# document

id: 76230d6c77095cecd8b3274cdfcf19d7
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18015
content:
"(), ,, \r Greenhouse gases* (GHGs)\r aerosol masking of warming effect of, 819\r AR5 assessment in tropospheric warming, 444\r Arctic sea ice loss driver, 426\r attribution of Arctic sea ice loss, 468\r attribution of contemporary trends in, 769\r attribution of contribution to warming, 425\r attribution of temperature extremes, 1552\r attribution of warming to, 439\r climate response to reduction of emissions, 619\r CO2, CH4, N2O driving of radiative balance, 712\r CO2 uptake and storage (SSPs), 20\r concentration changes in, 158, 676\r contemporary trends and attribution, 769\r cumulative emissions effects, 202\r driver of hot and cold extremes, 426\r driver of warming, 1547\r effective radiative forcing (1750-2019), 926, 947\r effects of local forcing, 1553\r effects with continued warming, 1146\r forcing of extreme conditions, 1522\r forcing of hot and cold extremes, 1517\r glacial-interglacial records of, 684\r global annual mean mixing ratios (2011-2019), \r 302\r [...]"


id: 6dfb06e9df7394c9abb8630f7df35b73
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 16612
content:
"[...] global land monsoon precipitation effects, 463\r global precipitation changes, 1113\r heavy precipitation changes, 1518\r historical and projections for changes in, 2140\r historical trends, variability and budgets for, 687\r influence of anthropogenic, 1552\r influence on Brazil water shortage, 1996\r in sea level change, 481\r instrumental mixing ratios, 2140\r irreversible changes with, 21"


id: 9a3f00890d93fc6d99822835861eaeb3
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 24375
content:
"surface freshening of ocean in, 1214\r temperature variability in, 598\r warming compared to low latitudes, 613\r High Mountain Asia, 1275, 1984\r High-resolution cloud resolving models (CRMs), \r 972\r High-Resolution Model Intercomparison Project \r (HighResMIP), 431\r High spectral resolution radiative transfer \r models, 944\r High-warming storylines\r annual mean precipitation change with, 638\r changes in annual mean temperature, 636\r Hindu Kush Himalaya (HKH) region\r annual precipitation change in, 1973\r climate change over, 1456-1459\r glacier melting in, 1979\r glacier projections for, 1122\r glacier trends in, 1458\r historical surface air temperature linear trend, \r 1457\r landslides in, 1800\r precipitation trends, 1458\r projections for change, 1458\r snow cover reduction in, 139\r temperature trends, 1456\r westerly disturbance interactions with, 1978\r Historical period simulations. See also\r Paleoclimate (proxy*) reconstructions\r aerosol effective radiative forcing changes, 857\r [...]"


id: 7f29193fef034b7bd103a9f3a9a2ff12
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 19525
content:
"[...] CMIP reproduction of large-scale surface \r temperature patterns, 431\r greenhouse gas effects, 819\r marine heatwave definition by, 1227\r models participating in CMIP6 DECK, 2101\r net effect on globally averaged surface \r temperature, 188\r Paleoclimate Model Intercomparison Project \r Phase 4 (PMIP4), 957\r Paleoclimate Modelling Intercomparison Project \r Phase III (PMIP3), 298\r pre-satellite dataset for biomass burning \r emissions, 832\r short-lived climate forcer emissions, 885\r use in model scenarios, 1936\r Holocene period\r global mean sea level during, 1294\r greenhouse gas concentrations, 687\r thermokarst processes in, 727\r wetting trend, 329\r Homogenization of data, 1384\r Horn of Africa, 1968, 1970, 1971\r Human-induced climate change\r Antarctic mass balance assessment, 473\r AR5 assessments of effects on water cycle, 1063\r atmosphere, ocean and land warming, 4\r atmospheric circulation, 459\r atmospheric oxidizing capacity, 848\r atmospheric water vapour changes, 451\r [...]"


id: 4afca0e9eacafb2c46416f91f27a8c6d
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 10433
content:
"[...] attribution of change to, 51\r carbon and geochemical cycles, 676\r carbon dioxide as driver of, 158\r cause-effect chain, 1012"


id: c022c79a206f3f11edc17a59432c8817
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 31094
content:
"increases in, 864\r intensity and duration (1950-2011), 1550\r North American changes, 1693, 1828\r projections for, 1554\r Small Islands changes, 1837\r Heavy precipitation and pluvial floods. See also\r Extreme precipitation\r African changes, 1619, 1794\r agricultural and infrastructure impact, 1783\r anthropogenic forcing contribution, 1562\r Asian changes, 1638, 1800\r Australasian changes, 1659, 1808\r Central and South American changes, \r 1672, 1816\r changes since 1950s, 8\r changes with warming, 1518\r daily precipitation change with warming, 1566\r daily precipitation trends (1950-2018), 1560\r detection and event attribution, 1562-1564\r European changes, 1684, 1822\r extreme hourly precipitation, 1564\r factors in heavy precipitation/flooding change, \r 1156\r global scale frequency and intensity, 1560\r increased warming effects on, 16\r mechanism and drivers for, 1557\r model evaluation, 519, 1561-1562\r multi-model mean bias in daily precipitation \r (1979-2014), 1561\r [...]"


id: 2ad409ea001dd39fe7632cce21cb17fd
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 4766
content:
"[...] North American changes, 1697, 1831\r observed trends, 1557-1560\r polar terrestrial changes, 1844\r processes determining, 1072-1073\r projections for, 1518, 1563-1565\r projections for regional changes, 1853\r projections from AR5, 1563\r regional climate information, 1605\r signal emergence, 1854\r Small Islands changes, 1838\r trends in sub-daily extremes, 1558\r Heavy snowfall and ice storms\r Asian changes, 1803\r energy infrastructure and transportation impacts, \r 1785\r European changes, 1825\r North American changes, 1834\r polar terrestrial changes, 1847\r High-cloud altitude feedback, 972\r High-latitude climates\r carbon release from permafrost, 632\r high-warming storylines for, 637\r Northern Hemisphere cooling trend reversal, 438\r Northern Hemisphere land precipitation changes, \r 426\r Northern Hemisphere precipitation (1966-2005), \r 455\r Northern Hemisphere temperature change, 613\r observed extreme winds in, 1598\r ocean freshening and warming effects, 478\r [...]"


id: e49bbfe8a2ee2fa820dbd4d3edda1f71
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 37508
content:
"[...] precipitation projections for, 615\r snow water equivalent changes in, 134\r Southern Hemisphere changes, 426\r Southern Hemisphere wetting, 456"


id: 289fd6839ea71919a496bca7f2a4c143
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 4359
content:
"changes (1750-1850), 192\r climatic impact-driver index changes, 1853\r cold, hot and wet extremes, 1525\r compound event probability with warming, 1519\r compound extreme event changes, 9\r cryosphere, 466-491\r detection and attribution methods, 429\r distribution of aerosol effective radiative forcing, \r 852\r dry season water availability, 1579\r eastern boundary water upwelling, 1243\r effects on modes climate variability, 427\r evolution from theory to fact, 150\r extratropical atmospheric circulation, 606\r extratropical jets, storm tracks and blocking, \r 463-464\r extreme sea level events, 1310\r from land use forcing, 956\r global mean surface air temperature \r (2010-2019), 425\r global monsoon, 461\r global scale flooding, 1569\r global warming from, 187\r global water cycle changes with, 1057\r greenhouse gas level effects in scenarios, 31\r increased CO2, CH4, and N2O in atmosphere, 676\r in current observed warming, 60\r large-scale precipitation changes, 426\r [...]"


id: 4cbab66217bdc22f9e1fd1f410d72cb0
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 10765
content:
"[...] large-scale temperature and precipitation \r changes, 457\r last 2000 years, 161\r limiting cumulative CO2 emissions for, 27-28\r local and regional streamflow change, 456\r long-term context for, 159\r natural climate variability masking, 150\r natural drivers and internal variability \r modulation of, 23\r natural versus human-induced changes, 202\r Northern Hemisphere snow cover, 426\r observed change and human contribution, 1532\r ocean acidification, 677\r ocean heat content increase, 1228\r ocean salinity changes, 1234\r on cryosphere, 426\r precipitation, humidity and streamflow, 449-453\r primary causes and consequences, 153\r probabilistic approaches to, 430\r radiative forcing effects, 11\r regional meteorological droughts, 1577\r since the mid-20th century, 161\r snow cover, 471-552\r SROCC assessment, 188\r stabilization of global temperature increase, \r 97-102\r stratospheric temperatures, 445\r strengthened evidence for, 428\r sudden stratospheric warmings, 466\r surface temperature, 430\r [...]"


id: 49cbd9f0392250bb6b8a48a226baaee4
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 10217
content:
"[...] tropospheric temperature, 443-446\r upper air temperature, 443-445\r upper air temperatures and atmospheric \r circulation, 70-72\r upper troposphere moistening (since 1979), 451"


id: c212344d48eb1f7f4226b07dc109683b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 31441
content:
"direct radiative forcing effects of, 823\r historical abundances and effective radiative \r forcing, 2142\r rates of increase, 304\r total chlorine from, 843\r Hydrofluorocarbons* (HFCs)\r atmospheric lifetime of, 823\r changes in abundances of, 819\r contribution to warming in scenarios \r (2019-2040), 885\r direct radiative forcing effects of, 823\r effects on global surface air temperature, 886\r emissions (1990-2100), 879\r historical abundances and effective radiative \r forcing, 2142\r increases in, 304\r scenario projections for, 882\r significant increases in, 843\r warming effects by scenario, 889\r Hydrological drought*\r African changes, 1624, 1794\r Asia changes, 1644, 1801\r Australasian changes, 1662, 1809\r Central and South America changes, 1675, 1816\r European changes, 1686, 1823\r incremental warming effects on, 15\r North American changes, 1701, 1831\r regional occurrence of, 1575\r Small Islands changes, 1838\r water management use of indices, 1783\r [...]"


id: 3e31c9c7ac07380ac24905acd8af3d0a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 8119
content:
"[...] Hydrological models, flooding consideration \r in, 1569\r Hydrological sensitivity*, 1066-1067\r Hydroxyl (OH) radical\r atmospheric oxidising capacity and, 848\r biogenic volatile organic compounds \r estimations, 831\r global mean trend of (1950-1980), 851\r global OH trends and interannual variability, 849\r interannual variations in global mean, 849\r lifetime of, 849\r lightning impact on, 830\r primary methane sink in troposphere, 835\r response to climate change and variability, 849\r sink for short-lived climate forcers, 825\r source of tropospheric OH, 848\r tropospheric concentration evolution, 850\r tropospheric concentration trends, 819\r Hypoxic* areas (of ocean), 1844"


id: 91b38a2898c05b5177485d32c33ba34c
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 22862
content:
"terrestrial latent heat flux estimation, 939\r urbanization effects on temperature, 1374\r warming compared to ocean surface, 15\r Land-use change*\r anthropogenic CO2 emissions, 676, 687\r carbon fluxes from, 688\r driving changes in water cycle, 1076\r effective radiative forcing from, 310\r effects on Earth's albedo, 310\r effects on Indian summer monsoon, 1979\r estimates of CO2 flux from, 688-689\r forcing from, 1528\r forcing from surface property changes, 956\r heavy precipitation effects of, 1557\r local and regional water cycle responses to, 1057\r local climate effects of, 1374\r local use effects on heavy precipitation, 1557\r over the industrial period, 312\r projections for human-caused changes due to, \r 1119\r reconstruction from pollen data, 310\r Land-water storage* (LWS)\r in sea level budget, 1288\r method and projections for, 1299\r processes and changes in, 1220\r Lapse rate* (LR) feedback\r contribution to warming, 95\r quantification of radiative flux, 969\r [...]"


id: 39f1c3bd3a2c02532db15b0ee513cdf9
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 7406
content:
"[...] upper-level temperature gradient, 579\r Large eddy simulations (LES), 972\r Large-scale atmospheric circulation\r Atlantic Zonal Mode effects over Europe, 2171\r changes and impacts on regional water cycle, \r 1126\r change since the mid-20th century, 291\r continued warming effects on, 1146\r convection changes in, 2164\r drivers for local and regional extremes, 1528\r effects on extreme conditions, 1528\r Hadley and Walker circulations, 335, 459\r impact of biases on regional climate projections, \r 1411\r model projections for, 616\r non-linearities in, 1144-1146\r North Atlantic Oscillation variability, 2156\r short-lived climate forcer alteration of, 893\r short-term change in Greenland Ice Sheet, 1256\r teleconnections and regional variability, 1092\r Large-scale climate change\r atmospheric indicators for, 312\r biospheric indicators for, 314\r changes in indicators (1995-2014), 64\r CMIP reproduction of temperature patterns, 431\r cryospheric indicators for, 313\r [...]"


id: 9140db63057814fbb0b1725d5f05c8e0
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 22759
content:
"[...] forcing and internal variability in, 312\r global to continental or ocean-basin scales of, 153\r human influence on temperature and \r precipitation extremes, 457-459\r indicators of, 312\r main modes of variability, 2155\r marine biosphere changes with warming, 292\r modes of variability in, 314-316\r observations and projections for, 63-67"


id: fe7fce93ee655a85399829b998b699f
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 42147
content:
"oceanic indicators for, 313\r past changes of, 293\r projections for water cycle changes in, 1124\r short-lived climate forcer emissions effects on, \r 820\r simulated and observed change in indicators, 507\r spatial distribution of precipitation extremes, \r 1562\r terrestrial biosphere changes with, 292\r Large-scale modes of variability\r AR5 assessment of, 2155\r circulation effects on, 556\r effects of circulation on water cycle, 1092\r precipitation extremes modulation by, 1557\r Last deglacial transition* (LDT)\r atmospheric CO2 during, 299, 300, 686\r changes in ocean pH during, 715\r climate state in, 295\r global mean sea level during, 1294\r methane release during, 727\r reconstructions for global mean surface \r temperature, 315\r Last Glacial Maximum* (LGM)\r atmospheric CO2 concentration, 299\r climate state in, 295\r equilibrium climate sensitivity estimates from, 1000\r global mean sea level during, 1294\r global mean surface temperature reconstructions \r for, 315\r [...]"


id: 5e6359dc7799135ff2321549463b2db5
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 13898
content:
"[...] hydroxyl radical estimations, 850\r polar amplification in, 986\r terrestrial moisture changes during, 450\r Walker circulation trends, 336\r wetland methane emissions, 684\r Last Interglacial* (LIG) period\r Antarctic ice sheet retreat in, 1269\r atmospheric CO2 concentration, 299\r climate state during, 295\r global mean sea level in, 1293\r temperatures in, 292\r Latin America. See also Central and South \r America\r biomass burning emissions in, 869\r particulate matter emissions sources in, 821\r tropospheric NO2 levels over, 839\r Leaf area index, in terrestrial carbon cycle, 486\r Leaf-level CO2 fertilization, 722\r Least-squares approach (for attribution), 1415\r Length of frost-free period (LFFP), 2155\r Lesser Antilles\r Inter-tropical Convergence Zone effects on \r rainfall, 1991\r precipitation projections for, 2012\r projections for warming over land, 2012\r reference region for, 1991\r Levant, prolonged dry spells in, 449\r Light-absorbing particles* (LAPs) on snow and \r ice, 956\r [...]"


id: 2e83aebd2518e02949b796e69c64bb56
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 5462
content:
"[...] Lightning, contribution to emissions, 830, 859\r Likelihood*\r statement of confidence and uncertainty, \r 169-171\r use in AR6, 38"


id: 1e5f2a612cccbd393558901812596daf
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 2542
content:
"Madagascar (MDG)\r key climatic features, 1967\r tropical cyclones projections, 135, 1795\r Madden-Julian Oscillation* (MJO)\r climate variability and, 2156\r climatic effects in Africa, 1967\r diagnostics for characteristics of, 1395\r evaluation in climate models, 2179\r global impacts through teleconnections, 2179\r influence on South American Monsoon \r variability, 1994\r intra-seasonal East Asian monsoon variability \r and, 2197\r intra-seasonal variability influence of, 1981\r rainfall variability in northern Australia, 1986\r real-time multivariate index, 2177\r regions of influence of, 2178\r tropical intra-seasonal variability time scale, \r 2177\r water cycle effects of, 1104\r MAGICC6 emulator, 963\r MAGICC7 emissions-based emulator, 964\r Marine aerosols, 832\r Marine biosphere/ecosystem\r carbon dioxide removal effects, 100\r changes in, 292\r marine heatwave impacts on, 1227\r Marine cloud brightening* (MCB), for solar \r radiation modification, 624, 628, 860\r Marine heatwaves* (MHWs)\r [...]"


id: 5fb50a93f8814d0a7a11189671087fbf
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 14141
content:
"[...] African changes, 1796\r Asian changes, 1805\r Australasian changes, 1812\r Central and South American changes, 1818\r changes with 2degC warming, 143\r definition and impact of, 1227\r ecosystem and economic impacts of, 1787\r European changes, 1826\r frequency changes, 1214, 1842\r global ocean projections for, 1844\r in tropical ocean and Arctic, 15\r North American changes, 1836\r polar terrestrial changes, 1847\r projections, 188\r regional probability ratio of, 1228\r scenario-based projections, 1227\r signal emergence, 1855\r Small Islands changes, 1841\r trends with future warming, 1227\r Marine ice cliff instability* (MICI)\r effects on global mean sea level, 1217\r in Antarctic mass loss, 1269\r incorporation into projections, 1305"


id: f8aab1ffaed7f44d7bacba877c24d8b3
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 41113
content:
"effective radiative forcing effects, 819, 853, 945\r emissions from permafrost regions, 726\r emissions from wetlands and landfills, 737\r emissions- versus abundance-based forcing \r effects, 855\r estimation of global chemical sink, 835\r estimations of emissions and sinks (2008-2017), \r 705\r feedback sources for, 737\r from human activity, 180\r from permafrost thaw (21st century), 740\r from wildfires, 737\r future abundances projections for, 2144\r global budget, 703, 705\r global warming and temperature-change \r potentials for, 927\r growth rate changes, 303, 676, 701\r historical abundances and effective radiative \r forcing, 2141\r in current short-lived climate forcer emissions, 821\r land biospheric sources and sinks, 704\r lifetime assessment of, 823, 835, 836\r lightning effects on lifetime of, 830\r methane perturbation lifetime, 836\r methods for removal from atmosphere, 765\r modelled wetland emissions anomalies, 707\r ocean and inland water emissions and sinks, 704\r [...]"


id: 88d9317678a0833379dbeb0daddbbd3d
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 21239
content:
"[...] pre-industrial sources for, 684\r pulsed geologic release of, 686\r radiative efficiency change (since 2011), 947\r rate of atmospheric change in last century, 686\r recent concentrations of, 8\r reduction of emissions for mitigation, 825\r regional warming projections for, 888\r release from clathrates, 740\r response to future warming, 677\r role in feedback processes, 677\r sources and sinks, 706\r trees and wetland forests contribution to, 704\r trends, variability and budget, 700\r tropospheric adjustment effects on effective \r radiative forcing, 925\r tropospheric OH estimates from paleo time \r scales, 850\r uptake from soil, 835\r wetland emissions of, 684\r ethyl chloroform (MCF)\r constraint of methane lifetime assessment, 835\r in estimation of global OH abundance, 849\r crobial/biogenic processes\r anaerobic ammonium oxidation, 719\r methane uptake by soil, 704\r nitrification/denitrification of soil, 830\r ddle East. See also Arabian Peninsula and\r West Central Asia\r [...]"


id: 40e0b5e02ae495733b0aa1024b620abc
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 8601
content:
"[...] Atlantic Multi-decadal Variability effects in, 2177\r natural sources of surface ozone in, 869\r NO2 trends over, 839\r particulate matter emissions sources in, 821\r surface ozone and particulate matter projections, \r 882\r d-Holocene* (MH), atmospheric CO2\r concentrations, 299"


id: 946aac445c379853aeb76d5522c77370
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 23320
content:
"coastal and oceanic climatic impact-driver \r indices change, 1834\r confidence in climatic impact-driver projections \r for, 1835\r current short-lived climate forcers, CO2, and NO2\r emissions, 821\r distribution of short-lived climate forcers over, \r 819\r drought trends and projections for changes by \r warming levels, 1701\r emissions with fossil fuel use, 829\r extreme precipitation changes, 1560, 1566\r fire weather exposure and vulnerability, 1832\r global surface temperature trends and \r projections for, 2008\r greenhouse gas emissions for, 713\r hail changes for, 1834\r heat and cold changes for, 141\r heat stress indicators in, 1830\r heavy precipitation trends and projections by \r warming levels, 1697\r lake-effect snowstorms projections for, 2008\r mean surface air temperature and precipitation \r changes, 2007\r model performance assessment, 2005\r NO2 decreases, 839\r non-methane volatile organic compound trends \r in, 828, 842\r Pacific Decadal Variability effects on, 2174\r [...]"


id: c19db600cd53191633c6d3752657e683
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 31368
content:
"[...] particulate matter emissions sources in, 821\r pattern of changes in climatic impact-drivers, \r 1832\r precipitation changes with Atlantic Multi\u0002decadal Variability, 2177\r precipitation trends and projections for, 2008\r previous IPCC assessments, 2004\r projections for hot and cold extremes for, 1556\r projections for in climatic impact-driver indices, \r 1829\r rain-on-snow event evolution in 21st century, \r 2008\r regional climate features in, 2004\r regional climate model testing in, 2005\r regional relative sea level projections, 141, 1834\r regional sea level and shoreline retreat, 141\r regional surface air temperature signal \r emergence, 2004\r regional wind changes (2degC warming), 141\r sand and dust storm shift toward extremes, 1833\r shoreline progradation in, 142\r short-lived climate forcer effects in, 888\r snow and ice changes, 141, 1833-1834\r snowfall transition zone shift in, 2008\r snow mass trends for, 2005\r snow-related projections for, 2008\r [...]"


id: aba41e16bf5970c7727bdefd5a3a8188
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 27436
content:
"[...] snow water equivalent projections for high\u0002latitude climates, 2009\r solar radiation projections for, 1791\r south-western drought attribution to \r anthropogenic forcing, 1421\r subregional precipitation projections, 2007\r subregion reanalysis/historical simulations, 1943\r sulphate aerosol trends, 846-846"


id: cac273714a555837f1e666d3a43e0d4d
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 33015
content:
"ocean, inland water body and estuary emissions, \r 710\r primary natural production of, 708\r production in the ocean, 737\r projected trends for oceanic emissions, 719\r radiative efficiency changes (since 2011), 947\r recent concentrations of, 8\r response of future warming, 677\r terrestrial ecosystems release of, 737\r tropospheric adjustment effects on forcing, 925\r N-limited forests and grasslands, reactive nitrogen \r deposition in, 857\r NOAA National Centers for Environmental \r Prediction (NCEP)/National Center for \r Atmospheric Research (NCAR) reanalysis, \r 213\r Noise-induced tipping, 202\r Non-CO2 biogeochemical feedbacks, 975\r Non-CO2 greenhouse gases\r biogeochemical feedbacks, 857, 860, 975\r emissions from agriculture, 866\r estimates from Earth system models, 820\r Non-methane volatile organic compounds* \r (NMVOCs)\r anthropogenic emissions sources, 828\r anthropogenic light alkanes (C2-C5) trend, 841\r effective radiative forcing effects (1750-2019), \r 819\r [...]"


id: 5d8f9245f4a5fc663d8e3ab5536d6a25
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 13745
content:
"[...] indirect climate forcing by, 823\r net global emissions-based effective radiative \r forcing of, 855\r North Africa. See also Mediterranean (MED) \r region.\r anthropogenic climate forcing in, 1969\r Atlantic Multi-decadal Variability effects in, 2177\r drought duration and intensity, 1119\r precipitation changes over, 1968, 1971\r temperature projections for, 1971\r wind projections for, 135\r North America\r aerosol effective radiative forcing over, 852\r agricultural and ecological droughts, 1831\r air temperature and precipitation for subregions \r of, 1943\r annual maximum snow depth for cold-season \r periods, 2005\r annual mean surface air temperature change \r (2070-2099), 2008\r annual precipitation trends, 2004\r anthropogenic emissions effects in, 2004\r anthropogenic signal detection over, 2004\r assessment and synthesis of projections, 2006\r assessment, observations, trends, and \r attribution, 2004\r Atlas, 2004-2014\r atmospheric sulphur dioxide reduction \r (2000-2015), 843\r [...]"


id: 8c26b0a84c05cb30c68d2549fde88899
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 21829
content:
"[...] biomass burning emissions in, 869\r black carbon estimates of, 848\r carbonaceous aerosol emissions in, 828\r climate changes, 141, 1828, 1830\r climatic reference regions, 2004"


id: 60e1a2b3c8a8092c1a9d60792eb17d7f
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 14342
content:
"summary of changes, 126, 141, 2008\r surface ozone concentration changes in, 882\r temperature changes in, 1550\r temperature extreme trends and projections by \r warming levels, 1693\r trends in coastal climatic impact-drivers, 1836\r wet and dry regional changes in, 141\r wind changes, 141, 1832\r North American monsoon* (NAmerM)\r changes in, 1098, 1130\r Gulf of California low-level jet effects on, 2198\r history and definition of, 2198\r seasonal climate influence of, 1991\r warming trends in, 1994\r North American Regional Climate Change \r Assessment Program (NARCCAP), 2005\r North Asia\r assessment and synthesis of projections, 1977\r changes with 2degC global warming, 138\r greenhouse gas emissions for, 713\r model performance assessment, 1977\r observations, trends and attribution, 1976\r precipitation and temperature summary, 1978\r previous assessment findings, 1976\r reference regions in, 1975, 1976\r regional climate and findings, 1975\r seasonal snow duration and extent in, 139\r [...]"


id: 58cc03d2c74a247880f43ad35eb455fc
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 12866
content:
"[...] snow season trends (1980-2015), 1976\r temperature change (2080-2099), 1978\r temperature reanalysis (1976-2010), 1977\r North Atlantic Deep Water (NADW)\r freshening trends and decadal variability in, \r 1235\r in Circumpolar Deep Water formation, 1236\r internal variability in, 1230\r warming projections for, 1233\r North Atlantic Ocean (NAO)\r acidification in subtropical and equatorial \r regions, 489\r biases in model simulation of storm tracks, 464\r jet stream changes, 2158\r mode of large-scale variability, 2156\r redistribution of ocean heat in basin, 1231\r regional mean relative sea level change in, 1826\r salinity projections for, 1842\r sea level change signal in, 1290\r shift in blocking anticyclones, 1101\r subpolar gyre warming projections, 1223\r subpolar warming in, 1222, 1229\r subtropical gyre, 1320\r thermohaline circulation in, 202\r tripole pattern, 2176\r wind stress changes in, 1225\r North Atlantic Oscillation*/Northern Annular \r Mode* (NAO/NAM)\r [...]"


id: 8b54544ec967ae401e9676edf3348f00
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 21675
content:
"[...] Arabian Peninsula climate influence by, 1983\r boreal wintertime modes, 2157\r climate variability and, 2156\r CMIP scenario simulations for, 578\r correlation with Northern Annular Mode, 489\r cryosphere-atmosphere coupling and variability \r in, 2158\r drivers of2156"


id: 1386e871068031f8868be29fc961b2c9
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 648
content:
"emissions scenario dependence of, 677\r growth of sink stops (2050), 723\r increasing CO2 emissions effects on, 19\r near-term changes with high emissions, 587\r ocean carbon flux scenario projections, 587\r response to the growing ocean sink, 676\r Ocean circulation/currents. See also Atlantic \r Meridional Overturning Circulation* \r (AMOC)\r Antarctic Circumpolar Current, 485, 1239, 1240\r Atlantic Meridional Overturning Circulation, 483\r 1214, 1236, 1321\r coastal systems and marginal seas, 1244\r Eastern boundary upwelling systems, 1214, \r 1243-1244\r eddy exchanges, 1234\r effects on air-sea fluxes, 745\r Gulf Stream, 1320\r gyres, western boundary currents, and inter\u0002basin exchange, 1241-1243\r in heat and freshwater transport, 483-487\r pattern of carbon dioxide uptake/storage, 744\r Southern Ocean, 485, 1239-1240\r tropical oceans, 1241\r western boundary currents, 143, 1222, 1241\r Ocean-climate feedback, 719\r Ocean CO2 sink (Socean)\r modelled evolution of (1850-2100), 734\r [...]"


id: c020d33b0725d4f869d0e0fa22d8d17f
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 31092
content:
"[...] multi-decadal trends for, 692\r pCO2-based reconstructions (1960-2019), 691\r scenario trajectories for, 677\r solar radiation modification effects on, 679\r Ocean deoxygenation*\r anthropogenic CO2 absorption, 714-718\r areas of signal emergence for, 1855\r changes with 2degC warming, 143\r drivers of, 714, 720\r effects on N2O flux to atmosphere, 719\r heterogeneity in coastal ocean and shoreline, \r 720, 722\r implications for greenhouse gases, 717\r in tropical oceans, 719\r in upper ocean regions, 5\r low oxygen zone expansion, 143\r marine ecosystem effects of, 1787\r oxygen concentration projections with high \r emissions, 1842\r paleoclimate and pre-industrial, 714\r projections of subsurface oxygen loss, 42\r projection with ocean warming, 677\r reduction of anthropogenic nutrient inputs, 722\r spatial and temporal variability in surface \r processes, 720\r spatial characteristics of response to \r atmospheric CO2, 721\r total N2O production in ocean, 719\r Ocean dynamic sea level change*\r [...]"


id: 77a3cadda4073be3faf6d74c4ca98d0a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18253
content:
"[...] contribution to relative sea level change, 1304\r detectable signal for, 1290\r Ocean fluxes, projections with high emissions, \r 1224\r Ocean heat content (OHC)\r air-sea flux inferred from, 1225"


id: 39205a59a54dda6f229b9d7a1b464e65
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 7258
content:
"evidence of warming from, 290\r for atmosphere, land and hydrological cycle, 209\r historical simulations, 41\r ship-based sampling for ocean temperatures, \r 1230\r sources of uncertainty in, 293\r threats to capacity or continuity, 212\r use in modelling to improve projections, 563\r use in simulations and scenarios, 446, 819, 2062\r Ocean*\r absorption of anthropogenic CO2 emissions, 714\r acidification and deoxygenation of, 677\r acidification of, 161\r biogeochemical changes in, 488\r brominated and iodinated species from, 843\r carbon uptake and mitigation levels, 723\r changes in geochemistry, 292\r changes in heat and salinity, 1228-1234\r climatic impact-driver indices for open and \r deep ocean, 1841\r continued warming of, 447\r dynamic sea level, 1246, 1247, 1300\r ecosystem impacts of temperature shift, 1786\r expansion of observations, 209\r human influence on, 426, 473-516\r initialized predictions/projections for, 563\r in physical system, 157\r integration of paleo-oceanographic data with \r [...]"


id: df6252ee75275815208e8284c6ece33
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 36546
content:
"[...] modelling, 47\r interior change in, 717\r manifestation of deep warming in, 1233\r mean fluxes with high emissions, 1224\r mean temperature shifts, 1786\r model development since AR5, 473\r N2O emissions from ocean, 737\r observational capacity for, 151\r ocean-related quantities for climate change, 1966\r oxygen concentration changes, 488\r paleo-evidence and recently observed changes \r in, 74-76\r past and future changes, 75\r projected N2O emissions trends, 719\r projection of stressors, 488-489\r projections for ocean warming (by 2100), 1232\r properties for prediction of variability, 563, 564\r reanalyses improvements, 214\r recent global changes in, 291\r sea surface temperature increase signal, 1855\r Southern Hemisphere subsurface temperature \r increase, 1235\r SROCC warming assessment, 187, 188\r storage and transport of heat, carbon, and \r freshwater, 473\r surface changes, 1221-1234\r surface-intensified warming, 1214\r temperature in model evaluation, 473\r [...]"


id: bcde21caae29c81bb42d055af8fa9d9d
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 30469
content:
"[...] upper ocean historical trends and spatial \r characteristics, 715\r upper ocean warming, 5\r uptake of anthropogenic CO2 with RCPs, 576\r warming of, 158\r Ocean acidification*"


id: 7da9cd3f0aba706e97692910f707e2a5
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 19280
content:
"anthropogenic CO2 driving of, 427, 489, 677, \r 714-718\r Asian changes, 1804\r Australasian changes, 1813\r biological processes in, 720\r carbon dioxide removal effects on, 29, 100\r Central and South American changes, 1819\r changes with 2degC global warming, 143\r CO2 emissions driving of, 5\r continued growth of, 720\r effects of ventilation processes, 717\r European changes, 1827\r eutrophication effects on, 721\r extent in ocean interior, 717\r future projections for, 719, 1790\r global average surface ocean pH, 577\r heterogeneity in coastal ocean and shoreline, \r 720\r long-term change of annual and zonal ocean \r pH, 609\r marine ecosystem effects of, 1787\r metabolic CO2 release in intermediate waters, 717\r model-simulated long-term trend of, 608\r multi-decadal pH trends in surface layer, 716\r North American changes, 1835\r observations in recent decades, 716\r of ocean surface waters with increased \r atmospheric CO2, 717\r paleoclimate and pre-industrial, 714\r pH in scenarios, 135\r [...]"


id: 6b96d548fd2abc567942f076dc0f09a4
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 16234
content:
"[...] pH time series reconstruction, 715\r pre-industrial spread from surface to interior, 718\r projections for signal emergence, 1855\r reconstructed centennial trends in, 715\r reconstructions of paleo ocean pH, 211\r regional coastal response to, 721\r regional mean surface pH change, 1842\r regional signal emergence, 1855\r reversal by CO2 removal, 720\r Small Islands changes, 1840\r solar radiation modification effects on, 679, 768\r spatial and temporal variability in surface \r processes, 720\r subpolar and polar zone changes, 716\r subtropical ocean changes in pH, 716\r surface ocean pH simulations (RCP/ SSP), 577\r ean alkalinization*, for carbon sequestration, \r 764\r ean-atmosphere-land biosphere system, 684\r ean carbon fluxes\r 10-, 20- and 30-year trends (2021-2040), 587\r CO2 storage in ocean, 691-694\r multi-decadal trends in, 691\r regional and global variability, 693\r ean carbon-heat nexus\r changes and impact of ocean processes on, 745\r climate change commitment and, 743\r [...]"


id: 8b6f3839b4adc4028f57624cca651632
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 21691
content:
"[...] drivers and change in, 744\r ean carbon uptake and storage\r biological drivers of future uptake, 729\r biological processes in CMIP5 and CMIP6, 729\r climate effects on future uptake, 728\r drivers of weakening CO2 uptake723"


id: 2aca10dd9a5368f1eb8169a0badf61ec
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 4756
content:
"effective radiative forcing from, 311\r effective radiative forcing from precursors, 830\r effect of dedicated air pollution or climate policy \r on, 891\r effects of precursor emissions abatement, 883\r effects of solar radiation modification on surface, \r 769\r effects on carbon dioxide uptake and methane \r emissions, 857\r effects on photosynthesis and plant growth, 857\r energy and land transportation sector \r contribution to, 821\r estimates of tropospheric burden of, 838\r evolution of surface concentrations of, 882\r forcing effects on Southern Annular Mode, 427\r global mean tropospheric burden (1850-2100), \r 837\r global pre-industrial abundance of, 837\r global tropospheric budget for, 837\r impact of lightning on, 830\r loss in stratosphere, 307\r meteorology driven feedbacks on climate, 859\r methane mitigation effects of surface, 875\r photo-oxidation of biogenic volatile organic \r compound emissions in budget, 831\r precursor emissions in SSPs, 30\r production of tropospheric, 848\r [...]"


id: ac952cb8e7f36f43219761e465cdb4d8
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 27606
content:
"[...] projections for surface change (2015-2100), 883\r recovery and greenhouse gas effects on \r Southern Annular Mode, 609\r regional surface concentrations from natural \r surfaces, 869\r stratosphere depletion of, 5\r stratospheric levels, 306, 838\r surface and tropospheric trends, 308\r surface concentration change with warming, 862\r temperature effects in polluted areas, 864\r total tropospheric column, 836\r transportation contribution to surface, 868\r tropospheric, 307-308, 836\r tropospheric production with methane, 946\r vapour abundances and temperature effects on, \r 861\r one-depleting substances* (ODS)\r atmospheric mixing ratios of, 304"


id: 5c64f148406f036e1734c1e21bab972a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 13510
content:
"eoclimate Modelling Intercomparison \r Project Phase 4 (PMIP4), 957\r eoclimate Modelling Intercomparison \r Project Phase III (PMIP3), 298\r eoclimate (proxy) reconstructions. See also\r Historical period simulations\r advances since AR5, 211\r Atlantic Multi-decadal Variability-related signal \r reconstructions, 2177\r avalanche in the Indian Himalayas, 1803\r Cenozoic CO2 record from marine sediment, 683\r centennial- to millennial-scale variations, 160\r CH4 and N2O emissions under glacial climate \r conditions, 685\r climate system evidence from, 45\r context for drought projections, 1120\r cooling in the Northern Hemisphere, 161\r drought reconstruction and models, 1121\r equatorial warm pool gradient, 989\r equilibrium climate sensitivity estimates, 11, \r 999, 1001\r equilibrium sea surface temperature patterns, \r 1223\r estimates of OH in last glacial maximum, 850\r feedbacks between climate and carbon cycle, \r 683\r fluctuations of Indian Ocean Basin/Indian Ocean \r Dipole, 2167\r [...]"


id: e8445f23c87a12eb7f961ad04fd477ed
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 38198
content:
"[...] for Paleocene-Eocene Thermal Maximum, 714\r global hydrological cycle perspectives, 329\r global mean sea level over 20th century, 1287\r global mean surface temperature estimation, \r 294\r global monsoon variations with forcing, 461\r global surface air temperature extension to \r 2300, 633\r greening of the Sahara and Sahel, 1150\r ice core proxies for carbon-climate feedbacks, \r 684\r impacts of eruptions on contemporary society, \r 593\r improvements in radiocarbon calibration \r datasets, 211\r in AR5 and AR6, 154\r Indian Ocean Dipole and Indian Ocean basin, \r 2168\r isotope analysis of continental and marine \r sediments, 298\r key indicators for, 159\r longitudinal sea surface temperature gradient \r changes in, 988\r millennial rates of CO2 concentration change, \r 686\r non-methane volatile organic compounds, 842\r North Atlantic Oscillation index, 2159\r ocean heat content, 1233\r ocean pH change with atmospheric CO2\r concentrations, 715\r of Atlantic Meridional Mode and Atlantic Zonal \r [...]"


id: 792effa9d0ec0372c7555d7936df7620
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18512
content:
"[...] Mode, 2171\r of El Nino-Southern Oscillation, 2164\r of ice-sheet mass response, 47\r Pacific Decadal Variability reconstructions, 2174"


id: 6d755f824344de2fa0943688f5243c1e
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 16524
content:
"Phosphorus availability, effects on carbon \r storage response in plants, 723\r Photosynthesis*\r acclimation to long-term CO2 exposure, 722\r control of land CO2 sink, 694\r effects of solar radiation modification on, 768\r feedback on anthropogenic climate change, 723\r ozone effects on, 857\r radiation fluxes effects on, 1787\r Photosynthetically active radiation (PAR), 1788\r Physical emulators and simple climate models, \r 219\r Phytoplankton, 292, 729\r Pinatubo (1991) volcanic eruption, 327, 629\r Planck response (P), 95, 926, 932, 967, 968\r Planetary albedo, 970\r Plant physiology\r atmospheric CO2 effects on, 1580\r CO2 uptake relation to water loss, 722\r effects of climate variability and warming on, \r 724\r effects of elevated CO2 on, 722\r phosphorus and nitrogen limitation effects, 723\r temperature versus vapour pressure deficit \r effects on, 724\r Pliocene Model Intercomparison Project Phase \r 1 (PlioMIP1) models, 989\r Pluvial floods, 1783. See also Heavy precipitation \r and pluvial floods\r [...]"


id: 94e8f1c34caade8819a11aee1d22e9f8
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 23403
content:
"[...] Polar amplification*\r Arctic versus global average for warming, 596\r changes with 2degC warming, 142\r CO2 emissions and, 985\r confidence in occurrence of, 987\r critical processes driving, 982-984\r driving processes for, 982\r in paleo proxies and models, 986\r mid-Pliocene Warm Period, 1293\r overall assessment, 987\r paleoclimate model simulation of, 985\r projections for Arctic heat extremes, 1844\r Southern and Northern Hemisphere projections, \r 597\r Polar regions. See also Antarctic; Arctic\r Arctic Oscillation/North Annular Mode and \r strength of vortex, 2156\r Atlas, 2016-2028\r changes for, 1932\r climatic impact-driver changes (2degC warming), \r 142\r heat and cold changes (2degC warming), 142\r heat and cold changes in, 1844\r projections for, 2016-2058\r recent and future climatic changes, 1844\r regional annual mean surface air temperature \r and precipitation changes, 2016\r regional subdivisions of, 2016\r relative sea level changes, 1847\r remote effects of vortex collapse, 2158\r [...]"


