# document

id: fbbec16cb8c8b60f59eeddfb9e68337d
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 41660
content:
"U\r Uganda 1113, 1578, 1746, 1766\r Ukraine 870\r uncertainty* 157, 181\r AFOLU emissions accounting 752\r AFOLU mitigation 751, 753, 780, 824\r bioenergy and BECCS 800, 802\r CDR methods 1265, 1274\r coastal wetlands conversion rates 787\r emission metrics 1830\r emissions 222-226, 240\r AFOLU emissions 756-758, 757, 830\r GHG emissions 6n, 7\r historical emissions 6, 222\r financing needs 1569-1570\r low-carbon innovation 696\r mitigation potentials 1253\r modelled temperature outcomes 316, 318\r NDC estimates 423-424\r remaining carbon budget 322\r scenarios 1876\r shifting development pathways and accelerated \r mitigation 471-472\r sub-national and non-state action 429-430\r sustainable development pathways 1770\r technology investments 1651\r unit costs 11, 12, 28, 89, 98, 1052\r United Kingdom (UK)\r accelerated mitigation pathways 439, 455\r buildings 439, 989, 990, 1003, 1005\r CDR policies and R&D 1277-1278\r climate governance and institutions 1366, 1366, \r 1367\r climate laws 1361, 1363\r [...]"


id: 5ca66f1997bf238bcabf3d76dfe6242c
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 13562
content:
"[...] consumption-based emissions 243\r dietary shifts 547\r Emissions Trading System (ETS) 1384\r energy regulatory policy 1389\r energy sector 1766\r energy system model 1848\r energy transition policies 700\r food system 804\r food waste reduction initiative 1750-1751\r household emissions 260\r industry policy 1215\r net zero targets 432, 1277-1278\r Offshore Wind Accelerator Project 1216\r policies 1277-1278\r policy impacts 270\r public trust 555\r REDD+ 1503\r regulatory analysis 1391\r social movements 1508\r transport 1060"


id: fd69fe705a38c67e9f623ea47450a516
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 41941
content:
"circular economy and recycling 901, 902, \r 909-910\r climate action 866-867, 879\r and climate change 864, 866-867, 877-880, \r 905\r climate networks 914, 1378-1379, 1512-1513, \r 1756\r climate-resilient development 878-879\r climate-smart villages (CSV) 795\r co-benefits 378, 864, 873-877, 874, 878, 897, \r 903-908, 903-904, 905-907, 1755-1756\r competitiveness 875\r construction materials 901-902, 901\r COVID-19 pandemic 925-926\r cross-sector effects 864\r cross-sectoral coordination 898, 917, 924\r cross-sectoral implications 1313\r deep decarbonisation and systemic \r transformation 864, 894\r defining 867-868, 895-896\r developing countries 869, 870-871\r digitalisation 1760\r economic development 875-876, 917\r economic growth 255\r electrification and energy switching 899-902, \r 920\r emissions accounting frameworks 871-873, 927\r emissions data 926, 927\r emissions forecasts 890-894, 890, 891, 926\r emissions reduction 864\r emissions trends and drivers 8, 255, 768, 863, \r [...]"


id: ffe3335729acf3540f45d2451c2dbd93
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 42414
content:
"[...] 867, 881, 884-886, 887, 925-926\r energy demand 898, 899-901\r energy-driven urban design 923\r energy efficiency 899, 908-909\r energy systems 873, 875, 899-901, 921\r energy use 897, 898, 899, 905, 908-909\r expansion 882, 883-884, 883, 887-890, 888, \r 889\r extended metropolitan regions 870\r FAQs 927\r feasibility assessment 867, 917, 918\r food systems 910\r GHG abatement potential 911\r governance, institutions, and finance 865, 878, \r 911-917\r growth typologies 919-921, 919\r heating and cooling 898-899, 907\r household emissions 260, 262, 263\r housing 897-898\r Illustrative Mitigation Pathways (IMPs) 893, 894\r informal sector 925\r economy 870, 910\r settlements 864-865, 884\r information and communication technology \r 924-925\r infrastructure 869, 890, 894-896, 926\r blue infrastructure 864, 875, 876, 877\r cycling and 908, 926\r green infrastructure 864, 875, 876, 877, \r 902-908, 903-904, 905-907\r investment 915"


id: 47df727130801b7a98ac9fd67aa1e01
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 9857
content:
"sustainability experiments 1694\r sustainable development 795, 867, 873-875, \r 874, 898-899, 900\r synergies and trade-offs with SDGs 41-42, 903, \r 903-904, 1730, 1762, 1763, 1764, 1770, \r 1771\r towns 869-870, 870\r transformational change 865\r transport 1060, 1062, 1755-1756\r active transport 908, 926\r 'Avoid' policies 565-566\r cycling and urban infrastructure 908, 926\r modal shift from private 558-559\r public transport 915, 1079-1080, 1081, \r 1082\r smart technology and 1062-1063, 1062\r and urban form 897-898, 1058-1059, \r 1058, 1059\r urban planning and transport 1058-1059, \r 1059\r vulnerability 878-879\r waste and waste management 909-910\r water systems 910\r wood products building materials 804-805\r see also cities*\r urbanisation* 166, 863, 864\r biophysical effects 766\r and climate change 877-880\r demand for materials 1175-1176\r developing countries 869, 870-871\r development pathways and emissions 452-453, \r 466-467\r emerging economies 870\r and emissions 768, 887\r [...]"


id: 362953ee4ed16d0ffafdc05cbac277ae
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
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vector_id: 6779
content:
"[...] and income 868, 868, 887\r megatrend 877-880\r rapid 255\r resource-efficient and walkable 893\r scenarios of future urban land expansion \r 887-890, 888, 889, 891, 892\r Uruguay 256\r USD100 billion a year commitment 1560, 1565, \r 1604\r USEPA emissions data 764"


id: a8f31c2c24478fd7883d2cab4d4232df
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 26934
content:
"integrated spatial planning 864, 865, 896-899, \r 909, 911, 920, 921, 1304\r international cooperation 1514\r investment and finance 871, 915-916, 1597\r jobs 897-898\r land use mix 897-898\r land use trends 880-884, 881, 882, 883, \r 887-890, 887, 888, 889\r local decision making and community \r involvement 900\r lock-in 268, 697, 863, 894-896, 895-896, 899, \r 911, 1059\r low-carbon urban development 875, 878, 880, \r 924\r material demand 923, 923\r mitigation options and strategies 864, 867, \r 873-877, 874, 884, 894-911, 920, 927\r active transport 908, 909\r avoiding carbon lock-in 894-896, 899, 911\r avoiding, minimising and recycling waste \r 909-910\r cascading effects 864, 894, 895-896, 920, \r 923\r cross-sectoral integration 910-911\r electrification and energy switching \r 899-902, 920\r green and blue infrastructure 902-908, \r 903-904, 905-907, 920\r material efficiency 911\r net-zero emissions materials and supply \r chains 901-902\r resource efficiency 911\r socio-behavioural aspects 908-910, 920\r [...]"


id: 4150c0dcb0f18b3704def84e87201306
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 8674
content:
"[...] spatial planning, urban form and \r infrastructure 864, 865, 896-899, 897, \r 909, 911, 920, 921\r urban-rural linkages 910\r mitigation pathways for different urban growth \r typologies 919-925, 920\r mitigation potential 884, 890, 893, 897, 899, \r 905, 905-907, 907-908, 910, 913-914, \r 920, 921\r net-zero emissions targets 30, 914-915, 923\r net zero GHG emissions 864, 872\r policies 864, 878, 879-880, 1756\r population 768, 869, 870\r population decline 870\r population density 881, 883, 898, 899, 900, 925\r population growth 863, 868-870, 869, 901-902\r resilience 877-879, 880\r rural development 795\r scenarios and pathways 30, 887-894, 888, 889, \r 890, 891, 892, 893\r SDG linkages 903, 903-904\r sequencing mitigation strategies 864, 919\r settlement types 869-870, 870\r smart cities 1653\r socio-economic context 871\r stormwater reduction and management \r 907-908\r street connectivity 897-898\r subnational actors 913-914\r suburbanisation 466-467"


id: 6b7193605eaed936b02fa6c1ccb4735d
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 16201
content:
"CDR and CCS 668, 705-706\r hydropower 666, 1303\r nuclear power 640\r power plants with CCS 643\r water use efficiency 793\r well-being* 176, 254-255, 375-377, 505, 508, \r 509-510\r AFOLU linkages 827, 829\r buildings 956\r co-benefits of urban mitigation 894, 898, 905\r and demand-side mitigation 521-525, 572\r eudaimonic 513\r and GHG emissions 512-514\r hedonic 513\r impacts of solar radiation modification (SRM) \r 1491-1492\r metrics 512-514, 515, 516, 570\r policies for 521-524\r positive feedbacks 522\r services for 514-516, 515, 517, 519\r social well-being benefits of buildings mitigation \r 1003-1004\r women 525-527\r West and East Africa 795\r white certificates 1011, 1677, 1680\r wildfires 670\r wind energy* 11, 12, 634-637, 635, 636, 1752\r capacity and generation 615, 627, 627\r capacity factors 635-636\r climate change impacts 665, 667\r costs 168, 634, 635, 636-637, 636\r costs and potential 634-635\r critical strategic minerals 637-638\r electricity prices 615\r environmental/ecological impacts 637\r [...]"


