea), with the \r\npercentage of coastline now experiencing such events at least once \r\nevery 6 years increasing by between 3% and 11% by the end of the \r\n21st century (Bevacqua et al., 2019)."


id: 5e01a3757576412ad0e5ed9c987de3cc
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 13837
content:
"Under RCP8.5, regions in Russia, France and Germany are projected \r\nto experience an increase in the frequency and the length of wet and \r\ncold compound events, while Spain and Bulgaria are projected to stay \r\nlonger in the hot and dry state by mid-century (Sedlmeier et al., 2016)."


id: dd7d5d176e44d8ab4f6164054c1832b2
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 36236
content:
"Compound events of dry and hot summers have increased in Europe. \r\nManning et al. (2019) found that the probability of such compound \r\nevents has increased across much of Europe between 1950-1979 \r\nand 1984-2013, notably in southern, eastern and western Europe. \r\nCompound hot and dry extremes are projected to increase in Europe by \r\nmid-century for the SRES A1B and RCP8.5 with a particularly strong \r\nsignal projected in southern and eastern Germany and the Czech \r\nRepublic (Sedlmeier et al., 2016)."


id: 5fd91b0e2523ee93af1367d40853e555
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 14170
content:
"Extreme heat: Section 11.9 assessed that extreme temperatures in \r\nNorth America have increased in recent decades (medium evidence,\r\nmedium agreement) other than in Central and Eastern North America \r\n(low confidence), and extreme heat in all regions is projected to \r\nincrease with climate change (high confidence). Observed trends in \r\nextreme heat are more positive for heat extreme indices that include \r\ntemperature and humidity given historical expansion of irrigation \r\nand intensification of agriculture (Mueller et al., 2017; Grotjahn and \r\nHuynh, 2018; Thiery et al., 2020). Several studies noted statistically \r\nsignificant increases in intensity and particularly the frequency, \r\nduration, and seasonal length of the physiologically hazardous \r\nextreme heat conditions across North America (Grineski et al., 2015; \r\nHabeeb et al., 2015; Martinez-Austria et al., 2016; Petitti et al., 2016; \r\nL.A. Vincent et al., 2018; Garcia-Cueto et al., 2019)."


id: ae095082a398c395c5e30253f659c73
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 27859
content:
"The assessed direction of change in climatic impact-drivers for Europe \r\nand associated confidence levels are illustrated in Table 12.7, together \r\nwith emergence time information (Section  12.5.2). No assessable \r\nliterature could be found for sand and dust storms, although these \r\nphenomena may be relevant in parts of the region."


id: 515111e619e77e547ae5b9a9d6cde7d2
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 11583
content:
"Major changes in North American CIDs were assessed in WGII AR5 \r\nChapter  26 (Romero-Lankao et  al., 2014), with additional detail "


id: 5a94ea0f7ef020ce2ef97d0bae524c73
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 13195
content:
"Climate change is virtually certain to shift the balance of \r\ntemperature towards warming trends and away from cold \r\nextremes, with increases in the magnitude, frequency, duration \r\nand seasonal and spatial extent of heat extremes driving \r\nimpacts across North America. The frequency of dangerous \r\nheat threshold exceedance (such as HI > 41degC) is particularly \r\nsensitive to scenario pathway, with 75-150 days more under \r\nSSP5-8.5 but less than 60 days more under SSP1-2.6 by the \r\nend of the century in NCA, CNA and the south-western USA."


id: cd2676a527fb9740bf667f94e9d28278
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 33429
content:
"The number of days crossing dangerous heat thresholds such as \r\nHI  >  41degC will be very sensitive to the mitigation scenario at the \r\nend of the century (Wuebbles et al., 2014; Zhao et al., 2015; Dahl \r\net al., 2019; Schwingshackl et al., 2021). At the end of the century \r\nunder SSP5-8.5, a CMIP6 median increase of exceedances of 75-150 \r\ndays per year is projected over much of North Central America, \r\nCentral North America and the south-western USA while this \r\nincrease is projected to remain limited below 60 days under SSP1-2.6 \r\n(Figure  12.4d,f and Figure 12.SM.2). Steinberg et  al. (2018) also \r\nprojected more frequent and longer 'heat-health' events in California \r\nextending into October."


id: 2edec03274ce6927ee112e9fd4bc08f6
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 5521
content:
"Mean precipitation: Atlas.9.2 found that trends in annual \r\nprecipitation over 1960-2015 are generally non-significant, though \r\nthere are consistent positive trends over parts of ENA and CNA, \r\ntogether with significant decreases in precipitation in parts of the \r\nsouth-western USA and north-western Mexico."