id: dcec52b9a09a2fe681af0e9c7884801d
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 36131
content:
"[...] surface warming amplification of, 927\r temperature, precipitation and mass balance in, \r 2016-2018\r terrestrial snow and ice changes, 1845"


id: e62b5c6338499a7b04d06db26db15c78
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 37796
content:
"distribution of major aerosol components, 844\r effects of climate change on, 863\r emissions source-sector attribution of regional \r population, 871\r evolution of surface concentrations of, 882\r in air pollution/quality simulation, 861\r in future air quality, 820\r in nitrate formation, 846\r regional changes in surface concentrations, 883\r residential and commercial sector contribution, \r 821\r typical atmospheric lifetime of, 863\r warming effects on concentrations, 863\r wet deposition of, 863\r Particulate organic carbon (POC), 729\r Passive microwave satellite observations, 1980\r Pathway independence, 743\r Pattern scaling\r climate change representation, 565\r mid-latitude atmospheric circulation and global \r surface air temperature, 616\r observational constraints on the magnitude, 991\r radiation changes affected by, 990\r Peatland restoration, 763\r Perfect-prognosis models, 1391\r Perfluorocarbons (PFCs), 304, 2141\r Permafrost*\r Asian changes, 138, 1802, 1979 \r [...]"


id: 6227edc58c10278c393e6a4861187222
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 14542
content:
"[...] biogenic emissions with thaw, 740\r carbon accumulation after thawing of, 727\r carbon content of Arctic and boreal, 188\r carbon feedback projections to 2100-2300, 728\r carbon feedbacks to climate, 726-730\r carbon release from thawing, 677\r Central and South American changes, 1818\r CH4-climate feedback estimation, 728\r change from sink to source of CO2, 727\r East Siberia changes, 1976\r European changes, 1825\r expectations of emissions with thawing, 727\r infrastructure hazards with thaw, 1785\r in remaining carbon budgets, 747\r methane release from thaw, 728\r model evaluation, 1281-1283\r near-surface volume loss of, 1216\r North America changes, 1833\r observed and reconstructed changes for, \r 1280-1281\r observed versus simulated extent of by warming \r level, 1282\r polar regions changes, 1845-1847 \r projections for changes in, 727, 1282\r time scales of irreversibility in thawing, 21\r uncertainty in scaling carbon feedback with \r warming, 728\r warming effects on, 16\r [...]"


id: 6e3806ab95ebf35b214c07f24e2a8f4
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 16657
content:
"[...] Permian era, CO2 proxy estimates for, 299\r Peroxy radical recycling, 848\r Perturbation lifetime (fpert), 836\r Perturbed-parameter ensemble (PPE) \r modelling, 222, 562\r Perturbed-physics ensembles for regional-scale \r attribution, 1416"


id: 320f13a22a7fc7731c7f552dc1be9115
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 6066
content:
"Reanalysis*\r applications of, 215\r as evidence in assessments, 151\r atmospheric, 213\r intercomparison of models, 213\r model output constrained by observations, 212\r ocean, 214\r of pre-instrumental era, 214\r precipitation minus evaporation, 334\r sparse input of instrumental era, 214\r Reasons for Concern* (RFCs)\r AR6 WGII assessment of hazards, 1771\r ecosystem impact in Siberia, 1976\r risk with climate change consequences, 1857\r risk with low-likelihood outcomes, 199\r Reduced-complexity climate model, 962. See\r Climate model emulators\r Reduced Complexity Model Intercomparison \r Project (RCMIP), 963\r Reference Land and Ocean Regions, 208\r Reforestation*. See Afforestation*/\r reforestation*\r Regional climate\r abrupt changes with anthropogenic \r perturbations, 678\r actor and community values in, 1430\r aerosol forcing effects on, 1528\r anthropogenic change and internal variability \r interplay, 1413\r anthropogenic signal robustness and emergence, \r 1423-1426\r [...]"


id: c31f5a5f695e8930af4a8c93ba90e583
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 31601
content:
"[...] assessing response to external forcing, 1414\r assessment of, 172, 1435\r Atlantic Multi-decadal Variability influence, 2176\r attribution approaches for, 1415\r attribution examples for, 1416-1422\r attribution of precipitation and temperature \r changes, 1422\r challenges for assessment, 1384\r challenges in information construction, 1459\r changes in climate extremes in, 1517\r classes used in AR6, 208\r combining approaches for constructing, \r 1427-1429\r commonly used indices and thresholds for \r impact drivers, 1788-1792\r confidence assessment of information, 1436\r conflicting information from different sources, \r 1428\r constructing user-relevant information, 1429\r data scarcity, 1385\r definition of regions, 1371\r derived gridded datasets for, 1386\r derived observational product use, 1383\r distillation and synthesis of independent \r assessments, 1436\r distillation of information for, 1375\r drivers of variability and change, 113-116\r droughts, 1605\r [...]"


id: 34eac580974538d4e24c173a1a66dc9e
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 6552
content:
"[...] El Nino-Southern Oscillation impact on, 2167\r extreme event interactions, 1529\r extreme precipitation modulation, 1557\r fitness for purpose of information, 1436"


id: aa8cba29beab729e24aa467299bfe4a9
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 27228
content:
"long-term seasonality changes, 1115\r Madden-Julian Oscillation simulated changes \r and, 1105\r model skill for multi-year/decadal forecasts, 564\r near-term change of seasonal mean, 585\r near-term projections for changes in, 556\r non-linearities in, 1144-1146\r Northern Hemisphere high-latitudes change \r (1966-2005), 455\r Northern Hemisphere temperate land regions, \r 158\r observed and simulated trends over land, 455\r precipitation and precipitation-\r evapotranspiration indices (1951-2016), 1574\r projections for increases by scenarios, 573\r projections for seasonal patterns of, 584\r reconstruction Mid-Holocene trends, 449\r regional detection of changes, 1414\r regions with recorded deficits, 1573\r scale of change emergence, 1542\r scenario-based projections and near-term \r information, 556\r seasonality change projections for, 1058\r signal emergence for increase, 1855\r spatial patterns of change with warming, 615\r tropical mean annual anomalies, 454\r uncertainties in regional changes, 1124\r [...]"


id: c8807548cfc39750bf9a2554fea87900
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 32579
content:
"[...] volcanic eruption effects on, 1144\r wet removal efficiency for pollutants, 861\r with tropical cyclones, 1132\r cipitation deficits\r detection and attribution of deficits, 1577\r jif9"


id: 4a541b96791948f69cbaaa3325d2da00
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 10316
content:
"Radiative forcing* (RF)\r anthropogenic sulphur dioxide emissions \r impact on, 845\r assessment by IPCC reports, 180\r as uncertainty source, 196\r aviation climate forcing and, 867\r by volcanic activity, 958\r CMIP models for, 2100\r combined effects of all, 926\r direct forcing by short-lived climate forcers, 823\r efficiencies of background compounds, 1012\r energy accumulation in Earth system, 90-93\r equilibrium climate sensitivity estimation, 11\r evolution with CO2 concentration increase, 995\r forcing from solar and volcanic activity \r (1750-1900), 150\r from contrails, 866\r historical and abrupt4xCO2 relationships \r in models, 992\r implications of COVID-19 restrictions, 876\r labels on Shared Socio-economic Pathways \r and RCP, 618\r major changes in forcing since AR5, 959\r RCP and SSP comparisons of, 562\r solar irradiance (1750-2011), 296\r Radioactive fallout, 180\r Radiocarbon (14C) studies, attribution of \r increasing CO2 levels, 180\r Radio occultation (RO), 327\r Rainfall See Precipitation\r [...]"


id: e9a2d320d695d3c877d3b19949275e6b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 38456
content:
"[...] Randolph Glacier Inventory (RGI), 1273\r RAPID Array measurements, 1236, 1238\r RAPID-MOCHA array, 483\r Reactive nitrogen (Nr) deposition\r effects of, 857\r effects on natural CO2 sinks, 857\r in N-limited forests and grasslands, 857\r Realised added value, 1990\r Real-time multivariate Madden-Julian \r Oscillation (RMM) index, 2177"


id: adaef747276a9dbbfadedcd53710837a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 27800
content:
"using models for constructing, 1388\r weather and climate prediction framework, 1372\r gional Climate Centres (RCCs), 1862\r gional climate change\r Africa, summary of changes, 122, 135, 1971\r agricultural and ecological droughts, 1519\r Antarctic, summary of changes, 127, 142, 2025\r anthropogenic and biomass burning emissions \r (1850-2100), 880\r Arctic, summary of changes, 127, 142, 2022\r Asia, summary of changes, 123, 138, 1986\r assessing change and Interactive Atlas, 111-112\r attribution of observed changes in, 11\r Australasia, summary of changes, 124, 139, 1990\r Central and South America, summary of changes, \r 125, 140, 1991\r changes daily maximum temperature for land \r area by scenarios, 1524\r climate information for risk assessment, 40\r climatic impact-driver indices for, 2155, 2212\r data integration in Atlas, 1934\r defined, 1370\r direct anthropogenic influence on water cycle, \r 1075\r distillation and climate services, 110\r effects of further warming on, 24-25\r [...]"


id: f53ac612f3f215bae3a86b54a273ff48
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 40511
content:
"[...] emergence of extreme changes, 1542\r Europe, summary of changes, 126, 140, 2003\r generation and communication of information, \r 107\r impact and risk assessment, 57-59\r implications for extremes and climatic impact\u0002drivers, 120-124\r information for, 1369\r information on extremes, 1604-1607\r large-scale teleconnection and anomalies in, \r 2155\r linking global to regional climate change, \r 1363-1512\r mean relative sea level rise through 21st \r century, 25\r methods for attribution of, 1414\r North America, summary of changes, 126, 141, \r 2008\r observational data and reanalyses used in, \r 1938-1941\r observed and attributable changes, 109\r precipitation amount, frequency, and intensity \r changes, 1081-1083\r projections for water cycle changes, 1124\r regional and local processes in cryosphere, 1221\r remote influences on, 2155\r responses to short-lived climate forcer \r mitigation, 885\r short-lived climate forcer emissions effects on, \r 887\r Small Islands, summary of changes, 127, 142, \r [...]"


id: 39e74dae52013534a02b81ad19e1a779
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 7396
content:
"[...] 2012\r spatial and temporal scales for, 1371-1372\r temperature at year 100 of abrupt4xCO2\r simulations, 983\r tipping points and abrupt changes in, 202"


id: 153745d6fd1b2b4a2eb41a3f3ba53869
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 950
content:
"summary of climatic impact-driver hazards, 1858\r egional climate models* (RCM)\r anthropogenic signal emergence, 1367\r assessment of projection uncertainties, 1367\r assumptions for simulations, 1389\r atmosphere-only general circulation models for, \r 1389, 1397\r components of, 1390\r contributing to CORDEX experiment, 2090\r detection and attribution studies and observed \r emergence analysis, 1367\r ensemble use to assess uncertainty, 1410\r extreme rainfall event capture by, 1562\r fitness of climate models for projections, 1367, \r 1405\r for downscaling global simulation, 1140\r general circulation models for, 1396\r global climate model use for, 1389\r horizontal resolution for, 1389-1390\r improving the representation of regional climate, \r 1367\r observation types used in, 1382\r participating in CORDEX, 2089\r performance for climate and change simulations, \r 1406\r projections for change in summer precipitation, \r 1405\r projections for temperature-related extremes \r in, 1555\r [...]"


id: 7028a26fedac71764cfd328846ad2cff
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 16987
content:
"[...] regional responses to El Nino-Southern \r Oscillation, 1398\r simulating large-scale phenomena and \r teleconnections, 1396\r simulation of climatology extremes, 1551\r simulations and models used in CORDEX, 2099"


id: 465f2d9bd11816e882a386ba25741a1b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 9604
content:
"Asian changes, 1800\r Australasian changes, 1808\r calculation of index, 2210\r Central and South American changes, 1815\r European regional changes, 1822\r extreme river flow trends, 1569\r index of, 2210\r infrastructure and agricultural impact of, 1783\r North American changes, 141, 1830\r projections for, 1518\r regional projections for, 1853\r Small Islands changes, 1837\r spatial variability in changes, 1851\r Robustness/uncertainty*\r analysing climate change signals &, 1953\r climate change display in maps, 1948\r display and quantification for models, 567\r display in maps, 1945-1950\r map representation of projections, 1949\r multi-model ensembles for assessment, 561, 568\r of regional anthropogenic signals, 1423\r tropospheric temperature change, 599\r Rossby Centre Regional Climate Model (RCA4), \r 1993\r Rossby waves\r Arctic amplification effects on, 1380\r extratropical influence of Madden-Julian \r Oscillation, 2179\r large-scale, 2164\r mechanism, 2158\r [...]"


id: f31c91d8d431b8a83cbf5efcb37afe0a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 40155
content:
"[...] tropical-extratropical teleconnections, 2164\r Walker circulation alteration and, 2174\r zonal temperature anomalies and, 2172\r Runoff*, streamflow and flooding\r Atlantic Multi-decadal Variability regional effects \r on, 2177\r changes in, 1086\r from glaciers, 1122\r projections for, 1117\r seasonal mean runoff projections, 1118\r with increased warming, 1119\r Russian Arctic (RAR), 1971, 2016, 2022\r Russian Far East (RFE)\r climate features of, 1975\r El Nino-Southern Oscillation influence, 1976\r Pacific Decadal Variability influence, 1976\r precipitation trends in, 1976\r snow depth trends in, 1977\r warning trends in (1976-2014), 1976, 1978"


id: fbcb0132bbf17e48f5a599f5dadc48f1
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 41668
content:
"assessed budget and uncertainties in, 753\r components contributing to, 750, 751\r cumulative CO2 emissions relationship to surface \r air temperature increase, 750\r developments for climate stabilization, 770\r estimate of CO2 levels for warming stabilization, \r 97-99, 189, 681, 742\r estimates and uncertainties, 98, 752\r framework and approaches for, 749\r historical warming in assessment of, 751\r importance of permafrost in, 747\r methodological advancements for estimation, \r 754\r non-CO2 contribution to warming, 751\r threshold exceedance estimates, 750\r Representative Concentration Pathway* (RCP) \r scenarios\r acronyms used with, 231\r anthropogenic forced signal emergence, 1855\r assessing future climate change, 229\r assumptions used for emissions trajectories, 878\r biodiversity hotspot projections, 1848\r comparison with Shared Socio-economic \r Pathways, 618\r emulator estimation of scenario differences, 619\r extratropical storm projections with, 1593\r for model simulations, 561\r [...]"


id: 6e868535d52f2449be7c2c9fa05ea660
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 16710
content:
"[...] in projections using CORDEX-EA models, 1975\r ocean particulate organic carbon flux \r projections, 729\r ocean salinity projections, 1842\r projections for climate changes in AR5, 184\r relative sea level, coastal flood and coastal \r erosion signals, 1855\r use in scenario-based projections, 555\r Representative Key Risks (RKRs)\r categories of concern, 1857\r hazards assessed by AR6 WGII, 1771\r Revelle Factor, 744\r Reversibility (of transient climate response to \r cumulative CO2 emissions), 747\r Risk assessment*/framework*. See also Climate \r risk and adaptation assessment (CRA)\r AR6 framing and assessment of, 200\r assessment of changes in climatic impact\u0002drivers, 1857\r climate information for regional use, 23\r hazard versus risk use in AR6, 201\r impacts, vulnerability and adaptation, 153\r in communication to decision makers, 40\r lliklihdhihii202"


id: 19b3a6f60cf1ea64173457f26432072d
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 1723
content:
"precipitation changes, 1417, 1971\r rainfall changes in, 1968\r rainfall projections for, 1971\r reference region, 208\r sub-region defined for Africa, 1967\r West African monsoon in, 2197\r Samalas eruption (1257), 593\r Sand and dust storms\r African regional projections, 1795\r Asian regional changes, 1802\r Australasian changes, 1810\r hazards associated with, 1784\r impact in deserts and semi-arid areas, 1849\r North America changes, 1833\r Satellite Application Facility on Climate \r Monitoring (CM SAF), 938\r Satellite-based observations\r essential climate variables from, 1382\r sea ice thickness estimation in, 1251\r spatial allocation of emissions activity, 830\r Scenario-based climate projections (RCP/SSP)\r AR5 and AR6 use of, 227\r Asian regional change, 1799\r baseline and temporal scales for, 1935\r carbon dioxide emissions levels and outcomes, 618\r change under overshoot trajectories, 617\r climate goals, overshoot, and path-dependence, \r 617\r climatic impact projections for Asia, 1799-1806\r [...]"


id: dbe7aa3f255238f36894ada07f833a94
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 35973
content:
"[...] extreme heat for North America, 1830\r for Africa and subregions, 1793-1800\r for modes of variability, 2155\r for North Asia, 1978\r for ocean salinity, 1842\r greenhouse gas concentrations, 2140\r Greenland Ice Sheet sea level contribution (by \r 2100), 1260\r land and ocean transition from sink to source of \r carbon, 677\r long-term increase Northern Annular Mode, 556\r methodology used, 561\r ocean acidification, 608\r ocean heat uptake in scenarios, 1232\r ocean sink change with medium emissions, 676\r overview and scope of, 227, 929\r probabilistic statements of outcomes, 559\r projection analysis across scenarios, 1935\r projections for Southern Annular Mode, 609\r regional solar radiation projections, 1791\r Representative Concentration Pathways use in, 184\r ScenarioMIP simulations in, 562, 2101\r sea surface temperature changes, 1223\r South and South East Asian monsoon, 1127\r Southern Annular Mode change projections, 556\r temperature projections for Australasia, 1989\r [...]"


id: 8c616f89f5480aaf51f3a48b8068c009
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 21873
content:
"[...] translating regional information for end users, \r 1542-1544\r uncertainty in, 196\r use for climate projections, 562\r warming in the Arctic, 596\r Science-society linking\r climate change understanding, communication \r d titi168"


id: 9ab3b83ea153e72f082892d28d393a34
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 24459
content:
"Sequestration* (of carbon dioxide), 762\r Sesquiterpene emissions, 831\r Severe convective storms\r detection and attribution, 1596\r mechanisms and drivers, 1594-1595\r model evaluation, 1595\r observed trends, 1595-1596\r societal impacts of, 1583\r Severe wind storms\r African regional changes, 1795\r Asian regional changes, 1801\r Australasian changes, 1810\r Central and South American changes, 1817\r European changes, 1824\r North American changes, 1832\r Small Island changes, 1839\r SGMIP coordinated effort for regional climate \r modelling, 1390\r Shared Socio-economic Pathway* (SSP) \r scenarios\r abrupt human-caused water cycle changes, 1059\r acronyms used with, 231\r air pollution levels and precursor emissions \r trajectories, 883\r air quality projections, 820\r anthropogenic and natural effective radiative \r forcing, 2147-2148\r Arctic Ocean sea ice changes in, 1215\r Arctic sea ice projections, 1843\r Arctic surface warming projections, 596\r assumptions on pollution control policies for, \r 879\r [...]"


id: 68f8979511ad324c42e2a36ed241c883
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 15734
content:
"[...] Atlantic Meridional Overturning Circulation \r projections, 745, 1214\r carbon cycle responses over time with CO2\r removal, 759\r categorization and use of, 230\r changes in short-lived climate forcers on climate \r response, 884-885\r climate response to short-lived climate forcers \r in, 878\r committed ocean warming with, 21\r comparison of paleo temperatures and projected \r (2080-2100), 294\r comparison of RCPs and SSPs, 52, 235\r core scenarios, 228, 230, 233\r core scenarios and storylines, 232\r coupled climate-carbon cycle projections, 733\r emissions-driven simulations, 561\r extension to 2300, 631\r for information integration, 227\r future abundances of forcers, 2144\r future global climate projections, 553-672\r future trajectories of ocean CO2 sink, 677\r generation process, 236\r glacial mass loss variations between scenarios, \r 1279\r glacier mass loss in, 1215\r global carbonaceous aerosol projections, 881\r global land monsoon precipitation index \r projections, 586\r [...]"


id: 43d16feb19b634fb8a0c964c917454d7
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 9161
content:
"global mean sea level projections for, 21, 576, \r 1296, 1302-1305\r global surface temperature projections, 43, 228\r global surface temperature beyond 2300, 632\r global warming levels, regional climate response \r and impacts, 1543\r greenhouse gas levels in, 30-31\r heat thresholds and mitigation, 1830\r high-warming storylines for high emissions, 637\r historical and projected concentrations of CO2, \r CH4 and N2O and temperatures, 229\r history of scenarios within IPCC, 237\r hydrofluorocarbon projections for, 882\r ice-sheet mass loss projections, 1215\r idealized scenario experiments, 230\r integration across Working Groups, 151\r integration in scientific communities and across \r time scales, 230\r key climate forcer datasets used, 234\r long-term extensions and overshoot, 741\r maps of net carbon changes under scenarios, \r 734\r marine heatwave projections for, 1227\r mean sea level pressure projections, 603\r near-surface air temperature projections, 595\r [...]"


id: 52da1a4e951b5eb3f0c07f91ec006e9b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11843
content:
"[...] near-term warming effects of short-lived climate \r forcers, 820\r numeric designations of, 555\r observed, simulated and projected key indicator \r changes (1995-2014), 66\r ocean heat content projections for, 1232\r precipitation change at 2degC global warming \r level, 1544\r projections beyond 2100, 558\r projection scenarios for Asian regions, 1969\r projections for changes with CMIP5 and CMIP6, \r 576\r projections for short-lived climate forcers, 879\r quantification of urbanization for, 878\r RCP and SSP comparison of fossil fuel and \r industrial CO2 emissions, 237\r RCP and SSP run with single emulator, 619\r RCP comparison, 572, 618\r regional annual mean surface ozone projections \r (2015-2100), 883\r 'regional rivalry' storyline in, 889\r regional sea level change for 2100, 1303\r regional surface ozone and particulate matter \r projections, 882\r results and evidence presentation for, 562\r scenario generation process, 236\r scenarios used for AR6, 12-14\r [...]"


id: f447deac3af5f37d1e900c0c19e6cfcf
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 40346
content:
"[...] sea level projections based on warming levels, \r 1304\r sea level projections for, 1302\r short-lived climate forcer mitigation effects, 591, \r 888-892\r short-lived climate forcer projections, 825\r short-lived climate forcer ranges in, 820\r short-lived climate forcers and \r hydrofluorocarbons effects on warming, 889\r simulated climate changes to 2300, 632"


id: 8b07e65dc6e234d55eb35cd4e9d90ac6
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 21628
content:
"indirect radiative forcing by, 857\r induced warming rate scenario, 820\r influence on projected global surface air \r temperature change, 591\r laboratory studies, observations and climate \r models for, 834\r mechanism of climate effects, 825\r methane and ammonia from agriculture, 866\r mitigation effects of signal emergence, 591\r mitigation strategies and opportunities, 873\r models for projections, 827\r near-term effects on global air surface \r temperature, 887\r near-term warming from, 820\r non-methane volatile organic compounds, 828\r of short-lived climate forcers burden and \r distribution, 833\r overview of characteristics of, 824\r previous assessments of, 825\r process level studies and global chemistry-\r climate models, 833\r projections and climate response in SSPs, 878\r projections for air pollution management, 820\r projections for effects on global surface air \r temperature, 820\r projections of future abundances of, 882\r pulse emission decay rate of, 821\r [...]"


id: c8b69827354c56af4e54f165b1c9f9a6
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 32631
content:
"[...] radiative forcing and climate effects, 825\r reduction policies and mitigation opportunities, \r 871\r reductions of methane and black carbon for \r mitigation, 825\r reduction to curb climate change, 864\r regional anthropogenic and biomass burning \r emissions (1850-2100), 880\r regional contribution to temperature change, \r 887\r regional emissions effects on temperature, 887\r regional scale of effects, 824\r residential and commercial cooking, heating, \r 866\r scenario experiments with, 591, 825\r sea level commitment association, 1245\r sources and processes for atmospheric burden, \r 823\r sources, lifetime and contribution to warming \r (1750-2019), 894\r sources on land, 825\r spatial and temporal emission patterns of, 829\r surface temperature response to change in, 865\r targeted reduction policies for, 864\r temperature effects in scenarios (2019-2040), 885\r temperature response to high emissions, 821\r time course of mitigation efforts, 865\r values in chemistry-climate models, 834\r [...]"


id: fc8eb22b89b87ac0747f2926165ebedd
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 41802
content:
"[...] warming and cooling gases and aerosols, 893\r warming effects by scenario, 889\r warming in core SSSP scenarios, 892\r ort-lived climate pollutants* (SLCPs), 864. See \r also Short-lived climate forcers (SLCFs)\r ort-lived halogenated species, sources of, 843\r ortwave (SW) radiation*\r mineral dust interactions with, 858"


id: 82ad9146050265d62d1c65ef02c1be52
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 20122
content:
"simultaneous changes in CH4, aerosol, and ozone \r precursors, 30\r South Asia projections, 1981\r temperature effects of regional emissions of \r short-lived climate forcers, 887\r time evolution of short-lived climate forcers and \r hydrofluorocarbons, 886\r time series for all climate forcers for SSP1-1.9, \r 2145\r uncertainty of emissions representation in, 566\r used in WGI, 232\r use with models, 224\r warming levels and patterns of change with, 56\r warming with stringent mitigation policy, 821\r zonal wind and westerly jet projections, 604\r horeline progradation, 135, 139, 142\r horeline retreat, 139, 141, 1853. See also\r Coastal erosion\r hort-lived climate forcers* (SLCFs)\r air pollution control for reduction of, 864\r air quality responses in Shared Socio-economic \r Pathways, 103\r anthropogenic and natural sources of, 825\r anthropogenic regional and sectoral \r contributions to, 829\r aviation emissions of, 866\r biofuel and fossil fuel contributions, 866\r chapter roadmap for, 826\r [...]"


id: 368874afc7f83b8564a507fbbc929480
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 6826
content:
"[...] climate evolution in response to emissions of, \r 884\r climate response to, 591-592, 851, 855\r consequences for air quality and climate system, \r 893\r contrails and cirrus cloud formation, 866\r contribution to warming, 751\r current yearly emissions compared to CO2\r emissions, 821\r direct and indirect forcing by, 823\r effective radiative effects of ozone, 311\r effect on global warming in future, 42\r effects compared to CO2, 101\r effects of future changes in, 821\r effects of strong abatement for emissions, 881\r effects on effective radiative forcing, 855\r effects on global surface temperature and air \r pollution, 104\r emissions changes (1750-2019), 819\r emissions and abundances projections, 878\r emissions by natural systems, 830\r emissions from wildfires, 859\r evolution and abundances of emissions, 819\r evolution of effects on air temperature in \r scenarios, 886\r extension of effects on radiative forcing in AR6, \r 41\r global and regional temporal evolution of \r emissions, 827\r [...]"


id: 306203f3aad48aff70afda831b31e34f
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 5766
content:
"[...] global anthropogenic and biomass burning \r emission (1850-2100), 879\r global climate system effects of, 592\r heterogenous forcing effects of, 865\r ice-core analyses of, 892\r importance for climate and air quality, 823"


id: f64717671b2c8d13ea197c42556469ea
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 40693
content:
"regional projections for, 1791\r short-lived climate forcers effect on, 852\r solar radiation modification effects on, 860\r tropospheric aerosols influence on, 857\r Signal-to-noise ratio (S/N)\r detection and attribution of regional sea level \r change, 1290\r in signal emergence, 1853\r methods for improving, 429\r Simple climate model* (SCM), 219, 965\r Single-model initial-condition large ensembles \r (SMILEs)\r anthropogenic signal delay, 1367\r ensemble size for robust use of, 1409\r internal variability and lack/late anthropogenic \r signal emergence, 1427\r investigation of uncertainty with, 222\r realistic representation of internal variability, \r 1409\r regional-scale forced response to external \r forcing, 1409\r separation of model uncertainty and internal \r variability in projections, 1367, 1410\r south-eastern South America summer wetting \r attribution, 1420\r Sixth Assessment Report (AR6)\r 20-year baseline (1995-2014), 1935\r abrupt changes and tipping point assessment, \r 741\r [...]"


id: a66dbcc8d1ffc88c5b97e572519f30ff
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 26503
content:
"[...] advances since AR5 and SROCC, 691\r AR5 and AR6 report chapter relations, 155\r AR6 Working Group I (WGI), 153\r assessment of recent warming, 41\r baselines, reference periods and anomalies, \r 189-191\r baseline use for (1995-2014), 191\r boron isotope and ice core agreement, 299\r calculation of contrail cirrus forcing in, 867\r climate regions used in, 206-208\r climate risk framework in, 151\r climate services advances, 172\r constraining variability of carbon sources and \r sinks, 680\r context of WGI assessment, 156\r contributions to, 4\r core concepts of, 39\r data, tools and methods used, 151\r defining Reference Sets of Land Regions, 208\r Earth's energy budget closure in, 937\r emissions metrics in, 220\r estimates of gross and net fluxes, 688\r foundations and concepts for WGI, 189\r future changes assessed in AR6, 12\r global warming levels for dimension of \r integration, 1304\r improved complex climate models, 151\r information on the input data used, 154\r [...]"


id: 218d8c7a71144c7a814197ad0b05d73c
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 3112
content:
"[...] integration with Working Groups II and III, 156\r Interactive atlas (WGI), 1934\r key findings on water cycle, 1063\r land and open ocean reference regions for AR6 \r WGI, 1938\r major developments since AR5, 208"


id: 7afeb9c67dbcc097a087b0175ccf195e
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18841
content:
"temperature projections for, 2011\r warming changes for, 19, 142, 1839, 1932, 2012\r water resources for, 2012\r water stress in, 1838\r wet and dry conditions in, 1837\r wind projections for, 142\r Snow and ice\r African climatic impact-driver changes, 1795\r Asian climatic impact-driver changes, 1802-\r 1804, 1976\r Australasian climatic impact-driver changes, \r 1810, 1987, 1990\r Central and South American changes, 1817\r climatic impact-drivers and indices for, \r 1784-1785\r effects of light-absorbing particles on, 956\r emergence of change signal, 1855\r European climatic impact-driver changes, 1825\r lake, river and sea ice ecosystem effects of, 1785\r local hydrological processes related to, 1071\r low elevation projections, 1850\r North American climatic impact-driver changes, \r 1833\r polar region changes (2degC warming), 142\r polar terrestrial changes, 1845\r regional changes in climatic impact-drivers, 134\r seasonal change in snowmelt and runoff, 1071\r snow season length, 2211\r [...]"


id: ab1c97706ff7096ad3e8fb1362d07fed
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 27328
content:
"[...] societal impact and risks with, 1784\r Snow avalanche\r Asian changes, 1802\r European changes, 1825\r North American changes, 1834\r polar terrestrial changes, 1844\r transportation and tourism impacts, 1785\r Snow cover extent* (SCE)\r changes in, 1122\r changes with warming, 1216\r CMIP5, CMIP6 and observations, 470\r CMIP6 simulated and observed, 1286\r correlation between mean surface temperature \r and, 470\r Eurasian seasonal changes, 1802\r European changes, 1825\r global projections for, 1852\r in Northern Hemisphere and Southern \r Hemisphere, 1283\r model evaluation of seasonal snow, 1285\r North American changes, 1833\r North America projections for, 2008\r observed changes of seasonal snow cover, 1283\r observed Northern Hemisphere trends and \r anomalies, 1285\r projections for amount and seasonal duration, \r 1123\r projections for changes in, 1287\r regional projections for, 1853\r variables in terrestrial snow cover, 1283\r warming effects on, 16\r Snowfall/snowmelt\r [...]"


id: 501e2ba6981915635b1246f5d496121e
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11381
content:
"projections for precipitation falling as snow, \r 2008\r projections in snow-dominated regions, 1119\r snow water equivalent for defining snow season\r 2211\r Snow, glacier and ice-sheet indices, 1785\r Snow season length (SWE100), 2211\r Snow water equivalent* (SWE)\r continental-scale trends (1980-2018), 1285\r importance of greenhouse gases in change of, \r 2005\r in defining snow season length, 2211\r mountainous regions, 1285\r North American projections for, 2008\r regional climate model simulation, 2006\r seasonal changes in, 1283\r trends in mountain areas, 1284\r Social media platforms, 173\r Societal and environmental impacts\r heat and cold events, 1780-1783\r in framing climate science information, 172\r interaction of scientific information with values, \r 151\r of climate change, 1773\r Soil\r biochar effects on soil carbon, 763\r carbon recovery and prevention of loss, 763\r carbon response to climate change, 725\r methane uptake and lifetime assessment, 835\r nitrogen oxides emissions from, 830\r [...]"


id: 198263e25379cb717034f2327c53e87
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 1698
content:
"[...] soil NOx emissions, 830, 863\r Soil Moisture Active Passive (SMAP) satellite \r retrievals, 209, 1234\r Soil Moisture and Ocean Salinity (SMOS), 209, \r 1234\r Soil Moisture Ocean Salinity Earth Explorer \r (SMOS) mission, 1382\r Soil moisture* (SM)\r and vapour pressure deficit changes, 1120\r changes in Africa, 1794\r changes in annual mean, 17\r deficit projections for, 1581\r deficits, 1571\r detection and attribution of deficits, 1578\r during Last Glacial Maximum, 450\r evapotranspiration effects on, 1571\r increased evapotranspiration effects on, 1058\r index computation for, 2211\r observational studies on deficits, 1573\r plant water stress and, 1571\r uncertainty in projections for topsoil layer, 1119\r Soil nitrogen oxides (SNOx) emissions, 830\r Solar and orbital forcing\r changes in, 296\r CMIP6 trends (1998-2012), 425\r of North Atlantic Oscillation, 2158\r solar cycle effects on atmospheric circulation, \r 1373\r Solar radiation\r changes under cloud-free conditions, 938\r [...]"


id: bd8ae6108eaaf94afd89b1f1e1aa4096
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 30606
content:
"ll assessment of models. See Climate \r modelling techniques\r ding law, model variations due to, 1269\r all Islands\r agricultural and ecological droughts, 1838\r AR5 findings for, 2009, 2013\r Atlas, 2009\r climate hazards and consequences, 2009\r climatic impact-driver changes (2degC warming), \r 142\r climatic impact-driver projections, 1840\r climatic impact-drivers affecting, 1836\r coastal and oceanic hazards, 1841\r coastal and oceanic impact-driver projections, \r 1839\r cryosphere changes in, 1932\r difficulty in assessing climate change in, 2010\r global mean sea level projections for, 2009\r heat and cold changes for, 142, 1837\r heat stress projections for, 1837\r heavy precipitation changes, 1560, 1838\r model performance assessment, 2010\r observations, trends and attribution, 2009, 2012, \r 2013-2015, 2015\r observed trends for, 2014\r precipitation projections for (2081-2100), 2012\r previous IPCC assessments, 2009\r projection assessment and synthesis, 2011\r [...]"


id: 44cc0206b44b8ddf1ae1e296ac18474c
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 9330
content:
"[...] rainfall and sea level projections for, 2015\r regional climate features, 2009\r regional context of, 2013\r regional rainfall and drying trends, 142\r scenario-based projections, 2013\r summary of changes, 127, 142, 2012\r temperature, precipitation and sea level changes, \r 2011"


id: ebbd85806c50cf9a6f7b19fd1e3d7ca2
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 38836
content:
"regional climate model simulations for, 1996\r regional extreme heat conditions, 1437\r regional precipitation and drought projections, \r 140\r regional precipitation projections for, 1997\r regional surface air temperature and \r precipitation, 1992\r seasonal change projections for, 1997\r summary, 1997\r temperature extreme trends and projected \r changes by warming levels, 1665\r temperature extreme trends in, 1995\r temperature projections for, 613, 1991, 1994, \r 1997\r South American monsoon* (SAmerM)\r changes in, 1099\r climatic features and drivers, 1994\r Inter-tropical Convergence Zone migration \r effects on, 1994\r precipitation changes for, 1130\r projections for, 1997\r regional circulation system characteristics, 2198\r regional rate of warming in, 15\r South and South East Asian monsoon* \r (SAsiaM), See also Indian summer monsoon \r characteristics of, 2196\r climatological onset of, 2196\r regional climate model for monsoon and \r hydrological processes, 1980\r [...]"


id: 455f11c33513b013b66033d645ad3e05
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 9425
content:
"[...] scenario-based precipitation projections, 1127\r South Asia (SAS)\r aerosol effective radiative forcing, 852\r aerosol observations for, 310\r aerosol optical depth over, 290\r air pollution in, 869\r assessment and synthesis of projections, 1980\r changes with 2degC global warming, 138\r climate changes in, 1981\r glacier mass balance loss/retreat trends in, 1979\r greenhouse gas emissions for, 713\r heat stress thresholds in, 1799\r key regional climate features, 1978\r model performance assessment, 1979\r observations, trends and attribution, 1979\r particulate matter emission sources in, 821\r precipitation projections, 1978, 1980\r precipitation trends in, 1978, 1980\r previous IPCC findings for, 1978\r river flow projections, 1981\r short-lived climate forcers distribution, 819\r snow cover extent trends in (1960-2010), 1979\r snowfall/snowmelt projections for, 1979\r sulphur dioxide emissions in, 845\r summer monsoon precipitation projections, 1981\r [...]"


id: 5ce157622b36b483ecab502290845f0
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 13607
content:
"[...] surface ozone and particulate matter projections, \r 882\r surface ozone sources in, 869\r temperature changes in, 1978\r tropospheric NO2 level growth, 839\r warming level projections, 1981\r South Atlantic Convergence Zone (SACZ) \r formation, 2199"


id: 530699c5885da102c5af8918a49f3003
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11865
content:
"dimming and brightening with aerosol changes, \r 1791\r insolation cycle relation to monsoons, 2195\r variation from Earth's orbit, 297\r Solar Radiation and Climate Experiment \r (SORCE), 935\r Solar radiation modification* (SRM)\r abrupt water cycle responses to, 1059, 1151\r approaches to, 624\r AR5 assessed the climate response to, 624\r biogeochemical responses to, 767\r carbon cycle effects of, 768\r carbon dioxide removal implications for, 678\r cirrus cloud thinning for, 628\r climate response to, 619, 629\r consequences and termination effects, 768\r defined, 755\r Earth system response to, 104-105\r effective radiative forcing by aerosols in, 860\r effects on anthropogenic warming, 557\r effects on land and ocean sinks, 679\r equatorial sulphate injection modelling studies, \r 627\r feasibility assessments for, 770\r impact for climate mitigation, 681\r large-scale consequences of, 676\r marine cloud brightening, 628\r stratospheric aerosol injections for, 627, 860\r [...]"


id: 1646fc081ac4f4d1d0fbf84cc48d9532
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 1136
content:
"South Atlantic Ocean (SAO), salinity projections \r for, 1842\r South Atlantic Subtropical Dipole mode, \r El Nino-Southern Oscillation influence on, \r 2164\r Southern Central America (SCA). See also\r Central America\r climatic features of, 1991\r midsummer drought projections for, 1994\r precipitation projections for, 1991\r projections for drying in, 1993\r temperature projections for, 1993\r South East Asia (SEA)\r assessment of observations, trends and \r attribution, 1981\r assessment of temperature and precipitation \r projections, 1982\r biomass burning emissions in, 869\r carbon monoxide from biomass burning, 841\r changes with 2degC global warming, 138\r climate model evaluation, 1983\r El Nino-Southern Oscillation climatic effects, \r 1981\r El Nino-Southern Oscillation influence on \r temperature, 1981\r findings from previous IPCC assessments, 1981\r greenhouse gas emissions for, 713\r Indian Ocean Basin/Indian Ocean Dipole \r effects in, 1981\r mean and extreme temperature projections for, \r 1981\r [...]"