id: 68873b0fd3d70eff11a92faecb4c2e70
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 15657
content:
"[...] impact on climate 670-671\r industry 1183, 1216\r land occupation, impacts and risks 1302\r levelised costs of electricity (LCOE) 636, 636, \r 662\r low-carbon energy transition 689\r net-zero energy systems 674\r offshore 257, 258, 634, 635-637\r onshore 257, 258, 634, 635, 636\r public support 637\r synergies and trade-offs 1697, 1761\r technical potential 634-635\r technology improvement 257, 259\r technology transfer and cooperation 1502\r trends 627, 627\r women 525-527\r wood products 804-805, 995-996, 1299\r World Business Council on Sustainable \r Development (WBCSD) 1511\r World in 2050 Initiative (TWI2050) 1742\r World Trade Organization (WTO) 1500-1501\r Y\r youth activism 506, 525, 557, 1375, 1508-1509, \r 1765"


id: d2433ab33a027b2c80abf7fd4b610dc7
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 34348
content:
"waste and waste management 1192, 1763\r anaerobic digestion 1301\r animal waste management 795-796, 806\r biochar production 1301-1302\r co-benefits 876, 1210\r costs and potentials 38-39, 1257, 1258\r e-waste 539, 540\r emissions sources 1833\r food loss and waste 254, 803-804, 1285, 1290, \r 1750-1751\r food system GHG emissions 1281, 1281, 1282\r industry 1169-1170, 1179, 1180, 1186, 1189, \r 1192, 1210\r SDG co-benefits 1210\r urban symbiosis 1180\r urban systems and other settlements 876\r waste heat to power (WHP) 1181\r waste-to-energy 649-650, 910\r water\r availability/quality 825-826, 1301, 1741\r demand 374-375, 666\r energy-water-land nexus 1859\r mitigation and sustainable development \r 374-375\r resources 1751-1753\r water-energy-food nexus 1295-1296, 1317-1318\r accelerated mitigation pathways 442\r accelerating sustainable transitions 1751-1754, \r 1758, 1759, 1760-1761\r Food-Energy-Water (FEW) nexus 1402-1403, \r 1406\r technology and innovation 1691\r water footprint 647-648\r [...]"


id: c47631ca2a43fe55b43b3016a95d0173
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 31867
content:
"Nerilie Abram (Australia), Carolina Adler (Switzerland/Australia), Nathaniel L. Bindoff (Australia), \r Lijing Cheng (China), So-Min Cheong (Republic of Korea), William  W.  L. Cheung (Canada), \r Matthew Collins (UK), Chris Derksen (Canada), Alexey Ekaykin (Russian Federation), Thomas \r Frolicher (Switzerland), Matthias Garschagen (Germany), Jean-Pierre Gattuso (France), Bruce \r Glavovic (New Zealand), Stephan Gruber (Canada/Germany), Valeria Guinder (Argentina), \r Robert Hallberg (USA), Sherilee Harper (Canada), Nathalie Hilmi (Monaco/France), Jochen Hinkel \r (Germany), Yukiko Hirabayashi (Japan), Regine Hock (USA), Anne Hollowed (USA), Helene Jacot \r Des Combes (Fiji), James Kairo (Kenya), Alexandre K. Magnan (France), Valerie Masson-Delmotte \r (France),  J.B. Robin Matthews (UK), Kathleen McInnes (Australia), Michael Meredith (UK), \r Katja  Mintenbeck (Germany), Samuel Morin (France), Andrew Okem (South Africa/Nigeria), \r [...]"


id: 39c2a90107752599c9e26753e2ba1e78
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 7376
content:
"[...] Michael Oppenheimer (USA), Ben Orlove (USA), Jan Petzold (Germany), Anna Pirani (Italy), Elvira \r Poloczanska (UK/Australia), Hans-Otto Portner (Germany), Anjal Prakash (Nepal/India), Golam \r Rasul (Nepal), Evelia Rivera-Arriaga (Mexico), Debra C. Roberts (South Africa), Edward A.G. Schuur \r (USA), Zita Sebesvari (Hungary/Germany), Martin Sommerkorn (Norway/Germany), Michael \r Sutherland (Trinidad and Tobago), Alessandro Tagliabue (UK), Roderik Van De Wal (Netherlands), \r Phil Williamson (UK), Rong Yu (China), Panmao Zhai (China)"


id: eba7474247f91296ffae26335caaaecd
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 38822
content:
"Human communities in close connection with coastal environments, small islands (including Small Island Developing \r States, SIDS), polar areas and high mountains7\r  are particularly exposed to ocean and cryosphere change, such as sea \r level rise, extreme sea level and shrinking cryosphere. Other communities further from the coast are also exposed to \r changes in the ocean, such as through extreme weather events. Today, around 4 million people live permanently in \r the Arctic region, of whom 10% are Indigenous. The low-lying coastal zone8\r  is currently home to around 680 million \r people (nearly 10% of the 2010 global population), projected to reach more than one billion by 2050. SIDS are home \r to 65 million people. Around 670 million people (nearly 10% of the 2010 global population), including Indigenous \r peoples, live in high mountain regions in all continents except Antarctica. In high mountain regions, population is \r [...]"


id: d23fcaf926dbb3c8bcec69f73b0f63a8
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 34345
content:
"[...] projected to reach between 740 and 840  million by 2050 (about  8.4-8.7% of the projected global population). \r {1.1, 2.1, 3.1, Cross-Chapter Box 9, Figure 2.1} "


id: 1d526877a3f15d7ffad49a82025ae99b
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
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vector_id: 2338
content:
"Figure SPM.1 (continued): Changes are shown for: (a) Global mean surface air temperature change with likely range. {Box SPM.1, Cross-Chapter \r Box 1 in Chapter 1} Ocean-related changes with very likely ranges for (b) Global mean sea surface temperature change {Box 5.1, 5.2.2}; (c)\r Change factor in surface ocean marine heatwave days {6.4.1}; (d) Global ocean heat content change (0-2000 m depth). An approximate steric sea \r level equivalent is shown with the right axis by multiplying the ocean heat content by the global-mean thermal expansion coefficient (e  0.125 m per \r 1024 Joules)12 for observed warming since 1970 {Figure 5.1}; (h) Global mean surface pH (on the total scale). Assessed observational trends are \r compiled from open ocean time series sites longer than 15 years {Box 5.1, Figure 5.6, 5.2.2}; and (i) Global mean ocean oxygen change (100-600 \r [...]"


id: ccab803fff9099fa9339ad1151cb2446
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 33333
content:
"[...] m depth). Assessed observational trends span 1970-2010 centered on 1996 {Figure 5.8, 5.2.2}. Sea level changes with likely ranges for (m) Global \r mean sea level change. Hashed shading reflects low confidence in sea level projections beyond 2100 and bars at 2300 reflect expert elicitation on the \r range of possible sea level change {4.2.3, Figure 4.2}; and components from (e,f) Greenland and Antarctic ice sheet mass loss {3.3.1}; and (g) Glacier \r mass loss {Cross-Chapter Box 6 in Chapter 2, Table 4.1}. Further cryosphere-related changes with very likely ranges for (j) Arctic sea ice extent \r change for September13 {3.2.1, 3.2.2 Figure 3.3}; (k) Arctic snow cover change for June (land areas north of 60oN) {3.4.1, 3.4.2, Figure 3.10}; and \r (l) Change in near-surface (within 3-4 m) permafrost area in the Northern Hemisphere {3.4.1, 3.4.2, Figure 3.10}. Assessments of projected changes \r [...]"


id: 7fbbab6864e8672bb3c0a4dec79c32c7
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 19607
content:
"[...] under the intermediate RCP4.5 and RCP6.0 scenarios are not available for all variables considered here, but where available can be found in the \r underlying report. {For RCP4.5 see: 2.2.2, Cross-Chapter Box 6 in Chapter 2, 3.2.2, 3.4.2, 4.2.3, for RCP6.0 see Cross-Chapter Box 1 in Chapter 1}"


id: 1ea7af2a5b3b45b5c9a97cdd4a9cc2c8
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 2599
content:
"Figure SPM.2 | Synthesis of observed regional hazards and impacts in ocean24 (top) and high mountain and polar land regions (bottom) assessed \r in SROCC. For each region, physical changes, impacts on key ecosystems, and impacts on human systems and ecosystem function and services are \r shown. For physical changes, yellow/green refers to an increase/decrease, respectively, in amount or frequency of the measured variable. For impacts \r on ecosystems, human systems and ecosystems services blue or red depicts whether an observed impact is positive (beneficial) or negative (adverse), \r respectively, to the given system or service. Cells assigned 'increase and decrease' indicate that within that region, both increase and decrease of \r physical changes are found, but are not necessarily equal; the same holds for cells showing 'positive and negative' attributable impacts. For ocean \r [...]"


id: 5b2e63bc9408f76bd5a4f407d4ef528f
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 13293
content:
"[...] regions, the confidence level refers to the confidence in attributing observed changes to changes in greenhouse gas forcing for physical changes and to \r climate change for ecosystem, human systems, and ecosystem services. For high mountain and polar land regions, the level of confidence in attributing \r physical changes and impacts at least partly to a change in the cryosphere is shown. No assessment means: not applicable, not assessed at regional \r scale, or the evidence is insufficient for assessment. The physical changes in the ocean are defined as: Temperature change in 0-700 m layer of the \r ocean except for Southern Ocean (0-2000 m) and Arctic Ocean (upper mixed layer and major inflowing branches); Oxygen in the 0-1200 m layer \r or oxygen minimum layer; Ocean pH as surface pH (decreasing pH corresponds to increasing ocean acidification). Ecosystems in the ocean: Coral \r [...]"


id: 5774f0cb9b4acdfa8012058aba36ef20
created_at: 2023-04-19 13:23:23
updated_at: 2023-04-19 13:23:23
content_type: text
index: climate_gpt_v2
vector_id: 12651
content:
"[...] refers to warm-water coral reefs and cold-water corals. The 'upper water column' category refers to epipelagic zone for all ocean regions except Polar \r Regions, where the impacts on some pelagic organisms in open water deeper than the upper 200 m were included. Coastal wetland includes salt \r marshes, mangroves and seagrasses. Kelp forests are habitats of a specific group of macroalgae. Rocky shores are coastal habitats dominated by \r immobile calcified organisms such as mussels and barnacles. Deep sea is seafloor ecosystems that are 3000-6000 m deep. Sea-ice associated includes \r ecosystems in, on and below sea ice. Habitat services refer to supporting structures and services (e.g., habitat, biodiversity, primary production).\r Coastal Carbon Sequestration refers to the uptake and storage of carbon by coastal blue carbon ecosystems. Ecosystems on Land: Tundra refers to \r tundra and alpine meadows, and includes terrestrial Antarctic ecosystems. "


id: e1a2dcd074e6784fe0a70f0e054d8226
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 36968
content:
"Figure SPM.3 (continued): (a) depth integrated net primary production (NPP from CMIP527), (b) total animal biomass (depth integrated, including \r fishes and invertebrates from FISHMIP28), (c) maximum fisheries catch potential and (d) impacts and risks for coastal and open ocean ecosystems. The \r three left panels represent the simulated (a,b) and observed (c) mean values for the recent past (1986-2005), the middle and right panels represent \r projected changes (%) by 2081-2100 relative to recent past under low (RCP2.6) and high (RCP8.5) greenhouse gas emissions scenario {Box SPM.1}, \r respectively. Total animal biomass in the recent past (b, left panel) represents the projected total animal biomass by each spatial pixel relative to the \r global average. (c) *Average observed fisheries catch in the recent past (based on data from the Sea Around Us global fisheries database); projected \r [...]"