id: ec90c4c205bbc5e350fb66bd7c336ba0
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 38978
content:
"Cold spell: Chapter  11 assessed high confidence in decreasing \r\nfrequency and intensity of cold spells over North America (Section 11.9). \r\nThe number of days with extreme wind chill hours (humidex <-30) \r\ndecreased at 76% of examined Canadian stations from 1953 to 2012 \r\n(Mekis et al., 2015) and cold days and coldest nights decreased in \r\nMexico from 1980 to 2010 (Garcia-Cueto et al., 2019)."


id: b99be53143faa628cb13bbad114e099b
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 29862
content:
"Atlas.9.4 assessed very high confidence in increases in mean \r\nprecipitation over most of northern and Eastern North America, with \r\nmedium confidence of decrease over Northern Central America and \r\nlow confidence elsewhere (see Figure Atlas.26, and Cross-Chapter \r\nBox Atlas.1, Figure  1). Changes are most dramatic in the spring \r\nand winter, when wet conditions are projected to extend from the \r\nnorthern portions of the continent as far south as the central Great \r\nPlains, while Mexico becomes drier; in contrast, summer changes are \r\nuncertain across most of the continent other than wetter conditions \r\nin northern Canada (Easterling et al., 2017; Bukovsky and Mearns, \r\n2020; Almazroui et al., 2021; Teichmann et al., 2021)."


id: 32fa4a421641049449b86a20b525d187
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 6233
content:
"River flood: There is limited evidence and low agreement on \r\nobserved climate change influences for river floods in North America \r\n(Section 11.5). Trends in streamflow indices are mixed and difficult \r\nto separate from river engineering influences, with large changes \r\nbut little spatial coherence across the USA, making it difficult to \r\nidentify trends with confidence (Peterson et  al., 2013; Mallakpour \r\nand Villarini, 2015; Archfield et al., 2016; Wehner et al., 2017; Villarini \r\nand Slater, 2018; Hodgkins et al., 2019; Neri et al., 2019). There is \r\nhigh confidence in historical shifts in the timing of peak streamflow \r\ntowards higher winter and earlier spring flows in snowmelt-driven \r\nbasins in Canada (Burn and Whitfield, 2016; Bonsal et al., 2019) and "


id: 413fb3d858b27947301e88dd4d078ac1
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 8663
content:
"increases in evapotranspiration that will counteract precipitation \r\nchanges over much of the country (Coe, 2016)."


id: 6542714e4572cea651e58953cfc0eb96
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 15092
content:
"Heavy precipitation and pluvial flood: Section 11.4 assessed high \r\nconfidence in observed increases in extreme precipitation events \r\n(including hourly totals) in Central and Eastern North America with \r\nlow confidence in broad trends elsewhere in the continent despite \r\nobservational increases in some portions of each region (L.A. Vincent \r\net al., 2018; Garcia-Cueto et al., 2019; X. Zhang et al., 2019)."


id: 9430dc0d025e72b313f82066e292b545
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 23279
content:
"Hydrological drought: Section  11.9 asssessed low confidence of \r\nsignificant observational trends and projected future changes in the \r\ncharacteristics of episodic hydrological drought in North America given \r\nlimited evidence and low agreement in modeled changes. C. Zhao \r\net al. (2020) found that increases in hydrological drought frequency \r\n(particularly the 100 yr drought) were far more prevalent than for \r\nmeteorological drought across 5797 watersheds in the USA and Canada, \r\nindicating a strong influence of evaporative demand. Reductions in the \r\noverall supply of meltwater from a declining snowpack also increase \r\nthe potential for intermittent hydrological droughts in the western USA \r\n(Mote et al., 2018; Livneh and Badger, 2020)."


id: 3f0d3fea6aa466c6b6568b00f63a7cb2
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 8279
content:
"evaporative demand will extend the regions where more intense \r\necological and agricultural droughts develop when meteorological \r\ndroughts occur (Wehner et al., 2017; B.I. Cook et al., 2019, 2020). \r\nStudies utilizing a  variety of drought indices and soil moisture \r\nprojections consistently project increased drought extending from \r\nMexico into the southern Canadian Plains during the summer (Swain \r\nand Hayhoe, 2015; Ahmadalipour et  al., 2017; Feng et  al., 2017; \r\nBonsal et al., 2019; Tam et al., 2019; B.I. Cook et al., 2020)."