id: 9c87e94e05441e64abaac0041c1dcdd6
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 24789
content:
"[...] natural sources of surface ozone in, 869\r Pacific Decadal Variability effects on, 2174\r precipitation projections for, 1983\r regional climate features, 1981\r regional climate model precipitation projections, \r 1983\r subsidence projections for, 1983\r summary of trends and projections, 1983\r surface ozone and particulate matter projections, \r 882\r warming trends in, 1982\r South Eastern Africa (SEAF)\r key climatic features, 1967\r rainfall change projections, 1971\r shoreline progradation, 135\r tropical cyclone projections for, 1795\r South-Eastern South America (SES)\r annual rainfall change in, 1996\r attribution example, 1418, 1418-1420\r climatic features and drivers, 1995\r mean precipitation trend and drivers (1951-\r 2014), 1419\r stratospheric ozone depletion attribution, 1420\r Southern Africa\r greenhouse gas emissions for, 713\r Indian Ocean warming effects, 1971\r rainfall changes in, 1969\r rainfall projections for, 1971\r temperature changes in, 1968\r [...]"


id: f94e75293e3f204ae32dca5d6b2f19fb
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 41224
content:
"[...] warming projections for, 1969, 1971\r wind projections for, 135\r Southern Annular Mode* (SAM)"


id: 3c302e06d6cf99eb439a80bbffcd66be
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 7776
content:
"anthropogenic CO2 sink, 729\r anthropogenic forcing of warming, 1229\r atmospheric forcing of, 1240\r circulation influence on the global climate, 1239\r connections between ocean basins, 485\r deep ocean warming in, 1228, 1230\r heat uptake in (1870-1995), 1229\r marine heatwave frequency projections, 1227\r meltwater from Antarctic Ice Shelf in, 1240\r partial pressure of CO2 trends in, 489\r projections for freshening, 1844\r temperature changes in, 1222\r uncertainty in modelling circulation, 485\r upper overturning cell change (since 1990s), 427\r uptake of anthropogenic CO2 and heat, 745\r warming projections for, 1224\r zonal increase in wind stress, 1225\r Southern South America (SSA), climatic features \r and drivers, 1995\r South Pacific Decadal Oscillation (SPDO), \r drivers of, 2172\r South Pacific Ocean (SPO), subtropical gyre \r changes, 1241\r South Pole Observatory (SPO), atmospheric CO2\r measurements from, 689\r South West Asia\r assessment and synthesis of projections, 1985\r [...]"


id: 7b5f169bc138d6fa5455ac967fc92048
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18903
content:
"[...] changes with 2degC warming, 138\r findings from previous IPCC assessments, 1983\r model performance assessment, 1985\r observations, trends and attribution, 1984\r permafrost degradation in, 139\r regional climate and sub-regions, 1983\r South-Western North America drought (case \r study), 1420-1422\r South-Western South America (SWS), 1577, 1995\r Spatial patterns of surface warming, 565, 989\r Special Report on Climate Change and Land \r (SRCCL)\r anthropogenic contribution to, 188\r aridification of climate in East Asia, 1976\r changes for water cycle, 1062-1064\r global vegetation photosynthetic activity change, \r 485\r in assessment cycle, 187\r land temperatures increases, 596\r land use assessment, 1374\r land-use change in China (1871-2007), 1973\r regional and global climate links in, 1378\r short-lived climate forcers on land, 825\r source of greenhouse gases, 866\r wildfire changes, 724\r Special Report on Emissions Scenarios (SRES), \r scenarios used, 237\r [...]"


id: 34d35a885022ab40afaf34518f3ee004
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 6536
content:
"[...] Special Report on Global Warming of 1.5degC \r (SR1.5)\r changes in global monsoons with warming, 615\r emission pathways to limit warming, 189\r framing for climate policy relevance, 172\r global and regional climate links, 1378\r global warming levels above 1850-1900, 1936\r methane and sulphur dioxide emissions and \r limiting warming, 825"


id: cd24808385166b0d608482b194420413
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 33427
content:
"Storyline approach*\r 21st-century seal level rise, 1308\r changes in temperature in high-warming, 636\r constructing and communicating climate \r information, 1433\r defined, 40\r explaining and exploring, 199\r for communication of relevance, 1957\r for consideration of risk, 151\r high-warming, 555\r low-likelihood, high-warming, 635\r precipitation changes with high warming, 638\r Stratosphere*\r aerosol-induced heating and surface climate \r change, 627\r aerosol injection for solar modification, 860\r assessment of methane lifetime, 835\r effects of sudden warmings in, 2156\r factors determining temperature trends, 599\r global mean temperature through depth of, 425\r halogen loading of, 843\r lifetime of ozone in, 838\r lower warming and upper cooling of, 327\r lower warming over Antarctic pole, 599\r model simulations of temperatures in, 445-446\r projections for end of 21st century, 556\r sudden warming effects on teleconnections, \r 2179\r temperature changes in, 291\r [...]"


id: 3d01691de1cc57aca1d460d87d3e5dce
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 7913
content:
"[...] temperature changes in lower and upper, 445\r temperature response to greenhouse gases and \r ozone depletion, 445\r tropopause height relation to temperature in, \r 328\r water vapour and ozone contribution to forcing, \r 926\r Stratosphere-troposphere coupling, 2164\r Stratosphere-troposphere exchange* (STE)\r air pollutant effects on, 861\r effects on surface ozone, 863\r NH3 transport in, 842\r tropospheric ozone budget control by, 837"


id: 565149217ae164537db082d312f8b2a2
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 12452
content:
"human influence driving of, 427\r projections for, 1232\r Third Assessment Report (TAR), equilibrium \r climate sensitivity and transient climate \r response derivation in, 1007\r Threshold avoidance budgets (TAB), 749\r Threshold exceedance budgets (TEB), 749\r Thresholds for climatic impact-drivers. See also\r Tipping points*/elements*\r criteria for emergence of climate change signal, \r 1853\r defined, 1773\r for heat indices, 1851\r probability of exceeding hot extreme, 1555\r Tibetan Plateau (TIB)\r frequency and intensity of snowfall in, 139\r glacier retreat trends in, 1979\r precipitation projections, 1981\r snow and snow water equivalent projections, \r 1980\r snow depth and cover reanalyses, 1980\r solar radiation change in, 938\r surface temperature projections, 1981\r topographical mechanical effect on moisture, \r 1978\r warming projections for, 1974\r Tide gauge network, 134\r Tides, surges and waves, amplitude changes \r in 21st century, 1312\r Time scale separation methods (for attribution), \r [...]"


id: a3a5372184be542d74996ab1a0a5408e
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 25995
content:
"[...] 1415\r Tipping points/elements*. See also Abrupt \r climate change*\r abrupt change with, 202, 739\r assessment of biogeochemical, 740\r bifurcation tipping, 202\r changes in forcing with, 202\r climate effects of, 202\r components susceptible to tipping points/abrupt \r change, 634\r defined, 739\r for vulnerability, exposure for risk or opportunity, \r 1773\r illustration of types, 203\r irreversibility and abrupt changes with, 106\r loss of Arctic summer sea ice, 1215\r narrow regions of parameter space, 202\r noise-induced, 202\r paleoclimate evidence for, 106\r seasonal change role in, 634\r thresholds for climatic impact-drivers, 1777\r West and East Antarctic ice sheets as tipping \r elements, 1272\r Titanium dioxide (TiO2) for stratospheric \r injection, 627\r Top-down (inverse) observational constraints, \r 954\r Top-down observational inversion methods \r (TD), 835\r Top-of-the-atmosphere (TOA) energy budget\r adjustments to carbon dioxide forcing in, 945\r anomalies in fluxes, 936\r [...]"


id: f42dd9236bf762965be618e443049a6a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 40330
content:
"pp, \r upper-tropospheric equator-to-pole meridional \r gradient, 606\r variance and skewness changes in, 597\r mperature extremes\r attribution of human influence on, 457, 1553\r attribution of short duration temperature \r extremes, 1553\r comparison of global observed and simulated \r changes, 458\r concurrent precipitation seasonality (2018), 1603\r constraints for projections, 1554\r effects of modifying weather patterns, 1526\r exceeding threshold for hot and cold events, \r 1555\r globally averaged annual daily maximum and \r minimum, 1548\r global projections for, 1851\r global projections for heat extremes, 1556\r linear scaling with global warming, 1554\r maximum/minimum projections for changes with \r warming levels, 1554\r mechanisms and drivers, 1546-1549\r multi-model bias (1979-2014), 1551\r observed trends for warm and cold days, \r 1548-1551\r percentage land area affected by, 1601\r probability of occurrence, 1553\r projected change over land, 18\r [...]"


id: d6160dedfcde0d0ad09379ab0f39131a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 34982
content:
"[...] projected intensity changes with warming levels, \r 1555\r projections for warming levels, 1530\r projections in continental regions, 1555\r regional changes in daily maximum \r temperatures for land areas, 1524\r regional climate, 1605\r similarity of observed and simulated, 1550\r studies since AR5 on, 1552\r thermodynamic responses and feedbacks with, \r 1526\r mperature patterns\r dependence of feedbacks on, 989\r relationship between feedbacks and, 981\r rrestrial carbon cycle, 485-487, 741, 768\r rrestrial cryosphere. See also Cryosphere*\r indicators of changes in, 291\r rrestrial snow cover. See Snow cover extent* \r (SCE)\r rrestrial vegetation. See Vegetation\r ermal expansion*, 1220\r ermal radiation, changes since 1970s, 939\r ermodynamic response to warming\r enhanced moisture flux with warming, 601\r global monsoon precipitation enhancement, 603\r ermosteric* change (in ocean). See also Steric \r sea level change*\r anthropogenic forcing of, 481\r contribution to steric sea level change, 1220"


id: ccea41a7211de952d5f80645bb3cca85
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 33394
content:
"greenhouse gas forced warming, 444, 445\r halogen loss, 835\r human-induced warming (since 1979), 425\r hydroxyl (OH) radical trends in, 819\r hydroxyl radical change in (1850-2000), 851\r lightning NOx release in, 830\r lower warming trend, 327\r mean NO2 and time evolution of, 839\r model estimation of nitrate burden, 846\r moistening in the upper troposphere, 451\r moistening in upper, 426\r Northern Hemisphere mid-latitudes aerosol \r concentrations, 290\r NOx abundance (1850-2015), 839\r observed change in free atmospheric \r temperatures, 329\r OH abundance and short-lived climate forcer \r emissions, 849\r ozone changes in, 858\r process-level studies to chemistry-climate \r models, 833\r projections for long-term temperature changes, \r 599\r projections for pattern for end of 21st century, \r 598\r propagation of geopotential height anomalies, \r 2156\r sulphate burden trends (1850-2005), 846\r temperature changes in, 291\r temperature response to sea surface \r temperature, 990\r [...]"


id: c018f78d9f8586cf56d12297228be0bf
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 31087
content:
"[...] upper warming in tropics, 556\r warming biases in models, 443\r warming projection scenarios, 599\r warming since the mid-20th century, 328\r water vapour and temperature lapse rate in \r feedback analysis, 969\r water vapour changes in, 451\r Tropospheric ozone*\r control of budget for, 837\r emissions from human activity, 180\r lightning NOx emission effects, 859\r present-day estimates of burden, 838\r trends in, 308\r Twomey effect, 860\r Type I and Type II errors, 172\r Typhoon Haiyan, 1589\r Typological Regions, 208"


id: 5247d406871f6ee37e05223282b7a0e1
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11751
content:
"detection and attribution, event attribution, \r 1588-1590\r global changes in Category 4-5 storms, 1839\r hazards associated with, 1784\r increased warming effects on, 16\r intensity and frequency in warmer climate, 1313\r intensity and latitude shifts in, 9\r intensity and precipitation projections, 2009\r landfall on eastern Australia, 1987\r mechanisms and drivers of, 1585\r model evaluation, 1587-1590\r North American changes, 1832\r observed trends in, 1585\r Pacific Decadal Variability effects on formation, \r 2174\r past and projections for change summary, 1586\r projections for, 1590-1592\r projections for global change in, 1852\r rain rates with warming, 1519\r sea-salt aerosol interaction effects on, 478\r Small Islands changes, 1839\r storm-surge driven extreme sea level events, \r 1310\r wind speed changes with warming, 1519\r ropical forests\r biodiversity in, 1850\r changes with 2degC warming, 143\r climatic impact-driver changes of importance, \r 1850\r potential for dieback due to drought, 634\r [...]"


id: 4089ec1f2489375cf967e71729f793fc
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 8546
content:
"[...] projections for carbon accumulation in, 740\r ropical high-cloud amount feedback, 972\r ropical Pacific Decadal Variability (TPDV), 2172\r ropical Pacific Ocean\r regional pH changes in, 716\r sea surface temperature gradients in, 987\r surface temperature biases in CMIP5 andCMIP6, \r 2010\r ropical regions"


id: 1b30b1904f3ddc22be0aeb0703e2254c
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 1973
content:
"attribution studies for, 1578\r carbon cycle interaction under drought \r conditions, 697-699\r carbon dioxide removal effects on, 100\r causes of observed changes, 1057\r change from AR5 and special reports, \r 1062-1064\r changes across warming levels, 1112\r changes for in seasonality of, 1113\r changes in Madden-Julian Oscillation \r implications for, 2179\r changes in polar regions, 142, 1847\r changes since 1980, 85\r changes with high-warming storylines, 637\r chapter structure and content, 2176\r constraints on regional, 1067\r depiction of present day, 1061\r detectable effects since AR5, 42\r direct anthropogenic influence on regional, 1075\r effects of continued warming, 19\r expectations for future, 1065\r freshwater reservoirs, 1089-1092, 1122\r future change projections, 1058\r global changes in, 158, 291\r groundwater, 1091\r high-warming storyline manifestations, 637\r human-caused changes in, 85\r importance for human societies and ecosystems, \r 1060\r [...]"


id: a89e42bead3b3abd26a77475dbf29604
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 26875
content:
"[...] Indian Ocean Basin and Indian Ocean Dipole, \r 2168\r intensity and P-E over land and oceans \r projection, 1106\r land surface responses and feedbacks effects \r in, 1146\r large-scale changes in, 1057\r large-scale responses in atmospheric circulation \r patterns, 1069\r limits for projections, 1135\r local processes related to ice and snow, 1071\r local/regional effects of land-use change and \r irrigation, 1057\r local-scale physical processes affecting, 1071\r modulation by relative humidity change, 600\r nonlinear at the regional scale, 1148\r observational capacity expansion, 209\r observed changes in, 1079\r overview of climate system and, 1060\r ozone-vegetation interaction effects, 857\r Pacific Decadal Variability implications for, 2174\r physical basis for change in, 1057\r potential for abrupt human-caused changes in, \r 1059\r precipitation minus evaporation, 333\r precipitation minus evaporation over land and \r oceans, 1079\r projected changes, 1106\r projected water cycle changes, 87\r [...]"


id: eaa02d51fdacd04e5a6c56f0b2279e3f
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 38638
content:
"[...] projections for deficits, 1582\r projections for trends in near-term, 1144\r reconstructions and model-data comparisons, 46\r region-specific changes with 2degC warming, 135"


id: 2fcdc3f90b5e68a22cc0ffb36d1d3596
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 5667
content:
"responses to a collapse of Atlantic Meridional \r Overturning Circulation, 1148\r river and pluvial flood event projections, 1518\r runoff, streamflow and flooding, 1086\r seasonal snow cover, 1090\r solar modification effects on, 1059\r streamflow and surface water deficits, 1572\r streamflow observations for detection and \r attribution, 456\r streamflow record evidence for deficits, 1574\r tropical forest effects of, 1851\r variability and extremes in, 1058\r wetlands and lakes, 1090\r Water management\r effects on land surface hydrology, 1143\r heavy precipitation and flood impacts on, 178\r snow, glacier and ice-sheet indices use in, 178\r snowpack changes and storage, 1221\r use of drought indices in, 1783\r Water masses*\r entry into glacial fjords, 1257\r formation in marginal sea areas, 1244\r heat storage in Southern and North Atlantic, \r 1214, 1225\r ice shelf penetration by, 1268\r ocean heat uptake circulation by, 1235\r redistribution of, 1246\r salinity changes and rate of formation, 1234\r [...]"


id: 974a2a463ea75c05c735fe35239da6d2
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 23814
content:
"[...] salinity changes in, 1235\r subduction in Southern Hemisphere Mode \r Waters, 1231\r variability on Antarctic continental shelf, 1240\r warming in subduction regions, 1232\r Water-use efficiency (WUE), 697, 722\r Water vapour\r and temperature lapse-rate feedbacks, 969\r attribution of tropospheric changes in, 451\r CMIP6 projections for, 1107\r contribution to global warming, 95\r increased atmospheric content of, 1526\r stratospheric increase with methane, 946\r transport of, 1080\r trends (1998-2019), 450\r Wave-mean flow interaction, 2156\r Waves\r contribution to extreme sea level, 1310\r response to surface conditions, 1313\r wind-generated, 1221\r Weather and climate extreme events in a \r changing climate\r attribution of extremes, 1525, 1532, 1540\r changes in low-likelihood, high-impact extrem\r 1534-1536\r compound events, 1598-1604\r concurrent meteorological conditions (July \r 2018), 1603\r confidence for changes at 2degC, 1529\r data and methods, 1536-1543\r data sources for studies of, 1537\r [...]"


id: 78f6183e86f6d73cdb98d0a92515493c
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18472
content:
"[...] definition of extremes, 1536\r detection and attribution, 1552-1553\r droughts, 1518, 1570-1587\r extratropical storms1592-1594"


id: 9d849d6d6694ea4fe08936e1f72f1c56
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 24951
content:
"West Africa. See Western Africa\r West African Monsoon Modelling and \r Evaluation (WAMME), 2198\r West African monsoon* (WAfriM)\r anthropogenic forcing of, 1097\r Atlantic Multi-decadal Variability effects, 2177\r Atlantic Zonal Mode influence, 1968\r Atlantic Zonal Mode link between, 2171\r CORDEX climate models, 1969\r domain and characteristics of, 2197-2198\r drivers of variability in, 2198\r projections, 1130\r variability time scales, 2198\r West Antarctica (WAN), 2016\r West Antarctic Ice Sheet* (WAIS)\r contribution to recent ice loss, 473\r ice-sheet instability effects on, 1269\r ongoing grounding line retreat in, 1265\r response to stabilization of warming, 106\r thinning of outlet glaciers in, 1264\r threshold instability/tipping, 1269, 1273\r West Central Asia (WCA)\r glacier projections, 1122\r global warming level projections, 1985\r influence on regional climate, 1983\r precipitation changes, 1983-1986\r snow cover extent projections, 1984\r surface air temperature trend, 1984\r [...]"


id: 27f45c5ed1f34a4168e6b66225236502
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 4224
content:
"[...] Westerly winds at midlatitudes, 2158\r Western Africa (WAF), \r climate features of, 1967\r climate simulation, 2198\r droughts over, 2198\r extreme changes in, 1613, 1619, 1624\r rainfall changes in, 1968, 1971\r temperature changes in, 1968, 1969\r wind projections for, 135 \r Western and Central Europe (WCE), 1998, 1999\r Western boundary currents (WBCs), 143, 1222, \r 1242\r Western North America (WNA)\r climatic features, 2004\r wind power projections, 1833\r Western Pacific \r rainfall and streamflow trends in, 2010\r sea level rise in, 1216\r temperature trends in, 2009\r West Siberia (WSB)\r climate features of, 1975\r snow depth trends, 1977\r West Southern Africa (SWAF)\r extreme total water level, 135\r key climatic features, 1967\r rainfall projections, 1971\r Wet and dry conditions\r Asia regional changes, 1800-1802\r Australasia changes, 1807-1811\r intensification of zonal mean patterns, 452\r North American changes in, 1830\r polar region changes (2degC warming), 142\r [...]"


id: 7af3240ae332ba4b1ae750bd92afa844
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18832
content:
"[...] regional changes in climatic impact-drivers, 132\r terrestrial polar region changes, 1844\r Wet-gets-wetter, dry-gets-drier paradigm, 456, \r 584, 601\r Wetland CH4-climate feedback, 737\r Wetlands* and lakes\r lake and river ice projections, 1123, 1847\r mechanisms of climate impact, 1090\r projections for changes for extent, 1123\r SRCCL and SROCC discussion of, 1123\r Wet scavenging, 845, 848\r Wet tropics-dry subtropics contrast, 456\r Wildfire Decision Support System (WFDE5)\r calculation for wildfire/biomass burning, 2210\r data for atlas, 1941\r Wildfires/biomass burning\r bias adjusted heat index calculation, 2210\r climate-fire feedback, 859\r effects of climate change on, 724\r effects on surface ozone, 863\r increase in fire weather, 1852\r Pacific Decadal Variability effects, 2174\r Wind. See Wind Speed\r Wind-generated waves, 1221\r Wind power potential\r Africa, 135\r Australasia, 1810\r Europe, 1824\r North America, 1832, 1833\r projections for augmentation of, 1817\r [...]"


id: 5383a55829957d6934e36ad13049ec7e
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11966
content:
"[...] renewable energy impact wind changes, 1784\r Southern Africa, 135\r Western North America, 141\r Wind speed. See also Severe wind storms\r African changes, 1795\r Asian changes, 1801-1803\r Australasian changes, 1810\r Central and South American changes, 1817\r European changes, 1824\r impact of changes in, 1784\r North American changes, 1832\r observed mean surface wind speed trends, 1855\r polar terrestrial region changes, 142, 1845\r projections for changes in, 1519\r regional changes in climatic impact-drivers, 132\r sea-spray particle emission rate, 832\r Small Islands changes, 1839\r Southern Hemisphere westerlies strengthening, \r 1240\r Southern Hemisphere zonal mean Dec-Jan-Feb \r (1985-2014), 465\r surface wind speed changes, 1802\r transportation of Circumpolar Deep Water heat \r by, 1236\r tropical cyclone projections, 1592\r Wind stress\r Atlantic Meridional Mode fluctuations \r and anomalies, 2168\r North Atlantic Oscillation fluctuations \r and anomalies, 2159\r [...]"


id: e56a15bcd0c59af84e2c28233aab7808
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 37664
content:
"[...] ocean current change in response to, 1214\r Windward Islands, precipitation trends for, \r 2009\r World Climate Research Programme (WCRP)\r coordinated model results from, 428"


id: 7dbe930d7c28d346cd7e1357423679e9
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 19299
content:
"'Climate Change 2022: Impacts, Adaptation and Vulnerability', the \r Working Group II contribution to the Intergovernmental Panel on Climate \r Change's (IPCC) Sixth Assessment Report presents a comprehensive \r assessment of the current state of knowledge of the observed impacts \r and projected risks of climate change as well as the adaptation options. \r The report confirms the strong interactions of the natural, social and \r climate systems and that human-induced climate change has caused \r widespread adverse impacts to nature and people. It is clear that \r across sectors and regions, the most vulnerable people and systems are \r disproportionately affected and climate extremes have led to irreversible \r impacts. The assessment underscores the importance of limiting global \r warming to 1.5degC if we are to achieve a fair, equitable and sustainable \r world. While the assessment concluded that there are feasible and \r effective adaptation options which can reduce risks to nature and \r [...]"


id: 9b225ce8fef50bf0f390cb8d0ca10024
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 24545
content:
"[...] people, it also found that there are limits to adaptation and that there \r is a need for increased ambition in both adaptation and mitigation. \r These and other findings confirm and enhance our understanding of the \r importance of climate resilient development across sectors and regions \r and, as such, demands the urgent attention of both policymakers and \r the general public."


id: 7866ed8046572bcca256f7a8ce74be4a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18388
content:
"We are also grateful to the governments that supported their scientists' \r participation in developing this report and that contributed to the IPCC \r Trust Fund to provide for the essential participation of experts from \r developing countries and countries with economies in transition. We \r would like to express our appreciation to the government of Ethiopia \r for hosting the scoping meeting for the IPCC's Sixth Assessment Report, \r to the governments of South Africa, Nepal, Portugal and Guatemala for \r hosting drafting meetings of the Working Group II contribution and to \r the government of Germany for hosting the Twelfth Session of Working \r Group II held virtually for approval of the Working Group II Report. The \r generous financial support by the government of Germany and the \r logistical support by the Alfred Wegener Institute Helmholtz Centre for \r Polar and Marine Research (Germany), enabled the smooth operation \r [...]"


id: c43d584637f165dd1713145b7cdc17a7
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 31811
content:
"[...] of the Working Group II Technical Support Unit in Bremen, Germany. \r Additional funding from the Governments of Germany, Norway and \r New Zealand provided key support to the Technical Support Unit office \r in Durban, South Africa."


id: f5dbef93e9c9d7b43da1e623b9ad2ad6
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 40614
content:
"The Working Group II contribution to the Sixth Assessment Report \r of the Intergovernmental Panel on Climate Change (IPCC) provides \r a comprehensive assessment of the scientific, technical and socio\u0002economic literature relevant to impacts, adaptation and vulnerability. \r It builds upon the Working Group II contribution to the IPCC's Fifth \r Assessment Report, the three Special Reports of the Sixth Assessment \r cycle: 'Global Warming of 1.5degC. An IPCC Special Report on the \r impacts of global warming of 1.5degC above pre-industrial levels and \r related global greenhouse gas emission pathways, in the context of \r strengthening the global response to the threat of climate change, \r sustainable development, and efforts to eradicate poverty (SR1.5)'; \r 'Climate Change and Land: An IPCC Special Report on climate change, \r desertification, land degradation, sustainable land management, food \r security, and greenhouse gas fluxes in terrestrial ecosystems (SRCCL)'; \r [...]"


id: dee46140981e65afaa8261550646362f
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 36475
content:
"[...] 'IPCC Special Report on the Ocean and Cryosphere in a Changing \r Climate (SROCC)', and the Working Group I contribution to the IPCC \r Sixth Assessment Report."


id: b0be8881f25e81b56fb84c767016ca39
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 28325
content:
"Drafting Authors: Hans-O. Portner (Germany), Debra C. Roberts (South Africa), Helen Adams \r (UK), Carolina Adler (Switzerland/Chile/Australia), Paulina Aldunce (Chile), Elham Ali (Egypt), \r Rawshan Ara Begum (Malaysia/Australia/Bangladesh), Richard Betts (UK), Rachel Bezner Kerr \r (Canada/USA), Robbert Biesbroek (The Netherlands), Joern Birkmann (Germany), Kathryn Bowen \r (Australia), Edwin Castellanos (Guatemala), Gueladio Cisse (Mauritania/Switzerland/France), \r Andrew Constable (Australia), Wolfgang Cramer (France), David Dodman (Jamaica/UK), Siri \r H. Eriksen (Norway), Andreas Fischlin (Switzerland), Matthias Garschagen (Germany), Bruce \r Glavovic (New Zealand/South Africa), Elisabeth Gilmore (USA/Canada), Marjolijn Haasnoot (The \r Netherlands), Sherilee Harper (Canada), Toshihiro Hasegawa (Japan), Bronwyn Hayward (New \r Zealand), Yukiko Hirabayashi (Japan), Mark Howden (Australia), Kanungwe Kalaba (Zambia), \r [...]"


id: ffd6cfed4bdbe2d4ded34bd85666cd39
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 42406
content:
"[...] Wolfgang Kiessling (Germany), Rodel Lasco (Philippines), Judy Lawrence (New Zealand), \r Maria Fernanda Lemos (Brazil), Robert Lempert (USA), Debora Ley (Mexico/Guatemala), Tabea \r Lissner (Germany), Salvador Lluch-Cota (Mexico), Sina Loeschke (Germany), Simone Lucatello \r (Mexico), Yong Luo (China), Brendan Mackey (Australia), Shobha Maharaj (Germany/Trinidad and \r Tobago), Carlos Mendez (Venezuela), Katja Mintenbeck (Germany), Vincent Moller (Germany), \r Mariana Moncassim Vale (Brazil), Mike D Morecroft (UK), Aditi Mukherji (India), Michelle Mycoo \r (Trinidad and Tobago), Tero Mustonen (Finland), Johanna Nalau (Australia/Finland), Andrew \r Okem (SouthAfrica/Nigeria), Jean Pierre Ometto (Brazil), Camille Parmesan (France/USA/UK), \r Mark Pelling (UK), Patricia Pinho (Brazil), Elvira Poloczanska (UK/Australia), Marie-Fanny Racault \r (UK/France), Diana Reckien (The Netherlands/Germany), Joy Pereira (Malaysia), Aromar Revi \r [...]"


id: 2c8590819bc02ad9e5842809b0cdbc2b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 5100
content:
"[...] (India), Steven Rose (USA), Roberto Sanchez-Rodriguez (Mexico), E. Lisa F. Schipper (Sweden/\r UK), Daniela Schmidt (UK/Germany), David Schoeman (Australia), Rajib Shaw (Japan), Chandni \r Singh (India), William Solecki (USA), Lindsay Stringer (UK), Adelle Thomas (Bahamas), Edmond \r Totin (Benin), Christopher Trisos (South Africa), Maarten van Aalst (The Netherlands), David Viner \r (UK), Morgan Wairiu (Solomon Islands), Rachel Warren (UK), Pius Yanda (Tanzania), Zelina Zaiton \r Ibrahim (Malaysia)"


id: 41752618aa83706bcaa2104147c2ced7
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 8705
content:
"socioeconomic details and assumptions, WGII chapters contextualize impacts with respect to exposure, vulnerability and adaptation as \r appropriate for their literature, this includes assessments regarding sustainable development and climate resilient development. There are \r many emissions and socioeconomic pathways that are consistent with a given global warming outcome. These represent a broad range \r of possibilities as available in the literature assessed that affect future climate change exposure and vulnerability. Where available, WGII \r also assesses literature that is based on an integrative SSP-RCP framework where climate projections obtained under the RCP scenarios \r are analysed against the backdrop of various illustrative SSPs22. The WGII assessment combines multiple lines of evidence including \r impacts modelling driven by climate projections, observations, and process understanding. {1.2, 16.5, 18.2, CCB CLIMATE, WGI AR6 \r [...]"


id: a3b2415423cfd4fbed9fe18c47b860d0
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 26004
content:
"(b) Climate change has already had diverse adverse impacts on human systems, including on water security and food production, health and well-being, and cities, settlements and \r infrastructure. The + and - symbols indicate the direction of observed impacts, with a - denoting an increasing adverse impact and a +- denoting that, within a region or globally, both \r adverse and positive impacts have been observed (e.g., adverse impacts in one area or food item may occur with positive impacts in another area or food item). Globally, '-' denotes an \r overall adverse impact; 'Water scarcity' considers, e.g., water availability in general, groundwater, water quality, demand for water, drought in cities. Impacts on food production were \r assessed by excluding non-climatic drivers of production increases; Global assessment for agricultural production is based on the impacts on global aggregated production; 'Reduced \r [...]"


id: e91c0739376f0474665e7dab1201a765
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 38364
content:
"[...] animal and livestock health and productivity' considers, e.g., heat stress, diseases, productivity, mortality; 'Reduced fisheries yields and aquaculture production' includes marine and \r freshwater fisheries/production; 'Infectious diseases' include, e.g., water-borne and vector-borne diseases; 'Heat, malnutrition and other' considers, e.g., human heat-related morbidity \r and mortality, labour productivity, harm from wildfire, nutritional deficiencies; 'Mental health' includes impacts from extreme weather events, cumulative events, and vicarious or \r anticipatory events; 'Displacement' assessments refer to evidence of displacement attributable to climate and weather extremes; 'Inland flooding and associated damages' considers, \r e.g., river overflows, heavy rain, glacier outbursts, urban flooding; 'Flood/storm induced damages in coastal areas' include damages due to, e.g., cyclones, sea level rise, storm surges. \r [...]"


id: 4644cb28aa36bab26ace586d0aa50ac9
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 9581
content:
"[...] Damages by key economic sectors are observed impacts related to an attributable mean or extreme climate hazard or directly attributed. Key economic sectors include standard \r classifications and sectors of importance to regions (for methodology and detailed references to chapters and cross-chapter papers see SMTS.1 and SMTS.1.2)."


id: 1865516818a578b2607a4a90e8c3e2e2
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 1505
content:
"confidence). In rural areas vulnerability will be heightened by compounding processes including high emigration, reduced habitability and \r high reliance on climate-sensitive livelihoods (high confidence). Key infrastructure systems including sanitation, water, health, transport, \r communications and energy will be increasingly vulnerable if design standards do not account for changing climate conditions (high \r confidence). Vulnerability will also rapidly rise in low-lying Small Island Developing States and atolls in the context of sea level rise and \r in some mountain regions, already characterised by high vulnerability due to high dependence on climate-sensitive livelihoods, rising \r population displacement, the accelerating loss of ecosystem services and limited adaptive capacities (high confidence). Future exposure \r to climatic hazards is also increasing globally due to socioeconomic development trends including migration, growing inequality and \r [...]"


id: 7728c6e45b79732bf22b1bc89796913d
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18166
content:
"[...] urbanization (high confidence). {4.5, 5.5, 6.2, 7.2, 8.3, 9.9, 9.11, 10.3, 10.4, 12.3, 12.5, 13.6, 14.5, 15.3, 15.4, 16.5, CCP2.3, CCP4.3, \r CCP5.2, CCP5.3, CCP5.4, CCP6.2, CCB MIGRATE}"


id: 8b753e3ca72e8f7c3e89c0d6e2cb50f5
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 21699
content:
"(b) The Reasons for Concern (RFC) framework communicates scientific understanding about accrual of risk for five broad categories. Diagrams are shown for each RFC, assuming \r low to no adaptation (i.e., adaptation is fragmented, localized and comprises incremental adjustments to existing practices). However, the transition to a very high risk level has an \r emphasis on irreversibility and adaptation limits. Undetectable risk level (white) indicates no associated impacts are detectable and attributable to climate change; moderate risk \r (yellow) indicates associated impacts are both detectable and attributable to climate change with at least medium confidence, also accounting for the other specific criteria for key \r risks; high risk (red) indicates severe and widespread impacts that are judged to be high on one or more criteria for assessing key risks; and very high risk level (purple) indicates \r [...]"


id: a738441cf325d090cfd7e44170207b8e
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 26634
content:
"[...] very high risk of severe impacts and the presence of significant irreversibility or the persistence of climate-related hazards, combined with limited ability to adapt due to the nature \r of the hazard or impacts/risks. The horizontal line denotes the present global warming of 1.09degC which is used to separate the observed, past impacts below the line from the future \r projected risks above it. RFC1: Unique and threatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and \r have high endemism or other distinctive properties. Examples include coral reefs, the Arctic and its Indigenous Peoples, mountain glaciers and biodiversity hotspots. RFC2: Extreme \r weather events: risks/impacts to human health, livelihoods, assets and ecosystems from extreme weather events such as heatwaves, heavy rain, drought and associated wildfires, \r [...]"


id: 1e63a59d2e4a7d3c2fef126e3b58d87b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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"[...] and coastal flooding. RFC3: Distribution of impacts: risks/impacts that disproportionately affect particular groups due to uneven distribution of physical climate change hazards, \r exposure or vulnerability. RFC4: Global aggregate impacts: impacts to socio-ecological systems that can be aggregated globally into a single metric, such as monetary damages, lives \r affected, species lost or ecosystem degradation at a global scale. RFC5: Large-scale singular events: relatively large, abrupt and sometimes irreversible changes in systems caused \r by global warming, such as ice sheet disintegration or thermohaline circulation slowing. Assessment methods are described in SM16.6 and are identical to AR5, but are enhanced \r by a structured approach to improve robustness and facilitate comparison between AR5 and AR6. "


id: 70e6e155e39fdcbae73a7b7b3616d569
created_at: 2023-04-19 13:22:50
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"(f) Examples of regional key risks. Risks identified are of at least medium confidence level. Key risks are identified based on the magnitude of adverse consequences (pervasiveness \r of the consequences, degree of change, irreversibility of consequences, potential for impact thresholds or tipping points, potential for cascading effects beyond system boundaries); \r likelihood of adverse consequences; temporal characteristics of the risk; and ability to respond to the risk, e.g., by adaptation. The full set of 127 assessed global and regional key \r risks is given in SM16.7. Diagrams are provided for some risks. The development of synthetic diagrams for Small Islands, Asia and Central and South America were limited by the \r availability of adequately downscaled climate projections, with uncertainty in the direction of change, the diversity of climatologies and socioeconomic contexts across countries \r [...]"


id: 243c9a75dc269073dd3b91c90d6e7bf7
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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"[...] within a region, and the resulting low number of impact and risk projections for different warming levels. Absence of risks diagrams does not imply absence of risks within a region. \r (Box SPM.1) {Figure TS.4, Figure 2.11, Figure SM3.1, Figure 7.9, Figure 9.6, Figure 11.6, Figure 13.28, 16.5, 16.6, Figure 16.15, SM16.3, SM16.4, SM16.5, SM16.6 (methodologies), \r SM16.7, Figure CCP4.8, Figure CCP4.10, Figure CCP6.5, WGI AR6 2, WGI AR6 SPM A.1.2, WGI AR6 Figure SPM.8}"


id: 1a059ea80057e073b7577d6f7a37b281
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
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content:
"settlements, climate impacts to key infrastructure are leading to losses and damages across water and food systems, and affect \r economic activity, with impacts extending beyond the area directly impacted by the climate hazard (high confidence). In Amazonia, \r and in some mountain regions, cascading impacts from climatic (e.g., heat) and non-climatic stressors (e.g., land use change) will result \r in irreversible and severe losses of ecosystem services and biodiversity at 2degC global warming level and beyond (medium confidence). \r Unavoidable sea level rise will bring cascading and compounding impacts resulting in losses of coastal ecosystems and ecosystem \r services, groundwater salinisation, flooding and damages to coastal infrastructure that cascade into risks to livelihoods, settlements, \r health, well-being, food and water security, and cultural values in the near to long-term (high confidence). (Figure SPM.3) {Figure TS.10, \r [...]"


id: 136054670501bab23994d0c5861b5c68
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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content:
"[...] 2.5, 3.4, 3.5, Box 7.3, Box 8.7, Box 9.4, 11.5, Box 11.1, 12.3, 13.9, 14.6, 15.3, 16.5, 16.6, CCP1.2, CCP2.2, CCP5.2, CCP5.3, CCP6.2, \r CCP6.3, Box CCP6.1, Box CCP6.2, CCB EXTREMES, WGI AR6 Figure SPM.8d}"


id: 940e5574d10be10040d51ae74a08e350
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 23254
content:
"Figure SPM.4 |  (b) Climate responses and adaptation options, organized by System Transitions and Representative Key Risks, are assessed at global scale \r for their likely ability to reduce risks for ecosystems and social groups at risk, as well as their relation with the 17 Sustainable Development Goals (SDGs).\r Climate responses and adaptation options are assessed for observed benefits (+) to ecosystems and their services, ethnic groups, gender equity, and low-income groups, or observed \r dis-benefits (-) for these systems and groups. Where there is highly diverging evidence of benefits/ dis-benefits across the scientific literature, e.g., based on differences between \r regions, it is shown as not clear or mixed (*). Insufficient evidence is shown by a dash. The relation with the SDGs is assessed as having benefits (+), dis-benefits (-) or not clear or \r [...]"


id: fd2804727defff6b044272142ee9213f
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
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content:
"[...] mixed (*) based on the impacts of the climate response and adaptation option on each SDG. Areas not coloured indicate there is no evidence of a relation or no interaction with the \r respective SDG. The climate responses and adaptation options are drawn from two assessments. For comparability of climate responses and adaptation options see Table SM17.5. \r {17.2, 17.5, CCB FEASIB}"


id: 532af9ffa94af7f8ef30a4ef00f1bcf9
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11901
content:
"Authors: Hans Portner (Germany), Debra C. Roberts (South Africa), Helen Adams (UK), \r Ibidun Adelekan (Nigeria), Carolina Adler (Switzerland/Chile/Australia), Rita Adrian (Germany), \r Paulina Aldunce (Chile), Elham Ali (Egypt), Rawshan Ara Begum (Malaysia/Australia/Bangladesh), \r Birgit Bednar-Friedl (Austria), Rachel Bezner Kerr (Canada/USA), Robbert  Biesbroek (The \r Netherlands), Joern  Birkmann (Germany), Kathryn Bowen (Australia), Martina Angela Caretta \r (Sweden), Jofre  Carnicer (Spain), Edwin Castellanos (Guatemala), Tae Sung Cheong (Republic \r of Korea), Winston Chow (Singapore), Gueladio  Cisse (Mauritania/Switzerland/France), Susan \r Clayton (USA), Andrew Constable (Australia), Sarah R. Cooley (USA), Mark John Costello (New \r Zealand/Norway/Ireland), Marlies Craig (South Africa), Wolfgang Cramer (France), Richard Dawson \r (UK), David Dodman (Jamaica/UK), Jackson Efitre (Uganda), Matthias Garschagen (Germany), \r [...]"