id: a7248f1b810da22343d0f79293a94745
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 26621
content:
"[...] changes in maximum fisheries catch potential in shelf seas are based on the average outputs from two fisheries and marine ecosystem models. To \r indicate areas of model inconsistency, shaded areas represent regions where models disagree in the direction of change for more than: (a) and (b) \r 3 out of 10 model projections, and (c) one out of two models. Although unshaded, the projected change in the Arctic and Antarctic regions in (b) total \r animal biomass and (c) fisheries catch potential have low confidence due to uncertainties associated with modelling multiple interacting drivers and \r ecosystem responses. Projections presented in (b) and (c) are driven by changes in ocean physical and biogeochemical conditions e.g., temperature, \r oxygen level, and net primary production projected from CMIP5 Earth system models. **The epipelagic refers to the uppermost part of the ocean \r [...]"


id: 62929f90a44d9fef45b598ae672ea659
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 14631
content:
"[...] with depth <200 m from the surface where there is enough sunlight to allow photosynthesis. (d) Assessment of risks for coastal and open ocean \r ecosystems based on observed and projected climate impacts on ecosystem structure, functioning and biodiversity. Impacts and risks are shown in \r relation to changes in Global Mean Surface Temperature (GMST) relative to pre-industrial level. Since assessments of risks and impacts are based \r on global mean Sea Surface Temperature (SST), the corresponding SST levels are shown29. The assessment of risk transitions is described in Chapter \r 5 Sections 5.2, 5.3, 5.2.5 and 5.3.7 and Supplementary Materials SM5.3, Table SM5.6, Table SM5.8 and other parts of the underlying report. The \r figure indicates assessed risks at approximate warming levels and increasing climate-related hazards in the ocean: ocean warming, acidification, \r [...]"


id: 20f8247048ecd6fb9ef4344ad6ee46dd
created_at: 2023-04-19 13:23:24
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"[...] deoxygenation, increased density stratification, changes in carbon fluxes, sea level rise, and increased frequency and/or intensity of extreme events. \r The assessment considers the natural adaptive capacity of the ecosystems, their exposure and vulnerability. Impact and risk levels do not consider \r risk reduction strategies such as human interventions, or future changes in non-climatic drivers. Risks for ecosystems were assessed by considering \r biological, biogeochemical, geomorphological and physical aspects. Higher risks associated with compound effects of climate hazards include \r habitat and biodiversity loss, changes in species composition and distribution ranges, and impacts/risks on ecosystem structure and functioning, \r including changes in animal/plant biomass and density, productivity, carbon fluxes, and sediment transport. As part of the assessment, literature was \r [...]"


id: 2fb40ba13dd5a5ae55f55b44245ce015
created_at: 2023-04-19 13:23:24
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"[...] compiled and data extracted into a summary table. A multi-round expert elicitation process was undertaken with independent evaluation of threshold \r judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 5, Sections 5.2 \r and 5.3 and Supplementary Material. {3.2.3, 3.2.4, 5.2, 5.3, 5.2.5, 5.3.7, SM5.6, SM5.8, Figure 5.16, Cross Chapter Box 1 in Chapter 1 Table CCB1} "


id: f34db26caa5fff8076f15331b8031d14
created_at: 2023-04-19 13:23:24
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"3 Globally, a  slower rate of climate-related ocean and cryosphere change provides greater \r adaptation opportunities (high confidence). While there is high confidence that ambitious adaptation, including \r governance for transformative change, has the potential to reduce risks in many locations, such benefits can vary \r between locations. At global scale, coastal protection can reduce flood risk by  2-3 orders of magnitude during \r the 21st century, but depends on investments on the order of tens to several hundreds of billions of US$ per year \r (high confidence). While such investments are generally cost efficient for densely populated urban areas, rural and \r poorer areas may be challenged to afford such investments with relative annual costs for some small island states \r amounting to several percent of GDP (high confidence). Even with major adaptation efforts, residual risks and \r [...]"


id: d136007a41a608b3609b536346700f7
created_at: 2023-04-19 13:23:24
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content:
"[...] associated losses are projected to occur (medium confidence), but context-specific limits to adaptation and residual \r risks remain difficult to assess. {4.1.3, 4.2.2.4, 4.3.1, 4.3.2, 4.3.4., 4.4.3, 6.9.1, 6.9.2, Cross-Chapter Boxes 1-2 in \r Chapter 1, SM.4.3, Figure SPM.5} "


id: bf08a5b89495c52a1ce80368d647a74e
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content:
"Figure SPM.4 | The effect of regional sea level rise on extreme sea level events at coastal locations. (a) Schematic illustration of extreme sea level \r events and their average recurrence in the recent past (1986-2005) and the future. As a consequence of mean sea level rise, local sea levels that \r historically occurred once per century (historical centennial events, HCEs) are projected to recur more frequently in the future. (b) The year in which \r HCEs are expected to recur once per year on average under RCP8.5 and RCP2.6, at the 439 individual coastal locations where the observational \r record is sufficient. The absence of a circle indicates an inability to perform an assessment due to a lack of data but does not indicate absence of \r exposure and risk. The darker the circle, the earlier this transition is expected. The likely range is +-10 years for locations where this transition is \r [...]"


id: fbc8c13d57559ed4ebf7aacdc8d96fb0
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"[...] expected before 2100. White circles (33% of locations under RCP2.6 and 10% under RCP8.5) indicate that HCEs are not expected to recur once per \r year before 2100. (c) An indication at which locations this transition of HCEs to annual events is projected to occur more than 10 years later under\r RCP2.6 compared to RCP8.5. As the scenarios lead to small differences by 2050 in many locations results are not shown here for RCP4.5 but they are \r available in Chapter 4. {4.2.3, Figure 4.10, Figure 4.12}"


id: ef1912217bc70699701a204f2a64a0dd
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"C.1.4 Financial, technological, institutional and other barriers exist for implementing responses to \r current and projected negative impacts of climate-related changes in the ocean and cryosphere, impeding resilience \r building and risk reduction measures (high confidence). Whether such barriers reduce adaptation effectiveness or \r correspond to adaptation limits depends on context specific circumstances, the rate and scale of climate changes \r and on the ability of societies to turn their adaptive capacity into effective adaptation responses. Adaptive capacity \r continues to differ between as well as within communities and societies (high confidence). People with highest \r exposure and vulnerability to current and future hazards from ocean and cryosphere changes are often also those \r with lowest adaptive capacity, particularly in low-lying islands and coasts, Arctic and high mountain regions with \r [...]"


id: c894bef996c8fdb11a5bc2c0d4f59add
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"[...] development challenges (high confidence). {2.3.1,  2.3.2,  2.3.7, Box  2.4,  3.5.2,  4.3.4,  4.4.2,  4.4.3,  5.5.2,  6.9, \r Cross-Chapter Boxes 2 and 3 in Chapter 1, Cross-Chapter Box 9}"


id: 8fa29c367ee123ae8e95667cbd66c585
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index: climate_gpt_v2
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content:
"C.3.1 The higher the sea levels rise, the more challenging is coastal protection, mainly due to \r economic, financial and social barriers rather than due to technical limits (high confidence). In the coming decades, \r reducing local drivers of exposure and vulnerability such as coastal urbanization and human-induced subsidence \r constitute effective responses (high confidence). Where space is limited, and the value of exposed assets is high \r (e.g., in cities), hard protection (e.g., dikes) is likely to be a cost-efficient response option during the 21st century \r taking into account the specifics of the context (high confidence), but resource-limited areas may not be able to \r afford such investments. Where space is available, ecosystem-based adaptation can reduce coastal risk and provide \r multiple other benefits such as carbon storage, improved water quality, biodiversity conservation and livelihood \r [...]"


id: 43f2f3aa3eaf318b66eaec4a96252631
created_at: 2023-04-19 13:23:24
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content:
"Figure SPM.5 | Sea level rise risks and responses. The term response is used here instead of adaptation because some responses, such as retreat, \r may or may not be considered to be adaptation. (a) shows the combined risk of coastal flooding, erosion and salinization for illustrative geographies \r in 2100, due to changing mean and extreme sea levels under RCP2.6 and RCP8.5 and under two response scenarios. Risks under RCPs 4.5 and 6.0 \r were not assessed due to a lack of literature for the assessed geographies. The assessment does not account for changes in extreme sea level beyond \r those directly induced by mean sea level rise; risk levels could increase if other changes in extreme sea levels were considered (e.g., due to changes \r in cyclone intensity). Panel a) considers a socioeconomic scenario with relatively stable coastal population density over the century. {SM4.3.2} Risks to \r [...]"


id: 4b68d47dd1433c27ad75d8f4a6524d7c
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"[...] illustrative geographies have been assessed based on relative sea level changes projected for a set of specific examples: New York City, Shanghai and \r Rotterdam for resource-rich coastal cities covering a wide range of response experiences; South Tarawa, Fongafale and Male' for urban atoll islands; \r Mekong and Ganges-Brahmaputra-Meghna for large tropical agricultural deltas; and Bykovskiy, Shishmaref, Kivalina, Tuktoyaktuk and Shingle Point \r for Arctic communities located in regions remote from rapid glacio-isostatic adjustment. {4.2, 4.3.4, SM4.2} The assessment distinguishes between \r two contrasting response scenarios. \"No-to-moderate response\" describes efforts as of today (i.e., no further significant action or new types of \r actions). \"Maximum potential response\" represents a combination of responses implemented to their full extent and thus significant additional efforts \r [...]"