id: d8a96a508c8f00a6737bf415a3e5f7c3
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 35411
content:
"Mean wind speed: Mean wind speeds have declined in North \r\nAmerica - as in other Northern Hemisphere areas - over the past \r\nfour decades (medium confidence) (AR5 WGI) with a reversal in the \r\nlast decade (low confidence) not fully consistent across studies (Tian \r\net al., 2019; Zeng et al., 2019; Z. Zhang et al., 2019). Tian et al. (2019) \r\nfound a corresponding reduction in the wind power potential across \r\nthe eastern parts of North America."


id: ab4dae363a9e40076aa8bc3adb5363c6
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 27365
content:
"Mean wind speeds are expected to decline over much of North \r\nAmerica (Figure 12.4m-o), but the only broad signal of consistent \r\nchange across model types is a reduction in wind speed in Western \r\nNorth America (high confidence). These declines reduce wind power \r\nendowment by 2050 and as early as the 2020-2040 near-term period \r\nin the USA Mountain West, while there is disagreement between \r\nglobal- and regional-model change projections in the upper and \r\nlower Great Plains, Ohio River Valley, Mexico and eastern Canada \r\n(Karnauskas et al., 2018a; Jung and Schindler, 2019; Chen, 2020)."


id: 26568755062cec02d2c5377df9fa4889
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 3915
content:
"Severe wind storm: There is limited evidence and low agreement\r\nin observed changes in North American CID indices associated with \r\nextratropical cyclones (Section  11.7), severe thunderstorms, severe \r\nwind bursts (derechos), tornadoes, or lightning strikes (Vose et al., \r\n2014; Easterling et  al., 2017; Kossin et  al., 2017). Observational \r\nstudies have indicated a reduction in the number of tornado days in \r\nthe USA, but increases in outbreaks with 30 or more tornadoes in one \r\nday (Brooks et al., 2014), the density of tornado clusters (Elsner et al., \r\n2015), and overall tornado power (Elsner et al., 2019)."


id: a99493a6c69ee790dbb6aa4003853b81
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 27059
content:
"Tropical cyclone: Section  11.7.1 identified recent reductions in \r\ntropical cyclone translation speed and higher tropical cyclone rainfall \r\ntotals over the North Atlantic, as well as substantial natural variability. \r\nProjections indicate low confidence in change in North Atlantic tropical \r\ncyclone numbers, but medium confidence in Mexico and the US Gulf and \r\nAtlantic coasts for more intense storms with higher wind, precipitation, \r\nand storm surge totals when they do occur (Section 11.7.1; Diro et al., \r\n2014; DOE, 2015; Walsh et  al., 2016a; Kossin et  al., 2017; Marsooli \r\net  al., 2019; Ting et  al., 2019; Knutson et  al., 2020). A  more rapid \r\nintensification of tropical cyclone winds and destructive power also "


id: f263a9459b3294964c40be1d6600e83c
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 40040
content:
"Changes in North American wet and dry climatic impact\u0002drivers are largely organized by the 'north-east (more wet) to \r\nsouth-west (more dry)' pattern of mean precipitation change, \r\nalthough heavy precipitation increases are widespread and \r\nincreasing evaporative demand expands aridity, agricultural \r\nand ecological drought, and fire weather (particularly in \r\nsummer) (high confidence)."


id: 8d56819b30a5b6bd2552a95dbef23e81
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 22044
content:
"(see Atlas.9.5). Changes include a reduction in the number of days with \r\nsnowfall in across all of North America, with the exception of northern \r\nCanada (Danco et al., 2016; McCrary and Mearns, 2019), a delay of \r\nabout a  week in first snowfall in the western USA by 2050 under \r\nRCP8.5 (Pierce and Cayan, 2013), and more prominent reductions in \r\nCanadian snow cover in the October-December period (Mudryk et al., \r\n2018). Reduced total snowpack and earlier snowmelt lower dry season \r\nstreamflow (Kormos et al., 2016; Rhoades et al., 2018). Figure 12.10b \r\nshows a reduction in days suitable for skiing (SWE > 10 cm; Wobus \r\net al., 2017b) across the USA and southern Canada, although some \r\nportions of northern central Canada see an increase."


id: 3561def31ea09ee1d2bfba9d7c1428dd
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 6639
content:
"heightens the tropical cyclone hazard (Bhatia et al., 2019). Greenhouse \r\ngas forcing is projected to shift tropical cyclones poleward (Kossin \r\net al., 2016), while also holding the potential for higher precipitation \r\ntotals (Risser and Wehner, 2017; Knutson et al., 2020) particularly given \r\nevidence that storms increasingly stall near North American coastlines \r\n(Hall and Kossin, 2019)."