id: 1ddc916fd76198f2920d6002f55049a5
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
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content:
"[...] Elisabeth Gilmore (USA/Canada), Bruce Glavovic (New Zealand/South Africa), David Gutzler \r (USA), Marjolijn  Haasnoot (The Netherlands), Sherilee Harper (Canada), Toshihiro Hasegawa \r (Japan), Bronwyn Hayward (New Zealand), Jeffrey Hicke (USA), Yukiko Hirabayashi (Japan), Cunrui \r Huang (China), Kanungwe Kalaba (Zambia), Wolfgang Kiessling (Germany), Akio Kitoh (Japan), \r Rodel Lasco (Philippines), Judy Lawrence (New Zealand), Maria Fernanda Lemos (Brazil), Robert \r Lempert (USA), Christopher Lennard (South Africa), Debora Ley (Guatemala/Mexico), Tabea \r Lissner (Germany), Qiyong Liu (China), Emma Liwenga (Tanzania), Salvador Lluch-Cota (Mexico), \r Sina Loeschke (Germany), Simone Lucatello (Mexico), Yong Luo (China), Brendan Mackey (Australia), \r Katja Mintenbeck (Germany), Alisher  Mirzabaev (Uzbekistan), Vincent Moeller (Germany), \r Mariana Moncassim Vale (Brazil), Mike Morecroft (UK), Linda Mortsch (Canada), Aditi Mukherji \r [...]"


id: 2c0d35ff26ba2b269cd255cd0682875d
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 5008
content:
"[...] (India), Tero Mustonen (Finland), Michelle Mycoo (Trinidad and Tobago), Johanna Nalau (Australia/\r Finland), Mark New (South Africa), Andrew Okem (South Africa/Nigeria), Jean Pierre Ometto \r (Brazil), Brian O'Neill (USA), Rajiv Pandey (India), Camille Parmesan (France/UK/USA), Mark Pelling \r (UK), Patricia Fernanda Pinho (Brazil), John Pinnegar (UK), Elvira S. Poloczanska (UK/Australia/\r Germany), Anjal Prakash (India), Benjamin Preston (USA), Marie-Fanny Racault (UK/France), Diana \r Reckien (The Netherlands/Germany), Aromar Revi (India), Steven K. Rose (USA), E. Lisa F. Schipper \r (Sweden/UK), Daniela Schmidt (UK/Germany), David Schoeman (Australia), Rajib Shaw (Japan), \r Nicholas P. Simpson (Zimbabwe/South Africa), Chandni Singh (India), William Solecki (USA), \r Lindsay Stringer (UK), Edmond Totin (Benin), Christopher Trisos (South Africa), Yongyut Trisurat \r (Thailand), Maarten van Aalst (The Netherlands), David Viner (UK), Morgan Wairiu (Solomon \r [...]"


id: a4aefc52170af1b25efdbd621bb83d7a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 26189
content:
"[...] Islands), Rachel Warren (UK), Philippus Wester (Nepal/The Netherlands), David Wrathall (USA), \r Zelina Zaiton Ibrahim (Malaysia)"


id: e88caeca6e945e01a983527015a99ac9
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 38250
content:
"Portner, H.-O., D.C. Roberts, H. Adams, I. Adelekan, C. Adler, R. Adrian, P. Aldunce, E. Ali, R. Ara Begum, B. Bednar\u0002Friedl, R. Bezner Kerr, R. Biesbroek, J. Birkmann, K. Bowen, M.A. Caretta, J. Carnicer, E. Castellanos, T.S. Cheong, \r W. Chow, G. Cisse, S. Clayton, A. Constable, S.R. Cooley, M.J. Costello, M. Craig, W. Cramer, R. Dawson, D. Dodman, \r J. Efitre, M. Garschagen, E.A. Gilmore, B.C. Glavovic, D. Gutzler, M. Haasnoot, S. Harper, T. Hasegawa, B. Hayward, \r J.A. Hicke, Y. Hirabayashi, C. Huang, K. Kalaba, W. Kiessling, A. Kitoh, R. Lasco, J. Lawrence, M.F. Lemos, R. Lempert, \r C. Lennard, D. Ley, T. Lissner, Q. Liu, E. Liwenga, S. Lluch-Cota, S. Loschke, S. Lucatello, Y. Luo, B. Mackey, K. Mintenbeck, \r A. Mirzabaev, V. Moller, M. Moncassim Vale, M.D. Morecroft, L. Mortsch, A. Mukherji, T. Mustonen, M. Mycoo, J. Nalau, \r M. New, A. Okem, J.P. Ometto, B. O'Neill, R. Pandey, C. Parmesan, M. Pelling, P.F. Pinho, J. Pinnegar, E.S. Poloczanska, \r [...]"


id: bd218880dc7b2f186982d70df645b86a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 30528
content:
"[...] A. Prakash, B. Preston, M.-F. Racault, D. Reckien, A. Revi, S.K. Rose, E.L.F. Schipper, D.N. Schmidt, D. Schoeman, R. Shaw, \r N.P. Simpson, C. Singh, W. Solecki, L. Stringer, E. Totin, C.H. Trisos, Y. Trisurat, M. van Aalst, D. Viner, M.Wairiu, R.Warren, \r P.Wester, D.Wrathall, and Z. Zaiton Ibrahim, 2022: Technical Summary. [H.-O. Portner, D.C. Roberts, E.S. Poloczanska, \r K. Mintenbeck, M. Tignor, A. Alegria, M. Craig, S. Langsdorf, S. Loschke, V. Moller, A. Okem (eds.)]. In: Climate Change \r 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the \r Intergovernmental Panel on Climate Change [H.-O. Portner, D.C. Roberts, M. Tignor, E.S. Poloczanska, K. Mintenbeck, \r A. Alegria, M. Craig, S. Langsdorf, S. Loschke, V. Moller, A. Okem, B. Rama (eds.)]. Cambridge University Press, Cambridge, \r UK and New York, NY, USA, pp. 37-118, doi:10.1017/9781009325844.002."


id: 1abc1c3dc21498916a1f8ccbc1d86a33
created_at: 2023-04-19 13:22:50
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content_type: text
index: climate_gpt_v2
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content:
"This technical summary complements and expands the key findings of \r the Working Group (WG) II contribution to the Sixth Assessment Report \r (AR6) presented in the Summary for Policymakers and covers literature \r accepted for publication by 1 September 2021. It provides technical \r understanding and is developed from the key findings of chapters and \r cross-chapter papers (CCPs) as presented in their executive summaries \r and integrates across them. The report builds on the WGII contribution \r to the Fifth Assessment Report (AR5) of the IPCC and three special \r reports of the AR6 cycle providing new knowledge and updates. The \r three special reports are the Special Report on Global Warming of \r 1.5degC (2018), an IPCC special report on the impacts of global warming \r of 1.5degC above pre-industrial levels and related global greenhouse \r gas emission pathways in the context of strengthening the global \r response to the threat of climate change, sustainable development \r [...]"


id: c448b1af6a940cfeae197fe4adba1938
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 31823
content:
"[...] and efforts to eradicate poverty; the Special Report on Climate Change \r and Land, which is concerned with climate change, desertification, \r land degradation, sustainable land management, food security, and \r greenhouse gas fluxes in terrestrial ecosystems (2019); and the Special \r Report on the Ocean and Cryosphere in a Changing Climate (2019). \r The WGII assessment integrates with the WGI (the physical science \r basis) and WGIII (mitigation of climate change) contributions and \r contributes to the Synthesis Report."


id: 4e11de22df1b4b2feb03d6027b43cbe0
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11000
content:
"Confidence in the key findings of this assessment is communicated \r using the IPCC calibrated uncertainty language. This calibrated \r language is designed to consistently evaluate and communicate \r uncertainties that arise from incomplete knowledge due to a lack \r of information or from disagreement about what is known or even \r knowable. The IPCC calibrated language uses qualitative expressions \r of confidence based on the robustness of evidence for a finding \r and (where possible) uses quantitative expressions to describe the \r likelihood of a finding. Each finding is grounded in an evaluation of \r underlying evidence and agreement. A level of confidence is expressed \r using five qualifiers, very low, low, medium, high and very high, and \r typeset in italics, for example, medium confidence. The following terms \r have been used to indicate the assessed likelihood of an outcome or \r a result: virtually certain 99-100% probability, very likely 90-100%, \r [...]"


id: 69f53deac25ada7a5d5e6f505e449899
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updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
vector_id: 15905
content:
"[...] likely 66-100%, as likely as not 33-66%, unlikely 0-33%, very unlikely\r 0-10%, exceptionally unlikely 0-1%. Assessed likelihood is typeset in \r italics, for example, very likely. This is consistent with AR5 and the \r other AR6 reports. (Figure TS.1) {1.3.4}"


id: 7b3ba6637b8fe319f8db17c9add78835
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18880
content:
"The contribution of Working Group II (WGII) to the Sixth Assessment \r Report (AR6) of the IPCC summarizes the current understanding of \r observed climate change impacts on ecosystems, human societies \r and their cities, settlements, infrastructures and industrial systems, as \r well as vulnerabilities and future risks tied to different socioeconomic \r development pathways. The report is set against a current backdrop \r of rapid urbanisation, biodiversity loss, a growing and dynamic global \r human population, significant inequality and demands for social justice, \r rapid technological change, continuing poverty, land degradation \r and food insecurity, and risks from shocks such as pandemics and \r increasingly intense extreme events from ongoing climate change. \r The report also assesses existing adaptations and their feasibility and \r limits. Any success of adaptation is dependent on the achieved level of \r mitigation and the transformation of global and regional sustainability \r [...]"


id: 1a4b6170b9a49e10d62912a893d1817b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
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content:
"[...] outlined in the Sustainable Development Goals (SDGs). Accordingly, \r adaptation is essential for climate resilient development. Compared to \r earlier IPCC assessments, this report integrates more strongly across \r the natural, social and economic sciences, highlighting the role of social \r justice and diverse forms of knowledge, such as Indigenous knowledge \r and local knowledge, and reflects the increasing importance of urgent \r and immediate action to address climate risk. {1.1.1}"


id: 18caec8a2388cf046c6ad0ec679d6f3b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
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content:
"Vulnerability is a component of risk, but also, independently, an important focus. Vulnerability in this report is defined as the propensity \r or predisposition to be adversely affected and encompasses a variety of concepts and elements, including sensitivity or susceptibility \r to harm and lack of capacity to cope and adapt (Annex II: Glossary). Over the past several decades, approaches to analysing and \r assessing vulnerability have evolved. An early emphasis on top-down, biophysical evaluation of vulnerability included--and often started \r with--exposure to climate hazards in assessing vulnerability. From this starting point, attention to bottom-up, social and contextual \r determinants of vulnerability, which often differ, has emerged, although this approach is incompletely applied or integrated across \r contexts. Vulnerability is now widely understood to differ within communities and across societies, also changing through time. In WGII \r [...]"


id: 69a2baf2fa419c7a9099d68494500767
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content_type: text
index: climate_gpt_v2
vector_id: 15851
content:
"[...] AR6, assessment of the vulnerability of people and ecosystems encompasses the differing approaches that exist within the literature, \r both critiquing and harmonising them based on available evidence. In this context, exposure is defined as the presence of people; \r livelihoods; species or ecosystems; environmental functions, services and resources; infrastructure; or economic, social or cultural assets \r in places and settings that could be adversely affected. Potentially affected places and settings can be defined geographically, as well as \r more dynamically, for example through transmission or interconnections through markets or flows of people. {1.2.1, Annex II: Glossary}"


id: e4e4169f2928c601bd4bbf34750343b6
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 37555
content:
"Adaptation in this report is defined, in human systems, as the process of adjustment to actual or expected climate and its effects in \r order to moderate harm or exploit beneficial opportunities. In natural systems, adaptation is the process of adjustment to actual climate \r and its effects; human intervention may facilitate this (see Annex II: Glossary). Adaptation planning in human systems generally entails \r a process of iterative risk management. Different types of adaptation have been distinguished, including anticipatory versus reactive, \r autonomous versus planned and incremental versus transformational adaptation. Adaptation is often seen as having five general stages: \r (a) awareness, (b) assessment, (c) planning, (d) implementation and (e) monitoring and evaluation. Government, non-government, and \r private-sector actors have adopted a wide variety of specific approaches to adaptation that, to varying degrees, conform to these five \r [...]"


id: 458ba11199084d8b12fc0c734c5e9426
created_at: 2023-04-19 13:22:50
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content:
"[...] general stages. Adaptation in natural systems includes autonomous adjustments through ecological and evolutionary processes. It also \r involves the use of nature through ecosystem-based adaptation. The role of species, biodiversity and ecosystems in such adaptation \r options can range from the rehabilitation or restoration of ecosystems (e.g., wetlands or mangroves) to hybrid combinations of so\u0002called green and grey infrastructure (e.g., horizontal levees). The WGII AR6 emphasises the assessment of observed adaptation-related \r responses to climate change, governance and decision-making in adaptation and the role of adaptation in reducing key risks and global\u0002scale reasons for concern, as well as limits to such adaptation. {1.2.1, 17.4}"


id: abdd69b08860fd1aab602f29186fe4b3
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 27476
content:
"Assessments of climate risks consider possible future climate change, societal development and responses. This report assesses literature \r including that based on climate model simulations that are part of the fifth and sixth Coupled Model Intercomparison Project phase \r (CMIP5, CMIP6) of the World Climate Research Programme. Future projections are driven by emissions and/or concentrations from \r illustrative Representative Concentration Pathways (RCPs)1\r  and Shared Socio-economic Pathways (SSPs)2 scenarios, respectively3. Climate \r impacts literature is based primarily on climate projections assessed in AR5 or earlier, or assumed global warming levels, though some \r recent impacts literature uses newer projections based on the CMIP6 exercise. Given differences in the impacts literature regarding \r socioeconomic details and assumptions, WGII chapters contextualize impacts with respect to exposure, vulnerability and adaptation as \r [...]"


id: ec5109ea8210cf3ca136f45bd14aa915
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 38942
content:
"[...] appropriate for their literature, this includes assessments regarding sustainable development and climate resilient development. There are \r many emissions and socioeconomic pathways that are consistent with a given global warming outcome. These represent a broad range \r of possibilities as available in the literature assessed that affect future climate change exposure and vulnerability. Where available, WGII \r also assesses literature that is based on an integrative SSP-RCP framework where climate projections obtained under the RCP scenarios \r are analysed against the backdrop of various illustrative SSPs2\r . The WGII assessment combines multiple lines of evidence including \r impacts modelling driven by climate projections, observations, and process understanding. {1.2, 16.5, 18.2, CCB CLIMATE, WGI AR6 \r SPM.C, WGI AR6 Box SPM.1, WGI AR6 1.6, WGI AR6 12, WGI AR5}"


id: 122d78e339ac9d877c9109acb94ad4a4
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 389
content:
"[...] and coastal flooding. RFC3: Distribution of impacts: risks/impacts that disproportionately affect particular groups due to uneven distribution of physical climate change hazards, \r exposure or vulnerability. RFC4: Global aggregate impacts: impacts to socio-ecological systems that can be aggregated globally into a single metric, such as monetary damages, lives \r affected, species lost or ecosystem degradation at a global scale. RFC5: Large-scale singular events: relatively large, abrupt and sometimes irreversible changes in systems caused \r by global warming, such as ice sheet disintegration or thermohaline circulation slowing. Assessment methods are described in SM16.6 and are identical to AR5, but are enhanced \r by a structured approach to improve robustness and facilitate comparison between AR5 and AR6. Risks for (c) terrestrial and freshwater ecosystems and (d) ocean ecosystems. "


id: 3a70a3547d08bfcd337039d074772071
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 7481
content:
"(f) Examples of regional key risks. Risks identified are of at least medium confidence level. Key risks are identified based on the magnitude of adverse consequences (pervasiveness \r of the consequences, degree of change, irreversibility of consequences, potential for impact thresholds or tipping points, potential for cascading effects beyond system boundaries); \r likelihood of adverse consequences; temporal characteristics of the risk; and ability to respond to the risk, e.g., by adaptation. The full set of 127 assessed global and regional key \r risks is given in SMTS.4 and SM16.7. Diagrams are provided for some risks. The development of synthetic diagrams for Small Islands, Asia and Central and South America were \r limited by the availability of adequately downscaled climate projections, with uncertainty in the direction of change, the diversity of climatologies and socio-economic contexts \r [...]"


id: f4357f7ed039e52348c4b559a0e62635
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 40335
content:
"[...] across countries within a region, and the resulting low number of impact and risk projections for different warming levels. Absence of risks diagrams does not imply absence \r of risks within a region. (Box TS.2) {Figure 2.11, Figure SM3.1, Figure 7.9, Figure 9.6, Figure 11.6, Figure 13.28, 16.5, 16.6, Figure 16.15, SM16.3, SM16.4, SM16.5, SM16.6 \r (methodologies), SM16.7, Figure CCP4.8, Figure CCP4.10, Figure CCP6.5, WGI AR6 2, WGI AR6 SPM A.1.2, WGI AR6 Figure SPM.8}"


id: 57395097f8be8b9ec14babaecc8ccec4
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 12600
content:
"are estimated to increase nutrition-related diseases and the number of \r undernourished people by 2050, affecting tens (under low vulnerability \r and low warming) to hundreds of millions of people (under high \r vulnerability and high warming, i.e., SSP-3-RCP6.0), particularly among \r low-income households in low- and middle-income countries in sub\u0002Saharan Africa, South Asia and Central America (high confidence), for \r example, between 8 million under SSP1-6.0 to up to 80 million people \r under SSP3-6.0. At 3degC or higher global warming levels, adverse \r impacts on all food sectors will become prevalent, further stressing \r food availability (high confidence), agricultural labour productivity and \r food access (medium confidence). Regional disparity in risks to food \r security will grow at these higher warming levels, increasing poverty \r traps, particularly in regions characterised by a high level of human \r vulnerability (high confidence). {4.5.1, 4.6.1, 5.2.2, 5.4.3, 5.4.4, 5.5.3, \r [...]"


id: 74cbbca4206be988b3d82164ea9f2538
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 17786
content:
"[...] 5.8.3, 5.9.3, 5.12.4, 7.3.1, 9.8.2, 9.8.5, 13.5.1, 14.5.4, 16.5.2, 16.6.3, \r CCB MOVING PLATE}"


id: a94141213538a2f2f5bf4bf35714e55a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 27000
content:
"decrease by 5.7% +- 4.1% and 15.5% +- 8.5% under SSP1-2.6 and \r SSP5-8.5 respectively by 2080-2099 relative to 1995-2014 (medium \r confidence), affecting food provisioning, revenue value and distribution. \r Catch composition will change regionally, and the vulnerability of \r fishers will partially depend on their ability to move, diversify and \r leverage technology (medium confidence). Global marine aquaculture \r will decline under increasing temperature and acidification conditions \r by 2100, with potential short-term gains for finfish aquaculture in \r some temperate regions and overall negative impacts on bivalve \r aquaculture due to habitat reduction (medium confidence). Changes \r in precipitation, sea level rise, temperature and extreme events will \r negatively affect food provisioning from inland aquatic systems \r (medium confidence), which provide a significant source of livelihoods \r and food for direct human consumption, particularly in Asia and Africa. \r [...]"


id: 41a99f8f9a9360f9b71da9633e1411bd
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 8741
content:
"[...] {3.4.2, 3.4.3, 3.5.3, 3.6.2, 3.6.3, 5.8.3, 5.9.3, 5.13, 9.8.5, 13.5.1, 14.5.2, \r CCP6.2.3, CCP6.2.4, CCP6.2.5, CCP6.2.6, CCP6.2.8, CCB MOVING \r PLATE, CCB SLR}"


id: 56e482196884b90570598e6be769b760
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 12536
content:
"TS.C.6.4 Climate impacts on food systems are projected to \r increase undernutrition and diet-related mortality and risks \r globally (high confidence). Reduced marine and freshwater fisheries \r catch potential is projected to increase malnutrition in East, West \r and Central Africa (medium to high confidence) and in subsistence\u0002dependent communities across North America (high confidence). \r By 2050, disability-adjusted life years due to undernutrition and \r micronutrient deficiencies are projected to increase by 10% under \r RCP8.5 (medium evidence, high agreement). These projected changes \r will increase diet-related risk factors and related non-communicable \r diseases globally and increase undernutrition, stunting and related \r childhood mortality, particularly in Africa and Asia (high confidence). \r Near-term projections (2030) of undernutrition are the highest for \r children (confidence), which can have lifelong adverse consequences \r [...]"


id: 1e9f9ab29170727d9ad919d9362f11df
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 2591
content:
"[...] for physiological and neurological development as well as for earnings \r capacity. Climate change is projected to put 8  million (SSP1-6.0) \r to 80  million people (SSP3-6.0) at risk of hunger in mid-century, \r concentrated in sub-Saharan Africa, South Asia and Central America \r (high confidence). These climate change impacts on nutrition could \r undermine progress towards the eradication of child undernutrition \r (high confidence). {4.5.3, 5.2.2, 5.12.4, Box 5.10, 7.3.1, 9.8.5, 9.10.2, \r 10.4.7, Figure  10.11, 13.7.1, 14.5.6, 15.3.4, CCP6.2, CCB MOVING \r PLATE}"


id: b4418cfb7b4e87712d0ff0d0a298a01c
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 28947
content:
"TS.C.6.5 Vector-borne disease transmission is projected to \r expand to higher latitudes and altitudes, and the duration \r of seasonal transmission risk is projected to increase (high \r confidence), with the greatest risk under high emissions \r scenarios. Dengue vector ranges will increase in North America, Asia, \r Europe and sub-Saharan Africa under RCP6 and RCP8.5, potentially \r putting another 2.25 billion people at risk (high confidence). Higher \r incidence rates of Lyme disease are projected for the Northern \r Hemisphere (high confidence). Climate change is projected to increase \r malaria's geographic distribution in endemic areas of sub-Saharan \r and southern Africa, Asia and South America (high confidence), \r exposing tens of millions more people to malaria, predominately \r in east and southern Africa, and up to hundreds of millions more \r exposed under RCP8.5 (high confidence). {7.3.1, 9.10.2, Figure 9.32, \r [...]"


id: 19d8e143632c3eec1c871fde707393a8
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 1744
content:
"[...] 10.4.7, Figure 10.11, 11.3.6, 12.3.2, 12.3.5, 12.3.6, Figure 12.5, 13.7.1, \r Figure 13.24, 14.5.6, 15.3.4, CCB ILLNESS}"


id: 8efc77c3d262eab0613403eaeabbb961
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 22347
content:
"TS.C.7.1 Future climate-related migration is expected to vary \r by region and over time, according to future climatic drivers, \r patterns of population growth, adaptive capacity of exposed \r populations and international development and migration \r policies (high confidence). Future migration and displacement \r patterns in a changing climate will depend not only on the physical \r impacts of climate change, but also on future policies and planning at \r all scales of governance (high confidence). Projecting the number of \r people migrating due to slow onset events is difficult due to the multi\u0002causal nature of migration and the dominant role that socioeconomic \r factors have in determining migration responses (high confidence). \r Increased frequency of extreme heat events and long-term increases \r in average temperatures pose future risks to the habitability of \r settlements in low latitudes; this, combined with the urban heat island \r [...]"


id: 7bf48a47bfff2292fe81f1dbfa427487
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 19017
content:
"[...] effect, may in the long term affect migration patterns in exposed areas, \r especially under high emissions scenarios, but more evidence is needed.\r High emissions/low development scenarios raise the potential for both \r increased rates of migration and displacement and larger involuntary \r immobile populations that are highly exposed to climatic risks but lack \r the means of moving to other locations (medium confidence). {4.5.7, "


id: b6a1ed0b3af024eb3e481b594933f638
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 29333
content:
"TS.C.9 Climate change increases risks for a larger number of \r growing cities and settlements across wider areas, especially in \r coastal and mountain regions, affecting an additional 2.5 billion \r people residing in cities mainly in Africa and Asia by 2050 (high \r confidence). In all cities and urban areas, projected risks faced \r by people from climate-driven impacts has increased (high \r confidence). Many risks will not be felt evenly across cities and \r settlements or within cities. Communities in informal settlements \r will have higher exposure and lower capacity to adapt (high \r confidence). Most at risk are women and children who make up \r the majority populations of these settlements (high confidence). \r Risks to critical physical infrastructure in cities can be severe \r and pervasive under higher warming levels, potentially resulting \r in compound and cascading risks, and can disrupt livelihoods \r both within and across cities (high confidence). In coastal cities \r [...]"


id: 87e788140ce12ed2f728abf1c55d9f48
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 21066
content:
"[...] and settlements, risks to people and infrastructure will get \r progressively worse in a changing climate, sea level rise and with \r ongoing coastal development (very high confidence). {2.6.5, 6.1, \r 6.1.4, 6.2, 9.9.4, 16.5, 14.5.5, Box 14.4, CCP2.2}"


id: c0effec5b77e10f3c44920a6f195176f
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 31247
content:
"TS.C.9.2 Asian and African urban areas are considered high-risk \r locations from projected climate, extreme events, unplanned \r urbanisation and rapid land use change (high confidence). These \r could amplify pre-existing stresses related to poverty, informality, \r exclusion and governance, such as in African cities (high confidence). \r Climate change increases heat stress risks in cities (high confidence) \r and amplifies the urban heat island across Asian cities at 1.5degC and \r 2degC warming levels, both substantially larger than under present \r climates (medium confidence). Urban population exposure to extreme \r heat in Africa is projected to increase from 2 billion person-days per \r year in 1985-2005 to 45  billion person-days by the 2060s (1.7degC \r global warming with low population growth) and to 95 billion person\u0002days (2.8degC global warming with medium-high population growth) \r (medium confidence). Risks driven by flooding and droughts will also \r [...]"


id: af20b488dec59116ecebeb1626b7b497
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 28057
content:
"[...] increase in cities (high confidence). Urban populations exposed to \r severe droughts in West Africa will increase (65.3+-34.1  million) at \r 1.5degC warming and increase further at 2degC (medium confidence). \r Urban land in flood zones and drylands exposed to high-frequency \r floods is expected to increase by as much as 2600% and 627% \r respectively across East, West and Central Africa by 2030. Higher \r risks from temperature and precipitation extremes are projected for \r almost all Asian cities under RCP8.5 (medium confidence), impacting \r on freshwater availability, regional food security, human health and \r industrial outputs. {4.3.4, 4.3.5, 4.5.4, 6.1, 6.2, Table 6.3, Table 6.4, \r 9.9.4, 10.3.7, 10.4.6, 15.3.3, 15.3.4, 15.4.3, CCP2.2, CCP6.2.7, CWGB \r URBAN}"


id: 51680de9310bd5ea2363d06b8ae07e6a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11600
content:
"TS.C.9.3 Globally, urban key infrastructure systems are \r increasingly sites of risk creation that potentially drive \r compounding and cascading risks (high confidence). Unplanned \r rapid urbanisation is a major driver of risk, particularly where \r increasing climate-driven risks affect key infrastructure and potentially \r result in compounding and cascading risks as cities expand into \r coastal and mountain regions prone to flooding or landslides that \r disrupt transportation networks, or where water and energy resources \r are inadequate to meet the needs of growing settlements (high \r confidence). These infrastructure risks expand beyond city boundaries; \r climate-related transport and energy infrastructure damage is \r projected to be a significant financial burden for African countries, \r reaching tens to hundreds of billions of US dollars under moderate \r and high emissions scenarios (high confidence). Projected changes \r [...]"


id: fefe4511997747491144f338b6165a51
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 42262
content:
"[...] in both the hydrological cycle and the cryosphere will threaten urban \r water infrastructure and resource management in most regions \r (very high confidence). South and Southeast Asian coastal cities can \r experience significant increases in average annual economic losses \r between 2005 and 2050 due to flooding, with very high losses in \r east Asian cities under RCP8.5 (high confidence). By 2050, permafrost \r thaw in the pan-Arctic is projected to impact 69% of infrastructure, \r more than 1200 settlements, 36,000 buildings, and 4 million people \r in Europe under RCP4.5. In small islands, degraded terrestrial \r ecosystems decrease resource provision (e.g., potable water) and \r amplify the vulnerability of island inhabitants (high confidence). \r Projections suggest that 350 million (+- 158.8 million) more people in \r urban areas will be exposed to water scarcity from severe droughts \r at 1.5degC warming and 410.7 million (+- 213.5) at 2degC warming (low \r [...]"


id: 723d01ebbe857f9fb0689d33a71e289f
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 17340
content:
"TS.C.10.1 Without limiting warming to 1.5degC global warming \r level, many key risks are projected to intensify rapidly in \r almost all regions of the world, causing damage to assets and \r infrastructure and losses to economic sectors and entailing high \r recovery and adaptation costs (high confidence). Severe risks are \r more likely in developing regions that are already hotter and in regions \r and communities with a large portion of the workforce employed \r in highly exposed industries (e.g., agriculture, fisheries, forestry, \r tourism, outdoor labour). In addition to market damage and disaster \r management costs, substantial costs of climate inaction are projected \r for human health (high confidence). At higher levels of warming, climate \r impacts will pose risks to financial and insurance markets, especially if \r climate risks are incompletely internalised (medium confidence), with \r adverse implications for the stability of markets (low confidence). While \r [...]"


id: 6b498cb4ce53ce4c1dbdf886502e74a3
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 16175
content:
"[...] the overall economic consequences are clearly negative, opportunities \r may arise for a few economic sectors and regions, such as from longer \r growing seasons or reduced sea ice, primarily in northern latitudes \r (medium to high confidence). {4.4.4, 4.7.5, 9.11.2, 10.4.6, 11.6, 13.9.2, \r 13.10.3, 14.5.4, 14.5.5, 14.5.7, 14.5.8, 14.5.9, Box  14.5, Box  14.6, \r 16.5.2, 16.5.3, CCP4.2, CCP6.2, CCB INTEREG}"


id: 26c859658d2635c18ba4535c62acbaf
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 3978
content:
"increased relative to the range reported in AR5, though there is low \r agreement and significant spread within and across methodology types \r (e.g., statistical, structural, meta-analysis), resulting in an inability to \r identify a best estimate or robust range (high confidence). Under high \r warming (>4degC) and limited adaptation, the magnitude of decline in \r annual global GDP in 2100 relative to a non-global-warming scenario \r could exceed economic losses during the Great Recession in 2008-\r 2009 and the COVID-19 pandemic in 2020. Much smaller effects are \r estimated for less warming, lower vulnerability and more adaptation \r (medium confidence). Regional estimates of GDP damage vary (high \r confidence). Severe risks are more likely in (typically hotter) developing \r countries (medium confidence). For Africa, GDP damage is projected to \r be negative across models and approaches (high confidence). {4.4.4, \r 4.7.5, 9.11.2, 10.4.6, 13.10.2, 13.10.3, 14.5.8, Box 14.6, 16.5.2, 16.6.3, \r [...]"


id: 17832270d68ec0841308a30a15d68f4
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 1346
content:
"TS.C.11.2 Climate hazards cause multiple impacts, interacting \r to compound risks to food security, nutrition and human health \r (high confidence). Compound risks to health and food systems \r (especially in tropical regions) are projected from simultaneous \r reductions in food production across crops, livestock and fisheries \r (high confidence), heat-related loss of labour productivity in \r agriculture (high confidence), increased heat-related mortality (high \r confidence), contamination of seafood (high confidence), malnutrition \r (high confidence) and flooding from sea level rise (high confidence). \r Malnourished populations will increase through direct impacts on \r food production with cascading impacts on food prices and household \r incomes, reducing access to safe and nutritious food (high confidence). \r Food safety will be undermined from increased food contamination \r for seafood with marine toxins from harmful algal blooms and \r [...]"


id: 517114eb6cf6d03b2b9a0b0fb71c4dd0
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11609
content:
"[...] chemical contaminants, worsening health risks (high confidence). \r (Figure TS.10 COMPLEX RISK) {4.5.1, 5.2.2, 5.4.3, 5.8.1, 5.8.3, 5.11.1, \r 5.12, Figure 5.2, 5.12.4, Box 5.10, 7.3.1, 9.10.2, 9.8.2, 9.8.3, 14.5.6, \r CCP5.2.3, CCP6.2.3, CCB ILLNESS}"


id: 5d0a7ece71f0b9c1abe1748f61711132
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 13636
content:
"TS.C.13.4 Solar radiation modification (SRM) approaches have \r the potential to offset warming and ameliorate other climate \r hazards, but their potential to reduce risk or introduce novel \r risks to people and ecosystems is not well understood (high \r confidence). SRM effects on climate hazards are highly dependent \r on deployment scenarios, and substantial residual climate change or \r overcompensating change would occur at regional scales and seasonal \r time scales (high confidence). Due in part to limited research, there is \r low confidence in projected benefits or risks to crop yields, economies, \r human health or ecosystems. Large negative impacts are projected \r from rapid warming for a sudden and sustained termination of SRM \r in a high-CO2 scenario. SRM would not stop CO2 from increasing in the \r atmosphere or reduce resulting ocean acidification under continued \r anthropogenic emissions (high confidence). There is high agreement \r [...]"


id: cb8dd8a2af21b2785f33d62abc0565cb
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 33142
content:
"[...] in the literature that for addressing climate change risks SRM is, at \r best, a supplement to achieving sustained net zero or net negative CO2\r emission levels globally. Co-evolution of SRM governance and research \r provides a chance for responsibly developing SRM technologies with \r broader public participation and political legitimacy, guarding against \r potential risks and harms relevant across a full range of scenarios. \r {CWGB SRM}"


id: c89513f0ca125c3938dc5abd08b5b1a9
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 32606
content:
"Figure TS.5 ECOSYSTEMS  | (a) Left: Observed global and regional impacts on ecosystems and human systems attributed to climate change. Confidence levels reflect uncertainty \r in attribution of the observed impact to climate change. For more details and line of sight to chapters and cross-chapter papers see Figure TS.3a, SMTS.1 and Table SMTS.1. Right: \r Observed species richness across latitude for three historical periods. {3.4.3, Figure 3.18}. (b) Left: Global warming levels (GMST) modelled across the ranges of more than 30,000 \r marine and terrestrial species. Middle: Global warming levels (GSAT); change indicated by the proportion of species (modelled n=119,813 species globally) for which the climate \r is projected to become unsuitable across their current distributions. Right: Modelled 12,796 marine species globally. {2.5.1, Figure 2.6, 3.4.3, Figure 3.18, Figure 3.20a, CCP1.2.4, \r [...]"


id: 8557f86be9e20b30aa485555fe8e2167
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 20596
content:
"[...] Figures AI.6, AI.15, AI.16}. (c) {2.6.2, Table 2.6, 3.6.2, Figure 3.24}. (d) Some actions facilitate sustainable use but also increase space for nature. {2.4 2, 2.6.2, 2.6.3, 2.6.5, 2.6.7, \r 2.6.8, 3.6.2, 3.6.5, Table 3.30, 5.6.3, Box 5.11, 9.3.1, 9.3.2, 9.6.3, 9.6.4, 9.12 .3, 10.4.2, 10.4.3, 11.3.1, 11 .3.2, 11 .7.3, 12.5. 1, 12. 5.2, 12.5.9, 12.6.1, 13.3.2, 13.4.2, 13.5 \r .2, 13.10.2, 14.5.1, 14.5.2, Box 14.2, Box 14.7, 15.5.4, 15.3.3, Table 15 .6, 16.5.2, 16.6.3, CCP1.3, CCP3. 2.2, CCP4.4.1, CCP5 .2.5, CCP5.4.1, CCP6.3.2, CCP7.5, CCP7 .5. 1, \r CCPBox7.1, Table CCP7 .3, CCB EXTREMES, CCB NATURAL}"


id: 78d2da1fdeb5ccbcd386a4e7b4e7367b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18446
content:
"Figure TS.6 FOOD-WATER | (a) {5.4.1.1, Box 5.1, FAQ 5.1, SM5.1, Figure Al.20}. (b) Projected increase in the global share of area and population impacted from droughts. \r Changes are calculated based on the RCP6.0 concentration pathway for Terrestrial Water Storage (TWS) droughts, which can be considered to be a combination of agricultural, \r ecological and hydrological droughts. TWS is the sum of continental water stored in canopies, snow and ice, rivers, lakes and reservoirs, wetlands, soil and groundwater. {Figure 4.19; \r 4.4.5}. (c) Projected impacts are for RCP4.5 mid 21st century, taking into account adaptation and CO2 fertilisation for the crop yield productivity {4.3.1, 4.2.7, 4.5.1, Figure 4.2, \r 5.5.3, 5.4.1, Figure 5.3, Figure 9.22, 15.3.3, 15.3.4}. (d) Projections used five CMIP5 climate models, three global hydrological models from ISIMIP, and three Shared Socioeconomic \r [...]"


id: f47db9accd1c84cb4ee73586176522f0
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 40390
content:
"[...] Pathways (SSPs).{Box 4.1, Figure Box 4.1.1, Figure AI.48}. (e) {4.6.2, Figure 4.29, Figure 4.28, SM4.7, SM4.8, 5.5.4, 5.6.3}."


id: 6f0ee2cc18400dc7c32e9ef98454321c
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 16806
content:
"Figure TS.7 VULNERABILITY | (a) The global map of vulnerability is based on two comprehensive global indicator systems, namely INFORM Risk Index and WorldRiskIndex \r (2019). Climate change hazards and exposure levels are not included in this figure. The relative level of average national vulnerability is shown by the colours. Vulnerability values \r are based on the average of the two indices, classified into 5 classes using the quantile method. A hexagon binning method was used to simplify the global map and enlarge small \r states. The map combines information about the level of vulnerability (independent of the population size) with two classes of population density (high density >= 20 people/km2 \r and low density < 20 people/km2). The selected examples of local vulnerable populations underscore that there are also highly vulnerable populations in countries with overall low \r [...]"


id: ee515f7a9099d6cfe1515f09974be423
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 39300
content:
"[...] relative vulnerability {8.3.2, Figure 8.6} (b) This figure shows regional averages for selected aspects of human vulnerability. The indicators are a selection of the indicator systems \r used within the global vulnerability map (panel a). The colours represent the average value of the respective indicator for the regional level; classified into three classes using natural \r breaks. This regional information reveals that within all regions challenges exist in terms of different aspects of vulnerability, however, in some regions these challenges are more \r severe and accumulate in multiple-dimensions. For example, the indicator \"dependency ratio\" measures the ratio of the number of children (0-14 years old) and older persons \r (65 years or over) to the working-age population (15-64 years old). {8.3.2, Figure 8.7} (c) The pie charts show the number of deaths (mortality) per hazard (storm, flood, drought, \r [...]"


id: 37e9dc7bf805cf840db86a1bf8c653b4
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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content:
"[...] heatwaves and wildfires) event per continental region based on Emergency Events Database (EM-DAT) (Centre for Research on the Epidemiology of Disasters, 2020). The size of the \r pie chart represents the average mortality per hazard event while slices of each pie chart show the absolute number of deaths from each hazard. This reveals that significantly more \r fatalities per hazard (storms, floods, droughts, heatwaves and wildfires) did occur in the past decade in more vulnerable regions, e.g. Africa and Asia. {Figure 8.6} (d) The figure \r shows constraints that make it harder to plan and implement human adaptation. Across regions and sectors, the most significant challenges to human adaptation are financial, \r governance, institutional and policy constraints. The ability of actors to overcome these socio-economic constraints largely influences whether additional adaptation is able to be \r [...]"


id: 718d96faf5c12e12fb4cdcd1a983d733
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
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content:
"[...] implemented and prevent limits to adaptation from being reached. Low: <20% of assessed literature identifies this constraint; Medium: 20-40% of assessed literature identifies \r this constraint; High: >40% of assessed literature identifies this constraint. {9.3, 16.4.3, Figure 16.8}"


id: 1ddcd0f952a63b74201b6db70c7afdad
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 2444
content:
"TS.D.1.5 Systemic barriers constrain the implementation of \r adaptation options in vulnerable sectors, regions and social \r groups (high confidence). Key barriers are limited resources, lack \r of private-sector and citizen engagement, insufficient mobilisation of \r finance (including for research), lack of political leadership, limited \r research and/or slow and low uptake of adaptation science and \r a low sense of urgency. Most of the adaptation options to the key \r risks depend on limited water and land resources (high confidence). \r Governance capacity, financial support and the legacy of past urban \r infrastructure investment constrain how cities and settlements \r are able to adapt (high confidence). Critical urban capacity gaps \r include limited ability to identify social vulnerability and community \r strengths, the absence of integrated planning to protect communities, \r the lack of access to innovative funding arrangements and a limited \r [...]"