id: 9c1e4320a1a492ff073f3f4fc3fd70ef
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content:
"[...] compared to today, assuming minimal financial, social and political barriers. The assessment has been conducted for each sea level rise and response \r scenario, as indicated by the burning embers in the figure; in-between risk levels are interpolated. {4.3.3} The assessment criteria include exposure \r and vulnerability (density of assets, level of degradation of terrestrial and marine buffer ecosystems), coastal hazards (flooding, shoreline erosion, \r salinization), in-situ responses (hard engineered coastal defenses, ecosystem restoration or creation of new natural buffers areas, and subsidence \r management) and planned relocation. Planned relocation refers to managed retreat or resettlement as described in Chapter 4, i.e., proactive and \r local-scale measures to reduce risk by relocating people, assets and infrastructure. Forced displacement is not considered in this assessment. Panel (a)\r [...]"


id: f4fdc0bcd9e4a95e8d8527a81d7852f4
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"[...] also highlights the relative contributions of in-situ responses and planned relocation to the total risk reduction. (b) schematically illustrates the risk \r reduction (vertical arrows) and risk delay (horizontal arrows) through mitigation and/or responses to sea level rise. (c) summarizes and assesses \r responses to sea level rise in terms of their effectiveness, costs, co-benefits, drawbacks, economic efficiency and associated governance challenges. \r {4.4.2} (d) presents generic steps of an adaptive decision-making approach, as well as key enabling conditions for responses to sea level rise. \r {4.4.4, 4.4.5}"


id: d9fcc82b8e1baafe7da27c7c4f00f89a
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".4.4 Investments in education and capacity building at various levels and scales facilitates \r social learning and long-term capability for context-specific responses to reduce risk and enhance resilience (high \r confidence). Specific activities include utilization of multiple knowledge systems and regional climate information \r into decision making, and the engagement of local communities, Indigenous peoples, and relevant stakeholders in \r adaptive governance arrangements and planning frameworks (medium confidence). Promotion of climate literacy and \r drawing on local, Indigenous and scientific knowledge systems enables public awareness, understanding and social \r learning about locality-specific risk and response potential (high confidence). Such investments can develop, and in \r many cases transform existing institutions and enable informed, interactive and adaptive governance arrangements \r [...]"


id: f1a3029be9ae141c7e2172e5dee4ca10
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content:
"[...] (high confidence). {1.8.3, 2.3.2, Figure 2.7, Box 2.4, 2.4, 3.5.2, 3.5.4, 4.4.4, 4.4.5, Table 4.9, 5.5.2, 6.9}"


id: e2d04208cadc700e9c9c6432b58b5c31
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index: climate_gpt_v2
vector_id: 37201
content:
"Amro Abd-Elgawad (Egypt), Nerilie Abram (Australia), Carolina Adler (Switzerland/Australia), \r Andres Alegria (Honduras), Javier Aristegui (Spain), Nathaniel L. Bindoff (Australia), \r Laurens Bouwer (Netherlands), Bolivar Caceres (Ecuador), Rongshuo Cai (China), Sandra Cassotta \r (Denmark), Lijing Cheng (China), So-Min Cheong (Republic of Korea), William W.  L.  Cheung \r (Canada), Maria Paz Chidichimo (Argentina), Miguel Cifuentes-Jara (Costa Rica), Matthew Collins \r (United Kingdom), Susan Crate (USA), Rob Deconto (USA), Chris Derksen (Canada), \r Alexey Ekaykin (Russian Federation), Hiroyuki Enomoto (Japan), Thomas Frolicher (Switzerland), \r Matthias  Garschagen (Germany), Jean-Pierre Gattuso (France), Tuhin Ghosh (India), \r Bruce Glavovic (New Zealand), Nicolas Gruber (Switzerland), Stephan Gruber (Canada/Germany), \r Valeria A. Guinder (Argentina), Robert Hallberg (USA), Sherilee Harper (Canada), John Hay \r [...]"


id: 96213765da8cc2c77310f108e85062cf
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content:
"[...] (Cook  Islands), Nathalie Hilmi (France), Jochen Hinkel (Germany), Yukiko Hirabayashi (Japan), \r Regine Hock (USA), Elisabeth Holland (Fiji), Anne Hollowed (USA), Federico Isla (Argentina), \r Miriam Jackson (Norway), Helene Jacot Des Combes (Fiji), Nianzhi Jiao (China), Andreas Kaab \r (Norway), James  G.  Kairo (Kenya), Shichang Kang (China), Md Saiful Karim (Australia), \r Gary Kofinas (USA), Roxy Mathew Koll (India), Raphael Martin Kudela (USA), Stanislav Kutuzov \r (Russian Federation), Lisa Levin (USA), Inigo Losada (Spain), Andrew Mackintosh (New Zealand), \r Alexandre K. Magnan (France), Ben Marzeion (Germany), Valerie Masson-Delmotte (France), \r Robin  Matthews (United  Kingdom), Kathleen McInnes (Australia), Jess Melbourne-Thomas \r (Australia), Michael Meredith (United Kingdom), Benoit Meyssignac (France), Alexander Milner \r (United Kingdom), Katja Mintenbeck (Germany), Ulf Molau (Sweden), Samuel Morin (France), \r [...]"


id: 7eebcf61b6bedf4cb0d52a9735e4a6be
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content:
"[...] Monica M.C. Muelbert (Brazil), Maike Nicolai (Germany), Sean O'Donoghue (South Africa), \r Andrew Okem (Nigeria), Michael Oppenheimer (USA), Ben Orlove (USA), Geir  Ottersen \r (Norway), Jan Petzold (Germany), Anna Pirani (Italy), Hans-Otto Portner (Germany), \r Elvira Poloczanska (United Kingdom/Australia), Anjal Prakash (India), Hamish Pritchard \r (United Kingdom), Sara R. Purca Cuicapusa (Peru), Golam Rasul (Nepal), Beate Ratter (Germany), "


id: 976454579de427b5a36a5261509ce655
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index: climate_gpt_v2
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content:
"Section TS.1 (Chapter 1) introduces important key concepts, \r summarizes the characteristics and interconnection of ocean and \r cryosphere and highlights their importance in the earth system and \r for human societies in the light of climate change. TS.2 (Chapter 2) \r assesses changes in high mountain cryosphere and their impacts \r on local mountain communities and far beyond. TS.3 (Chapter 3) \r evaluates the state of knowledge concerning changes and impacts \r in the Arctic and Antarctic ocean and cryosphere systems, including \r challenges and opportunities for societies. TS.4 (Chapter 4) focusses \r on regional and global changes in sea level, the associated risk to \r low-lying islands, coasts and human settlements, and response \r options. TS.5 (Chapter 5) assesses changes in the ocean and marine \r ecosystems, including risks to ecosystem services and vulnerability \r of the dependent communities. TS.6 (Chapter 6) examines extremes \r [...]"


id: e6142be5dcb3d47d3708aa22c33e5eca
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"[...] and abrupt or irreversible changes in the ocean and cryosphere \r in a changing climate, and identifies sustainable and resilient risk \r management strategies. All chapters and their Executive Summaries \r build on findings since the IPCC Fifth Assessment Report (AR5) and, \r whenever applicable, outcomes of the IPCC Special Report on Global \r Warming of 1.5oC (SR15)."


id: 66baebbc7801e25aaf0e2868e633f66e
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content:
"Figure TS.3 | Observed and modelled historical changes in the ocean and cryosphere since 19502\r , and projected future changes under low (RCP2.6) and high (RCP8.5) \r greenhouse gas emissions scenarios. Changes are shown for: (a) Global mean surface air temperature change with likely range. {Box SPM.1, Cross-Chapter Box 1 in Chapter 1} \r Ocean-related changes with very likely ranges for (b) Global mean sea surface temperature change {Box 5.1, 5.2.2}; (c) Change factor in surface ocean marine heatwave days \r {6.4.1}; (d) Global ocean heat content change (0-2000 m depth). An approximate steric sea level equivalent is shown with the right axis by multiplying the ocean heat content \r by the global-mean thermal expansion coefficient (B  0.125 m per 1024 Joules3\r ) for observed warming since 1970 {Figure 5.1}; (h) Global mean surface pH (on the total \r [...]"


id: e2e53e2f37bb50659a32a591132f416e
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content:
"[...] scale). Assessed observational trends are compiled from open ocean time series sites longer than 15 years {Box 5.1, Figure 5.6, 5.2.2}; and (i) Global mean ocean oxygen change \r (100-600 m depth). Assessed observational trends span 1970-2010 centered on 1996 {Figure 5.8, 5.2.2}. Sea level changes with likely ranges for (m) Global mean sea level \r change. Hashed shading reflects low confidence in sea level projections beyond 2100 and bars at 2300 reflect expert elicitation on the range of possible sea level change {4.2.3, \r Figure 4.2}; and components from (e,f) Greenland and Antarctic ice sheet mass loss {3.3.1}; and (g) Glacier mass loss {Cross-Chapter Box 6 in Chapter 2, Table 4.1}. Further \r cryosphere-related changes with very likely ranges for (j) Arctic sea ice extent change for September4\r  {3.2.1, 3.2.2 Figure 3.3}; (k) Arctic snow cover change for June (land areas \r [...]"


id: 2974910c999f6bd706fcd1d02a841946
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content:
"[...] north of 60oN) {3.4.1, 3.4.2, Figure 3.10}; and (l) Change in near-surface (within 3-4 m) permafrost area in the Northern Hemisphere {3.4.1, 3.4.2, Figure 3.10}. Assessments \r of projected changes under the intermediate RCP4.5 and RCP6.0 scenarios are not available for all variables considered here, but where available can be found in the underlying \r report. {For RCP4.5 see: 2.2.2, Cross-Chapter Box 6 in Chapter 2, 3.2.2, 3.4.2, 4.2.3, for RCP6.0 see Cross-Chapter Box 1 in Chapter 1}"


id: 18ed78556c6dfc297c73f14b56646bb4
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index: climate_gpt_v2
vector_id: 1599
content:
"Societies will be exposed, and challenged to adapt, to changes \r in the ocean and cryosphere even if current and future efforts \r to reduce greenhouse gas emissions keep global warming well \r below 2oC (very high confidence). Ocean and cryosphere-related \r mitigation and adaptation measures include options that address the \r causes of climate change, support biological and ecological adaptation, \r or enhance societal adaptation. Most ocean-based local mitigation \r and adaptation measures have limited effectiveness to mitigate \r climate change and reduce its consequences at the global scale, but \r are useful to implement because they address local risks, often have \r co-benefits such as biodiversity conservation, and have few adverse \r side effects. Effective mitigation at a global scale will reduce the need \r and cost of adaptation, and reduce the risks of surpassing limits to \r adaptation. Ocean-based carbon dioxide removal at the global scale \r [...]"