id: 1d983e3d9b37c826e92acdd901f9dc4
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 2392
content:
"Tropical cyclones, severe wind and dust storms in North \r\nAmerica are shifting towards more extreme characteristics, \r\nwith a  stronger signal towards heightened intensity than \r\nincreased frequency, although specific regional patterns are \r\nmore uncertain (medium confidence). Mean wind speed and \r\nwind power potential are projected to decrease in Western \r\nNorth America (medium confidence) with differences between \r\nglobal and regional models lending low confidence elsewhere."


id: a37a81835c7796204f16150f899150da
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 25967
content:
"Permafrost: Warmer ground temperatures are expected to extend the \r\ngeographical extent and depth of permafrost thaw across northern \r\nNorth America (very high confidence) (Section 9.5.2). Observations \r\nacross Canada show that permafrost temperature is increasing and \r\nthe active layer is getting thicker (Section  2.3.2.5; Derksen et  al., \r\n2018; Biskaborn et al., 2019; Romanovsky et al., 2020). Slater and \r\nLawrence (2013) note that the RCP8.5 end-of-century period in North \r\nAmerica only has shallow permafrost as the most probable condition \r\nin the Canadian Archipelago. Melvin et  al. (2017) noted the loss \r\nof shallow permafrost in five RCP8.5 CMIP5 models across a wide \r\nswathe of southern Alaska by 2050, along with increases of active \r\nlayer thickness. There is high confidence in continued reductions in \r\nmountain near-surface permafrost area with high spatial variability \r\ngiven local snow and temperature changes (Section 9.5.2; Peng et al., \r\n2018; Hock et al., 2019)."


id: afc131dc00b5f4ac1e5c76c34d10bc90
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 28157
content:
"Snow: The seasonal extent of snow cover has reduced over North \r\nAmerica in recent decades (robust evidence, high agreement) \r\n(see also Sections 2.3.2.2 and 9.5.3, and Figure Atlas.25). The average \r\nsnow-cover extent in North America decreased at a  rate of about \r\n8500  km2  yr-1 over the 1972-2015 period, reducing the average \r\nsnow cover season by two weeks, primarily due to earlier spring melt \r\n(US EPA, 2016). Observations indicate earlier spring snowpack melting \r\n(Dudley et  al., 2017) and a  reduction in end-of-season snowpack \r\nmetrics important to water resources over the Rocky Mountains \r\n(particularly since 1980) and Pacific Northwest (Pederson et al., 2013; \r\nKormos et al., 2016; Kunkel et al., 2016; Fyfe et al., 2017; Mote et al., \r\n2018). In situ measurements in Canada show more heterogenous \r\ntrends in snow amount and density (Brown et al., 2019)."


id: 647b86ebff4a79bc2a8529da9d41bdd1
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
content_type: text
index: climate_gpt_v2
vector_id: 14954
content:
"Lake, river and sea ice: Anthropogenic warming reduces the seasonal \r\nextent of lake and river ice over many North American freshwater \r\nsystems, with ice-free winter conditions pushing further north with \r\nrising temperatures (high confidence). Observations in Central and \r\nEastern North America show reduced average seasonal lake-ice cover \r\nduration (Benson et  al., 2012; Mason et  al., 2016; US EPA, 2016). \r\nSatellite observations show declines in lake ice (Du et al., 2017) and \r\nloss of more than 20% of winter river-ice length in much of Alaska \r\n(2008-2018 compared to 1984-1994; Yang et al., 2020a). Spring lake \r\nand river ice in Canada is projected to break up 10-25 days earlier \r\nwhile autumn freeze-up occurs 5-15 days later by mid-century, with \r\nlarger declines in lake-ice season closer to the coasts (Dibike et  al., \r\n2012) and for rivers in the Rocky Mountains and north-eastern USA "


id: d37a0cc75e8bdc88a67bc8f7fe8b5883
created_at: 2023-04-19 13:21:41
updated_at: 2023-04-19 13:21:41
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index: climate_gpt_v2
vector_id: 34543
content:
"(Yang et al., 2020a), although global models have difficulty with frozen \r\nfreshwater system dynamics (Derksen et al., 2018). Substantial ice loss \r\nis projected over the Laurentian Great Lakes (Hewer and Gough, 2019; \r\nMatsumoto et  al., 2019). The southern extent of lakes experiencing \r\nintermittent winter ice cover moves northward with rising temperature, \r\npushing nearly out of the continental USA at low elevations under a \r\n4.5degC GWL (Sharma et al., 2019). Higher spring flows and the potential \r\nfor winter thaws are also projected to heighten the threat of ice jams \r\n(Rokaya et al., 2018; Bonsal et al., 2019) while reducing the seasonal \r\nviability of ice roads and recreational use (Pendakur, 2016; Mullan \r\net al., 2017; Knoll et al., 2019)."