id: b07fc737123192855e17032479288691
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 28288
content:
"[...] capability to manage finance and commercial insurance (medium \r confidence). Prioritisation of options and transitions from incremental \r to transformational adaptation are limited due to vested interests, \r economic lock-ins, institutional path dependencies and prevalent \r practices, cultures, norms and belief systems. For example, Africa faces \r severe climate data constraints and inequities in research funding and \r leadership that reduce adaptive capacity (very high confidence)--from \r 1990 to 2019 research on Africa received just 3.8% of climate-related \r research funding globally, and 78% of this funding for Africa went \r to European Union- and North America-based institutions and only \r 14.5% to African institutions. {3.6.3, 9.1.5, 9.5.1, 9.8.4, 12.5.1, 12.5.5, \r 12.5.7, 12.8, 13.11, 14.7.2, 15.6.1, 15.7, CCP7.6, CCB FEASIB}"


id: 99296fe681d31d045f4c60f29cd5ee9e
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 24159
content:
"TS.D.2 There is increasing evidence on limits to adaptation \r which result from the interaction of adaptation constraints \r and the speed of change (high confidence). In some natural \r systems, hard limits have been reached (high confidence) and \r more will be reached beyond 1.5degC (medium confidence). \r Surpassing such hard, evolutionary limits causes local species \r extinctions and displacements if suitable habitats exist (high \r confidence). Otherwise, species' existence is at very high risk \r (high confidence). In human, managed and natural systems, soft \r limits are already being experienced (high confidence). Financial \r constraints are key determinants of adaptation limits in human \r and managed systems, particularly in low-income settings \r (high confidence), while in natural systems key determinants \r for limits are inherent traits of the species or ecosystem (very \r high confidence). (Figure TS.7 VULNERABILITY) {2.4.2, 2.6.1, 3.3, \r [...]"


id: cd8ecd24a6e35b29eb78f15a046706d0
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 33500
content:
"TS.D.1.6 Insufficient financing is a key driver of adaptation gaps \r (high confidence). Annual finance flows targeting adaptation \r for Africa, for example, are billions of US dollars less than the \r lowest adaptation cost estimates for near-term climate change \r (high confidence). Finance has not targeted more vulnerable countries \r and communities. From 2014 to 2018 a greater amount of financial \r commitments to developing countries was in the form of debt rather \r than grants, and--excluding multilateral development banks--only \r 51% of commitments targeting adaptation were dispersed (compared \r to 85% for other development projects). Tracked private-sector finance \r for climate change action has grown substantially since 2015, but \r the proportion directed towards adaptation has remained small (high \r confidence); in 2018 contributions were 0.05% of total climate finance \r and 1% of adaptation finance. Globally, private-sector financing of \r [...]"


id: d2c101e793ee188b0d924bf93cb04b6b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
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content:
"[...] adaptation has been limited, especially in developing countries (high \r confidence). {3.6.3, 4.7,4, 4.7.5, 4.8.2, 6.4.5, Table 6.10, 9.4.1, 12.5.4, \r 12.5.8, 15.6.3, 17.4.3, CCB FINANCE}"


id: 31749d1a5c2e00f95349781716e08601
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 5942
content:
"TS.D.2.2 Limits to adaptation have been observed for terrestrial \r and aquatic species and ecosystems and for some human and \r managed systems in specific geographies such as small island \r states and mountain regions (high confidence). Beginning at \r below 1.5degC, autonomous and evolutionary adaptation responses \r by more terrestrial and aquatic species and ecosystems will face hard \r limits, resulting in species extinctions, loss of ecosystem integrity and \r a resulting loss of livelihoods (high confidence). Examples of hard \r limits being exceeded include observed population losses and species \r extinctions and loss of whole ecosystems from certain locations (e.g., \r irrecoverable loss of tropical coral reefs locally). Large local population \r declines of wild species have already impacted human food sources \r and livelihoods (e.g., for Indigenous Arctic communities). Soft limits are \r currently being experienced in particular by individuals, households, cities \r [...]"


id: 9b57ade15174d97207a235307cea99bb
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 24580
content:
"[...] and settlements along the coast and by small-scale farmers (medium \r confidence). As sea levels rise and extreme events intensify, coastal \r communities face limits due to financial, institutional and socioeconomic \r constraints and a short timeline for adaptation implementation, reducing "


id: c8f903324436f451dbf8d4db5474d64b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 32678
content:
"them of food and livelihoods and reinforces and entrenches \r existing inequalities (high confidence). Rights-based approaches \r to adaptation, participatory methodologies and inclusion of local \r and Indigenous knowledge, combined with informed consent, deliver \r mechanisms to avoid these pitfalls (medium confidence). Adaptation \r solutions benefit from engagement with Indigenous and marginalised \r groups, solve past equity and justice issues and offer novel approaches \r (medium confidence). Indigenous knowledge is a powerful tool to \r assess interlinked ecosystem functions across terrestrial, marine and \r freshwater systems, bypassing siloed approaches and sectoral problems \r (high confidence). Lastly, engagement with Indigenous knowledge \r and marginalised groups often offers an intergenerational context for \r adaptation solutions needed to avoid maladaptation (high confidence). \r {2.6.5, 4.6.9, 8.4, 8.4.5, 5.12.8, 5.13.4, 11.4.1, 11.4.2, 12.5.8, 13.8.1, \r [...]"


id: a7111eea879f01ba7bbf7d76a9e80cb3
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 26607
content:
"TS.D.4 Diverse, self-sustaining ecosystems with healthy bio\u0002diversity provide multiple contributions to people that are \r essential for climate change adaptation and mitigation, thereby \r reducing risk and increasing societal resilience to future climate \r change (high confidence). Better ecosystem protection and \r management is key to reduce the risks that climate change poses \r to biodiversity and ecosystem services and build resilience; it \r is also essential that climate change adaptation be integrated \r into the planning and implementation of conservation and \r environmental management if it is to be fully effective in future \r (high confidence). Risks to ecosystems from climate change can \r be reduced by protection and restoration and also by a range \r of targeted actions to adapt conservation practice to climate \r change (high confidence). Protected areas are key elements of \r adaptation but need to be planned and managed in ways that \r [...]"


id: 4e9390c23fd19b94218a7c16ce5fb279
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11093
content:
"[...] take account of climate change, including shifting species distri\u0002butions and changes in biological communities and ecosystem \r structure. Adaptation to protect ecosystem health and integrity \r is essential to maintain ecosystem services, including for climate \r change mitigation and the prevention of greenhouse gas \r emissions. (Figure TS.12, Figure TS.5 ECOSYSTEMS) {2.5.4, 2.6.2, \r 2.6.3, 2.6.6, 2.6.7, 3.6.2, 3.6.3, 3.6.5, 4.6.6, Box  4.6, 5.14.1, \r 12.5.1, 13.3.2, 13.4.2, Box 14.7, 15.5.4, 15.5.6, CCP1, CCP5.4.1, \r CCP5.4.2, CCB NATURAL}"


id: aa2559ab428288c4f48ef1e81f474750
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 27157
content:
"TS.D.3.3 Reliance on hard protection against sea level rise can \r lead to development intensification, which compounds risk and \r locks in exposure of people and assets as socioeconomic and \r governance barriers and technical limits are reached. Avoiding \r maladaptive responses to sea level rise depends on immediate mitigation \r and application of adaptive planning that sets out near-term, low-regret \r actions while keeping open options to account for ongoing committed \r sea level rise (very high confidence). Such forward-looking adaptive \r pathway planning and iterative risk management can address the \r current path dependencies that lead to maladaptation and can enable \r timely adaptation alignment with long implementation lead times, as \r well as addressing uncertainty about rate and magnitude of local sea \r level rise, and ensuring that adaptation will be more effective (medium \r confidence). As sea level rise advances, only avoidance and relocation \r [...]"


id: 3aa542e1892e3d1246498a1fb3c27b01
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 7524
content:
"[...] will eliminate coastal risks (high confidence). Other measures only \r delay impacts for a time, increasing residual risk, perpetuating risk and \r creating ongoing legacy effects and inevitable property and ecosystem \r losses (high confidence). While relocation may in the near term appear \r socially unacceptable, economically inefficient or technically infeasible, \r it may become the only feasible option as protection costs become \r unaffordable and technical limits are reached (medium confidence). \r {3.4.2, 3.5.5, 3.6.3, 11.7.3, Box  11.6, 12.5.7, 12.5.8, 13.10, 15.3.4, \r 15.5.1, 15.5.2, 15.5.3, CCP2.2.3, CCP4, CCB DEEP, CCB SLR}"


id: d218a960f98f23721bcc00a467dbb7fe
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
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vector_id: 34317
content:
"TS.D.4.1 Ecosystem protection and restoration can build resil\u0002ience of ecosystems and generate opportunities to restore eco\u0002system services with substantial co-benefits (high confidence) \r and provision of ecosystem-based adaptation.7 Ecosystem-based \r adaptation includes protection and restoration of forests, grasslands, \r peatlands and other wetlands, blue carbon systems (mangroves, salt \r marshes and seagrass meadows), and agroecological farming practices. \r In coastal systems, nature-based solutions, including ecosystem-based \r adaptation, can reduce impacts for human settlements until sea level \r rise results in habitat loss. High rates of warming and drought may \r severely threaten the success of nature-based solutions such as forest \r expansion or peatland restoration. Ecosystem-based adaptation is \r being increasingly advocated in coastal defence against storm surges, \r terrestrial flood regulation, reducing urban heat and restoring natural \r [...]"


id: f4a3353da34ea590d7bee029c755f167
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 40413
content:
"[...] fire regimes. Nature-based solutions, including ecosystem-based \r adaptation, can therefore reduce risks for ecosystems and benefit \r people, provided they are planned and implemented in the right way \r and in the right place. For example, coastal wetlands and ecosystems \r can also be seriously damaged by coastal defences designed to protect "


id: d795bcc6c3b9f8a882a5544cb75adf7b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 35235
content:
"TS.D.3.4 Maladaptation can be reduced using the principles of \r recognitional, procedural and distributional justice in decision\u0002making, responsibly evaluating who is regarded as vulnerable \r and at risk, who is part of decision-making, who is the beneficiary \r of adaptation measures and integrated and flexible governance \r mechanisms that account for long-term goals (high confidence). \r Examples include selecting native and appropriate species in habitat \r restoration, monitoring key social and environmental indicators for \r adaptation progress, embedding strong monitoring and evaluation \r processes, considering measures of efficiency and social welfare, \r and social and political drivers and power relationships. Integrated \r approaches, such as the water-energy-food nexus and inter-regional \r considerations of risks can reduce the risk of maladaptation, building \r on existing adaptation strategies, increasing community participation \r [...]"


id: a990a66c2adff5240e7fd3e521f24042
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 27053
content:
"Figure TS.12 |  This figure shows the interconnectedness between different ecosystems and system transitions, with human activities in urban, rural and \r coastal locations embedded in ecosystems. Maintaining biosphere integrity is essential for biodiversity, human and societal health and a precondition for climate resilient \r development. Panel a) illustrates how adaptation, mitigation and development actions characterised by exploitation and degradation lead to unsustainable development and \r adverse outcomes for human well-being and ecosystem integrity. Panel b) illustrates how adaptation options, implemented in an integrated way with mitigation and development \r and based on ecosystem stewardship, can support climate resilient development (Figure TS.13). The protection or restoration of one or more of these ecosystems also provides \r [...]"


id: 829ba5db5ab1124f55c1f85e5a17e6b8
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 20105
content:
"[...] benefits to the other ecosystems and enhances the services provided that improve livelihoods. Protecting and restoring ecosystem health as a part of societal development and \r through societal choices is a key transformative solution space for climate resilient development {2.5, 2.6, 3.5, 3.6, 4.3, 5.13, 6.3, 7.4, CCP1, CCP3, CCP5, Box 18.5}"


id: 7985ee584c73c67e55512b02295363ec
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18585
content:
"TS.D.6.5 Key innovations in adaptation in social policy and \r nature-based solutions have not been matched by innovation \r in adaptation finance, which tends to favour established \r mechanisms, often led by grey/physical infrastructure at the \r national scale. Social policy innovations include social safety nets, \r inclusive approaches to disaster risk reduction and the integration \r of climate adaptation into education. Nature-based solutions \r include green and blue infrastructure in and around cities, including \r hinterlands, that increase water access and reduce hazards for cities \r and settlements, for example reforestation of hill-slope and coastal \r areas. In Europe, many urban innovations are pilot tested, but their up\u0002scaling remains challenging. Where inclusive approaches to adaptation \r policy and action are supported, this can enable wider gains of more \r equitable urbanisation (medium confidence). (Figure  TS.9 URBAN) \r [...]"


id: 8610c2335d5567c4b85e3753118f56a4
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 20731
content:
"[...] {2.6.3, 4.6.5, 4.7.1, 6.3.3, 6.3.5, 6.4.3, 12.5.5, 13.6.2 13.11.3, CCB \r FEASIB, CWGB URBAN}"


id: 4e53866c93fc0d0e57442cd05dc14a81
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11055
content:
"TS.D.6.3 Globally, urban adaptation gaps exist for all climate \r change-driven risks, although the limits to adaptation are \r unevenly distributed (medium confidence). Governance capacity, \r financial support and the legacy of past urban infrastructure \r investment constrain how cities and settlements can adapt to key \r climate risks (medium confidence). The gap between what can be \r adapted to and what has been adapted to is uneven; it is larger for \r the poorest 20% of populations than for the wealthiest 20%. The \r adaptation gap is also geographically uneven; it is highest in Africa \r (medium confidence). Limits to adaptation are often most pronounced \r in rapidly growing urban areas and smaller settlements, including \r those without dedicated local government. At the same time, legacy \r infrastructure in large and mega cities, designed without taking \r climate change risk into account, and past adaptation decisions \r [...]"


id: 7b529f53ae0fed564a94e5e0731f8c10
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18898
content:
"[...] constrain innovation, leading to stranded assets and with increasing \r numbers of people unable to avoid harm, including heat stress and \r flooding, without transformative adaptation (medium confidence). \r {6.3, 6.4, 12.5.5, 13.2, 13.2.3, 13.6.2, 13.6.2, 13.11.3, Box  14.4, \r CCP2.3.6, CCP2.4, CCP2.5, CWGB URBAN}"


id: 2033a9ecde2caf927adcf0b37e4adb4b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 2877
content:
"TS.D.6.6 Many urban adaptation plans focus narrowly on climate \r risk reduction and specific climate-associated risks, missing \r opportunities to advance co-benefits with climate mitigation \r and sustainable development (high confidence). This narrow \r approach limits opportunity for urban and infrastructure adaptation \r to tackle the root causes of inequality and exclusion, especially \r among marginalised groups, including women. Urban adaptation \r measures have many opportunities to contribute to climate resilient \r development pathways (medium confidence). They can enhance \r social capital, livelihoods, human and ecological health and contribute \r to low-carbon futures. Urban planning, social policy and nature\u0002based solutions bring great flexibility with co-benefits for climate \r mitigation and sustainable development. Participatory planning for \r infrastructure provision and risk management in informal, precarious \r and underserved neighbourhoods, the inclusion of Indigenous \r [...]"


id: 36d0def74d5a498b31ae9ff6d7eaf883
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 6869
content:
"[...] knowledge and local knowledge, and communication and efforts \r to build local leadership especially among women and youth are \r examples of inclusive approaches with co-benefits for equity. Targeted \r development planning across the range of innovation and investment \r in social policy, nature-based solutions and grey/physical infrastructure \r can significantly increase the adaptive capacity of urban settlements \r and cities and their contribution to climate resilient development (high \r confidence). (Figure TS.9 URBAN) {4.6.5, 6.1, 6.3, 6.4, Box 6.6, 7.4.1, \r 7.4.2, 7.4.3, 10.5, 10.6, 12.5.5, 12.5.7, 13.11.3, 14.5.5, 15.6.1, 15.7, \r CCP5.4.3, CCB COVID, CCB FEASIB}"


id: 525c32f73bc9ebcb48c0ffc9b287ef20
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11767
content:
"TS.D.6.4 The greatest gaps between policy and action are in \r projects to integrate justice concerns into adaptation action, \r address complex interconnected risks where solutions lie \r outside as well as within a city, for example in the food-energy-\r water-health nexus, and resolve compound risks such as the \r relationships between air quality and climate risk (medium \r confidence). The most critical capacity gaps at the city and community \r levels that hinder adaptation include an ability to identify social \r vulnerability and community strengths and to plan in integrated ways to \r protect communities, alongside the ability to access innovative funding \r arrangements and manage finance and commercial insurance, as well \r as locally accountable decision-making with sufficient access to science, \r technology and local knowledge to support application of adaptation \r solutions at scale. As ecosystems provide important additional benefits \r [...]"


id: 953a316a8198db8fc38425327564ef20
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 23455
content:
"[...] to human well-being and coastal livelihoods, urban adaptation \r strategies can be developed for settlements and nearby ecosystems; \r combining these with engineering solutions can extend their lifetime \r under high rates of sea level rise (medium confidence). In Central and \r South America, the adoption of nature-based solutions and hybrid \r (green-grey) infrastructure are still emerging. Monitoring and evaluation \r frameworks that incorporate questions of justice, ecological health and \r multi-sector considerations can help to move away from more narrow, \r static, indicator-based approaches to adaptation. (high confidence) \r {4.6.5, Box 4.8, 5.12.5, 6.1, 6.3, 6.4, 10.3.4, 12.5.5, 13.6.1, 13.6.2}"


id: 45df2cb64fd958fc67efce41e031527a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
vector_id: 9513
content:
"TS.D.7.5 Adaptation is costly, but the benefit-to-cost ratio is high \r for urbanised coastal areas with high concentrations of assets \r (high confidence). Protection has a high benefit-cost ratio during the \r 21st century but can become unaffordable and insufficient to reduce \r coastal risk (e.g., due to salinisation, drainage of rivers and excess \r water), reaching technical limits (high confidence). Hard protection \r sets up lock-in of assets and people to risks and reaches limits by the \r end of the century or sooner, depending on the scenario, local sea level \r rise effects and community tolerance thresholds (high confidence). \r Considering coastal retreat as part of the solution space could lower \r global adaptation costs but would result in large land losses and high \r levels of migration for South and Southeast Asia in particular and in \r relative terms, small island nations would suffer most (high confidence). \r [...]"


id: fd2b7b2b19760417066560ce7df29755
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 41890
content:
"[...] Solutions include disincentivising developments in high-risk areas and \r addressing existing social vulnerabilities now (high confidence). {3.4.2, \r 3.5.5, 3.6.3, 5.13.4, 9.4.1, Box 11.6, 13.2, 14.5.3, 15.5.1, 15.5.2, 15.5.3, \r 16.5.2, CCP2.3, CCB MIGRATE, CCB NATURAL, CCB SLR}"


id: 492319938ce1974b2a0320d962f8760f
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 10093
content:
"TS.D.7.1 As the scale and pace of sea level rise accelerates \r beyond 2050, long-term adjustments may in some locations be \r beyond the limits of current adaptation options and for some \r species and some locations could be an existential risk in the \r 21st century (medium confidence). Nature-based interventions, \r for example wetlands and salt marshes, can reduce impacts and \r costs while supporting biodiversity and livelihoods but have limits \r under high warming levels and rapid sea level rise (high confidence). \r Ecological limits and socioeconomic, financial and governance barriers \r will be reached first and are determined by the type of coastline and \r city or settlement (medium confidence). Accommodation can reduce \r impacts on people and assets but can address only limited sea level \r rise. Considering the long term now will help to avoid maladaptive \r lock-in, to build capacity to act in a timely and pre-emptive manner \r [...]"


id: 96442913dacb9f6ecd8b974c4c7c2fe6
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 23630
content:
"[...] and to reduce risks to ecosystems and people. {3.4.2, 3.6.3, 11.7.3, \r 13.2, 14.5.2, 15.3.4, CCP2.3, CCB DEEP, CCB SLR}"


id: 76127b9fbdc910005a60de1de700deba
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18000
content:
"TS.D.8.2 Continued investment in general health systems and in \r systems enhancing health protection is an effective adaptation \r strategy in the short to medium term (high confidence). Although \r some mortality and morbidity from climate change are already \r unavoidable, targeted adaptation and mitigation actions can reduce \r risks and vulnerabilities (high confidence). The burden of diseases \r could be reduced and resilience increased through health systems, \r generating awareness of climate change impacts on health (medium \r confidence), strengthening access to water and sanitation (high \r confidence), integrating vector control management approaches (very \r high confidence), expanding existing early-warning monitoring systems \r (high confidence), increasing vaccine development and coverage \r (medium confidence), improving the heat resistance of the built \r environment (medium confidence) and building financial safety nets \r [...]"


id: f127468a0ba03bac534538ea01dce35b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 39811
content:
"[...] (medium confidence). {2.6.4, 4.6.4, 5.12.5, 5.14, 7.4.1, 7.4.2, Table 7.2, \r 9.10.3, 10.4.7, 11.3.6, 12.5.6, Table 12.9, 13.7.2, Figure 13.25, 14.5.6, \r Table 14.5, CCP6.2.6, CCB FEASIB, CCB ILLNESS}"


id: 75f32c89ee30b6410c2ee73a75d1a100
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 17976
content:
"TS.D.7.7 Experience in coastal cities and settlements highlights \r critical enablers for addressing coastal hazard risk compounded \r by sea level rise (high confidence). These enablers include building \r and strengthening governance capacity and capabilities to tackle \r complex problems; taking a long-term perspective in making short\u0002term decisions; enabling more effective coordination across scales, \r sectors and policy domains; reducing injustice, inequity and social \r vulnerability; and unlocking the productive potential of coastal \r conflict while strengthening local democracy (medium evidence, \r high agreement). Flexible options enable responses to be adjusted as \r climate risk escalates and circumstances change, which may increase \r exposure  (medium confidence). Legal and financial provisions can \r enable managed retreat from the most at-risk locations (medium \r confidence) but require coordination, trust and legitimate decisions by \r [...]"


id: 8247afa7a60b72e8e092b65de268547d
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 20048
content:
"[...] and across policy domains and sectors (high confidence) that prioritise \r vulnerability, justice and equity (medium confidence). Inclusive, \r informed and meaningful deliberation and collaborative problem\u0002solving depend on safe arenas for engagement by all stakeholders \r (high confidence). {CCP2.4, Table CCP2.1, Table CCP2.2, CCB SLR}"


id: 217c2926589e7b0011b36db19556ab8f
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 3101
content:
"TS.D.8.3 Many adaptation measures that benefit health and \r well-being are found in other sectors (e.g., food, livelihoods, \r social protection, water and sanitation, infrastructure) (high \r confidence). Such cross-sectoral solutions include improved air quality \r through renewable energy sources (very high confidence), active \r transport (e.g., walking and cycling) (high confidence) and sustainable \r food systems that lead to healthier diets (high confidence). Heat \r Action Plans have strong potential to prevent mortality from extreme \r heat events and elevated temperature (high confidence). Nature\u0002based solutions reduce a variety of risks to both physical and mental \r health and well-being (high confidence). For example, integrated \r agroecological food systems offer opportunities to improve dietary \r diversity while building climate-related local resilience to food insecurity \r (high confidence), especially when combined with gender equity and \r [...]"


id: 339284b4f9ddfd33052a9264a44cc858
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 6323
content:
"[...] social justice. Social policy-based adaptation, including education and \r the adaptation of health systems, offers considerable future scope. The \r greatest gaps between policy and action are in failures to manage \r adaptation of social infrastructure (e.g., community facilities, services \r and networks) and failure to address complex interconnected risks \r for example in the food-energy-water-health nexus or the inter\u0002relationships of air quality and climate risk (medium confidence). \r {2.6.7, 4.6.4, 4.7.1, 5.12.5, 5.14.1, 6.3.1, 6.4.3, 6.4.5, 6.4.5, 6.4.5, 7.4.2, \r 9.10.3, 10.4.7, 11.3.6, 12.5.6, Table 12.9, 13.7.2, Figure 13.25, 14.5.6, \r Table 14.5, CCB GENDER, CCB HEALTH, CCB NATURAL}"


id: d35643a5e8a375c98938293c6405ba8d
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 34524
content:
"TS.D.8.6 Reducing future risks of involuntary migration and \r displacement due to climate change is possible by improving \r outcomes of existing migration patterns, addressing vulner\u0002abilities that pose barriers to in situ adaptation and livelihood \r strategies and meeting existing migration agreements and \r development objectives (medium confidence). Properly support\u0002ed and where levels of agency and assets are high, migration as an \r adaptation to climate change can reduce exposure and socioeconomic \r vulnerability (medium confidence). However, migration becomes a risk \r when climate hazards cause an individual, household or community \r to move involuntarily or with low agency (high confidence). Inability \r to migrate (i.e., involuntary immobility) in the face of climate hazards \r is also a potential risk to exposed populations (medium confidence). \r Broad-based institutional and cross-sectoral efforts to build adaptive \r [...]"


id: dad7771a94f576d96a67525793c5f34d
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 35794
content:
"[...] capacity, including meeting the SDGs, reduce future risks of climate\u0002related involuntary displacement and immobility (medium confidence), \r while policies such as the Global Compact on Safe, Orderly and Reg\u0002ular Migration (medium confidence) that are aimed at ensuring safe \r and orderly movements of people within and between states are \r potential components of climate resilient development pathways that \r can improve migration as an adaptation. {4.6.8, 7.4.4, 9.3.1, 12.5.8, \r CCP5.4.2, CCB FEASIB, CCB MIGRATE}"


id: 3139f49eb08158dd38bda1d5d0ee4920
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 5914
content:
"TS.D.11.3 Adaptation options that are feasible and effective to the \r 3.4 billion people living in rural areas around the world and who \r are especially vulnerable to climate change, include the provision \r of basic services, livelihood diversification and strengthening of \r food systems (high confidence). The vulnerability of rural areas to \r climate risks increases due to the long distances to urban centres and \r the lack of or deficient critical infrastructure such as roads, electricity \r and water. Providing critical infrastructure, including through distributed \r generation power systems through renewable energy, has provided many \r co-benefits (high confidence). Biodiversity management strategies have \r social co-benefits, including improved community health, recreational \r activities and ecotourism, which are co-produced by harnessing ecological \r and social capital to promote resilient ecosystems with high connectivity \r [...]"


id: 38630f5f3032cec4ca212ad6665a2ab6
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 7129
content:
"[...] and functional diversity. Strengthening local and regional food systems \r through strategies such as collective trademarks, participatory guarantee \r systems and city-rural links build rural livelihoods, resilience and self\u0002reliance (medium confidence). Livelihood diversification is a key coping \r and adaptive strategy to climatic and non-climatic risks. There is high \r evidence (medium agreement) that diversifying livelihoods improves \r incomes and reduces socioeconomic vulnerability, but feasibility changes \r depending on livelihood type, opportunities and local context. Key \r barriers to livelihood diversification include sociocultural and institutional \r barriers as well as inadequate resources and livelihood opportunities that \r hinder the full adaptive possibilities of existing livelihood diversification \r practices (high confidence). (Figure TS.11b) {4.6.2, 4.7.1, 5, 8, 14.5.9, CCB \r FEASIB}"


id: 720aae854f69b9876ed15578546ae2f3
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 17311
content:
"TS.D.11.1 A sub-set of adaptation options has been implemented \r that cuts across sectors to enable sector-specific adaptation \r responses. These options, such as disaster risk management, climate \r services and risk sharing, increase the feasibility and effectiveness \r of other options by expanding the solution space available (high \r confidence). For example, carefully designed and implemented disaster \r risk management and climate services can increase the feasibility \r and effectiveness of adaptation responses to improve agricultural \r practices, income diversification, urban and critical services and \r infrastructure planning (very high confidence). Risk insurance can be a \r feasible tool to adapt to transfer climate risks and support sustainable \r development (high confidence). They can reduce both vulnerability and \r exposure, support post-disaster recovery and reduce financial burden \r on governments, households and business. {3.6.3, 3.6.5, 4.6, 4.7.1, \r [...]"


id: 74db3c73f4f76e699135f0f93fb2da9a
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 17795
content:
"[...] 5.4.4, 5.6.3, 5.5.4, 5.8.4, 5.9.4, 5.12.4, 5.14.1, 5.14.2, 13.11.2, 14.7.2, \r 15.5.7, CCB FEASIB, CCB GENDER, CCB MOVING PLATE}"


id: 30bf8cd18f664ab3b43dfb237576aaaf
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 5831
content:
"TS.D.11.2 Transformations for energy include the options of \r efficient water use and water management, infrastructure \r resilience and reliable power systems, including the use of \r intermittent renewable energy sources, such as solar and wind \r energy, with the use of storage (very high confidence). These \r options are not sufficient for the far-reaching transformations required \r in the energy sector, which tend to focus on technological transitions \r from a fossil-based to a renewable energy regime. A resilient power \r infrastructure is considered for energy generation, transmission \r and distribution systems. Distributed generation utilities, such as \r microgrids, are increasingly being considered, with growing evidence \r of their role in reducing vulnerability, especially within underserved \r populations (high confidence). Infrastructure resilience and reliable \r power are particularly important in reducing risk in peri-urban and \r [...]"


id: 9513435ae546dd967dd9a12f7e47ef01
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 23432
content:
"[...] rural areas when they are supported by distributed generation of \r renewable energy by isolated systems (high confidence). The option \r for a resilient power infrastructure is considered for all types of \r power generation sources and transmission and distribution systems. \r Efficient water use and water management especially in hydropower \r and combined cycle power plants in drought-prone areas have a \r high feasibility (high confidence) with multiple co-benefits (medium "


id: 9eb0342f3de8f92b17996b8be8249cc5
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 25144
content:
"TS.E.1.3 System transitions are highly feasible. For energy system \r transitions, there is medium confidence in the high feasibility \r of resilient infrastructure and efficient water use for power \r plants and high confidence in the synergies of this option with \r mitigation. For coastal ecosystem transitions, there is medium to high \r confidence that ecosystem conservation and biodiversity management \r are increasing adaptive and ecological capacity with socioeconomic \r co-benefits and positive synergies with carbon sequestration. However, \r opportunity costs can be a barrier. For land ecosystem transitions, there \r is high confidence in the role of agroforestry to increase ecological and \r adaptive capacity, once economic and cultural barriers and potential \r land use change trade-offs are overcome. There is high confidence in \r improved cropland management and its economic feasibility due to \r improved productivity. For efficient livestock systems, there is medium \r [...]"


id: 223ae0bce1e5bb1a64667a08730b3fbc
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 3246
content:
"[...] confidence  in the high technological and ecological feasibility. \r (Figure TS.11a) {CCB FEASIB}"


id: 15c1a8e47eb86147106742c94f6d512e
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 1048
content:
"TS.E.1.1  Prevailing development pathways do not advance \r climate resilient development (very high confidence). Societal \r choices in the near term will determine future pathways. There \r is no single pathway or climate that represents climate resilient \r development for all nations, actors or scales, as well as globally, \r and many solutions will emerge locally and regionally. Global trends \r including rising income inequality, urbanisation, migration, continued \r growth in greenhouse gas emissions, land use change, human \r displacement and reversals of long-term trends toward increased \r life expectancy run counter to the SDGs as well as efforts to reduce \r greenhouse gas emissions and adapt to a changing climate.  With \r progressive climate change,  enabling conditions  will diminish, and \r opportunities for successfully transitioning systems for both mitigation \r and adaptation will become more limited (high confidence). Investments \r [...]"


id: 99ff421e6e83300cfbe9714b91d4bc80
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 24331
content:
"[...] in economic recovery from COVID-19 offer opportunities to promote \r climate resilient development (high confidence). (Figure TS.13) {16.6.1, \r 17.2.1, 18.2, 18.4, CCP5.4.4, CCB COVID}"


id: 189be476c755a5334de9c7529528088
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 1545
content:
"TS.E.1.4 For urban and infrastructure system transitions, there \r is  medium confidence  for sustainable land use and urban \r planning. There is  high confidence  in the economic and ecological \r feasibility of green infrastructure and ecosystem services, as well as \r sustainable urban water management, once institutional  barriers in \r the form of limited social and political acceptability are overcome. \r Social safety nets, disaster risk management and climate services and \r population health and health  systems are considered overarching \r adaptation options due to their applicability across all system \r transitions. There is medium to high confidence in the high feasibility of \r disaster risk management and the use of demand-driven and context\u0002specific climate services as well as in the socioeconomic feasibility of \r social safety nets. Improving health systems through enhancing access \r to medical services and developing or strengthening surveillance \r [...]"


id: 4b0b28c793951a5f10d1780c5a1f4853
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 10445
content:
"[...] systems can have high feasibility when there is a robust institutional \r and regulatory framework (high confidence). (Figure  TS.8 HEALTH, \r Figure TS.9 URBAN, Figure TS.11a, Figure TS.13) {6.3, CCB FEASIB}"


id: 18b4107e8a13596a2901926d8978ffb5
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 1564
content:
"TS.E.1.2  System transitions can enable climate resilient devel\u0002opment when accompanied by appropriate enabling conditions \r and inclusive arenas of engagement (very high confidence). Five \r system transitions are considered: energy, industry, urban and infra\u0002structure, land and ecosystems, and society. Advancing climate resilient \r development in specific contexts may necessitate simultaneous progress \r on all five transitions. Collectively, these system transitions can widen \r the solution space and accelerate and deepen the implementation \r of sustainable development, adaptation and mitigation actions by \r equipping actors and decision makers with more effective options (high \r confidence). For example, urban ecological infrastructure linked to an \r appropriate land use mix, street connectivity, open and green spaces \r and job-housing proximity provides adaptation and mitigation benefits \r that can aid urban transformation (medium confidence). These system \r [...]"


id: a74dbbd3952b4d9ce7339bee311c5012
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 26657
content:
"[...] transitions are necessary precursors for more fundamental climate \r and sustainable-development transformations but can simultaneously \r be outcomes of transformative actions. Enhancing equity and agency \r are cross-cutting considerations for all five transitions. Such transitions \r can generate benefits across different sectors and regions, provided "


id: aec429826981a6843ce0f772692e7275
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 27984
content:
"TS.E.1.5  There are multiple possible pathways by which \r communities, nations and the world can  pursue climate \r resilient development. Moving towards different pathways \r involves confronting complex synergies and trade-offs between \r development pathways and the options, contested values and \r interests that underpin climate mitigation and adaptation \r choices (very high confidence).  Climate resilient development \r pathways are trajectories for the pursuit of climate resilient development \r and navigating its complexities. Different actors, the private sector and \r civil society, influenced by science, local and Indigenous knowledges, \r and the media, are both active and passive in designing and navigating \r climate resilient development pathways. Increasing levels of warming \r may narrow the options and choices available for local survival and \r sustainable development for human societies and ecosystems. Limiting \r [...]"


id: 9c81481030564e67f7d132ea3c7812d5
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 24785
content:
"[...] warming to Paris Agreement goals will reduce the magnitude of climate \r risks to which people, places, the economy and ecosystems will have \r to adapt. Reconciling the costs, benefits and trade-offs associated with "


id: 7288ec5f8c063f707039d1555a368f0
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 17392
content:
"TS.E.1.6. Economic sectors and global regions are exposed to \r different opportunities and challenges in facilitating climate \r resilient development, suggesting adaptation and mitigation \r options should be aligned to local and regional context and \r development pathways (very high confidence). Given their current \r state of development, some regions may prioritise poverty and inequality \r reduction and economic development over the near term as a means \r of building capacity for climate action and low-carbon development \r over the long term. In contrast, developed economies with mature \r economies and high levels of resilience may prioritise climate action to \r transition their energy systems and reduce greenhouse gas emissions. \r Some interventions may be robust in that they are relevant to a broad \r range of potential development trajectories and could be deployed \r in a flexible manner. However, other types of interventions, such as \r [...]"


id: 46299aebab5096100fbc576b70ce1499
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 9564
content:
"[...] those that  are dependent upon emerging technologies, may require \r a specific set of enhanced enabling conditions or factors, including \r infrastructure, supply chains, international cooperation and education \r and training that currently limit their implementation to certain settings. \r Notwithstanding national and regional differences, development \r practices that are aligned to people, prosperity, partnerships, peace \r and the planet as defined in Agenda 2030 could enable more climate \r resilient development. (high confidence) {18.5, Figure 18.1}"


id: ecc6904139e4d5d8bf4fc782b948a701
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 39022
content:
"TS.E.1.7 Pursuing climate resilient development involves \r considering a broader range of sustainable development \r priorities, policies and practices, as well as enabling societal \r choices to accelerate and deepen their implementation  (very \r high confidence).  Scientific assessments of climate change have \r traditionally framed solutions around the implementation of specific \r adaptation and mitigation options as mechanisms for reducing \r climate-related risks. They have given less attention to a fuller set of \r societal priorities and  the role of non-climate policies, social norms, \r lifestyles, power relationships and worldviews in enabling climate action \r and sustainable development. Because climate resilient development \r involves different actors pursuing plural development trajectories  in \r diverse contexts, the pursuit of solutions that are equitable for all \r requires opening the space for engagement and action to a diversity \r [...]"


id: 9210920811dcae257e34d56e677b6b4c
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 22913
content:
"[...] of people, institutions, forms of knowledge and worldviews. Through \r inclusive modes of engagement that enhance knowledge sharing and \r realise the productive potential of diverse perspectives and worldviews, \r societies could alter institutional structures and arrangements, \r development processes, choices and actions that have precipitated \r dangerous climate change, constrained the achievement of SDGs and \r thus limited pathways to achieving climate resilient development. The \r current decade is critical to charting climate resilient development \r pathways that catalyse the transformation of prevailing development \r practices and offer the greatest promise and  potential for human \r well-being and planetary health (very high confidence). {18.4, Box 18.1}"


id: de143813cb50069621a3e9898ea877b3
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 36334
content:
"TS.E.2.3 Climate adaptation actions are grounded in local \r realities so understanding links with SDG 5 on gender \r equality ensures that adaptive actions do not worsen existing \r gender and other inequities within society (e.g., leading to \r maladaptation practices)  (high confidence). Adaptation actions \r do not automatically have positive outcomes for gender equality. \r Understanding the positive and negative links of adaptation actions \r with gender equality goals (i.e., SDG 5) is important to ensure that \r adaptive actions do not exacerbate existing gender-based and \r other social inequalities. Efforts are needed to change unequal \r power dynamics and to foster inclusive decision-making for climate \r adaptation to have a positive impact for gender equality  (high \r confidence).  There are very few examples of successful integration \r of gender and other social inequities in climate policies to address \r climate change vulnerabilities and questions of social justice (very \r [...]"


id: 2ebbeddd3902c17ae2bdc0a570f5dc
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 5499
content:
"[...] high confidence). Yet inequities in climate change literacy compounds \r women's vulnerability to climate change through its negative effect \r on climate risk perception {4.8.3, 9.4.5, 16.1.4, 17.5.1, CCB GENDER}"


id: 465a39390c0897dbf2fa88a1f30de817
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 9601
content:
"Panel (d) Appropriate choices for fostering climate resilient development pathways involve considering the portfolio of risks, the potential for adaptations to satisfactorily reduce \r risks and not exacerbate others, the potential for mitigation measures to interact with risks and adaptations within and across sectors, and how and whether adaptations can be \r enabled. The graphic table illustrates a possible assembly (not exhaustive) of these considerations for four sectors (agriculture, water, built environments, ecosystems) in the region \r Africa, showing (i) top panel: the potential for cascading and compounding effects amongst risks within sectors, between sectors and across boundaries and the possible constraints \r for adaptation (at what global warming level might risks become too great for adaptation - cell colour) and the adaptation gap to be filled (cell border) (risks are grouped by \r [...]"


id: f6986ff30459a15e5ac22bd3b27fba3c
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 40755
content:
"[...] Representative Key Risks); (ii) second panel: the potential for adaptations to reduce risks, including their feasibility (cell border), their interaction with other adaptations addressing \r the same or interacting risks, and whether they are limited by global warming level (cell colour) (possible adaptations are identified for Representative Key Risks); (iii) third panel: \r the mitigation measures grouped into categories that might interact with risks and adaptations, including showing their importance (cell border) and whether the interaction would \r be potentially positive, negative or a mixture of both (cell colour) (note: 'carbon' refers to carbon sequestration); (iv) bottom panel: Enabling conditions for sectors grouped into \r categories of enablers common across many sectors, showing their importance (cell border) and how they may be suitable across a number of sectors, along with an assessment of \r [...]"