id: d142d29c47f51d47b87646e8748c4cfd
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vector_id: 34167
content:
"[...] has potentially large negative ecosystem consequences. {1.6.1, 1.6.2, \r Cross-Chapter Box 2 in Chapter 1, Figure TS.4}"


id: fa670d7ab98d17594695f79e22170ce4
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vector_id: 41423
content:
"Observations show general decline in low-elevation snow \r cover (high confidence) glaciers (very high confidence) and \r permafrost (high confidence) due to climate change in recent \r decades. Snow cover duration has declined in nearly all regions, \r especially at lower elevations, on average by 5  days per decade, \r with a likely range from 0-10 days per decade. Low elevation snow \r depth and extent have declined, although year-to-year variation is \r high. Mass change of glaciers in all mountain regions (excluding the \r Canadian and Russian Arctic, Svalbard, Greenland and Antarctica) \r was very likely -490 +- 100 kg m-2 yr-1 (-123 +- 24 Gt yr-1) in 2006-\r 2015. Regionally averaged mass budgets were likely most negative \r (less than -850 kg m-2 yr-1) in the southern Andes, Caucasus and the \r European Alps/Pyrenees, and least negative in High Mountain Asia \r (-150 +- 110 kg m-2 yr-1) but variations within regions are strong. \r Between 3.6-5.2  million km2\r [...]"


id: 6fcf15f6e9e06c4497af359307e85695
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"[...]  are underlain by permafrost in the \r eleven high mountain regions covered in this chapter corresponding \r to 27-29% of the global permafrost area (medium confidence). \r Sparse and unevenly distributed measurements show an increase \r in permafrost temperature (high confidence), for example, by \r 0.19oC +- 0.05oC on average for about 28 locations in the European \r Alps, Scandinavia, Canada and Asia during the past decade. Other \r observations reveal decreasing permafrost thickness and loss of ice \r in the ground. {2.2.2, 2.2.3, 2.2.4, Figure TS.5}"


id: 1ea75649ced738bede8688743b25f6e0
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content:
"Glacier, snow and permafrost decline has altered the frequency, \r magnitude and location of most related natural hazards (high \r confidence). Exposure of people and infrastructure to natural \r hazards has increased due to growing population, tourism and \r socioeconomic development (high confidence). Glacier retreat \r and permafrost thaw have decreased the stability of mountain slopes \r and the integrity of infrastructure (high confidence). The number \r and area of glacier lakes has increased in most regions in recent \r decades (high confidence), but there is only limited evidence that \r the frequency of glacier lake outburst floods (GLOF) has changed. In \r some regions, snow avalanches involving wet snow have increased \r (medium confidence), and rain-on-snow floods have decreased at \r low elevations in spring and increased at high elevations in winter \r (medium confidence). The number and extent of wildfires have \r increased in the Western USA partly due to early snowmelt (medium \r [...]"


id: 1d83b916317f2aa599a5197d1430348c
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content:
"[...] endemics, in terrestrial and freshwater communities have declined \r in abundance (high confidence). While the plant productivity has \r generally increased, the actual impact on provisioning, regulating and \r cultural ecosystem services varies greatly (high confidence). {2.3.3}"


id: 4bbeb7c6851848415804a1e087279895
created_at: 2023-04-19 13:23:24
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vector_id: 10583
content:
"Figure TS.5 (next pages) | Synthesis of observed regional hazards and impacts in ocean5 (top) and high mountain and polar land regions (bottom) assessed in SROCC. The same data \r are shown in different formats in (a) and (b). For each region, physical changes, impacts on key ecosystems, and impacts on human systems and ecosystem function and services are shown. \r For physical changes, yellow/green refers to an increase/decrease, respectively, in amount or frequency of the measured variable. For impacts on ecosystems, human systems and ecosystems \r services blue or red depicts whether an observed impact is positive (beneficial) or negative (adverse), respectively, to the given system or service. Cells assigned 'increase and decrease' \r indicate that within that region, both increase and decrease of physical changes are found, but are not necessarily equal; the same holds for cells showing 'positive and negative' attributable \r [...]"


id: be5a64dda2520d3b8f6ea6f84ef7771d
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index: climate_gpt_v2
vector_id: 30752
content:
"[...] impacts. For ocean regions, the confidence level refers to the confidence in attributing observed changes to changes in greenhouse gas forcing for physical changes and to climate change for \r ecosystem, human systems, and ecosystem services. For high mountain and polar land regions, the level of confidence in attributing physical changes and impacts at least partly to a change \r in the cryosphere is shown. No assessment means: not applicable, not assessed at regional scale, or the evidence is insufficient for assessment. The physical changes in the ocean are defined \r as: Temperature change in 0-700 m layer of the ocean except for Southern Ocean (0-2000 m) and Arctic Ocean (upper mixed layer and major inflowing branches); Oxygen in the 0-1200 m \r layer or oxygen minimum layer; Ocean pH as surface pH (decreasing pH corresponds to increasing ocean acidification). Ecosystems in the ocean: Coral refers to warm-water coral reefs and \r [...]"


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"[...] cold-water corals. The 'upper water column' category refers to epipelagic zone for all ocean regions except Polar Regions, where the impacts on some pelagic organisms in open water deeper \r than the upper 200 m were included. Coastal wetland includes salt marshes, mangroves and seagrasses. Kelp forests are habitats of a specific group of macroalgae. Rocky shores are coastal \r habitats dominated by immobile calcified organisms such as mussels and barnacles. Deep sea is seafloor ecosystems that are 3000-6000 m deep. Sea-ice associated includes ecosystems \r in, on and below sea ice. Habitat services refer to supporting structures and services (e.g., habitat, biodiversity, primary production). Coastal Carbon Sequestration refers to the uptake and \r storage of carbon by coastal blue carbon ecosystems. Ecosystems on Land: Tundra refers to tundra and alpine meadows, and includes terrestrial Antarctic ecosystems. Migration refers to an \r [...]"


id: e2b5156ce25ec7a4d7f9f2827c2a586e
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 37187
content:
"[...] increase or decrease in net migration, not to beneficial/adverse value. Impacts on tourism refer to the operating conditions for the tourism sector. Cultural services include cultural identity, \r sense of home, and spiritual, intrinsic and aesthetic values, as well as contributions from glacier archaeology. The underlying information is given for land regions in tables SM2.6, SM2.7, \r SM2.8, SM3.8, SM3.9, and SM3.10, and for ocean regions in tables SM5.10, SM5.11, SM3.8, SM3.9, and SM3.10. {2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.3.5, 2.3.6, 2.3.7, Figure 2.1, 3.2.1, 3.2.3, \r 3.2.4, 3.3.3, 3.4.1, 3.4.3, 3.5.2, Box 3.4, 4.2.2, 5.2.2, 5.2.3, 5.3.3, 5.4, 5.6, Figure 5.24, Box 5.3}"


id: a1948898035197d0dfe2f9b9f1cec0f9
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 25642
content:
"[...] and very limited refugia exist (medium confidence). Woody shrubs \r and trees are projected to expand, covering 24-52% of the current \r tundra region by 2050. {3.2.2.1, 3.2.3, 3.2.3.1, Box 3.4, 3.4.2, 3.4.3}"


id: 5516b4cd390c46a4af0d97e2aae11393
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 12244
content:
"The projected effects of climate-induced stressors on \r polar marine ecosystems present risks for commercial and \r subsistence fisheries with implications for regional economies, \r cultures and the global supply of fish, shellfish, and Antarctic \r krill (high confidence). Future impacts for linked human \r systems depend on the level of mitigation and especially the \r responsiveness of precautionary management approaches \r (medium confidence). Polar regions support several of the \r world's largest commercial fisheries. Specific impacts on the stocks \r and economic value in both regions will depend on future climate \r change and on the strategies employed to manage the effects on \r stocks and ecosystems (medium confidence). Under high emission \r scenarios current management strategies of some high-value stocks \r may not sustain current catch levels in the future (low confidence); \r this exemplifies the limits to the ability of existing natural resource \r [...]"


id: 4ce1eedb5242cab2c33baf8e6c0f493c
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 10799
content:
"[...] management frameworks to address ecosystem change. Adaptive \r management that combines annual measures and within-season \r provisions informed by assessments of future ecosystem trends \r reduces the risks of negative climate change impacts on polar \r fisheries (medium confidence). {3.2.4, 3.5.2, 3.5.4}"


id: 150baa10a149618ef4d0a3dfbe2cbb3b
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 915
content:
"[...] measures taken in advance could reduce costs arising from thaw and \r other climate change related impacts such as increased flooding, \r precipitation, and freeze-thaw events by half (medium confidence). \r {3.4.1, 3.4.2, 3.4.3, 3.5.2}"


id: c5bb0b7b7267df371f8e0cb52a3d9b97
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 32097
content:
"Coastal ecosystems are already impacted by the combination \r of SLR, other climate-related ocean changes, and adverse \r effects from human activities on ocean and land (high \r confidence). Attributing such impacts to SLR, however, remains \r challenging due to the influence of other climate-related and \r non-climatic drivers such as infrastructure development and \r human-induced habitat degradation (high confidence). Coastal \r ecosystems, including saltmarshes, mangroves, vegetated dunes and \r sandy beaches, can build vertically and expand laterally in response to \r SLR, though this capacity varies across sites (high confidence). These \r ecosystems provide important services that include coastal protection \r and habitat for diverse biota. However, as a consequence of human \r actions that fragment wetland habitats and restrict landward \r migration, coastal ecosystems progressively lose their ability to adapt \r to climate-induced changes and provide ecosystem services, including \r [...]"


id: c07d7d16c6ae5fc5e0d293a2b8f9bf31
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
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content:
"A diversity of adaptation responses to coastal impacts \r and risks have been implemented around the world, but \r mostly as a reaction to current coastal risk or experienced \r disasters (high confidence). Hard coastal protection measures \r (dikes, embankments, sea walls and surge barriers) are widespread, \r providing predictable levels of safety in northwest Europe, East \r Asia, and around many coastal cities and deltas. Ecosystem-based \r adaptation (EbA) is continuing to gain traction worldwide, providing \r multiple co-benefits, but there is still low agreement on its cost and \r long-term effectiveness. Advance, which refers to the creation of \r new land by building into the sea (e.g., land reclamation), has a long \r history in most areas where there are dense coastal populations.\r Accommodation measures, such as early warning systems (EWS) for \r ESL events, are widespread. Retreat is observed but largely restricted \r [...]"