id: fa07463467882610f8eda43e3c9d3db8
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 41355
content:
"[...] the gap in the enabler for satisfactory adaptation (cell colour). Confidence levels on each cell are indicated as *= low confidence, ** = medium confidence, *** = high confidence.\r (see also SMTS.4, Table SMTS.5) {16.5.2, Table SM16.4}"


id: 605c08503024ae1e94dc218330527b66
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 14260
content:
"TS.E.2.6 Procedural and distributional justice and flexible \r institutions facilitate successful adaptation and minimise \r maladaptive outcomes. Reorienting existing institutions to become \r more flexible (e.g., through capacity building and institutional reform) \r and inclusive is key to building adaptive governance systems that are \r equipped to take long-term decisions (medium confidence). Enhancing \r climate governance, institutional capacity and differentiated policies \r and regulation from the local to global scale enables and accelerates \r climate resilient development. Transforming financial systems to \r deliver the SDGs, while accelerating system transitions and addressing \r physical and transition risks, is a precondition. Changes in lifestyles, \r human behaviour and preferences can have a significant impact \r on adaptation implementation, demand and hence emissions and \r decision-making around climate action (high confidence). Additionally, \r [...]"


id: 6d22c6ab365e5662f8635d9edb998ffb
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 16478
content:
"[...] the use of customary and traditional justice systems, such as those \r of Indigenous peoples, can enhance the equity of adaptation policy \r processes (high confidence). {4.8,  4.6,8, 5.2.3,  13.8,  15.6.1, 15.6.3, \r 15.6.4, 15.6.5, 17.1, 18.4}"


id: 28b273a3948d7682f514f705ac31c04
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updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 4376
content:
"TS.E.3.2 Some communities/regions are resilient with strong \r social safety nets and social capital that support responses \r and actions already occurring, but there is limited information \r on the effectiveness of adaptation practices and the scale of \r action needed (high confidence). Among island communities, \r greater insights into which drivers weaken local communities and \r Indigenous Peoples' resilience, together with recognition of the \r sociopolitical contexts within which communities operate, can assist \r in identifying opportunities at all scales to enhance climate adaptation \r and enable action towards climate resilient development pathways \r (medium evidence, high agreement). Adaptation responses to climate\u0002driven impacts in mountain regions vary significantly in terms of goals \r and priorities, scope, depth and speed of implementation, governance \r and modes of decision-making and the extent of financial and other \r [...]"


id: af75f459fa564e87d159f604f60b9759
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
vector_id: 28101
content:
"[...] resources to implement them (high confidence). Adaptation in Africa \r has multiple benefits, and most assessed adaptation options have \r medium effectiveness at reducing risks for present-day global warming, \r but their efficacy at future warming levels is largely unknown (high \r confidence). In Australia and New Zealand, a range of incremental \r and transformative adaptation options and pathways is available as \r long as enablers are in place to implement them (high confidence). \r Several enablers can be used to improve adaptation outcomes and \r to build resilience (high confidence), including better governance and \r legal reforms; improving justice, equity and gender considerations; \r building human resource capacity; increased finance and risk transfer \r mechanisms; education and awareness programmes; increased access \r to climate information; adequately downscaled climate data; inclusion \r of Indigenous knowledge; and integrating cultural resources into \r [...]"


id: 17bccb28942bdd2625e0dec129a31b26
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
vector_id: 1384
content:
"[...] decision-making (high confidence). {9.3, 9.6.4, 9.8.3, 9.11.4, 11.7.3, \r 14.4, Box 14.1, 15.6.1, 15.6.5, 15.7, 15.6.3, 15.6.4, 15.6.5, CCP5.2.4, \r CCP5.2.7, CCP6.3, CCP6.4, Box CCP6.2, CCB GENDER}"


id: 58962a3695767002db0cae3fdec2ccc5
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 12829
content:
"TS.E.3 A focus on climate risk alone does not enable effective \r climate resilience (high confidence).  The integration of \r consideration of non-climatic drivers into adaptation pathways \r can reduce climate impacts across food systems, human \r settlements, health, water, economies and livelihoods (high \r confidence). Strengthened health, education and basic social \r services are vital for improving population well-being and \r supporting climate resilient development (high confidence). The \r use of climate-smart agriculture technologies that strengthen \r synergies among productivity and mitigation is growing as \r an important adaptation strategy (high confidence). Pertinent \r information for farmers provided by climate information services \r is helping them to understand the role of climate  compared \r with other drivers in perceived productivity changes (medium \r confidence). Index insurance builds resilience and contributes \r [...]"


id: 8a34974e89a20e3f2cd7842149e91399
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
vector_id: 21493
content:
"[...] to adaptation both by protecting farmers' assets in the face \r of major climate shocks, by promoting access to credit and \r by adopting improved  farm technologies and practices (high \r confidence). {3.6.4, 4.6, 4.7.1, 7.4.6, Box 9.1, Box 9.7, Box 9.8, \r Box 9.9, Box 9.10, Box 9.11, 12.5.4}"


id: 77291d843a1cb3636d129f15a5d7a257
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18167
content:
"TS.E.5.3 Climate governance will be most effective when it has \r meaningful and ongoing involvement of all societal actors from \r local to global levels (very high confidence). Actors, including \r individuals and households, communities, governments at all levels, \r private-sector businesses, non-governmental organisations, Indigenous \r Peoples, religious groups and social movements, at many scales and in \r many sectors, are adapting already and can take stronger adaptation \r and mitigation actions. Many forms of adaptation are more effective, \r more cost-efficient and more equitable when organised inclusively \r (high confidence). Greater coordination and engagement across levels \r of government, business and community serves to move from planning \r to action and from reactive to proactive adaptation (high confidence). \r Inclusion of all societal actors helps to secure credibility, relevance and \r legitimacy, while fostering commitment and social learning (medium to\r [...]"


id: 70f8bc3088ae971ca23a5bd9268b3255
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 17138
content:
"[...] high confidence), as well as equity and well-being, and reduces long\u0002term vulnerability across scales (high evidence, medium agreement). \r Social movements in many cities, including those led by youth, have \r heightened public awareness about the need for urgent, inclusive \r adaptation that can enhance well-being, foster formal and informal \r cooperation and coherence between different institutions and build \r new adaptive capacities. City and local governments remain key actors \r facilitating climate change adaptation in cities and settlements (medium \r confidence). Private and business investment in key infrastructure, \r housing construction and insurance can drive adaptive action at \r scale but can exclude the priorities of the poor (medium confidence). \r Networked community actions can address neighbourhood-scale \r improvements and vulnerability at scale (very high confidence). {1.4.2, \r 3656164945Box94114111421463Box148172}"


id: 7bbc6f7d7cf911304af4c38156851b0
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18976
content:
"TS.E.5 Governance arrangements and practices are presently \r ineffective to reduce risks, reverse path dependencies and \r maladaptation and facilitate climate resilient development (very \r high confidence). Governance for climate resilient development \r involves diverse societal actors, including the most vulnerable, \r who can work collectively, drawing upon local and Indigenous \r knowledges and science, and are supported by strong political will \r and climate change leadership (medium confidence). Governance \r practices will work best when they are coordinated within and \r between multiple scales and levels (institutional, geographical \r and temporal) and sectors, with supporting financial resources, \r are tailored for local conditions, are gender-responsive and \r gender-inclusive and are founded upon enduring institutional and \r social learning capabilities to address the complexity, dynamism, \r uncertainty and contestation that characterise escalating climate \r [...]"


id: fc052469b2bc1a18f1c5c3dbbbb97b05
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
vector_id: 41698
content:
"[...] risk (medium confidence). {1.4.2, 3.6.2, 3.6.3, 4.8, 4.8.1, 4.8.2, \r 4.8.3, 4.8.4, 4.8.5, 4.8.6, 4.8.7, 6.4.3, 6.4.4, 9.4.5, 17.4, 17.6}"


id: e03aca7826e3bfc03c2fb8ee4906cc65
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 36700
content:
"TS.E.5.5 Multi-lateral governance efforts can help reconcile \r contested interests, worldviews and values about how to \r address climate change (medium confidence). Policy responses \r and strategies that localise development and expand the adaptation \r and mobility options of populations exposed to climatic risks can also \r reduce risks of climate-related conflict and political instability (high \r agreement, medium evidence). Formal institutional arrangements for \r natural resource management can contribute to wider cooperation and \r peacebuilding (high confidence). Reducing vulnerability depends on \r the inclusive engagement of the most vulnerable, is gender-responsive \r and includes key societal actors from civil society, the private sector \r and government, with an especially important role played by local \r government in partnership with local communities. Strong governance \r and gender-sensitive approaches to natural resource management \r [...]"


id: 85ef2f675450b346dfa5a4c22908f198
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 20707
content:
"[...] reduce the risk of intergroup conflict in climate-disrupted areas \r (medium confidence). {3.6.3, 3.6.4, 3.6.5, 4.8.5, 4.8.6, 4.8.7, 6.1, 7.4.4, \r 7.4.5, CCB COVID, CCB GENDER, CCB HEALTH, CCB INDIG}"


id: c6cc51c32c8ee1541cc38649e80e3d4d
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 32282
content:
"TS.E.6.1 Large-scale, transformational adaptation necessitates \r enabling improved approaches to governance and coordination \r across sectors and jurisdictions to avoid overwhelming current \r adaptive capacities and to avoid future maladaptive actions \r (high confidence). Response options in one sector can become \r response risks that exacerbate impacts in other sectors. A deliberate \r shift from primarily technological adaptation strategies to those \r that additionally incorporate behavioural and institutional changes, \r adaptation finance, equity and environmental justice and that align \r policy with global sustainability goals will facilitate transformational \r adaptation (high confidence). Application and efficacy testing \r of climate resilient development, or adaptation pathways, show \r promise for implementing transformational approaches (medium \r confidence), including expansion of ecosystem-based adaptation \r approaches. Climate information services that are demand driven \r [...]"


id: 8f3b267b184addf8c75c12bf66f21954
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 22403
content:
"[...] and context specific, combined with climate change literacy, have \r the potential to improve adaptation responses (high confidence). \r {5.14.3, 9.4.5, 14.7.2, 14.6, 17.6}"


id: 3816c4a4c68e39af6e3435957e83e581
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 7069
content:
"TS.E.5.6 A range of governance processes, practices and tools \r that are applicable across a range of temporal and spatial \r scales are available to support inclusive decision-making for \r adaptation and risk management in diverse settings (high \r confidence). National guidance and laws, policies and regulations, \r decision tools that can be tailored to local circumstances, innovative \r engagement processes and collaborative governance can motivate \r better understanding of climate risk and build climate resilient \r development (high confidence). Collaborative networks and \r institutions, including among local communities and their governing \r authorities, can help resolve conflicts (high confidence). A combination \r of robust climate information, adaptive decision-making under \r uncertainty, land use planning, public engagement and conflict \r resolution approaches can help to address governance constraints to \r prepare for climate risks and build adaptive capacity (high confidence). \r [...]"


id: 98984f24063f1a963a65988936e77b5f
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 24059
content:
"[...] New modelling, monitoring and evaluation approaches, alongside \r disruptive technologies, can help understand the societal implications \r of trade-offs and build integrated pathways of low-regret anticipatory \r options, established jointly across sectors in a timely manner, to avoid \r locked-in development pathways (high confidence). {3.6.2, 3.6.3, 3.6.4, \r 3.6.5, 5.14.1, 5.14.4, 11.4.1, 11.4.2, 11.7.1, 11.7.3, Box 11.5, 15.5.3, \r 15.5.4, 15.6.3, 15.6.4, 15.6.5, 17.3.1, 17.3.2, 17.4.2, 17.4.4, 17.6, \r CCP2.4.3, CCB DEEP, CCB NATURAL, CCB SLR, CWGB BIOECONOMY}"


id: 8fdd0ee1acee66722066d99bcce179c
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 22519
content:
"appropriate enabling conditions (high confidence). These enabling \r conditions include effective governance and information flow, policy \r frameworks that incentivise sustainability solutions, adequate financing \r for adaptation, mitigation and sustainable development, institutional \r capacity, science, technology and innovation, monitoring and evaluation \r of climate resilient development policies, programmes and practices \r and international cooperation. Investment in social and technological \r innovation could generate the knowledge and entrepreneurship needed \r to catalyse system transitions and their transfer. The implementation \r of policies that incentivise the deployment of low-carbon technologies \r and  practices within specific sectors, such as energy, buildings \r and agriculture, could accelerate greenhouse gas mitigation and \r deployment of climate resilient infrastructure in both urban and rural \r areas. Civic engagement is an important element of building societal \r [...]"


id: c008352de07349c78c0511ad6ace65c8
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 31077
content:
"[...] consensus and reducing barriers to action on adaptation, mitigation \r and sustainable development (very high confidence). {18.4}"


id: 673ae94ea3760c70052727d1314b7414
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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vector_id: 15436
content:
"Figure TS.AII.1 |  Synthesis of the severity conditions for Representative Key Risks (RKRs) by the end of this century. The figure does not aim to describe severity \r conditions exhaustively for each RKR, but rather to illustrate the risks highlighted in this report (Sections 16.5.2.3.1 to 16.5.2.3.8). Coloured circles represent the levels of warming \r (climate), exposure/vulnerability and adaptation that would lead to severe risks for particular key risks and RKRs. Each set of three circles represents a combination of conditions that \r would lead to severe risk with a particular level of confidence, indicated by the number of black dots to the right of the set, and for a particular scope, indicated by the number of \r stars to the left of the set. The two scopes are 'broadly applicable', meaning applicable pervasively and even globally, and 'specific', meaning applicable to particular areas, sectors \r [...]"


id: 78327c71ef07483779f376bec37715d6
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 18360
content:
"[...] or groups of people. Details of confidence levels and scopes can be found in Section 16.5.2.3. In terms of severity condition levels (Section 16.5.2.3), for warming levels (coloured \r circles labelled 'C' in the figure), high refers to climate outcomes consistent with RCP8.5 or higher, low refers to climate outcomes consistent with RCP2.6 or lower, and medium \r refers to intermediary climate scenarios. Exposure-vulnerability levels are determined relative to the range of future conditions considered in the literature. For adaptation, high \r refers to near maximum potential and low refers to the continuation of today's trends. Despite being intertwined in reality, exposure-vulnerability and adaptation conditions are \r distinguished to help understand their respective contributions to risk severity. {Figure 16.10}"


id: c5c8ef55012682a6acd1d496cfead447
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updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 32105
content:
"Contributing Authors: Maarten van Aalst (Netherlands), Gusti Anshari (Indonesia), Richard Betts \r (UK), Edward R. Carr (USA), Vanesa Castan Broto (UK), Connor J. Cavanagh (Norway), Eva Davidsdottir \r (Norway), Greg Flato (Canada), Katja Frieler (Germany), Nathan Gillett (Canada/UK), Lorena B. \r Gonzalez (Mexico), Marjolin Haasnoot (the Netherlands), Jo S Hermansen (Norway), Pandora Hope \r (Australia), Christian Huggel (Switzerland), Darrell S. Kaufman (USA), Wolfgang Kiessling (Germany), \r Timothy A. Kohler (USA), Aris Koutroulis (Greece), Sivapuram Venkata Rama Krishna Prabhakar \r (Japan/India), Judy Lawrence (New Zealand), Timo Leiter (Germany/UK), Martina K. Linnenluecke \r (Australia), Tabea Lissner (Germany), Leonardo Martinez-Diaz (USA), Md Shahin Mia (Malaysia/\r Bangladesh), Guy Midgley (South Africa), Jan Minx (Germany), Tero Mustonen (Finland), Johanna \r Nalau (Australia/Finland), Ben Orlove (USA), Friederike Otto (UK/Germany), Camille Parmesan \r [...]"


id: a9bcf108a8309329ecda3052d60c52ef
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
vector_id: 27083
content:
"[...] (France/UK/USA), Karishma V. Patel (USA), Asif Raihan (Bangladesh), Nussaibah Raja (Mauritius), \r Lauren Rickards (Australia), Joeri Rogelj (UK/Belgium), Maisa Rojas (Chile), Steven Rose (USA), \r Lisa Schipper (Sweden/UK), Daniela N. Schmidt (UK/Germany), Sonia I. Seneviratne (Switzerland), \r Nicholas Philip Simpson (South Africa), Chandni Singh (India), Jo Skeie Hermansen (Norway), Aimee \r Slangen (the Netherlands), William Solecki (USA), Daithi Stone (New Zealand), Laurent Terray \r (France), Adelle Thomas (Bahamas), Joe Thwaites (UK), Edmond Totin (Benin), Christopher Trisos \r (South Africa), Robert Vautard (France), Michael Weisberg (USA), Xuebin Zhang (Canada)"


id: f9d49ea9821cc05cb05d49e93c5afb41
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 41313
content:
"Since IPCC AR5, human influence on the Earth's climate has \r become unequivocal, increasingly apparent and widespread, \r reflected in both the growing scientific literature and in \r the perception and experiences of people worldwide (high \r confidence). Current changes in the climate system and those \r expected in the future will increasingly have significant and \r deleterious impacts on human and natural systems. The impacts of \r climate change and extreme weather events have adversely affected, \r or caused the loss of ecosystems including terrestrial, freshwater, \r ocean and coastal ecosystems, including tropical coral reefs; reduced \r food security; contributed to migration and displacement; damaged \r livelihoods, health and security of people; and increased inequality. \r Climate change impacts are concurrent and interact with other \r significant societal changes that have become more salient since AR5, \r including a growing and urbanising global population; significant \r [...]"


id: 5151d2927fd1d6ea9e9f5b5dd884daa2
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 11584
content:
"[...] inequality and demands for social justice; rapid technological change; \r continuing poverty, land and water degradation, biodiversity loss; food \r insecurity; and a global pandemic. {1.1.1; 1.3; Cross-Working Group \r Box ATTRIBUTION in Chapter 1}"


id: fa7c5dce5b2ef34ec080b1703c4464a2
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 41435
content:
"Risks from climate change differ through space and time and \r cascade across and within regions and systems. The total risk \r in any location may thus differ from the sum of individual \r risks if these interactions, as well as risks from responses \r themselves, are not considered (high confidence). The risks \r of climate change responses include the possibility of mitigation or \r adaptation responses not achieving their intended objectives or having \r trade-offs or adverse side effects for other societal objectives. Another \r core area of complexity in climate risk is the behaviour of systems, \r which includes multiple stressors unfolding together, cascading or \r compounding interactions within and across sectors and regions, and \r nonlinear responses and the potential for surprises. All of this is crucial \r for effective decision making and decision-support methods. The key \r risks assessed in this report become important in interaction with the \r [...]"


id: 822eb2ac5ac17d426529a69f3af26382
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
vector_id: 20031
content:
"[...] cultures, values, ethics, identities, experiences and knowledge systems \r of affected communities and societies. {1.3.1}"


id: e44aff34892cab58cd7e0677487cd2ed
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 37462
content:
"solution space, overcome soft limits to adaptation, reduce residual risk \r to tolerable levels and achieve societal goals. If such a transformation \r is not pursued or is not successful and risk remains above intolerable \r levels, a forced transformation may occur that is less consistent with \r societal goals. The literature describes incremental and transformational \r change as linked processes. The transformational adaptation literature \r suggests shifts from incremental to transformational processes are \r made possible by knowledge and skills, as well adjustments to vision, \r agendas and coalitions achieved through monitoring and learning. \r The socio-ecological and sustainability transitions literature suggests \r that actors seeking deliberate transformation may take incremental \r steps that aim to induce societal tipping point behaviour in the \r near or longer term. Alternative pathways for pursuing deliberate \r transformations range from a focus on modernisation of sectors such \r [...]"


id: 99fb4dc06a7f4d18bc75819d97a3e217
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 24322
content:
"[...] as energy, agriculture and the use of natural resources to proposals \r for degrowth that intentionally aim to decrease both gross domestic \r product (GDP) and coupled GHG emissions{1213; 144; 151}"


id: ee62362d2f80b71731039d15111817c7
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 39313
content:
"The concept of limits to adaptation is dynamic in terms of \r the temporal, spatial and contextual dimensions of climate \r change risks, impacts and response. Socioeconomic, technological, \r governance and institutional systems or policies can be changed or \r transformed in response to the different dimensions of adaptation \r limits to climate change and extreme events. Adaptation limits can be \r soft or hard. Soft adaptation limits occur when options may exist but \r are currently not available to avoid intolerable risks through adaptive \r actions. Hard adaptation limits occur when no adaptive actions \r are possible to avoid intolerable risks. The levels of GHG emissions \r reduction, adaptation and risk management measures are the key \r factors determining if and when adaptation limits are reached. When \r a limit (soft) is reached, then intolerable risks and impacts may occur \r and additional adaptations (incremental or transformational) would \r [...]"


id: a91c7657dea1e8b5fdaefce7e95b37ed
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 26969
content:
"[...] be required. Transformational adaptation can allow a system to extend \r beyond its soft limits and prevent soft limits from becoming hard \r limits. The loss and damage associated with the future climate change \r impacts, beyond the limits to adaptation, is an area of increasing \r focus. However, it is yet to be fully developed in terms of assessment \r methods, including non-economic values and identifying means to \r avoid and reduce both economic (loss of asset, infrastructure, land \r etc.) and non-economic (loss of societal beliefs and values, cultural \r heritage, biodiversity and ecosystem services) losses and damages. \r {1.4.4.1; 1.4.4.2}"


id: 850b2aee4f8872f802ee2ee07f2ef3bf
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 20550
content:
"Transformation is understood as a collective action challenge \r among actors with both common and differing values interacting \r with a mix of competition and cooperation. Significant innovations \r often begin in niches or protected spaces, sometimes introduced by \r new entrants or outsiders. The drivers of transformation are multi\u0002dimensional, involving social, cultural, economic, environmental, \r technical and political processes. The combination of these creates the \r potential for abrupt and systemic change, the stability of entrenched \r and interlocked power structures, and the importance of individual \r beliefs and behaviours. Decision frameworks that consider multiple \r objectives and multiple scenarios can avoid privileging some views \r over others and help multiple actors to identify resilient and equitable \r solutions to complex, deeply uncertain challenges. Nonetheless, \r common goals and narratives are both enablers of transformation and \r [...]"


id: 3c6b3622e3b755d1ca2884b6ee88efc6
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 7823
content:
"Numerous additional significant climate-related changes have unfolded \r worldwide since the publication of the IPCC Fifth Assessment Report \r (AR5) in 2014 (IPCC, 2014a). Consistent with projections, multiple \r concurrent changes in the physical climate system have grown more \r salient, including increasing global temperatures, loss of ice volume, \r rising sea levels and changes in global precipitation patterns (AR6 WGI \r Chapter 1, Chen et al., 2021). The changes in the physical climate system, \r most notably more intensive extreme events, have adversely affected \r natural and human systems around the world. This has contributed to \r a loss and degradation of ecosystems, including tropical coral reefs; \r reduced water and food security; increased damage to infrastructure; \r additional mortality and morbidity; human migration and displacement; \r damaged livelihoods; increased mental health issues; and increased \r [...]"


id: 1dd6c460c7abbcf279986f4f4e2ea7d1
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 2437
content:
"[...] inequality. Since AR5, a growing literature attributes change in specific \r climate variables to observed damages to specific localised human and \r natural systems in many regions of the world (Figure 1.1, also see Cross\u0002Working Group BOX ATTRIBUTION in Chapter 1)."


id: 80eae796c46351036854e3b613fabf17
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
content_type: text
index: climate_gpt_v2
vector_id: 19815
content:
"Concurrently, since AR5, a growing share of people around the world \r perceive a changing climate, regard these changes as significant and \r consider climate action to be a matter of high urgency (Wilson and \r Orlove, 2019; Section  17.4.5). A survey, representing over half the \r world's population, found that almost two-thirds of people across \r 50 countries view climate change as an emergency (Flynn et al., 2021), \r compared to just over half across 23 countries in 2013 (Fagan, 2019). \r The highest level of support for climate action is among small island \r developing states (SIDS) (74%), followed by high-income countries \r (72%), middle-income countries (62%) and, then, least developed \r countries (58%) (Flynn et al., 2021). Notably, after mid-2018, global \r media showed a large increase number of mentions of 'global \r warming', 'climate change' and similar terms (Thackeray et al., 2020). \r The business community now consistently includes climate change, \r [...]"


id: 776ac9c14911fb190af6f8888eff8e3d
created_at: 2023-04-19 13:22:50
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"[...] including 'climate action failure' as a major risk (World Economic Forum, \r 2021). In late 2019, protests calling for strengthened climate action \r reached an unprecedented level of over 6000 events in 185 countries, \r with a reported estimate of 7.6 million participants, largely led by the \r 'Fridays for Future' youth movement (Chase-Dunn and Almeida, 2020)."


id: e5139135c4ec834c1727308efeb0439e
created_at: 2023-04-19 13:22:50
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"Since AR5, climate action has grown at all levels of governance as \r well as among non-governmental organisations, small and large \r enterprises, and citizens. Two international agreements--the United \r Nations Framework Convention on Climate Change (UNFCCC) Paris \r Agreement and the 2030 Agenda for Sustainable Development--\r jointly provide overarching goals for climate action. The 2015 Paris \r Agreement frames direct local, national and private sector actions \r aligned with long-term goals addressing mitigation, adaptation and \r finance. For mitigation, the agreement calls for 'holding the increase \r in global average temperature to well below 2degC above pre-industrial \r levels', 'pursuing efforts to limit the temperature increase to 1.5degC' and \r 'reaching net zero greenhouse gas (GHG) emissions in the second half \r of this century' (UNFCCC, 2016). For adaptation, the agreement calls \r for 'increasing the ability to adapt to the adverse impacts of climate \r [...]"


id: b3fbbf6c476fb62e5b1eaae3fb9ee326
created_at: 2023-04-19 13:22:50
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"[...] change and foster climate resilience' (UNFCCC, 2016, Article 2), as \r well as having a dedicated 'global goal on adaptation' (Lesnikowski \r et al., 2017; Persson, 2019). For finance, the agreement seeks to make \r 'financial flows consistent with a pathway towards low GHG emissions \r and climate resilient development'."


id: 69b8a33647024c3d2d089da2790353d7
created_at: 2023-04-19 13:22:50
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"Risk Reduction (SFDRR) (Tozier de la Poterie and Baudoin, 2015; UNISDR, \r 2015), the finance-oriented Addis Ababa Action Agenda (UN, 2015) and \r the New Urban Agenda (UN, 2017). For example, the SFDRR recognises \r some disasters as 'exacerbated by climate change and increasing in \r frequency and intensity, significantly [impeding] progress towards \r sustainable development' (UNISDR, 2015). The Convention on Biological \r Diversity (CBD) is one of the key international legal instruments for \r sustainable development for 'the conservation of biological diversity, the \r sustainable use of its components and the fair and equitable sharing \r of the benefits arising out of the utilisation of genetic resources' (CBD, \r 2011). The CBD and its Aichi targets recognises that biodiversity is \r affected by climate change, with negative consequences for human well\u0002being, but biodiversity, through ecosystem services, contributes to both \r [...]"


id: 4149446f02e42393a91242e0e67686ee
created_at: 2023-04-19 13:22:50
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"[...] climate change mitigation and adaptation (CBD, 2010). There is concern \r that many of the proposed post-2020 biodiversity targets of the CBD \r may not be met due to climate change impacts (post-2020 biodiversity \r targets from Chapter 2; Arneth et al., 2020)."


id: 280a8756e85608e6a09b6a9da17c771
created_at: 2023-04-19 13:22:50
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"Knowledge about adaptation has significantly expanded since AR5 \r (Cross-Chapter Box  ADAPT in Chapter 1). While understanding \r regarding the extent of adaptation gaps remains limited, the available \r evidence suggests significant adaptation gaps exist (high confidence). \r Many current adaptation efforts constitute adaptation planning, rather \r than implementation (Section  16.3). Most current implementation \r efforts represent incremental as opposed to transformational \r adaptation despite the proximity to adaptation limits (Sections 17.2; \r 17.5.2). Some current adaptation efforts are considered maladaptive \r because they increase some climate-related risks even if they reduce \r others (Sections 1.4.2.4; 17.5; Chapter 16). Gaps exist in key enablers \r of adaptation, such as finance (Cross-Chapter Box FINANCE in Chapter \r 17). Given the long time scales involved with many adaptation actions \r [...]"


id: dcfec991cbf73c257afc2296a79a359a
created_at: 2023-04-19 13:22:50
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"[...] and the potential to significantly reduce longer-term costs with near\u0002term actions, closing many adaptation gaps requires actions over the \r next few years by governments, business, civil society and individuals \r at a scale and speed significantly faster than that represented by \r current trends."


id: 7d5c0adde836d7174f1973861e9d077e
created_at: 2023-04-19 13:22:50
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content:
"First, this AR6 assessment has an increased focus on risk- and solutions\u0002frameworks. The risk framing can move beyond the limits of single \r best estimates or most-likely outcomes and include high-consequence \r outcomes for which probabilities are low or in some cases unknown \r (Jones et  al., 2014; Mach and Field, 2017). In this report, the risk \r framing for the first time spans all three Working Groups, includes \r risks from the responses to climate change, considers dynamic and \r cascading consequences (Section  1.3.1.1), describes with more \r geographic detail risks to people and ecosystems, and assesses such \r risks over a range of scenarios (Chapter 16). The focus on solutions \r encompasses the interconnections among climate responses, \r sustainable development, and transformation, and the implications \r for governance across scales within the public and private sectors \r (Section  17.5.2; Chapter 18). The assessment therefore includes \r [...]"


id: b8f9d4f10fac4cbf42d033d0d95abec6
created_at: 2023-04-19 13:22:50
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"[...] climate-related decision making and risk management, climate \r resilient development pathways, implementation and evaluation \r of adaptation, and also limits to adaptation, and loss and damage \r (Cross-Chapter Box LOSS in Chapter 17; Section 1.4.4). Specific focal \r areas reflect contexts increasingly important for the implementation \r of responses, such as cities (Chapter 6)."


id: f104ed1f661e95cb620d3664266e704a
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"Risk framing is increasingly used to assess climate change impacts on \r human and natural systems (Sections 1.2.4.1; 16.1; 17.3; Cross-Chapter \r Box CLIMATE in Chapter 1; IPCC, 2012; Mach and Field, 2017; O'Neill \r et al., 2017; Connelly et al., 2018; see also Oppenheimer et al., 2014). \r A risk framing reflects key dimensions of the climate challenge. These \r features include the changing likelihoods of many different outcomes \r (including adverse consequences and beneficial opportunities), \r uncertainties that will persist, and different and contested values, \r priorities and goals (Jones and Preston, 2011; Mach et al., 2016). The \r IPCC AR6 and associated special reports apply a broad definition of \r risk. WGI Cross-Chapter Box 1.3. WGI uses the Climatic Impact Driver \r terminology, rather than hazard, to neutrally assess changing climatic \r conditions that are relevant to human and natural systems, leaving \r the determination of positive/negative consequences and resulting \r [...]"


id: e8ea95596e3883e833b208e6f3d1a130
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"[...] impacts and risks for WGII assessment (WGI Section  12.3). In most \r cases, throughout this WGII report, the term 'risk' refers to the risks of \r climate change impacts. The full assessment, however, incorporates all \r relevant risks from climate change impacts and responses."


id: e9dee54364d720968b6766255e9f715d
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"Vulnerability is a component of risk, but also an important focus \r independently. Vulnerability in this report is defined as the propensity \r or predisposition to be adversely affected. It encompasses a variety \r of concepts and elements, including sensitivity or susceptibility \r to harm and lack of capacity to cope and adapt (see Annex II: \r Glossary). Over the past several decades, approaches to analysing \r and assessing vulnerability have evolved. An early emphasis on top\u0002down, biophysical evaluation of vulnerability included--and often \r started with--exposure to climate hazards in assessing vulnerability. \r From this starting point, attention to bottom-up, social and contextual \r determinants of vulnerability, which often differ, has emerged, \r although this approach is incompletely applied or integrated across \r contexts (Bergstrand et al., 2015; Rufat et al., 2015; Spielman et al., \r 2020; Taberna et al., 2020). Vulnerability is now widely understood \r [...]"


id: bb3a9ec110f5306d241fc15121e48842
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"[...] to differ within communities and across societies, also changing \r through time (Kienberger et  al., 2013; Jurgilevich et  al., 2017; see \r also Chapter 16). In the WGII AR6, assessment of the vulnerability \r of people and ecosystems encompasses the differing approaches \r that exist within the literature, both critiquing and harmonising them \r based on available evidence. In this context, exposure is defined \r as the presence of people; livelihoods; species or ecosystems; \r environmental functions, services, and resources; infrastructure; \r or economic, social, or cultural assets in places and settings that \r could be adversely affected (Annex II: Glossary). Potentially affected \r places and settings can be defined geographically, as well as more \r dynamically, for example through transmission or interconnections \r through markets or flows of people."


id: 2ecbd28f1b812617fca515d617715c68
created_at: 2023-04-19 13:22:50
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content:
"The broad definition of risk involves quantitative and integrative \r understandings of risk ( Oppenheimer et al., 2014; Mach and Field, 2017; \r see also Section 17.3). Risk is sometimes defined as the probability \r of a consequence, multiplied by the magnitude of that consequence, \r acknowledging both the diversity of possible consequences and \r the relevance of values. Yet it also applies in circumstances where \r probabilities cannot be fully quantified (e.g., Adger et al., 2013). For \r example, in some cases the probability and magnitude of consequences \r may be more uncertain, dependent on complex dimensions of the \r climate (e.g., a cyclone, high tide, and heatwave co-occurring) or the \r vulnerability of different communities (e.g., the ways in which social \r networks and community cohesion support the most vulnerable \r individuals during disasters) (Ford et al., 2018). The determinants of \r risk vary dynamically through space and time (Jurgilevich et al., 2017; \r [...]"


id: 3840fbfd8ef778e826ad6a90d2edc7fb
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vector_id: 7102
content:
"[...] Viner et  al., 2020). They interact, compound, and cascade (Dawson, \r 2015; Adger et al., 2018; see also Section 16.1.2)."


id: dbf2bff2711b105ea55937917a11274f
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"climate change adaptation and disaster risk reduction communities (e.g., \r IPCC, 2012; UNDRR, 2019, especially Chapter 13 in that report). Building \r on the scientific literature and adaptation and risk reduction practice, the \r IPCC Special Report on Extremes resulted in several major IPCC advances \r that continue through the present report, including emphasis on risk and \r climate-related extremes (e.g., Burton et al., 2012; Lavell et al., 2012) \r and re-conceptualisation of vulnerability to encompass both social \r and biophysical orientations (i.e., bridging contextual/bottom-up and \r climate-driven/top-down approaches) (Polsky et al., 2007; Cardona et al., \r 2012). Linking disaster risk reduction and climate change adaptation can \r also be an important basis for discussion in climate negotiations on the \r allocation of funds needed for tackling climate change, especially in \r developing countries and SIDS (Begum et al., 2014). The integration of \r [...]"


id: 8d0367db62c90abd3af1393bc54e5995
created_at: 2023-04-19 13:22:50
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"[...] disaster risk management and climate change adaptation in the IPCC \r AR6 is seen, for example, in the assessment of key risks within and \r across sectors and regions, along with global-scale reasons for concern, \r which is attuned to extreme events and disasters (Oppenheimer et al., \r 2014; see also Chapter 16). Additionally, the assessment of adaptation \r has prioritised these interconnections (e.g., Mimura et  al., 2014), as \r have literature and practice especially in the context of sustainable \r development (e.g., Schipper et al., 2016)."


id: ca4bf11c11b6120e84d51ffa189962e
created_at: 2023-04-19 13:22:50
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"Adaptation in this report is defined, in human systems, as the process \r of adjustment to actual or expected climate and its effects, in order \r to moderate harm or exploit beneficial opportunities. In natural \r systems, adaptation is the process of adjustment to actual climate \r and its effects; human intervention may facilitate adjustment to \r expected climate and its effects (see Annex II: Glossary). Adaptation \r planning in human systems generally entails a process of iterative risk \r management. Different types of adaptation have been distinguished, \r including anticipatory versus reactive, autonomous versus planned \r and incremental versus transformational adaptation (Chapters 16-\r 18; IPCC WGII glossaries for the TAR, AR4, AR5, and AR6 (Annex II)). \r Adaptation is often seen as having five general stages: (a) awareness, \r (b) assessment, (c) planning, (d) implementation and (e) M&E (Moser \r and Boykoff, 2013; Jones et al., 2014; Mimura et al., 2014; Noble et al., \r [...]"


id: e11d32cb65b8ca4d9fe40f2341e93cc5
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"[...] 2014; see also Section 17.4). Government, non-government and private \r sector actors have adopted a wide variety of specific approaches to \r adaptation that, to varying degrees, address these five general stages. \r Adaptation in natural systems includes 'autonomous' adjustments \r through ecological and evolutionary processes. It also involves the use \r of nature through ecosystem-based adaptation. The role of species, \r biodiversity and ecosystems in such adaptation options can range \r from the rehabilitation or restoration of ecosystems (e.g., wetlands or \r mangroves) to hybrid combinations of 'green and grey' infrastructure \r (e.g., horizontal levees) (Chapters 2 and 3; IPBES, 2018)."


id: 31c8ee8a5041b80bd2259cd01eadc474
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"Resilience in this report is defined as the capacity of social, economic \r and environmental systems to cope with a hazardous event or trend \r or disturbance, responding or reorganising in ways that maintain their \r essential function, identity and structure, while also maintaining the \r capacity for adaptation, learning and transformation (see Annex II: \r Glossary). Resilience is an entry point commonly used, although under \r a wide spectrum of meanings (Reghezza-Zitt et al., 2012; Flood and \r Schechtman, 2014; Aldunce et al., 2015; Tanner et al., 2015; Fisichelli \r et  al., 2016; Meerow et  al., 2016; Moser et  al., 2019a). Resilience \r as a system trait overlaps with concepts of vulnerability, adaptive \r capacity, and thereby risk. Resilience as a strategy overlaps with risk \r management, adaptation and also transformation (Woodruff et  al., \r 2018; Moser et al., 2019a). Implemented adaptation is often organised \r [...]"


id: 7c1b4e38e75bbc4e5c3094ce1344758c
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content:
"[...] around resilience as bouncing back and returning to a previous state \r after a disturbance (Fisichelli et al., 2016)."


id: 4cfa6e4b59437a391db7ca1db43818db
created_at: 2023-04-19 13:22:50
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content:
"A narrative contains a storyline in addition to a set of actors \r (Elliott, 2005). A storyline is a series of events including their \r causal connections within a narrative. The IPCC and climate change \r literature more broadly often use the terms storylines and narratives \r interchangeably (O'Neill et al., 2017; see also WGI Cross-Chapter Box 6 \r in Chapter 1; Sections 1.4.4; 10.5.3). A scenario storyline refers to a \r narrative description of a scenario including its main characteristics, \r relationships between driving forces and how these factors evolve \r (AR6 WGI Section 1.4.4.2, Chen et al., 2021). Storylines are used to \r assess risks related to low-likelihood, but high-impact events (Sutton, \r 2018). In this use of the terms, narratives and storylines do not \r include specific actors. There is also a critical literature on the use of \r narratives and storylines based on projected scenarios, which points \r out the conservative character of these concepts whose performative \r [...]"


id: fea707e54bcecf704e0e617f32e13bfa
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"[...] effect tends to preserve the status quo and the current socioeconomic \r relationships. (Malm and Hornborg, 2014; Chollet and Felli, 2015; \r Lovbrand et al., 2015; Demortain, 2019; Theys and Cornu, 2019)."


id: ecfaef500d6dcc25d6a7876aa0321b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
vector_id: 39060
content:
"Often, development and adaptation communities of practice default to \r persistence and stability in their use of resilience (Cote and Nightingale, \r 2012; MacKinnon and Derickson, 2013). Such a framing aligns resilience \r with a long-standing but increasingly questioned belief that sustainable \r development can be achieved through incremental adjustments in \r behaviour and advances in technology that allow for the persistence of \r existing socioeconomic and socio-ecological arrangements (Klauer, 1999; \r Banerjee, 2003; Redclift, 2005; UN Inter-agency Task Force on Financing \r for Development 2019; Chapter 18, Section 1.5). However, the literature \r increasingly suggests that the achievement of sustainable development \r will require transformative change in socio-ecological systems at scales \r ranging from the community to the globe. The concept of climate \r resilient development, initially introduced in AR5 and now a key focus in \r [...]"


id: 947bcd58f35e610102e0d3070995102c
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updated_at: 2023-04-19 13:22:50
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content:
"[...] this report (see Chapter 18), engages with such transformations and the \r associated questions of justice, power and politics as shaped by internal, \r endogenous social factors and their interactions with other drivers of \r change (Eriksen et al., 2015; Nightingale, 2015b; Carr, 2019; Nightingale \r et al., 2019; see also Chapter 18)."


id: be0e32f16effba6414f396ea577d6717
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
vector_id: 30704
content:
"Standard research communication may fail to engage policymakers, \r media and the public at large (WGI AR6 Section 1.2.4, Chen et al., 2021). \r Rather, policies and decision making tend to be based on narratives \r and storylines (Roe, 1994; Roe, 2017). Although mathematical models \r and narratives are often presumed to be antithetical, in practice they \r may be complementary and work together (Morgan and Wise, 2017). \r Communicating research insights through storylines and narratives \r may have a better chance of transmitting key messages. AR6 employs \r these communication tools in many places, for instance storylines \r for constructing and communicating regional climate information \r or climate services (WGI AR6 Chapter 10, Doblas-Reyes et al., 2021; \r WGI AR6 Chapter 12, Ranasinghe et  al., 2021) or 'low likelihood \r high warming storylines' (Chapter 4). To better communicate deep \r uncertainty in sea level rise projections, WGI uses storylines to describe \r [...]"