id: 9d3219d1ed757fdfc2b1cecdd33c113a
created_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
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content:
"[...] to small communities or carried out for the purpose of creating new \r wetland habitat. {4.4.2.3, 4.4.2.4, 4.4.2.5}"


id: b9d31637d463dc19f66c5393d4f1d32
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
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content:
"Risk related to SLR (including erosion, flooding and \r salinisation) is expected to significantly increase by the end of \r this century along all low-lying coasts in the absence of major \r additional adaptation efforts (very high confidence). While \r only urban atoll islands and some Arctic communities are expected \r to experience moderate to high risk relative to today in a low \r emission pathway, almost high to very high risks are expected in all \r low-lying coastal settings at the upper end of the likely range for high \r emission pathways (medium confidence). However,  the transition \r from moderate to high and from high to very high risk will vary from \r one coastal setting to another (high confidence). While a slower \r rate of SLR enables greater opportunities for adapting, adaptation \r benefits are also expected to vary between coastal settings. Although \r ambitious adaptation will not necessarily eradicate end-century SLR \r [...]"


id: 726f22f12ed6ff1875fe2445fad97708
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 17372
content:
"[...] risk (medium confidence), it will help to buy time in many locations \r and therefore help to lay a robust foundation for adaptation beyond \r 2100. {4.1.3, 4.3.4, Box 4.1, SM4.2}"


id: 9a2cac611f6e16bd5caed31c7e6a8e0c
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 24364
content:
"Choosing and implementing responses to SLR presents society \r with profound governance challenges and difficult social choices, \r which are inherently political and value laden (high confidence). \r The large uncertainties about post 2050 SLR, and the substantial \r impact expected, challenge established planning and decision \r making practises and introduce the need for coordination within and \r between governance levels and policy domains. SLR responses also \r raise equity concerns about marginalising those most vulnerable and \r could potentially spark or compound social conflict (high confidence). \r Choosing and implementing responses is further challenged through \r a lack of resources, vexing trade-offs between safety, conservation and \r economic development, multiple ways of framing the 'sea level rise \r problem', power relations, and various coastal stakeholders having \r conflicting interests in the future development of heavily used coastal \r [...]"


id: a2354cf96cd08e2e68425349fd0065b
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 25772
content:
"Adaptation experience to date demonstrates that using a locally \r appropriate combination of decision analysis, land use planning, \r public participation and conflict resolution approaches can help \r to address the governance challenges faced in responding to \r SLR (high confidence). Effective SLR responses depend, first, on \r taking a long-term perspective when making short-term decisions, \r explicitly accounting for uncertainty of locality-specific risks beyond \r 2050 (high confidence), and building governance capabilities to \r tackle the complexity of SLR risk (medium evidence, high agreement). \r Second, improved coordination of SLR responses across scales, sectors \r and policy domains can help to address SLR impacts and risk (high \r confidence). Third, prioritising consideration of social vulnerability and \r equity underpins efforts to promote fair and just climate resilience \r and sustainable development (high confidence) and can be helped by \r [...]"


id: 4025f93f726e2d455f1b1e7b1cf93f60
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 8474
content:
"Figure TS.7 | Sea level rise risks and responses. The term response is used here instead of adaptation because some responses, such as retreat, may or may not be \r considered to be adaptation. (a) shows the combined risk of coastal flooding, erosion and salinization for illustrative geographies in 2100, due to changing mean and \r extreme sea levels under RCP2.6 and RCP8.5 and under two response scenarios. Risks under RCPs 4.5 and 6.0 were not assessed due to a lack of literature for the \r assessed geographies. The assessment does not account for changes in extreme sea level beyond those directly induced by mean sea level rise; risk levels could increase \r if other changes in extreme sea levels were considered (e.g., due to changes in cyclone intensity). Panel (a) considers a socioeconomic scenario with relatively stable \r [...]"


id: c390343d132e8dc6d1b2957f51fc92d0
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 31684
content:
"[...] coastal population density over the century. {SM4.3.2} Risks to illustrative geographies have been assessed based on relative sea level changes projected for a set of \r specific examples: New York City, Shanghai and Rotterdam for resource-rich coastal cities covering a wide range of response experiences; South Tarawa, Fongafale and \r Male' for urban atoll islands; Mekong and Ganges-Brahmaputra-Meghna for large tropical agricultural deltas; and Bykovskiy, Shishmaref, Kivalina, Tuktoyaktuk and Shingle \r Point for Arctic communities located in regions remote from rapid glacio-isostatic adjustment. {4.2, 4.3.4, SM4.2} The assessment distinguishes between two contrasting \r response scenarios. \"No-to-moderate response\" describes efforts as of today (i.e., no further significant action or new types of actions). \"Maximum potential response\" \r [...]"


id: 2326f7789f1306fc9dbbe6f7df13b807
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 3382
content:
"[...] represents a combination of responses implemented to their full extent and thus significant additional efforts compared to today, assuming minimal financial, social and \r political barriers. The assessment has been conducted for each sea level rise and response scenario, as indicated by the burning embers in the figure; in-between risk levels \r are interpolated. {4.3.3} The assessment criteria include exposure and vulnerability (density of assets, level of degradation of terrestrial and marine buffer ecosystems), \r coastal hazards (flooding, shoreline erosion, salinization), in-situ responses (hard engineered coastal defenses, ecosystem restoration or creation of new natural buffers \r areas, and subsidence management) and planned relocation. Planned relocation refers to managed retreat or resettlement as described in Chapter 4, i.e., proactive and \r [...]"


id: c10563e39e5bd882fab4a8ddb53d2c5
created_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
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content:
"[...] local-scale measures to reduce risk by relocating people, assets and infrastructure. Forced displacement is not considered in this assessment. Panel (a) also highlights the \r relative contributions of in-situ responses and planned relocation to the total risk reduction. (b) schematically illustrates the risk reduction (vertical arrows) and risk delay \r (horizontal arrows) through mitigation and/or responses to sea level rise. (c) summarizes and assesses responses to sea level rise in terms of their effectiveness, costs, \r co-benefits, drawbacks, economic efficiency and associated governance challenges. {4.4.2} (d) presents generic steps of an adaptive decision-making approach, as well as \r key enabling conditions for responses to sea level rise. {4.4.4, 4.4.5} "


id: 30c0d7fd47a022f4f25d2aac75219d28
created_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 5832
content:
"[...] worldwide reef degradation since 1997-1998 with cases of shifts to \r algal-dominated reefs (high confidence). Sessile calcified organisms \r (e.g.,  barnacles and mussels) in intertidal rocky shores are highly \r sensitive to extreme temperature events and acidification (high \r confidence), a reduction in their biodiversity and abundance have "


id: 449480422bcff8625a713145d76f8654
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 9300
content:
"New ocean states for a broad suite of climate indices will \r progressively emerge over a substantial fractions of the \r ocean in the coming century (relative to past internal ocean \r variability), with Earth System Models (ESMs) showing an \r ordered emergence of first pH, followed by sea surface \r temperature (SST), interior oxygen, upper ocean nutrient levels \r and finally net primary production (NPP). The anthropogenic pH \r signal has very likely emerged for three quarters of the ocean prior to \r 1950, with little difference between scenarios. Oxygen changes will \r very likely emerge over 59-80% of the ocean area by 2031-2050 \r and rises to 79-91% by 2081-2100 (RCP8.5 emissions scenario). \r The projected time of emergence for five primary drivers of marine \r ecosystem change (surface warming and acidification, oxygen loss, \r nitrate content and net primary production change) are all prior to \r 2100 for over 60% of the ocean area under RCP8.5 and over 30% \r [...]"


id: bb07f09e395e1bc9b7ff3b8041fc2391
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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vector_id: 30126
content:
"Figure TS.8 | Projected changes, impacts and risks for ocean regions and ecosystems. (a) depth integrated net primary production (NPP from CMIP5)8, (b) total animal \r biomass (depth integrated, including fishes and invertebrates from FISHMIP)9, (c) maximum fisheries catch potential and (d) impacts and risks for coastal and open ocean \r ecosystems. The three left panels represent the simulated (a,b) and observed (c) mean values for the recent past (1986-2005), the middle and right panels represent \r projected changes (%) by 2081-2100 relative to recent past under low (RCP2.6) and high (RCP8.5) greenhouse gas emissions scenario (see Table TS.2), respectively. Total \r animal biomass in the recent past (b, left panel) represents the projected total animal biomass by each spatial pixel relative to the global average. (c) *Average observed \r [...]"


id: 80a35a04f2516eb31ca0a6adee110176
created_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 19763
content:
"[...] fisheries catch in the recent past (based on data from the Sea Around Us global fisheries database); projected changes in maximum fisheries catch potential in shelf seas \r are based on the average outputs from two fisheries and marine ecosystem models. To indicate areas of model inconsistency, shaded areas represent regions where models \r disagree in the direction of change for more than: (a) and (b) 3 out of 10 model projections, and (c) one out of two models. Although unshaded, the projected change in \r the Arctic and Antarctic regions in (b) total animal biomass and (c) fisheries catch potential have low confidence due to uncertainties associated with modelling multiple \r interacting drivers and ecosystem responses. Projections presented in (b) and (c) are driven by changes in ocean physical and biogeochemical conditions e.g., temperature, \r [...]"


id: 5a50a71c75127a01201ec16a270096fc
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 13142
content:
"[...] oxygen level, and net primary production projected from CMIP5 Earth system models. **The epipelagic refers to the uppermost part of the ocean with depth <200 m from \r the surface where there is enough sunlight to allow photosynthesis. (d) Assessment of risks for coastal and open ocean ecosystems based on observed and projected \r climate impacts on ecosystem structure, functioning and biodiversity. Impacts and risks are shown in relation to changes in Global Mean Surface Temperature (GMST) \r relative to pre-industrial level. Since assessments of risks and impacts are based on global mean Sea Surface Temperature (SST), the corresponding SST levels are shown10. \r The assessment of risk transitions is described in Chapter 5 Sections 5.2, 5.3, 5.2.5 and 5.3.7 and Supplementary Materials SM5.3, Table SM5.6, Table SM5.8 and other \r [...]"


id: 9063662552ba5f620e09e16356ed9074
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 22605
content:
"[...] parts of the underlying report. The figure indicates assessed risks at approximate warming levels and increasing climate-related hazards in the ocean: ocean warming, \r acidification, deoxygenation, increased density stratification, changes in carbon fluxes, sea level rise, and increased frequency and/or intensity of extreme events. The \r assessment considers the natural adaptive capacity of the ecosystems, their exposure and vulnerability. Impact and risk levels do not consider risk reduction strategies such \r as human interventions, or future changes in non-climatic drivers. Risks for ecosystems were assessed by considering biological, biogeochemical, geomorphological and \r physical aspects. Higher risks associated with compound effects of climate hazards include habitat and biodiversity loss, changes in species composition and distribution \r [...]"


id: 34dd989bd1567b215dc50deb99300861
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 6544
content:
"[...] ranges, and impacts/risks on ecosystem structure and functioning, including changes in animal/plant biomass and density, productivity, carbon fluxes, and sediment \r transport. As part of the assessment, literature was compiled and data extracted into a summary table. A multi-round expert elicitation process was undertaken with \r independent evaluation of threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 5, \r Sections 5.2 and 5.3 and Supplementary Material. {3.2.3, 3.2.4, 5.2, 5.3, 5.2.5, 5.3.7, SM5.6, SM5.8, Figure 5.16, Cross Chapter Box 1 in Chapter 1 Table CCB1}"


id: a6956313d6e7d2435ec4efddf51cd77f
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 26521
content:
"Expected coastal ecosystem responses over the 21st century \r are habitat contraction, migration and loss of biodiversity \r and functionality. Pervasive human coastal disturbances will limit \r natural ecosystem adaptation to climate hazards (high confidence). \r Global coastal wetlands will lose between 20-90% of their area \r depending on emissions scenario with impacts on their contributions \r to carbon sequestration and coastal protection (high confidence). \r Kelp forests at low-latitudes and temperate seagrass meadows will \r continue to retreat as a result of intensified extreme temperatures, \r and their low dispersal ability will elevate the risk of local extinction \r under RCP8.5 (high confidence). Intertidal rocky shores will continue \r to be affected by ocean acidification, warming, and extreme heat \r exposure during low tide emersion, causing reduction of calcareous \r species and loss of ecosystem biodiversity and complexity shifting \r [...]"


id: 2d16db83393d93ff41a3f767297dc640
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updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 5212
content:
"[...] towards algae dominated habitats (high confidence). Salinisation and \r expansion of hypoxic conditions will intensify in eutrophic estuaries, \r especially in mid and high latitudes with microtidal regimes (high \r confidence). Sandy beach ecosystems will increasingly be at risk of \r eroding, reducing the habitable area for dependent organisms (high \r confidence). {5.3, 5.4.1}"


id: 74a648e25165d05cfdc122f540c2ae63
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 17759
content:
"[...] (medium confidence). Estuaries and sandy beaches are subject \r to highly dynamic hydrological and geomorphological processes, \r giving them more natural adaptive capacity to climate hazards. In \r these systems, sediment relocation, soil accretion and landward "


id: 91fb8b892c4a36ef261d62556014d17c
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 22901
content:
"Coastal blue carbon ecosystems, such as mangroves, salt \r marshes and seagrasses, can help reduce the risks and impacts \r of climate change, with multiple co-benefits. Some 151 countries \r around the world contain at least one of these coastal blue carbon \r ecosystems and 71 countries contain all three. Below-ground carbon \r storage in vegetated marine habitats can be up to 1000 tC ha-1, much \r higher than most terrestrial ecosystems (high confidence). Successful \r implementation of measures to maintain and promote carbon \r storage in such coastal ecosystems could assist several countries in \r achieving a balance between emissions and removals of greenhouse \r gases (medium confidence). Conservation of these habitats would \r also sustain the wide range of ecosystem services they provide and \r assist with climate adaptation through improving critical habitats \r for biodiversity, enhancing local fisheries production, and protecting \r [...]"


id: e964bb434cbb16d24cad16d97d84ea99
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 38421
content:
"[...] coastal communities from SLR and storm events (high confidence). \r The climate mitigation effectiveness of other natural carbon removal \r processes in coastal waters, such as seaweed ecosystems and \r proposed non-biological marine CO2 removal methods, are smaller or \r currently have higher associated uncertainties. Seaweed aquaculture \r warrants further research attention. {5.5.1.1, 5.5.1.1, 5.5.1, 5.5.2, \r 5.5.1.1.3, 5.5.1.1.4}"


id: 6888aaf142511f6a5a535ea687a0b347
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 15658
content:
"Ocean and cryosphere changes already impact Low-Lying \r Islands and Coasts (LLIC), including Small Island Developing \r States (SIDS), with cascading and compounding risks. \r Disproportionately higher risks are  expected  in the course \r of the 21st century. Reinforcing the findings of the IPCC \r Special Report on Global Warming of 1.5oC, vulnerable human \r communities, especially those in coral reef environments and \r polar regions, may exceed adaptation limits well before the \r end of this century and even in a low greenhouse gas emission \r pathway (high confidence). Depending on the effectiveness of \r 21st century mitigation and adaptation pathways under all \r emission scenarios, most of the low-lying regions around the \r world may face  adaptation limits beyond 2100, due to the \r long-term commitment of sea level rise (medium confidence). \r LLIC  host around 11% of the global population, generate about \r 14% of the global Gross Domestic Product and comprise many \r [...]"


id: 681dfbe55a6181899213c97cd4146cb5
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
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index: climate_gpt_v2
vector_id: 15586
content:
"[...] world cultural heritage sites. LLIC already experience climate-related \r ocean and cryosphere changes (high confidence), and they share \r both commonalities in their exposure and vulnerability to climate \r change (e.g.,  low elevation, human disturbances to terrestrial \r and marine ecosystems), and context-specificities (e.g., variable \r ecosystem climate sensitivities and risk perceptions by populations). \r Options to adapt to rising seas, e.g., range from hard engineering \r to ecosystem-based measures, and from securing current settings to \r relocating people, built assets and activities. Effective combinations \r of measures vary across geographies (cities and megacities, small \r islands, deltas and Arctic coasts), and reflect the scale of observed \r and projected impacts, ecosystems' and societies' adaptive capacity, \r and the existence of transformational governance (high confidence) \r {Sections 3.5.3, 4.4.2 to 4.4.5, 5.5.2, 6.8, 6.9, Cross-Chapter \r Box 2 in Chapter 1}."


id: af85a67607fc8d84ad018e1c1a01eec
created_at: 2023-04-19 13:23:24
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vector_id: 28113
content:
"[...] to 2081-2010 in the SST3-7.0 scenario. Observed trends have been calculated where data are present in both the first and last decade and for at least 70% of all \r years within the period using ordinary least squares. Significance is assessed with autoregressive AR(1) model correction and denoted by stippling. Hatched areas \r in the lower map show areas of conflicting model evidence on significance of changes. (c) Temperature from instrumental data for 1850-2020, including annually \r resolved averages for the four global surface temperature datasets assessed in Section 2.3.1.1.3 (see text for references). The grey shading shows the uncertainty \r associated with the HadCRUTv5 estimate. All temperatures are relative to the 1850-1900 reference period. (d) Recent past and 2015-2050 evolution of annual mean \r global surface temperature change relative to 1850-1900, from HadCRUTv5 (black), Coupled Model Intercomparison Project Phase 6 (CMIP6) historical simulations \r [...]"


id: 138141808cb97eb7e617ab29ab4371cf
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"[...] (Sweden), Sudarmanto Budi Nugroho (Indonesia), Chukwumerije Okereke (Nigeria/\r United Kingdom), Shonali Pachauri (India), Anthony Patt (Switzerland), Ramon Pichs-Madruga\r (Cuba), Joana Portugal-Pereira (Brazil), Lavanya Rajamani (India), Keywan Riahi (Austria),\r Joyashree  Roy (India/Thailand), Yamina Saheb (France/Algeria), Roberto Schaeffer (Brazil),\r Karen C. Seto (the United States of America), Shreya Some (India), Linda Steg (the Netherlands),\r Ferenc  L.  Toth (Austria/Hungary), Diana Urge-Vorsatz (Hungary), Detlef P. van Vuuren\r (the Netherlands), Elena  Verdolini (Italy), Purvi Vyas (India), Yi-Ming Wei (China), Mariama\r Williams (Jamaica/the United States of America), Harald Winkler (South Africa)."


id: 5d038038e39fd8a97914411c9ed2e8c0
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"Almut Arneth (Germany), Humberto Barbosa (Brazil), Tim Benton (United Kingdom), Katherine \r Calvin (The United States of America), Eduardo Calvo (Peru), Sarah Connors (United Kingdom), \r Annette Cowie (Australia), Edouard Davin (France/Switzerland), Fatima Denton (The Gambia), \r Renee van Diemen (The Netherlands/United Kingdom), Fatima Driouech (Morocco), Aziz Elbehri \r (Morocco), Jason Evans (Australia), Marion Ferrat (France), Jordan Harold (United Kingdom), \r Eamon Haughey (Ireland), Mario Herrero (Australia/Costa Rica), Joanna House (United Kingdom), \r Mark Howden (Australia), Margot Hurlbert (Canada), Gensuo Jia (China), Tom Gabriel Johansen \r (Norway), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Christopher Lennard (South \r Africa), Soojeong Myeong (Republic of Korea), Nagmeldin Mahmoud (Sudan), Valerie Masson\u0002Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), \r [...]"


id: cde8b4004b175149449044f5565454f1
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"[...] Alisher Mirzabaev (Germany/Uzbekistan), Angela Morelli (Norway/Italy), Wilfran Moufouma-Okia \r (France), Dalila Nedjraoui (Algeria), Suvadip Neogi (India), Johnson Nkem (Cameroon), Nathalie De \r Noblet-Ducoudre (France), Lennart Olsson (Sweden), Minal Pathak (India), Jan Petzold (Germany), \r Ramon Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom/Australia), Alexander Popp \r (Germany), Hans-Otto Portner (Germany), Joana Portugal Pereira (United Kingdom), Prajal \r Pradhan (Nepal/Germany), Andy Reisinger (New Zealand), Debra C. Roberts (South Africa), \r Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom/Germany), \r Elena Shevliakova (The United States of America), Priyadarshi R. Shukla (India), Jim Skea (United \r Kingdom), Raphael Slade (United Kingdom), Pete Smith (United Kingdom), Youba Sokona (Mali), \r Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Francesco Tubiello (The United \r [...]"