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updated_at: 2023-04-19 13:22:50
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"[...] the physical events that would have to unfold to generate its high-end \r estimates (Cross-Chapter Box DEEP in Chapter 17)."


id: 6d1f5127a61bed6c5713fc8c302c3dc3
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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content:
"AR6 WGI adopts a common set of reference years and time periods to assess observed and projected climate change, namely the pre\u0002industrial period, the current 'modern' period and future reference time periods. The IPCC Glossary (2021b) defines the pre-industrial \r period as 'the multi-century period prior to the onset of large-scale industrial activity around 1750. The reference period 1850-1900 is \r used to approximate pre-industrial global mean surface temperature (GMST).' The 'modern' period is defined as 1995 to 2014 in AR6, \r while three future reference periods are used for presenting climate change projections, namely near term (2021-2040), mid-term (2041-\r 2060) and long term (2081-2100), in both the AR6 WGI and WGII reports. Importantly, the historical rate of warming assessed by WGI \r in AR6 is different to that assessed in AR5 and Special Report on Global Warming of 1.5degC (SR1.5, IPCC, 2018b), due to methodological \r [...]"


id: 44035178f636c94291d2a0384e3a58f4
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"[...] updates (see WGI Cross-Chapter Box 2.3 in Chapter 2 for details (Gulev, 2021)). This means that the 'modern' period is assessed as slightly \r warmer compared to 1850-1900 than it would have been with AR5-era methods. This also has implications for the projected timing of \r reaching policy-relevant levels of global warming, which need to be understood."


id: dce1835d36e4ef90ed52cd53f8aafbfc
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content:
"The plausibility of emissions levels as high as the emissions scenario conventionally associated with the RCP8.5 and SSP5-8.5 concentration \r pathways has been called into question since AR5, as has the emissions pathway feasibility of the low scenarios (Hausfather and Peters, \r 2020; Rose and and Scott, 2020). However, these views are contested (Schwalm et al., 2020, for RCP8.5) It is important to realise that \r emissions scenarios and concentration pathways are not the same thing and higher concentration pathways, such as RCP8.5 could arise \r from lower emissions scenarios if carbon cycle feedbacks are stronger than assumed in the integrated assessment models (IAMs) used to \r create the standard scenarios (Booth et al., 2017). In the majority of full-complexity Earth System Models, these feedbacks are stronger \r than in the IAMs (Jones et al., 2013), so the RCP8.5 concentration pathway cannot be ruled out purely through consideration of the \r [...]"


id: e0f6cf4dafa876690de0df80c451cd97
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"[...] economic aspects of emissions scenarios. Nonetheless, the likelihood of a climate outcome, and the overall distribution of climate \r outcomes, are a function of the emissions scenario's likelihood. Note that the original RCPs were created explicitly to facilitate a broad \r range of climate modelling experiments, with the expectation that other issues, such as socioeconomic uncertainty, could be subsequently \r explored (Moss et al., 2010)."


id: 654a63811f8a80b2e963a6c1367e68b6
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updated_at: 2023-04-19 13:22:50
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"An important feature of the AR6 cycle is a stronger emphasis on the use of future GWLs to support consistency and comparability across \r the three IPCC Working Groups' contributions to the AR6 and improve communication. The common range of GWLs relative to the 1850 \r to 1900 period, termed the 'Tier 1' range by WGI, are 1.5, 2.0, 3.0 and 4.0degC. The use of GWLs assists in the comparison of climate states \r across climate change scenarios (projections) and in assessing the broader literature, as well as for cross-chapter and cross-working \r group comparisons. They facilitate the integration of climate projections, impacts, adaptation challenges and mitigation challenges within \r and across the three Working Groups as there is a close connection between the level of global warming and climate change impacts. Of \r particular interest is the timing of when the 'Tier 1' GWLs are reached, relative to the period 1850-1900, under the five SSP x-y scenarios, \r [...]"


id: bb8c59c7757a02486d2a12fb07759d94
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"[...] as well as RCP scenarios. For climate change impacts and adaptation responses, linking GWLs to RCP and SSP climate projections using \r a climate information translation resource is of great relevance for the WGII contribution to AR6."


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"WGII's common climate dimensions include (a) a common range of GWLs from WGI, (b) common ranges for other climate variables, \r (c) information for translating climate variable levels to climate projections and vice versa. See Table Cross-Chapter Box CLIMATE.1 for \r global warming level ranges by time periods for RCP and SSP climate projections, and Table Cross-Chapter Box CLIMATE.2 for information \r regarding the timing for when GWLs are reached in climate projections. The common GWL range is based on WGI's 'Tier 1' dimensions of \r integration range: 1.5degC, 2degC, 3degC and 4degC. The first table illustrates the greater levels of projected global warming with higher emissions \r pathways, as well as the increasing uncertainty in the climate response over time for a given pathway. The second table illustrates \r significant uncertainty in the timing for passing GWL thresholds which can narrow for a given GWL, the higher the emissions pathway. \r [...]"


id: 593cf92bdfdcdc80d8394ae760ca727f
created_at: 2023-04-19 13:22:50
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"[...] Finally, given the importance of geographic heterogeneity in projected changes in future climate, Table Cross-Chapter Box CLIMATE.3a \r and 3b are provided with ranges for select climate variables (temperature, precipitation, ocean) by GWL and continent (or ocean biome). \r The ranges illustrate spatial heterogeneity in potential physical changes in levels and uncertainty that are relevant to assessing climate \r impacts risk. There is significantly more spatial heterogeneity than represented in the table that is relevant to local decision makers (see, \r for instance, WGI Interactive Atlas)."


id: a6e0b802b5cee6fa54d5d6da845cbfb3
created_at: 2023-04-19 13:22:50
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content:
"Figure Cross-Chapter Box CLIMATE.1 |  Illustration of the use of global warming levels (GWLs) as a dimension of integration for impact studies: \r projected changes in river flows in major basins at 4degC global warming from four different multi-model ensembles. Results are shown for projected flow \r changes direct from Earth System Models (ESMs) in CMIP5 and CMIP6, for the Joint UK Land Environment Simulator (JULES) land surface model driven by meteorological \r outputs of the HadGEM3 and EC-Earth model in the High-End cLimate Impacts and eXtremes (HELIX) ensemble (Betts et al., 2018; Koutroulis et al., 2019), and nine \r hydrological models driven by a subset of five CMIP5 ESMs in the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP; Warszawski et al., 2014). Dots show results \r from individual models, blue for increased flows and red for decreased flows, black circles show the median for each ensemble, and black bars show the 95% confidence \r [...]"


id: a6b7784de4b57ae93a62e95e0e5d9295
created_at: 2023-04-19 13:22:50
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content:
"Common ranges for other 'climate' variables, such as minimum and maximum temperatures and regional climates, are available based \r on WGI projections. They are based on feasible combinations with GWLs taken into consideration using the WGI Interactive Atlas. Climate \r information translation may have been necessary within chapters for mapping the WGII literature and assessments of the common \r climate dimensions. WGII's climate impacts literature is based primarily on climate projections around AR5 and earlier or assumed \r temperature levels, though some recent impacts literature uses newer climate projections based on the CMIP6 exercise. Thus, it was \r important to be able to map climate variable levels to climate projections of different vintages and vice versa and adjust variables, \r when possible, to a common reference year. WGII chapters and CCPs only provide climate impact information for the common climate \r [...]"


id: 703bab688c88ee1826affc30fa2d9a62
created_at: 2023-04-19 13:22:50
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index: climate_gpt_v2
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"In an assessment using multiple lines of evidence, including models, observational constraints and improved understanding of climate \r sensitivity, WGI project a central estimate of the 20-year average warming crossing the 1.5degC GWL in the early 2030s in all scenarios \r assessed, except SSP5-8.5 (Lee et al., 2021). This is about 10 years earlier than the midpoint of the likely range (2030-2052) assessed in \r SR1.5, which assumed continuation of the observed warming rate reported at that time. However, this does not imply that the projected \r impacts of 1.5degC will be reached 10 years earlier, because roughly half of the 10-year difference is a result of updating the diagnosed \r historical rate of warming due to methodological advances, new datasets and other improvements (Gulev et al., 2021). The other half of \r the 10-year difference arises because, for central estimates of climate sensitivity, most scenarios show stronger warming over the near \r [...]"


id: 66fcb1f1f6f6487e6549c16527ebd150
created_at: 2023-04-19 13:22:50
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"Pathways are one element of a larger scenario (O'Neill et  al., 2017), \r focusing on just one element of a larger system of drivers, emissions \r or concentrations. Scenarios provide one means to represent deep \r uncertainty when there is disagreement or uncertainty about conceptual \r models (Cross-Chapter Box DEEP in Chapter 17; IPCC, 2019b). In addition, \r scenarios provide several important functions in decision support. A lack \r of strong association with probabilities enables scenarios to promote \r buy-in from parties to a decision who hold different expectations about \r the future, helping them to expand the range of futures and options \r they consider. The process of generating scenarios can serve as the focus \r of participatory stakeholder exercises and processes, and scenarios can \r also be used to support risk management by stress-testing alternative \r policies and identifying robust and adaptive policies under conditions of \r [...]"


id: fa1381d42702d67306ce944ef7c8af95
created_at: 2023-04-19 13:22:50
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"resources. The key risk assessment in the IPCC AR5 informed the long\u0002term temperature goal in the 2015 Paris Agreement--limiting the \r increase in global mean temperature to well below 2degC and pursuing \r efforts towards limiting warming to 1.5degC (Oppenheimer et al., 2014; \r Pachauri et al., 2014). The IPCC Special Report on Global Warming of \r 1.5degC, responding to an invitation by UNFCCC, used new scientific \r information to provide a specific risk assessment associated with the \r ambitious warming levels targeted by the Paris Agreement (Hoegh\u0002Guldberg et al., 2019). The Special Reports on Oceans and Land further \r advanced the methods of transparent risk assessment (Zommers et al., \r 2020). The current assessment expands significantly from the previous \r reports, aiming to inform and advance understanding of the following \r core themes: (a) the ways changes in vulnerability and exposure \r modulate risks of climate change impacts and risk complexity in \r [...]"


id: 39effffe6b58e1d872506bcc7fde7a7d
created_at: 2023-04-19 13:22:50
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content:
"[...] addition to warming; (b) the knowledge basis relevant to continued \r refinement of temperature goals; (c) the effectiveness of adaptation \r solutions; (d) the management of risks at higher levels of warming, \r should ambitious climate change mitigation be unsuccessful, including \r limits to adaptation; and (e) the benefits of climate change mitigation \r and emissions reductions (Section 16.1)."


id: 7f6814f81e022f509747926d82fc33fa
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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"To encompass the nature of climate risk, IPCC assessment since \r the Third Assessment Report has used five overarching domains, \r named 'reasons for concern', to assess increasing risk for societies \r and ecosystems under climate change (IPCC, 2014b; O'Neill et  al., \r 2017; see also Section  16.5; WGI Section  1.2.4.1). The reasons for \r concern approach has enabled evidence to be combined with expert \r judgement, in order to provide a holistic assessment across multiple \r lines of evidence (O'Neill et al., 2017). The approach also respects the \r uncertainties inherent to climate risk and highlights the ways in which \r values are relevant in connecting scientific knowledge to societal \r decision making and risk management. The different reasons for \r concern underscore that there is no single metric that can reflect all \r dimensions of climate-related risk and the diversity of consequences \r for lives and livelihoods, health and well-being, economic and \r [...]"


id: 2cd59581444ddee6d7b5f84657e207b6
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"[...] sociocultural assets, infrastructure and ecosystems (Mach and Field, \r 2017; see also Section 1.4.1.2)."


id: 12f66212236e3b6b4a544e5dbc10076b
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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content:
"magnitude of global warming, socioeconomic development pathways \r and levels of adaptation (Section  16.6). Risk levels are determined \r through a formal elicitation approach for both representative key \r risks and reasons for concern, following the authors' assessment of \r the literature. The reasons for concern consider unique and threatened \r systems (RFC1), such as coral reefs or Arctic Sea ice systems that \r have especially high vulnerability and low capacity to adapt. They \r also include the role of extreme weather events (RFC2), such as heat \r waves, heavy rain, drought, coastal flooding or wildfires. The reasons \r for concern address both the distributional and the aggregate impacts\r of climate change (RFC3, RFC4), including the unfairness factor for \r populations that have contributed little in terms of historic emissions \r but that are disproportionately vulnerable to the impacts of a changing \r climate. The final reason for concern relates to large-scale singular \r [...]"


id: 39fe349133dc7ee0f18ceedff06a6f64
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index: climate_gpt_v2
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content:
"[...] events, nonlinearities and tipping points (RFC5), including ice sheet \r collapse and ecosystem regime shifts."


id: 9841d47f123ee8d07c54d4dd741632ab
created_at: 2023-04-19 13:22:50
updated_at: 2023-04-19 13:22:50
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content:
"human and ecological systems, and also responses (see Section 1.2.1; AR6 \r Glossary, IPCC, 2021b; WGI AR6 Cross-Chapter Box 2 in Chapter 1, Chen \r et al., 2021; Oppenheimer et al., 2014). The determinants of risk all can \r vary and change through space and time in response to socioeconomic \r development and decision making (Figures  1.4; 1.5; Section  16.1). \r Hazards are affected by current and future changes in climate, including \r altered climate variability and shifts in frequency and intensity of \r extreme events (WGI AR6 Chapter 12, Ranasinghe et al., 2021). Such \r hazards can be sudden, for example, a heat wave or heavy rain event, or \r slower onset, for example, land loss, degradation and erosion linked to \r multiple climate hazards compounding. The severity of climate change \r impacts will depend strongly on vulnerability, which is also dynamic and \r includes the sensitivity and adaptive capacity of affected human and \r [...]"


id: f719868d169d9009e942f8096d9e5a67
created_at: 2023-04-19 13:22:51
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content:
"[...] ecological systems (McDowell et al., 2016; Jurgilevich et al., 2017; Ford \r et al., 2018; Viner et al., 2020). As a result, risks vary at fine scale across \r communities and societies and also among people within societies, \r depending, for example, on intersecting inequalities and context-specific \r factors such as culture, gender, religion, ability and disability, or ethnicity \r (Kuruppu, 2009; Jones and Boyd, 2011; Carr and Thompson, 2014; \r also Section 16.1.4). The dynamic social distribution of impacts is the \r subject of increasing attention within climate assessment and responses, \r including the role of adaptation, iterative risk management and climate \r resilient sustainable development (Section 16.1)."


id: 6dfcecdf0d144531e701cf5501c2b217
created_at: 2023-04-19 13:22:51
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content:
"The nature of climate risk also involves risks from responses \r themselves (Figure 1.5c). The risks of climate change responses include \r the possibility of responses not achieving their intended objectives or \r having trade-offs or adverse side effects for other societal objectives \r (Annex II: Glossary; Section  16.1). In particular, human responses \r may create novel hazards and unexpected side effects and entail \r opportunity costs and path dependencies (Boonstra, 2016). Such \r feedback loops can unfold at local and global scales, including large\u0002scale interactions among climate, ecological and human systems with \r human behaviour and decision making affecting such interactions. \r Response risks can originate from uncertainty in implementation, \r maladaptation, action effectiveness, technology development or \r adoption, or transitions in systems (see Sections 1.4 and 1.5). Typical \r risks may be related to regulation, litigation, competition, sociopolitics \r [...]"


id: 266db6d1c144bda02f7fa40317cd8498
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"[...] or reputation. Interactions across responses can importantly involve \r co-benefits for other objectives, such as for human health and \r well-being which may be improved from both reduced air pollution \r (e.g., AR6 WGI Chapter 6, Szope et  al., 2021; WGIII, IPCC, 2022) \r and enhanced adaptation to climate change. The nature of risk also \r entails residual impacts that will occur even with ambitious societal "


id: 2c2c89c2782711691525d3ef2338f05
created_at: 2023-04-19 13:22:51
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"In contrast to previous assessments, AR6 is increasingly focused on the \r needs for and challenges of assessing the societal response to climate \r change. The accurate tabulation of adaptation, a key question for \r examining the solution space, is difficult (Chapter 16; Cross-Chapter \r Box ADAPT in Chapter 1), since many forms of adaptation activity are \r under-represented in the peer-reviewed and grey literature. Moreover, \r the related question of assessing the effectiveness of adaptation, that \r is, the extent to which it reduces risk, is also difficult. Estimating risk \r reduction often involves counterfactuals, for instance, quantifying the \r damage a flood would have caused had a community not adapted prior \r to a storm or projecting the damage averted by today's adaptation in \r some future storm (see Cross-Chapter Box PROGRESS in Chapter 17). \r Many socioeconomic drivers affect risk, so attribution for any observed \r [...]"


id: 844bbfad88ec93f8c317000691f4cc25
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content:
"[...] or projected changes must be allocated among those that are due to \r adaptation and those due to economic development, cultural changes \r and other types of policies and trends. For instance, many measures of \r sustainable development overlap with those for adaptive capacity and \r both can reduce climate risk while also yielding benefits irrespective \r of future climate regimes (UNEP, 2018). There are also many different \r goals for adaptation both among and within different jurisdictions, so \r that adaptation efforts deemed effective by some individuals may not \r be deemed effective by others (Dilling et al., 2019)."


id: 76a4a80becf1f587a03dd14d404a3ca6
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content:
"Since AR5, social science literature on how individuals and societies \r perceive and respond to climate risk has advanced dramatically (Renn, \r 2008; Jones et al., 2014; Taylor et al., 2014; Neaves and Royer, 2017; Van \r Valkengoed and Steg, 2019). The literature is increasingly integrating \r and advancing long-standing scholarship on environmental and \r social governance, human dimensions of environmental change, risk \r perception and communication, and enabling conditions for effective \r policymaking. These emergent literatures on climate risk, human \r action and solution are reflected in three broad areas of analysis: \r (a) root drivers (i.e., role of cultural norms and social practice, social \r structures and economic development status that shape physical \r and social vulnerability; (b) context-specific barriers and enablers \r (i.e., governance structures, institutional structure and function, risk \r perceptions, access to financing and knowledge availability and needs) \r [...]"


id: 2d8ffaa6260622ce022de217412fb995
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content:
"[...] and (c) the solution-proximate decision space (i.e., climate urgency and \r catalysing conditions, risk communication strategies, M&E strategies) \r (see Solecki et al., 2017; Jorgenson et al., 2019)."


id: af6543bdea71bad29466e9b35c7606a3
created_at: 2023-04-19 13:22:51
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content:
"While scientific knowledge is vital, IK and LK are also necessary for \r understanding and acting effectively on climate risk (IPCC, 2014a; IPCC, \r 2019b, SROCC Chapter 1; see also Section 2.4). Indigenous knowledge\r refers to the understandings, skills and philosophies developed by \r societies with long histories of interaction with their natural surroundings \r (IPCC, 2019a). Local knowledge is defined as the understandings and \r skills developed by individuals and populations, specific to the places \r where they live (IPCC, 2019a). These definitions relate to the debates on \r the world's cultural diversity (UNESCO, 2018a), which are increasingly \r connected to climate change debates (UNESCO, 2018b). However, there \r is agreement that, in the same way that there is not a unique definition \r of Indigenous Peoples because it depends on self-determination (see \r below), there is not a single definition of neither IK and LK. Therefore, \r [...]"


id: 3e8c7cb2c8c1acf80df4249be63c28cf
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"[...] contextualisation is greatly needed. IK and LK will shape perceptions \r which are vital to managing climate risk in day-to-day activities and \r longer-term actions."


id: dcbb833cbc46d037fe05cf89021a103
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"The unambiguous framing of what is being attributed to what is a crucial first step for an assessment (Easterling et al., 2016; Hansen et al., \r 2016; Stone et al., 2021), followed by the identification of the possible and plausible drivers of change and the development of a hypothesis \r or theory for the linkage (see Figure ATTRIBUTION.1 in Chapter 1). The next step is to clearly define the indicators of the observed change \r or event and note the quality of the observations. There has been significant progress in the compilation of fragmented and distributed \r observational data, broadening and deepening the data basis for attribution research (Poloczanska et al., 2013; Ray et al., 2015; Cohen \r et al., 2018; WGI Section 1.5). The quality of the observational record of drivers should also be considered (e.g., volcanic eruptions: WGI \r Section 2.2.2). Impacted systems also change in the absence of climate change. This baseline and its associated modifiers such as agricultural \r [...]"


id: 5ffb645b691664ebc26170116fee54c0
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content:
"[...] developments or population growth need to be considered, alongside the exposure and vulnerability of people depending on these systems."


id: 124995967071cb86baa1a44d84ac3323
created_at: 2023-04-19 13:22:51
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content:
"Attribution of changes in atmospheric GHG concentrations to anthropogenic activity\r AR6 WGI Chapter 5 (Canadell et al., 2021) presents multiple lines of evidence that unequivocally establish the dominant role of \r human activities in the growth of atmospheric CO2, including through analysing changes in atmospheric carbon isotope ratios and the \r atmospheric O2:N2 ratio (WGI Section 5.2.1.1, Canadell et al., 2021). Decomposition approaches can be used to attribute emissions \r underlying those changes to various drivers such as population, energy efficiency, consumption or carbon intensity (Hoekstra and van \r den Bergh, 2003; Raupach et al., 2007; Rosa and Dietz, 2012). Combined with attribution of their climate outcomes, the attribution of \r the sources of GHG emissions can inform the attribution of anthropogenic climate change to specific countries or actors (Matthews, \r [...]"


id: 93f37f8829da3a69886bdd79a985b41e
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"[...] 2016; Otto et al., 2017; Skeie et al., 2017; Nauels et al., 2019) and, in turn, inform discussions on fairness and burden sharing (WGIII \r Chapter 14)."


id: 31d66c46fa7f5e6a90341c42a7496ecb
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"Changes in large-scale climate variables (e.g., global mean temperature) have been reliably attributed to anthropogenic and natural \r forcings (e.g., Hegerl et al., 2010; Bindoff and et al., 2014; WGI Section 1.3.4). The most established method is to identify the 'fingerprint' \r of the expected space-time response to a particular climate forcing agent such as the concentration of anthropogenically induced \r GHGs or aerosols, or natural variation of solar radiation. This technique disentangles the contribution of individual forcing agents to an \r observed change (e.g., Gillett et al., 2021). New statistical approaches have been applied to better account for internal climate variability \r and the uncertainties in models and observations (e.g., Naveau et al., 2018; Santer et al., 2019; WGI Section 3.2). There are many other \r approaches, for example, global mean sea level change has been attributed to anthropogenic climate forcing by attributing the individual \r [...]"


id: c3bb7c164464141b3fee78225dacdfec
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content:
"[...] contributions from, for example, glacier melt or thermal expansion, while also examining which aspects of the observed change are \r inconsistent with internal variability (WGI Sections 3.5.2; 9.6.1.4)."


id: 10c20bff7aa6ad2828ac1d8fa345e2a7
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index: climate_gpt_v2
vector_id: 130
content:
"New methods have emerged since AR5 to attribute the change in likelihood or characteristics of weather or climate events or classes of \r events to underlying drivers (National Academies of Sciences, 2016; Stott et al., 2016; Jezequel et al., 2018; Wehner et al., 2019; Wang et \r al., 2020; WGI Sections 10.4.1; 11.2.2). Typically, historical changes, simulated under observed forcings, are compared to a counterfactual \r climate simulated in the absence of anthropogenic forcing. Another approach examines facets of the weather and thermodynamic status \r of an event through process-based attribution (Hauser et al., 2016; Shepherd et al., 2018; Grose et al., 2020; WGI Section 10.4.1; WGI \r Chapter 11). Events where attributable human influences have been found include hot and cold temperature extremes (including some \r with widespread impacts), heavy precipitation, and certain types of droughts and tropical cyclones (e.g., Vogel et al., 2019; Herring et al., \r [...]"


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content:
"[...] 2021; WGI Section 11.9). Event attribution techniques have sometimes been extended to 'end-to-end' assessments from climate forcing \r to the impacts of events on natural or human systems (Otto et al., 2017; examples in Table 16.1; Section 16.2)."


id: 109cac8c342d4d7619ece28beeecee7a
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index: climate_gpt_v2
vector_id: 106
content:
"Impact attribution covers a diverse set of qualitative and quantitative approaches, building on experimental approaches, observations from \r remote sensing, long-term in situ observations and monitoring efforts, teamed with LK, process understanding and empirical or dynamical \r modelling (Section 16.2; Stone et al., 2013; Cramer et al., 2014). The attribution of a change in a natural or human system (e.g., wild species, \r natural ecosystems, crop yields, economic development, infrastructure or human health) to changes in climate-related systems (i.e., climate \r and ocean acidification, permafrost thawing or sea level rise) requires accounting for other potential drivers of change, such as technological \r and economic changes in agriculture affecting crop production (Hochman et al., 2017; Butler et al., 2018), changes in human population \r patterns and vulnerability affecting flood or wildfire induced damages (Huggel et al., 2015; Sauer et al., 2021), or habitat loss driving declines \r [...]"


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content:
"[...] in wild species (IPBES, 2019b). These drivers are accounted for by estimating a baseline condition that would exist in the absence of climate \r change. The baseline might be stationary and be approximated by observations from the past, or it may change over time and be simulated \r by statistical or process-based impact models (Section 16.2; Cramer et al., 2014). Assessment of multiple independent lines of evidence, \r taken together, can provide rigorous attribution when more quantitative approaches are not available (Parmesan et al., 2013). These include \r palaeodata, physiological and ecological experiments, natural 'experiments' from very long-term datasets indicating consistent responses \r to the same climate trend/event and 'fingerprints' in species' responses that are uniquely expected from climate change (e.g., poleward \r range boundaries expanding and equatorial range boundaries contracting in a coherent pattern worldwide, Parmesan and Yohe, 2003). \r [...]"


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"[...] Meta-analyses of species/ecosystem responses, when conducted with wide geographic coverage, also provide a globally coherent signal of \r climate change at an appropriate scale for attribution to anthropogenic climate change (Parmesan and Yohe, 2003; Parmesan et al., 2013)."


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"Observations provided by the historical, archaeological, and palaeontological records, together with paleoclimatic data, demonstrate \r that climatic variability has high potential to affect biodiversity and human society (high confidence). The evolution of the Earth's biota \r has been punctuated by global biodiversity crises often triggered by rapid warming (high confidence) (Figure PALEO.1; Bond and Grasby, \r 2017; Benton, 2018; Foster et al., 2018;). These so-called hyperthermal events were marked by rapid warming of >1degC, which coincided \r with global disturbances of the carbon and water cycles, and by reduced oxygen and pH in seawater ( Foster et al., 2018; Clapham and \r Renne, 2019). Magnitudes of global temperature shifts in hyperthermal events were sometimes greater than those predicted for the \r current century but extended over longer periods of time. Rates inferred from paleo records that are coarsely resolved are inevitably lower \r [...]"


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"[...] than those from direct observations during recent decades, and caution must be exercised when describing the rate of recent temperature \r changes as unprecedented (Kemp et al., 2015). Mass extinctions, each with greater than 70% marine species extinctions, occurred when \r the magnitude of temperature change exceeded 5.2degC (Song et al., 2021), albeit species extinctions occurred at lower magnitudes of \r warming (medium confidence)."


id: 282f65ef68cbdc5ca926328319bda0a1
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"Responses of biota to rapid climate change have included range shifts (very high confidence), phenotypic plasticity (high confidence), \r evolutionary adaptation (medium confidence), and species extinctions, including mass extinctions (very high confidence). While \r knowledge about the relative roles of these processes in promoting survival during times of climate change is still limited (Nogues-Bravo \r et al., 2018), they have influenced the evolutionary trajectories of species and entire ecosystems (high confidence), and also the course \r of human history (medium confidence). The combined ecological and evolutionary responses to ancient rapid warming events ranged \r from extinction of 81% of marine animal species and 70% of terrestrial tetrapod species on land at the end of the Permian period (~ \r 252 million years ago, Ma) (Smith and Botha, 2005; Stanley, 2016) to low rates of species extinctions but biome- and range shifts on land \r [...]"


id: d1a397756cf0ea761d94829d33f75738
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"[...] and in the ocean at the Palaeocene-Eocene Thermal Maximum (PETM, ~ 56 Ma) (Figure PALEO.1; Ivany et al., 2018; Fraser and Lyons, \r 2020; Huurdeman et al., 2021). Temperature and deoxygenation were key drivers of past biotic responses in the oceans (Gibbs et al., \r 2016; Penn et al., 2018; Section 3.3) (high confidence), whereas on land the interplay between temperature and precipitation is less well \r established in ancient hyperthermals (Frank et al., 2021) (medium confidence). Climate-driven extinction risk increased by up to 40% \r when a short-term climate change added to a long-term trend in the same direction, for example when a long-term warming trend was \r followed by rapid warming (Mathes et al., 2021)."


id: e6fdddbf33363aca6622030d7917fafd
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"Population range shifts including migrations are common adaptations to climate changes across multiple time scales and ecological \r systems in the past and in response to current warming (high confidence). Poleward expansions and retractions ( Reddin et al., 2018; \r Williams et al., 2018; Fordham et al., 2020) as well as migration upslope and downslope in response to warming and cooling were \r common adaptations (Ortega-Rosas et al., 2008; Iglesias et al., 2018;). During warming periods, diversity loss was common near the \r equator (medium confidence)(Kiessling et al., 2012; Kroger, 2017; Yasuhara et al., 2020), while diversity gains and forest expansion \r occurred in high latitudes (Brovkin et al., 2021). Comparison of contemporary shells and skeletons with historical collections in museums \r (Barnes et al., 2011) and the analysis of skeletons of long-lived organisms (Cantin et al., 2010) indicate significant climate-induced \r [...]"


id: 7ed8ecf45e1c96b94c7e5a23f689e546
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"The emergence of agriculture (~10.2 ka) in southwest Asia was associated with stable (within +-1degC global mean annual on multi-century \r time scale; WGI Chapter 2) warm and moist conditions (Richerson et al., 2001; Rohling et al., 2019; Palmisano et al., 2021). Variability in \r resource availability and agricultural production, entrained by climatic variability, is implicated in the disruption and decline of numerous \r past human societies (medium confidence) (d'Alpoim Guedes and Bocinsky, 2018; Cookson et al., 2019; Jones, 2019; Park et al., 2019). \r These crises are partially caused by regional climate anomalies including Holocene 'Rapid Climate Change Events' (Rohling et al., 2019) \r not visible in the globally averaged conditions shown in Figure PALAEO.2. Such anomalies affected human population size (Clark et al., \r 2019; Kuil et al., 2019; Riris and Arroyo-Kalin, 2019), health (Campbell and Ludlow, 2020) and social stability/conflict (Buntgen et al., \r [...]"


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"[...] 2011; Kohler et al., 2014), and triggered migrations (D'Andrea et al., 2011; Schwindt et al., 2016; Chiotis, 2018; Pei et al., 2018) or retarded \r them (Betti et al., 2020; FAQ 14.2). Populations have also been impacted by sea level change in coastal areas (Turney and Brown, 2007; \r Cross-Chapter Box SLR in Chapter 3)."


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content:
"Evidence for widespread droughts ~4.2 ka, lasting for several centuries in some regions, has been tentatively linked to declines of the \r Akkadian Empire (Weiss, 2017; Carolin et al., 2019), the Indus Valley (Giosan et al., 2018; Sengupta et al., 2020), and the Egyptian \r Old Kingdom and Yangtze River Valley (Ran and Chen, 2019). Deteriorating climates often exacerbate accumulating weaknesses in \r social systems to which population growth and urban expansion contribute (Knapp and Manning, 2016; Lawrence et al., 2021; Scheffer \r et al., 2021). The rather narrow climatic niche favoured by human societies over the last 6000 years is poised to move on the Earth's \r surface at speeds unprecedented in this time span (IPCC, 2021a), with consequences for human well-being and migration that could be \r profound under high-emission scenarios (Xu et al., 2020). This will overturn the long-lasting stability of interactions between humans and \r [...]"


id: c82001a774de92b8cb088c4fb51972d5
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"[...] domesticated plants and animals as well as challenge the habitability for humans in several world regions (Horton et al., 2021) (medium \r confidence)."


id: d1a9c0a9ce3ec10e1fe00488dfbf583e
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content:
"Indigenous Peoples have been faced with adaptation challenges \r for centuries and have developed coping strategies in changing \r environments (Coates, 2004). Along with other local groups, they hold \r relevant knowledge about the environment and environmental change, \r the impact of those changes on ecosystems and livelihoods, and \r possible effective adaptive responses (see Cross-Chapter Box  INDIG \r in Chapter 18). Therefore, the participation of Indigenous Peoples in \r climate change decisions and the inclusion of Indigenous knowledge \r in the IPCC assessment process should be of high priority (following \r recommendations in UNESCO, 2018b, and UN, 2020). Furthermore, the \r participation of scientifically trained climate specialists with indigenous \r backgrounds is valuable to the work of IPCC because the assessment \r must reflect a diverse range of views and expertise (for examples of \r IK, see Cross-Chapter Box INDIG in Chapter 18). Article 31 of the UN \r [...]"


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content:
"[...] Declaration on the Rights of Indigenous Peoples (2007) supports the \r inclusion of IK and LK in the IPCC assessment process, calling for the \r use of IK and LK to be protected and validated by Indigenous Peoples \r themselves and their inclusion as active participants in the assessment \r (Klenk et  al., 2017). Paying special attention to the mechanism \r whereby some forms of knowledge have been excluded in previous \r reports--such as the use of technical knowledge or acronyms, or the \r deployment of discipline-specific validation mechanism--is a first step "


id: 76c72baa26e94541e1c1f74843514dc3
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content:
"Moreover, IK and LK may be particularly relevant to ensuring that \r climate action does not cause further harm, and also addresses \r historical injustices committed against Indigenous Peoples and other \r marginalised social groups, recognising them as active agents of their \r own change (Nursey-Bray et  al., 2019). There are between 370 and \r 500 million people in at least 90 countries belonging to about 5,000 \r different ethnic groups that are classified as 'Indigenous' (Sangha et al., \r 2019). Although there is no single, universal definition of Indigenous \r Peoples, core criterion within both the ILO Convention on Indigenous \r and Tribal Peoples (1989) and the UN Declaration on the Rights of \r Indigenous Peoples (UN, 2007) include: (a) self-determination and (b) \r the recognition that Indigenous Peoples as distinct social and cultural \r groups that retain collective ancestral ties to the lands they inhabited \r or to the lands from which they have been displaced. Indigenous \r [...]"


id: e48d47725771bd75cfedd9105fe9200f
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"[...] Peoples attribute cultural and spiritual values to land, environmental \r features and landscapes (ILO, 2013; ILO, 2019). Indigenous Peoples \r suffer disproportionally. For example, they are three times more likely \r to live in extreme poverty than non-Indigenous Peoples; they are also \r more likely to suffer discrimination and violence (UN, 2020). At the \r same time, Indigenous Peoples have long led climate change and \r environmental protection agendas."


id: 4e06bcca1f7e1b793eabbd1762b6d62d
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"The AR4 was the first IPCC report to explicitly discuss the value of IK \r and LK in adaptation and mitigation processes. AR5 recognised the \r importance of creating synergies across disciplines in the production \r of knowledge, acknowledging the importance of 'non-scientific' \r sources such as IK, which may not follow discipline conventions but \r nevertheless reflects the outcomes of learning across generations \r (Burkett et al., 2014). This also explains the importance of including IK \r and LK and diverse stakeholder interests and values in local decision \r making processes (Jones et  al., 2014). Such processes should be \r done in partnership with IK and LK knowledge holders and, when \r possible, be led by them (Inuit Tapiriit Kanatami, 2018). Recent IPCC \r reports have included distinct sections dedicated to IK and LK (e.g., \r IPCC, 2019b). The IPCC Special Report on Climate Change and Land \r (SRCCL) includes a section on 'Local and Indigenous knowledge for \r [...]"


id: 37d241e8082afaa9da0fefff2e9a7549
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"[...] addressing land degradation' (2019a) and the IPCC Special Report \r on Ocean and Cryosphere (SROCC) describes LK as 'what non\u0002Indigenous communities, both rural and urban, use on a daily and \r lifelong basis,' a type of knowledge which is recognised as 'multi\u0002generational, embedded in community practices and cultures, and \r adaptive to changing conditions' (2019b). The IPCC Special Report \r on Global Warming of 1.5degC emphasised the high vulnerability of \r Indigenous Peoples to climate change. It stated that disadvantaged \r and vulnerable populations, including Indigenous Peoples and certain \r local communities, are at disproportionately higher risk of suffering \r adverse consequences with global warming of 1.5degC and beyond \r (IPCC, 2018b). The report also assessed evidence in relation to the \r importance of including IK and LK in adaptation options, explaining \r their role in early warning systems and arguing that they are part of a \r [...]"


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content:
"[...] range of approaches to catalyse wide-scale values and are consistent \r with adapting to and limiting global warming to 1.5degC (IPCC, 2018b)."


id: 99d080ec5dcf3da32ac77b2bc66a2bdf
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content:
"Since AR5, several academic publications have directly addressed the \r challenges of including IK and LK in climate research ( Ford et al., 2016; \r Yeh, 2016; David-Chavez and Gavin, 2018) and demonstrated its value \r in building resilience to extreme events related to climate change \r (Janif et al., 2016; Olazabal et al., 2021). For instance, IK and LK has \r proved useful in land management methods that reduce wildfire risk \r (Nepstad et al., 2006; Cook et al., 2012; Welch et al., 2013; Mistry et al., \r 2016). Since IK is traditionally communicated through storytelling \r and oral history, there are practical challenges to integrating it into \r an assessment that prioritises scientific knowledge. There is a need \r for increased critical engagement towards the co-production of \r knowledge (Ford et al., 2016). Scholars now recognise the ontological \r and epistemological differences in approaches, understandings and \r effects of climate change (Yeh, 2016). One common strategy has \r [...]"


id: 307b421c77b23870122defdeaa4b80d0
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"[...] been assessing Indigenous observations of climate change alongside \r scientific data (Klein et  al., 2014a) as a means to bridge the gap \r between scientific inquiry and Indigenous knowledge systems \r (Fernandez-Llamazares et  al., 2017). The Intergovernmental Science\u0002Policy Platform on Biodiversity and Ecosystem Services (IPBES) and \r the CBD have helped illustrate how to bridge multiple knowledge \r systems, particularly those conceived from different ontologies. Rather \r than viewing IK as a single source of knowledge to be compared with \r scientific data, recent scholarship suggests assessments, such as the "


id: 67f6028ab0afbddaccf38fc706d1ea26
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content:
"The guidance to authors additionally identifies other practices and \r approaches relevant in applying expert judgement and developing \r assessment findings (Mastrandrea et al., 2010; Mastrandrea and Mach, \r 2011; Mach and Field, 2017). First, authors are encouraged to carefully \r consider appropriate generalisation within assessment findings, \r emphasising insights that are integrative, nuanced and rigorous (IAC, \r 2010; Mastrandrea et  al., 2010; NEAA, 2010). Second, authors are \r instructed to attend to potential biases, including in group dynamics, \r such as tendencies towards overconfidence and anchoring or Type I \r (false positive) error aversion (Mastrandrea et al., 2010; Brysse et al., \r 2013; Anderegg et al., 2014; Morgan, 2014). Third, particular attention \r is drawn to the importance of evaluating and communicating ranges \r of potential outcomes to inform decision making and risk management \r (Mastrandrea et al., 2010). In some cases, deep uncertainties related to \r [...]"


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"[...] parameters or processes that are unknown or disagreed upon strongly \r benefit from dedicated methods of assessment and decision support \r (see Cross-Chapter Box  DEEP in Chapter 17). Fourth, the guidance \r explores the different ways that framings of conclusions can shape \r their interpretation by readers. Finally, the guidance underscores \r the importance of reflecting upon all sources of uncertainty, which \r can include deep, difficult-to-quantify and easy-to-underestimate \r uncertainties arising from incomplete understanding of relevant \r processes or competing conceptualisations across the literature \r (Mastrandrea et  al., 2010). A detailed review of literature assessing \r IPCC uncertainty characterisation methods is provided in WGI 1.2.3.1."


id: ee5a3027ce6aa4636ed2b9ba5fe216eb
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content:
"Procedural justice addresses the fairness of the processes by which \r decisions are made and the legitimacy of those making the decisions \r (Gutmann and Thompson, 2009; Kitcher, 2011). Criteria include \r transparency, the application of neutral principles among parties, \r respect for participants' rights and inclusive participation in decision \r making, which often takes the form of participatory processes. Article \r 6 of the Framework Convention creates a binding commitment on \r parties to promote public participation in addressing climate change. \r Increased participation by civil society in climate policy discussion, \r including new forums such as the Local Communities and Indigenous \r People's Platform of the UNFCCC work toward this goal (UNFCCC, \r 2021). Genuine, not merely formal, participation requires communities \r be well-acquainted with the climate change risks they face and are \r given a full voice in the process of adaptation planning. Many local \r [...]"


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"[...] communities, especially those most vulnerable to climate change, \r remain excluded, which is inconsistent with principles of procedural \r justice. In addition to a normative principle, models of decision making \r also suggest that diverse, representative decision makers can be \r expected to make better decisions than more limited groups (Hong \r and Page, 2004; Landemore, 2013; Singer, 2019)."


id: a2146d7aab01327580f85f1190a38767
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"The multi-criteria concept of well-being has been increasingly \r employed as a structured framework for measuring social progress \r in many areas of public policy (Lamb and Steinberger, 2017) including \r climate and health (Chapter 7) and, to a lesser extent, in other areas \r of the climate change adaptation literature (Singh et al., 2021). Well\u0002being reflects the ability of a person to pursue and realise the goals \r that they value (Sen, 1985). The disaster risk management community \r employs well-being to evaluate mental health impacts in terms of \r peoples' abilities to cope with trauma and loss because of natural \r disasters (Berry et  al., 2010; MacDonald et  al., 2015; Willox et  al., \r 2015). The term appears in the literature with concepts such as \r human security (Koren and Butler, 2006; Adger, 2010; Pasgaard et al., \r 2017), subjective well-being or happiness (Sekulova and van den \r Bergh, 2013; Rehdanz et al., 2015; Fanning and O'Neill, 2019), welfare \r [...]"


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"[...] (Gough, 2015) and living standards or quality of life (Degorska and \r Degorski, 2018; Rao and Min, 2018)."


id: c270fa5005e4e074db19a4bb74926c76
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content:
"Recent work has used quantified measures of well-being and multi\u0002objective decision-support tools to balance among equity and efficiency \r objectives in disaster risk management (Section  1.5.2; Chapter 17; \r Markhvida et al., 2020). Rather than focus on the economic value of \r lost assets, the well-being measure evaluates disaster impacts and \r recovery policies by considering the fraction of consumption lost at \r the household level for different income cohorts. Not surprisingly, poor \r households account for twice as much of the disaster losses when \r evaluated by effects on well-being rather than by asset losses. The \r most effective policy responses also differ when using well-being and \r asset loss-based measures. Ciullo et. al. (2020) compare flood control \r strategies using multi-objective decision criteria that include both \r benefit-cost and distributional components, show how the favoured \r strategy can depend on whether one seeks equitable risk or equitable \r [...]"


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content:
"[...] risk reduction, and propose tools that can help embed both ethical \r and efficiency considerations in adaptation decisions. Widespread use \r of such approaches could strengthen consideration of climate justice \r along with efficiency in the evaluation of climate risks and adaptation \r (Section 1.5.2; Dryzek et al., 2013)."


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updated_at: 2023-04-19 13:22:51
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index: climate_gpt_v2
vector_id: 9784
content:
"Aggregate, monetised economic measures are, however, insufficient \r to address issues of climate justice fully or to reflect that wide range \r of worldviews and values that different people bring to questions of \r climate action and development (Chambwera et al., 2014). While recent \r work has enriched the consideration of distributive justice in aggregate \r social welfare functions (Adler, 2012), multi-objective approaches that \r separately report several biophysical and socioeconomic attributes \r can prove valuable (Section  17.3.3). Many adaptation measures, in \r particular those that encompass transformational social changes \r (Section 1.5), involve complicated trade-offs among multi-dimensional \r benefits and costs (Adger, 2016). Different people commonly value \r such trade-offs differently, particularly in heterogeneous societies. \r Multi-objective measures can thus enhance transparency, fairness, \r legitimacy and participation by highlighting the different outcomes \r [...]"


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content:
"[...] that different people and communities might find important, making \r the specific trade-offs more transparent and explicit, and avoiding \r privileging any particular view on the appropriate trade-offs (Lempert \r et al., 2018; Siders, 2019b; Siders and Keenan, 2020)."


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vector_id: 42304
content:
"Adaptation actions taken by individuals, social groups and organisations \r in response to climate and environmental stimuli depend, in part, on \r the options they have (see Chapters 16 and 17). Actions previously \r taken can reduce the scale of responses needed subsequently, increase \r the options available, reduce barriers to additional action and increase \r capacity to respond. Successful adaptation sufficient to meet the goals \r of the Paris Agreement and SDGs needs to involve actors at many \r scales and in many sectors, including individuals and households, \r communities, governments at all levels, private sector businesses, non\u0002governmental organisations, religious groups and social movements. \r This report highlights the increased range of societal actors engaged \r in adaptation and the need for multi-level and polycentric governance. \r The section describes key concepts related to the process of adaptation \r and assessment of how human choices and exogenous changes can \r [...]"


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content:
"Previous IPCC reports have described in detail adaptation for individual \r actors as an iterative risk management process of scoping (identifying \r risks, vulnerabilities, objectives and decision-making criteria), \r analysis (identifying options, assessing risks, evaluating trade-offs) \r and implementation (implementing chosen options, monitoring, and \r reviewing and learning) (Jones et. al. 2014). This AR6 report expands \r the focus to consider adaptation processes with multiple actors and \r a richer temporal dimension in which actions taken at one time can \r expand or contract the set of feasible, effective and just options \r available at another time, thereby increasing or decreasing the ability of \r adaptation to reduce risks (Section 17.1). This AR6 report also expands \r the focus to include decision processes the implement both adaptation \r and mitigation (Chapter 18), as well as heightened attention to M&E, \r which is a key prerequisite for successful iterative risk management \r [...]"


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content:
"[...] and achieving effective and just adaptation outcomes at local to \r global levels (Sections  1.4.3; 17.5.2). The challenges of implications \r for adaptation, mitigation and sustainable development outcomes \r result from decision-making process at different levels (Von Stechow \r et al., 2015; Bertram et al., 2016). Overcoming these challenges often \r requires significant learning and innovative ways of linking science, \r practice and policy at all scales (Shaw and Kristjanson, 2014)."


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updated_at: 2023-04-19 13:22:51
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index: climate_gpt_v2
vector_id: 2813
content:
"Adaptation actions span a vast range of activities. Successful adaptation \r generally requires a portfolio of actions, often implemented by multiple \r actors in different sectors, often in different places and over time \r (Section  17.2.2). Useful taxonomies include categorising such actions \r around representative key risks (Figure  17.3), and by human systems \r and scenarios of adaptation extent for four components of adaptation \r (depth, scope, speed and limits) (Table 16.2). As shown in Chapter 17, for \r instance, ecosystem-based adaptation, hardening buildings and physical \r barriers, and changes to zoning and planned retreat can reduce risks to \r coastal socio-ecological systems. Restoration and protection of forests, \r enhancing ecosystem connectivity through corridors and ecosystem\u0002based adaptation can reduce risks to terrestrial and ocean ecosystems. \r Increased use of grey, green and blue infrastructure and upgrading \r [...]"


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vector_id: 34126
content:
"[...] design standards, city plans and more redundancy in power systems and \r other networks can reduce risks associated with critical infrastructure. \r Insurance and diversified or changed livelihoods can reduce risks to "


id: 22056cd3d4e7782e91df881abef0eaf1
created_at: 2023-04-19 13:22:51
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"According to the UNFCCC, adaptation finance includes public, private and alternative sources of finance for supporting adaptation \r actions, whereby adaptation and resilience are often used interchangeably in this context. Adaptation finance constitutes a crucial \r enabling condition and shaper of the solution space, depending on other enabling conditions, such as proper planning, implementation \r and governance, which are also the triggers for investments and finance to flow, ensuring positive adaptation outcomes. Details of \r adaptation finance can be found in Chapter 17 (Cross-Chapter Box FINANCE in Chapter 17; Section 17.4). The adaptation and resilience \r options offer multiple benefits, including avoiding risks and losses, economic growth and well-being, as well as social and environmental \r benefits (Agrawal and Lemos, 2015; Bayleyegn et al., 2018; Global Commission on Adaptation, 2019). Hence, the rate of return on \r [...]"


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"[...] adaptation is large; for example, there is a huge potential of net benefits, that is USD 7.1 trillion while investing USD 1.8 trillion globally \r in climate resilience and adaptation options, such as early warning systems, climate-resilient infrastructure, improved dryland agriculture \r crop production, global mangrove protection and building resilience of water resources (Global Commission on Adaptation, 2019). These \r net benefits resulted primarily from reducing future losses and risk, increasing productivity and innovation, and social and environmental \r benefits. Despite significant uncertainty and concerns over undue focus on efficiency (monetary), benefit-cost estimates often ignore \r important issues of non-economic values, effectiveness of risk reduction and climate justice (procedural/distributional)."


id: 6c09e5a9128c993e06417bb9e846872a
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"The current public and private financial flows to adaptation are much smaller than needed (Cross-Chapter Box FINANCE in Chapter 17). Only \r a small portion of overall adaptation finance needs is likely to be covered by public sector finance. Private sector investment thus needs to \r play a crucial role. Hence, tracking adaptation finance flows is important for enabling effective planning and prioritisation of investments, \r assessing whether needs are being met, and ensuring accountability towards funding commitments, such as the USD 100 billion promised \r to developing countries per year by 2020 under the Paris Agreement (Donner et al., 2016). Since AR5, significant progress has been made \r in tracking adaptation finance flows through UNFCCC channels, multi-lateral development banks and bilateral finance (Cross-Chapter \r Box FINANCE in Chapter 17), but large information gaps on adaptation finance via national public finance, commercial lenders, investors, \r [...]"


id: eb81423b0a2abbfe7968b2f1ca65ec6
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"[...] asset managers and insurers, company finance, and individuals and households remain. That these financial flows do not occur suggests \r misaligned incentives and other governance challenges that could be addressed as part of a response to climate change (Chapter 17). \r Across regions and sectors, financial constraints have been identified as the most common and important determinants leading to limits \r to adaptation (Chapter 16)."


id: 21ee8c212ede9d8f853e77141eae0032
created_at: 2023-04-19 13:22:51
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"Nature-based solutions (NbS) (Section 2.6; Cross-Chapter Box NATURAL in Chapter 2) provides an example of how innovative ideas \r can expand the climate solution space (IPCC, 2018b; Seddon et al., 2019). A commonly used definition of NbS is that of The World \r Conservation Union (IUCN), which defines it as 'actions to protect, sustainably manage, and restore natural or modified ecosystems, that \r address societal challenges effectively and adaptively, simultaneously providing human well-being and biodiversity benefits' (Cohen\u0002Shacham et al., 2016). In the context of IPCC, it focuses on NbS which deliver climate change adaptation or mitigation benefits. NbS \r generally benefits biodiversity and supports its role in both climate mitigation and adaptation. While the carbon-sequestering mitigation \r role of increasing forest and tree cover has dominated much of the earlier discussions, the role of NbS in promoting adaptation of natural \r [...]"


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content:
"[...] ecosystems and human societies to climate change is being increasingly emphasised. The details of different categories of ecosystem \r services in the ocean or on land, including biodiversity, food provision, other provisioning services (e.g., medicinal and commercial \r products), and regulating and cultural services are described in Chapters 2 and 3."


id: e347903a2acf99859e5f326de3906c29
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content:
"Forest restoration would certainly contribute substantially towards climate-proofing and achievement of several SDGs as well as the Paris \r Agreement. There is increasing evidence that diverse, native tree species plantations are more likely to be resilient to climate change in \r contrast to fast-growing monocultures, (Hulvey et al., 2013) often of exotic species. At the same time, other natural ecosystems such as \r savannas, grasslands, peatlands, wetlands and mangroves have considerable value in acting as carbon sinks as well as providing other \r ecosystem services such as hydrological regulation, coastal protection, maintaining biodiversity and contributing to human livelihoods \r especially pastoralists and fishermen (Veldman et al., 2015; Conant et al., 2017; Leifeld and Menichetti, 2018; Seddon et al., 2019). \r Coastal and marine ecosystems including wetlands and mangroves have featured prominently in studies of NbS in climate adaptation \r [...]"


id: 3c52b562d6dc712097b29f28c1a9cb7b
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"[...] and mitigation potential for 'blue carbon' sequestration (Inoue, 2019; Sections 3.6.2.1; 6.3.3; Cross-Chapter Paper 2.3.2.3). Agroecological \r practices such as agroforestry, intercropping, rotational grazing, organic manuring, and integrating livestock production with cropping \r etc can also consider as NbS which contribute to both climate mitigation and adaptation (Altieri and Nicholls, 2017; Webb et al., 2017; \r Bezner Kerr et al., 2019; Leakey, 2020; Box 5.10)."


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"Much of the conceptual framework for NbS has come from initiatives to bring environmental, social and economic dimensions to the \r same level of importance, particularly in the context of a highly urbanised society (Section 6.3.3; Faivre et al., 2017; Nesshover et al., \r 2017). Emphasis has been placed on urban storm water management (Section 2.6.5.2) and heat mitigation using measures, such as \r sustainable drainage systems, urban forests, parks and green roof-tops, apart from coastal defences using NbS (Section 13.6.2.3) This has \r triggered much debate on how distinct the concept of NbS is in relation to other similar concepts, such as ecosystem-based adaptation \r (EbA) approaches (Section 9.11.4.2). There are calls for an assessment framework for proving the 'effectiveness and efficiency' of NbS \r in providing superior ecosystem and societal benefits (Calliari et al., 2019). Instead, EbA can be treated as a subset of NbS (Chapter 2). \r [...]"


id: 5cfe32451940f50285cca1f2c025462a
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"[...] However, the time frame of EbA is also an important consideration; thus, grassland and forest restoration would operate at different \r time scales, while mangrove restoration can promote adaptation only at local to national scales, depending on the extent and nature of \r coastlines (Taillardat et al., 2018). Given the complex nature of plant and animal species adapting to climate change through dispersal \r and migration to more suitable habitat, this also means that landscape-scale approaches, as opposed to purely protected areas, are \r needed to promote adaptation, conserve and sustainably use biodiversity, and sustain livelihoods (Vos et al., 2008; Sukumar et al., 2016)."


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"The concept of the solution space provides a framework for assessing \r how the options available for adaptation for any particular community \r are not constant over time and can depend on the past, current and \r future choices of many actors. The solution space is defined as the \r space within which opportunities and constraints determine why, \r how, when and who adapts to climate risks (Haasnoot et al., 2020). \r The concept aims to capture the dynamic inter-temporal, spatial and \r jurisdictional interconnections among adaptation actions. A larger \r solution space indicates people and organisations with more options \r for adapting to and reducing their risk from climate change. Both \r human choices and exogenous changes in human and natural systems \r affect the future solution space. For instance, changes such as the \r magnitude and rate of climate change may shrink the space. Economic \r growth can generate more resources that expand the solution space as \r [...]"


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"[...] can implemented adaptation actions such as pilot projects, awareness \r raising and changes in laws and regulations."


id: 4596c0a2516b7eaba761511bdc08a763
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"The empirical literature on adaptation governance has advanced \r strongly since AR5. It shows that stronger general governance \r capabilities are usually associated with more ambitious adaptation \r plans and more effective implementation of such plans (UNEP, 2014; \r Chen et al., 2016; Keskitalo and Preston, 2019b: 24; ND-GAIN, 2019; \r Oberlack, 2017; Oberlack and Eisenack, 2018; Woodruff and Regan, \r 2019; UNEP, 2018; UNEP et al., 2021). Governance capabilities are, to a \r significant degree, but not exclusively, a function of available financial \r resources and technology. They are also a function of social capital \r and societal institutions, including well-functioning local, regional and \r national governments, and collaboration among these governmental \r actors and non-governmental stakeholders, including civil society and \r the private sector. The literature also points to governance conditions \r that are likely to enable transformational adaptation (Maor et  al., \r [...]"


id: 796e629b1fec29e5ffd141b75301fcfe
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"AR5 used the concept of solution space in its SPM Figure  8 (IPCC, \r 2014c). Several AR6 chapters, in particular Chapters 13, 14 and 18, use \r the concept to address challenges salient in AR6. In any assessment \r of solutions, what is feasible, effective and just depends not only \r on the potential solution itself but the particular biophysical and \r societal context in which it might occur (Section  17.5; Wise et  al., \r 2014; Gorddard et  al., 2016). Solutions can also be space and time \r dependent because the biophysical and societal context can change \r over space and time (Section 18.1.4). In addition, the large gap that \r exists between current climate action and that needed to meet policy \r goals suggests that decision makers may not only seek to implement \r available solutions but seek to actively expand the set of solutions \r (Chapters 17; 18). Finally, as used in this report, the concept of solution \r does not fully engage with questions of 'by whom?' and 'for whom?' In \r [...]"


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"[...] many cases solutions would necessarily be implemented by multiple, \r independent actors interacting with varying degrees of cooperation \r and competition (Sections 1.5.2)."


id: 233950b59bf98ef2bc386fea49a3fe7
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"Existing comparative data for adaptive capacity worldwide is at a rather \r coarse level of temporal and spatial resolution. It can, nonetheless, \r provide a very general picture of rates of change in adaptive capacity at \r the national scale, and differences between countries. Further empirical \r research is needed to identify the most important predictors of variation \r across countries and time, though the available data suggests that \r differing national income and education levels play a major role in \r accounting for differences in adaptive capacity (Andrijevic et al., 2020). \r Spatially more resolved (sub-national) data is needed because a large \r body of case study research suggests that there is strong variation within \r countries, particularly the large ones (e.g., India, China, Brazil, United \r States) (Chapter 16; see also Nalau and Verrall, 2021 and Cross-Chapter \r Box  ADAPT). Moreover, higher degrees of adaptive capacity do not \r [...]"


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"[...] mean that adaptation action will follow automatically, nor that it will \r succeed in terms of equity and effectiveness in reducing vulnerability \r to climate change and enhancing well-being. How differences across \r and within countries in climate risk exposure translate into adaptation \r action, contingent on differences in adaptive capacity, can to some \r extent be inferred from case studies, but this remains to be studied at a \r larger, comparable and generalisable scale."


id: 5346957d94d467f5869ab15e8e7095d2
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content:
"Governance and governing refer to the structures, processes and actions \r through which private and public actors interact to address societal \r goals. This includes formal and informal institutions and the associated \r norms, rules, laws and procedures for deciding, managing, implementing \r and monitoring policies and measures at any geographic or political \r scale, from global to local. Governance systems and the specific societal \r institutions through which they are organised are crucial to the feasibility \r and success of climate change adaptation, both in terms of its effectiveness \r in reducing climate risk and vulnerability, as well as equity (including \r climate justice), with respect to incremental as well as transformational \r adaptation. This is why AR6 WGII pays even more attention than previous \r assessments to governance as an important enabling condition, and to \r the wide range of new actors beyond governments involved in planning, \r [...]"


id: 4b10656c9cfa290938d67b1208bfec46
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"[...] implementing, monitoring and evaluating adaptation action. The \r assessments in subsequent chapters of AR6 WGII show that successful \r and equitable collective adaptation efforts at different levels and scales, \r based on key principles of iterative risk management, require strong, \r usually multi-level. governance systems. Multi-level governance refers \r to the dispersion of governance across multiple levels of jurisdiction and \r decision making, including global, regional, national and local, as well as "


id: a75c87635436576d95c75c5f26f40442
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"to evolve, as does understanding of appropriate response options and \r the actors involved. In addition, norms, values and practices may change \r in response to changing conditions (Jones et al., 2014). Much learning \r by individuals, communities and organisations is unplanned (National \r Research Council, 2009), as is much current adaptation (Berrang-Ford, \r 2020), which can reduce near-term costs and administrative complexity, \r but may prove maladaptive (Section 1.4.2.4). Iterative risk management \r (Section 1.2.1.1) and related concepts such as risk governance (Renn, \r 2008) describe a planned learning process of ongoing assessment, \r action and reassessment. Iterative risk management can be as simple \r as scheduling future updates of assessments and plans, as with the \r 5-year updates of the global stocktake after 2023 called for in the \r Paris Agreement, or encompass more elaborate learning processes, \r [...]"


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"[...] such as dynamic adaptive pathways (Haasnoot et al., 2019b; Cross\u0002Chapter Box  DEEP in Chapter 17) which include specific near-term \r actions, specific trends to monitor and specific contingency actions to \r take depending on the future conditions observed. While often more \r effective at meeting goals, such planned learning processes may pose \r implementation and governance challenges (Metzger et al., 2021)"


id: 9b93e03354853646864c52565840be4f
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"Maladaptation can result from many potential barriers, including \r administrative, human, financial and technical resource constraints \r (Hassanali, 2017; Pardoe et  al., 2018; Singh et  al., 2018); lack of \r transparency and/or capacity in governance (Friend et  al., 2014); \r unreliable information on climate impacts and the lack of key \r policy guidelines (Pilato et  al., 2018); entrenched institutional, legal \r and technical obstacles (Gao, 2018) and low literacy, including \r environmental and scientific literacy (Wright et  al., 2014); exclusion \r of vulnerable groups (Forsyth, 2018); governance fragmentation (that \r is, a fragmentation of laws, regulations, and policy requirements); \r and limited cross-sectoral collaboration, meaning that there is \r limited coordination and that top-down planning approaches are not \r connected to local dynamics (Archer et al., 2014; Pardoe et al., 2018). \r This report draws attention to maladaptation challenges recognising \r [...]"


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"[...] that not all adaptation-related responses reduce risks (Chapter 16). \r Besides, maladaptation is the opposite of successful adaptation, which \r is associated with reduction of climate risks and vulnerabilities for \r humans and ecosystems, increased well-being and co-benefits with \r other sustainable development objectives. (Chapter 17)"


id: ab4a44a088d61d2c4e6d404c51b27ab4
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"Academic work on adaptation now spans an increasing number of disciplines and countries and is published across diverse academic \r outlets and disciplines, with 28.5% annual average increase in adaptation specific publications (Nalau and Verrall, 2021). This expands \r the range of considerations and perspectives within adaptation research and increases the challenge of identifying and synthesising all \r relevant research on adaptation in reviews or assessments (Berrang-Ford et al., 2015; Webber, 2016; Singh et al., 2020; Sietsma et al., \r 2021). Also, large bodies of research and knowledge exist that support climate adaptation ideas, theoretical development and practical \r implementation, but are not explicitly framed as climate change adaptation (Dupuis and Biesbroek, 2013; Biesbroek et al., 2018; Keskitalo \r and Preston, 2019a). Therefore, debates still emerge about what actually counts as 'adaptation' (Dupuis and Biesbroek, 2013), and what \r [...]"


id: 2102a72b6b318bdda3e48d1752fd2186
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"One of the contributions of research 'on adaptation' is to track and debate the broader trends, core characteristics and overall assumptions \r embedded in adaptation knowledge. This reflexive turn about the foundational assumptions is itself one emerging trend in adaptation \r research (e.g., Preston et al., 2013; Nalau et al., 2015; Juhola, 2016; Atteridge and Remling, 2017). This signals the influence of more \r social science in adaptation research and increased awareness of the practical value of being transparent and critically reflective about \r the content, topics, frames and approaches that researchers use (Lacey et al., 2015; Nalau et al., 2021; Singh et al., 2021). For example, \r different conceptions of adaptation contribute to different definitions of 'adaptation success', different ideas about what 'effective' \r adaptation practice looks like and, thus, different conclusions about what is and is not working well (Berrang-Ford et al., 2019; Dilling \r [...]"


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"[...] et al., 2019; Magnan et al., 2020; Owen, 2020; Eriksen et al., 2021; Singh et al., 2021; Section 17.5.1.1). This diversity adds richness and \r options, but also poses challenges in constructing a conventional evidence base for decision and policymaking. Adaptation researchers \r are increasingly expected to offer clear and confident advice on adaptation success, yet are also increasingly aware of how context\u0002specific and contested success is (see also Lacey et al., 2015 on ethics)."


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"Helping to differentiate adaptation from mitigation during this period was a focus on theoretical principles and a framing of adaptation \r as local and context specific, in contrast to mitigation's global character (Nalau et al., 2015; Westoby et al., 2020), leading to locally \r oriented adaptation research and practice, including the rise of community-based adaptation (Kirkby et al., 2017). Since AR5, however, \r adaptation has extended beyond the local, recognising the 'borderless' character of many climate change risks and vulnerabilities (Benzie \r and Persson, 2019) and framing adaptation and global adaptation governance as a global public good (Persson, 2019). Encompassing \r this expanded scale is challenging for adaptation research compared to treating adaptation as a local issue, which fits more easily with \r social research methods. Adaptation now works across scales (Biesbroek et al., 2013; Dzebo and Stripple, 2015; Keskitalo and Preston, \r [...]"


id: 526c68e8299dc1e830f3d15271005706
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"[...] 2019a) and attends simultaneously to both the opportunities and risks arising from climate change (Juhola, 2016; Keskitalo and Preston, \r 2019a). This suggests that empirical adaptation research should incorporate multi-scalar research designs and methods."


id: 4175964987d220663d6b5acada77a64d
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"A strong focus has been and remains on case studies of adaptation practice, but adaptation science literature reviews have become \r common. Recent systematic reviews cover topics such as adaptation effectiveness (Owen, 2020), public participation and engagement \r (Hugel and Davies, 2020), the role of LK (Klenk et al., 2017), adaptive capacity (Mortreux and Barnett, 2017; Siders, 2019a; Mortreux et al., \r 2020), evolution of adaptation science (Nalau and Verrall, 2021), empirical adaptation research in the Global South (Vincent and Cundill, \r 2021), how cities are adapting (Reckien et al., 2018), how decisions can be made (Siders and Pierce, 2021), IK (Petzold et al., 2020) \r and SIDS (Robinson, 2020). Review papers have developed common methodologies for how to undertake robust reviews in adaptation \r research (Berrang-Ford et al., 2015; Biesbroek et al., 2018; Lesnikowski et al., 2019a; Singh et al., 2020), and noted an existing imbalance \r [...]"


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"[...] as the majority of the literature still originates from the Global North compared to Global South (Robinson, 2020; Nalau and Verrall, 2021; \r Sietsma et al., 2021)."


id: 5679e42973fa3b36c7966ef00c665ff
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content:
"At the same time, adaptation research is also challenged by increasing attention to transformational adaptation, which refers to fundamental \r changes going beyond existing practices, including new approaches to adaptation decision making (Section 1.5). Whereas AR5 noted \r transformational adaptation as an area of future research (Klein et al., 2014b), it has continued to grow in profile since then. Rather than \r a future or fringe consideration--for example, an extreme action necessitated by the limits of incremental adaptation-- transformational \r adaptation is increasingly an option that decision makers are considering today. This increasing attention to transformational adaptation \r is driven by a growing recognition of climate risks and impacts, as well as the need for urgent, systemic action as laid out in the IPCC's \r recent special reports (IPCC, 2018c). Yet what incremental and transformational adaptation look like, how they relate in practice and how \r [...]"


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"[...] to appropriately choose incremental or transformational options is uncertain and increasingly debated ( Section 17.2.2.3; Termeer et al., \r 2016; Few et al., 2017; Vermeulen et al., 2018; Magnan et al., 2020; Wilson et al., 2020). One of the main challenges is now to generate \r empirical evidence and policy relevant insights on transformational adaptation (e.g., Jakku et al., 2016). Transformative approaches are \r especially being discussed in the context of COVID-19 (Schipper et al., 2020; Cross-Chapter Box COVID in Chapter 7)."


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"Another characteristic of recent adaptation research is a stronger focus on ethics, justice and power (Byskov et al., 2021; Coggins et al., 2021; \r Eriksen et al., 2021; Singh et al., 2021). Researchers and practitioners are increasingly impatient to address the root causes of vulnerability \r and use inclusive climate adaptation processes to generate effective adaptation responses for marginalised and misrecognised groups \r (Tschakert et al., 2013; Eriksen et al., 2015; Scoones et al., 2015; Gillard et al., 2016; Wisner, 2016). Increasingly ambitious, normative \r adaptation research often challenges technological solutions that simply reinforce the existing status quo (Nightingale et al., 2019, p. \r 2) and calls for 'socially just pathways for change'. Here work on adaptation overlaps with mitigation, transitions and other large-scale \r social change, encouraging the move towards more systemic, integrated approaches that discern between options according to multiple \r [...]"


id: c7073f1dd838101f17c97c152381d68d
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
vector_id: 32329
content:
"how climate justice intersects with other justice agendas. Attention is also turning to relations and tensions between different adaptation \r approaches, scales, constraints, limits, losses, enablers and outcomes (Barnett et al., 2015; Pelling et al., 2015; Mechler and Schinko, 2016; \r Crichton and Esteban, 2017; Gharbaoui and Blocher, 2017; Deshpande et al., 2018; McNamara and Jackson, 2019). Evident here is an \r ongoing, serious knowledge gap around the long-term repercussions of adaptation interventions. There is growing awareness of the need \r to address the potential for maladaptation (Sections 1.4.2.4; 5.13.3; 15.5.1; 17.5.2; Chapter 4). Concerns about maladaptation have led \r to renewed calls to open the 'black box' of decision making to examine the influence of power relationships, politics and institutional \r culture (Biesbroek et al., 2013; Eriksen et al., 2015; Goldman et al., 2018), including the power-adaptation linkage itself (Woroniecki \r [...]"


id: 85b07132753bb6ee2ed900255d0db684
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
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index: climate_gpt_v2
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content:
"[...] et al., 2019), external factors outside the decision-making process (Eisenack et al., 2014) and the influence of leadership on adaptation \r processes and outcomes (Meijerink et al., 2014; Vignola et al., 2017)."


id: ac38866e699bc22f6b09db429d712738
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
vector_id: 27545
content:
"The effectiveness of adaptation efforts also depends on the constraints \r and limits that human and natural systems face when confronted with \r increasingly higher levels of climate risks. The concept of adaptation \r limits strongly affects any appropriate balance among adaptation and \r mitigation actions in the sense that less mitigation makes adaptation \r harder or even infeasible. Adaptation limits refer to the point at which \r an actor's objectives (or system needs) cannot be secured from intolerable \r risks through adaptive actions (Annex II: Glossary). Adaptation limits \r can be soft or hard. Soft adaptation limits occur when options may \r exist but are currently not available to avoid intolerable risks through \r adaptive actions and hard adaptation limits occur when no adaptive \r actions are possible to avoid intolerable risks. Intolerable risks are those \r which fundamentally threaten a private or social norm--threatening, \r [...]"


id: 7a103b94b93b73598750a3e7f367bd38
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
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index: climate_gpt_v2
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content:
"[...] for instance, public safety, continuity of traditions, a legal standard or a \r social contract--despite adaptive action having been taken (Dow et. al. \r 2013). Intolerable risks threaten core social objectives associated with \r health, welfare, security or sustainability (WGII AR5 Chapter 16, Klein \r et al., 2014b). Through the lens of resilience, hard limits represent the \r range of change or disturbance beyond which a system cannot maintain "


id: 1e02e2d6ab6bb62e680166f2c83bd1d5
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
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content:
"Existing case studies use varying criteria for assessing effectiveness, \r complicating comparisons. Judgements regarding successful \r adaptation are contingent on the chosen scale and perspective (success \r for whom?) (Adger et al., 2005; Dilling et al., 2019) and on the level \r of risk, that is increasing climate risks may cause previously successful \r adaptation to become insufficient. Rather than a binary outcome \r (successful or unsuccessful), adaptation can be viewed on a continuum \r from successful adaptation to maladaptation (Section  17.5.2). \r Assessments of adaptation success need to account for distributional \r effects and differential vulnerability, as well as consider connections \r across different scales and complex interactions with other change \r processes (Section 17.5.1). Recent literature has begun to identify how \r adaptation can better achieve its intended objectives (Eriksen et al., \r 2021). For instance, inclusive M&E can legitimise and validate M&E \r [...]"


id: 5ead2fda781fddcb100890c7a19fb5cc
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
vector_id: 13945
content:
"This report assesses adaptation limits (soft and hard) and residual risks \r for some actors and systems (Chapter 16). Residual risk is the risk \r that remains following adaptation and risk reduction efforts (SROCC). \r Residual risk is also used as other terms such as 'residual impacts', \r 'residual loss and damage' and 'residual damage'. As noted in AR5 \r WGII (IPCC, 2014a, b), the residual risk is larger or smaller depending \r on a society's choices about the appropriate level of adaptation and \r its ability to achieve an appropriate level. The intersection of inequality \r and poverty presents significant adaptation limits, resulting in residual \r impacts for vulnerable groups, including women, youth, elderly, ethnic \r and religious minorities, Indigenous People and refugees (Section 8.4.5). \r An appropriate level of adaptation, which ideally reflects a balance \r between the desired level of risk and the actions needed to achieve \r [...]"


id: 9d36256620c2d3e22420cb20322213b8
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
vector_id: 24896
content:
"[...] that level of risk, depends on the solution space, the society's views \r on climate justice, the tolerance for climate-related risks, the society's \r tolerance for the costs and other impacts of the actions needed to \r reduce risk. IPCC's special reports stated that residual risks rise with \r increasing global temperatures from 1.5degC to 2degC (SR 1.5) and emerge \r from irreversible forms of land degradation (SRCCL). Among other risks, \r this report evidenced that, at risk to coastal flooding from sea level \r rise, nature-based adaptation measures (e.g., coral reefs, mangroves, \r marshes) reach hard limits beginning at 1.5degC of global warming \r (Chapter 16). Residual risks may lead to exceeding the limits of \r adaptation, hence, this report underscores on the role of decision making \r on transformational adaptation for dealing with residual risk as well as \r soft and hard adaptation limits (Cross-Chapter Box  LOSS in Chapter \r [...]"


id: 6bad9dd9bebcb16a789ff7bea930999e
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
vector_id: 16252
content:
"[...] 17). Section 1.5 addresses transformational adaptation in the context \r of climate resilient development pathways since such adaptation is \r inseparable from mitigation and sustainable development."


id: 89c0b3745003dbc2da3bc5a0e5b938bc
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
vector_id: 21405
content:
"A species' ability to adapt may be significantly impacted by the \r dynamics of interactions between the ecosystems and species, so that \r a species may reach its limit to adapt even in a gradually changing \r environment, leading to sudden changes in range fragmentation \r (Radchuk et  al., 2019). As human interventions affect the ability \r of species and ecosystems to adapt, a deeper understanding on \r ecosystems and species interactions and evolution in response to \r climate change is important in order to reduce future biodiversity losses \r (Nadeau and Urban, 2019). Soft limits are usually associated with \r human systems whereas hard limits are more proximate for natural \r systems due to inability to adapt to biophysical changes (Chapter 16) \r (medium confidence). Many human and natural systems are near their \r soft adaptation limits for instance, terrestrial and aquatic species and \r ecosystems, coastal communities, water security, crop production, and \r [...]"


id: 9d05e063cadeefbcedf53fb51ee58b4a
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
vector_id: 24866
content:
"The concept of limits to adaptation is dynamic in terms of the temporal, \r spatial and contextual dimensions of climate change risks, impacts and \r responses (Chapter 17; Storch, 2018). Adaptation limits depend on a \r complex function of interactions between social, ecological, technological \r and climatic elements, which appear to have thresholds beyond which \r adaptation can be infeasible and represent limits to adaptation. Such \r thresholds are endogenous to society and hence contingent on ethics, \r knowledge, attitudes, culture, governance, institutions and policies \r (Abrahamson et  al., 2009; Tschakert et  al., 2017). Since AR5, the \r evidence on limits to adaptation has been advanced across regions and \r sectors. Many adaptation constraints (financial, governance, institutional \r and policy, etc.) lead to soft adaptation limits (see Chapter 16 for \r detailed evidence on constraints and adaptation limits). The ability of \r [...]"


id: 7fb1e16460bbe1d47284a049e19792b0
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
vector_id: 19602
content:
"[...] actors to overcome these constraints including social constraints to \r behavioural changes, depends on additional adaptation implementation. \r (Abrahamson et  al., 2009; Juan, 2011; Di Virgilio et  al., 2019). Thus, \r socioeconomic, technological, governance and institutional systems or \r policies can be changed or transformed in responses to the different \r dimension of adaptation limits to climate change and extreme events."


id: 693a48fb837ef0c228c9ff4a1a39a107
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
vector_id: 15778
content:
"The concept of Loss and Damage (with capitalised letters, L&D) \r refers to the discussion point under the UNFCCC, which is to 'address \r loss and damage associated with impacts of climate change, including \r extreme events and slow onset events, in developing countries that \r are particularly vulnerable to the adverse effects of climate change'. \r Lowercase letters of losses and damages refer broadly to harm from \r (observed) impacts and (projected) risks (IPCC, 2018a). The IPCC report \r uses the latter for its assessment on loss and damage which may provide \r useful information for the former. L&D associated with climate change \r has gained importance supported by the robust scientific evidence on \r anthropogenic climate change amplifying the frequency, intensity and \r duration of climate-related hazards (Mechler et  al., 2019). Loss and \r damage associated with those residual losses and damages that are felt \r [...]"


id: abae989cadd59d3d26ef9d8cc8d73b6e
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
vector_id: 27451
content:
"[...] beyond the adaptation actions taken imply a sense of limits to adaptation \r at a given time and within a spatial context (Tschakert et  al., 2017). \r IPCC's SRCCL also underlined the unavoidable loss and damage due to \r changes in tropical and extratropical cyclones and marine heatwaves, \r where adaptation and resilience limits are being exceeded for the people \r and ecosystems (Cross-Chapter Box LOSS in Chapter 17; IPCC, 2019a)."


id: bea2e078ea81a26b5b70c2c9ff5e8fae
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
vector_id: 30796
content:
"Boyd et al., 2017). It originated in assessing compensation for SIDS, \r related to sea level rise impacts. It has since become formalised under \r the UNFCCC, through the establishment of the Warsaw International \r Mechanism (UNFCCC, 2013) and Article 8 of the Paris Agreement \r (UNFCCC, 2015b). The Warsaw International Mechanism promotes \r the implementation of comprehensive risk management approaches, \r improves understanding of slow onset events, non-economic losses \r and human mobility (migration, displacement), and enhances action \r and support, including finance, technology and capacity building to \r avert, minimise and address loss and damage associated with climate \r change impacts, particularly on vulnerable and developing countries \r (UNFCCC, 2021). Different actors have defined loss and damage \r differently in reference to climate change impacts and responses \r (Surminski and Lopez, 2015; Roberts and Pelling, 2016; Boyd et  al., \r [...]"


id: 71e5474ddfdf69d75934000d20219ca8
created_at: 2023-04-19 13:22:51
updated_at: 2023-04-19 13:22:51
content_type: text
index: climate_gpt_v2
vector_id: 17284
content:
"[...] 2017; McNamara and Jackson, 2019). These understandings include \r the following: (a) an adaptation and mitigation perspective linking all \r human-induced climate change impacts to potential loss and damage \r and a mandate to avoid dangerous anthropogenic interference; (b) a \r risk management perspective emphasising interconnections among \r disaster risk reduction, climate change adaptation and humanitarian \r efforts; (c) a limits to adaptation perspective focused on residual \r loss and damage beyond adaptation and mitigation; and (d) an \r existential perspective highlighting inevitable harm and unavoidable \r transformation for some people and systems. This report assesses the \r growing literature on loss and damage across sectors and regions \r linking with adaptation constraints and limits, GWL and incremental \r and or transformational adaptation to climate risks (Section  8.3.4; \r Cross-Chapter Box LOSS in Chapter 17; Box 10.7)."