id: 75d997890bb781f8548a452b742d5cc
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"[...] States of America/Italy), Louis Verchot (The United States of America/Colombia), Koko Warner (The \r United States of America/Germany), Nora M. Weyer (Germany), Jianguo Wu (China), Noureddine \r Yassaa (Algeria), Panmao Zhai (China), Zinta Zommers (Latvia)."


id: aab5078a69a45880f89b6f3488868d1e
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"The production of the report was guided by a Steering Committee drawn from across the IPCC Bureau. We would like to thank \r our colleagues who served on this committee including: the Co-Chairs of Working Groups and the TFI: Priyadarshi Shukla, \r Jim Skea, Valerie Masson-Delmotte, Panmao Zhai, Hans-Otto Portner, Debra Roberts, Eduardo Calvo Buendia; Working Group \r Vice-Chairs: Mark Howden, Nagmeldin Mahmoud, Ramon Pichs-Madruga, Andy Reisinger, Noureddine Yassaa; and Youba \r Sokona, Vice-Chair of IPCC. Youba Sokona acted as champion for the report and his wise council was valued by all. Further \r support came from IPCC Bureau members: Edvin Aldrian, Fatima Driouech, Gregory Flato, Jan Fuglestvedt, Muhammad Tariq \r and Carolina Vera (Working Group I); Andreas Fischlin, Carlos Mendez, Joy Jacqueline Pereira, Roberto A. Sanchez-Rodriguez, \r Sergey Semenov, Pius Yanda and Taha M. Zatari (Working Group II); and Amjad Abdulla, Carlo Carraro, Diriba Korecha Dadi \r [...]"


id: 57cbe0e701cb8ed8e05b8205961aa8c4
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"Our particular appreciation goes to the Working Group Technical Support Units whose tireless dedication, professionalism and \r enthusiasm led the production of this Special Report. This Report could not have been prepared without the commitment of \r members of the Working Group III Technical Support Unit, all new to the IPCC, who rose to the unprecedented Sixth Assessment \r Report challenge and were pivotal in all aspects of the preparation of the Report: Raphael Slade, Lizzie Huntley, Katie Kissick, \r Malek Belkacemi, Renee van Diemen, Marion Ferrat, Eamon Haughey, Bhushan Kankal, Geninha Lisboa, Sigourney Luz, Juliette \r Malley, Suvadip Neogi, Minal Pathak, Joana Portugal Pereira and Purvi Vyas. Our warmest thanks go to the collegial and \r collaborative support provided by Sarah Connors, Melissa Gomis, Robin Matthews, Wilfran Moufouma-Okia, Clotilde Pean, \r Roz Pidcock, Anna Pirani, Tim Waterfield and Baiquan Zhou from the WG I Technical Support Unit, and Jan Petzold, Bard Rama, \r [...]"


id: 290cb00f00fc1d840390dd04469d335f
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"[...] Maike Nicolai, Elvira Poloczanska, Melinda Tignor and Nora Weyer from the WG II Technical Support Unit."


id: 3ceae5e521d8f6ffdbe55215507b5578
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"This Special Report on Climate Change and Land1 responds to the Panel decision in 2016 to prepare three Special Reports2 during the \r Sixth Assessment cycle, taking account of proposals from governments and observer organisations.3\r  This report addresses greenhouse \r gas (GHG) fluxes in land-based ecosystems, land use and sustainable land management4\r  in relation to climate change adaptation and \r mitigation, desertification5\r , land degradation6 and food security7. This report follows the publication of other recent reports, including the \r IPCC Special Report on Global Warming of 1.5degC (SR15), the thematic assessment of the Intergovernmental Science-Policy Platform on \r Biodiversity and Ecosystem Services (IPBES) on Land Degradation and Restoration, the IPBES Global Assessment Report on Biodiversity \r and Ecosystem Services, and the Global Land Outlook of the UN Convention to Combat Desertification (UNCCD). This report provides \r [...]"


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"[...] an updated assessment of the current state of knowledge8\r  while striving for coherence and complementarity with other recent reports. "


id: c4aa99c79071492509cc2ac5cd9c3ceb
created_at: 2023-04-19 13:23:24
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"Figure SPM.1: Land use and observed climate change | A representation of the land use and observed climate change covered in this assessment report. Panels \r A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and \r D-F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D-F are expressed \r relative to the starting year of the time series (rebased to zero). Data sources and notes: A: The warming curves are averages of four datasets {2.1, Figure 2.2, Table 2.1} \r B: N2\r O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires \r since 1997). All values expressed in units of CO2\r [...]"


id: 6586bc1b31211f050425696661b76aeb
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"[...] -eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O=265; CH4=28). \r (Table SPM.1) {1.1, 2.3} C: Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing \r land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total percentage of the ice-free area covered, with \r uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km2. The area of 'forest managed for timber and \r other uses' was calculated as total forest area minus 'primary/intact' forest area. {1.2, Table 1.1, Figure 1.3} D: Note that fertiliser use is shown on a split axis. The large \r percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised \r [...]"


id: 5271bc316ced501371a4d765fe1dc5d9
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"[...] cropland and grassland to increase food production. {1.1, Figure 1.3} E: Overweight population is defined as having a body mass index (BMI) > 25 kg m-2; underweight is \r defined as BMI < 18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980-2015) to identify areas \r where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation \r Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes \r in local wetland area over time. {3.1, 4.2, 4.6} "


id: 54273b55ff8b13a80f4896bbdb896c78
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"3\r  Estimates show the mean and assessed uncertainty of two databases, FAOSTAT and USEPA. 2012 {2.3, Table 2.2}\r 4\r  Based on FAOSTAT. Categories included in this value are 'net forest conversion' (net deforestation), drainage of organic soils (cropland and grassland), biomass burning \r (humid tropical forests, other forests, organic soils). It excludes 'forest land' (forest management plus net forest expansion), which is primarily a sink due to afforestation. \r Note: Total FOLU emissions from FAOSTAT are 2.8 (+-1.4) GtCO2\r  yr-1 for the period 2007-2016. {Table 2.2, Table 5.4} 5\r  CO2 emissions induced by activities not included in the AFOLU sector, mainly from energy (e.g., grain drying), transport (e.g., international trade), and industry (e.g., \r synthesis of inorganic fertilisers) part of food systems, including agricultural production activities (e.g., heating in greenhouses), pre-production (e.g., manufacturing of \r [...]"


id: afd6616a652c32dd9e3124d96cf8be3d
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"[...] farm inputs) and post-production (e.g., agri-food processing) activities. This estimate is land based and hence excludes emissions from fisheries. It includes emissions from \r fibre and other non-food agricultural products since these are not separated from food use in databases. The CO2\r  emissions related to the food system in sectors other \r than AFOLU are 6--13% of total anthropogenic CO2\r  emissions. These emissions are typically low in smallholder subsistence farming. When added to AFOLU emissions, \r the estimated share of food systems in global anthropogenic emissions is 21--37%. {5.4.5, Table 5.4} \r 6\r  Total non-AFOLU emissions were calculated as the sum of total CO2eq emissions values for energy, industrial sources, waste and other emissions with data from the \r Global Carbon Project for CO2\r , including international aviation and shipping and from the PRIMAP database for CH4 and N2O averaged over 2007-2014 only as that \r [...]"


id: e41ff24704732a7ee377fcceae83f32b
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"[...] was the period for which data were available. {2.3, Table 2.2}. \r 7\r  The natural response of land to human-induced environmental changes is the response of vegetation and soils to environmental changes such as increasing atmospheric \r CO2\r  concentration, nitrogen deposition, and climate change. The estimate shown represents the average from Dynamic Global Vegetation Models {2.3.1.2, Box 2.2, \r Table 2.3} \r 8\r  All values expressed in units of CO2eq are based on AR5 100-year Global Warming Potential (GWP) values without climate-carbon feedbacks (N2O = 265; CH4 = 28). \r Note that the GWP has been used across fossil fuel and biogenic sources of methane. If a higher GWP for fossil fuel CH4\r  (30 per AR5) were used, then total anthropogenic \r CH4\r  emissions expressed in CO2eq would be 2% greater. 9\r  This estimate is land based and hence excludes emissions from fisheries and emissions from aquaculture (except emissions from feed produced on land and used \r [...]"


id: 761db385e2df86420e59091d74fd8192
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"[...] in aquaculture), and also includes non-food use (e.g. fibre and bioenergy) since these are not separated from food use in databases. It excludes non-CO2\r  emissions \r associated with land use change (FOLU category) since these are from fires in forests and peatlands.\r 10 Emissions associated with food loss and waste are included implicitly, since emissions from the food system are related to food produced, including food consumed \r for nutrition and to food loss and waste. The latter is estimated at 8-10% of total anthropogenic emissions in CO2\r eq. {5.5.2.5} 11 No global data are available for agricultural CO2\r  emissions."


id: 200f6c2d303ce46cd4e5c539fa6173a8
created_at: 2023-04-19 13:23:24
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"Figure SPM.2: Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation \r choices in terrestrial ecosystems. | As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at \r which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The Figure indicates \r assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive \r capacity consistent with the SSP pathways as described below. Panel A: Risks to selected elements of the land system as a function of global mean surface \r temperature {2.1, Box 2.1, 3.5, 3.7.1.1, 4.4.1.1, 4.4.1.2, 4.4.1.3, 5.2.2, 5.2.3, 5.2.4, 5.2.5, 7.2, 7.3, Table SM7.1}. Links to broader systems are illustrative and \r [...]"


id: 1ef12aebf5286b186786ded483f614d6
created_at: 2023-04-19 13:23:24
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"[...] not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions \r broadly consistent with an SSP2 pathway. {Table SM7.4} Panel B: Risks associated with desertification, land degradation and food security due to climate change \r and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in \r drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food \r security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable \r due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {Box SPM.1}) excluding the effects of targeted \r [...]"


id: fca1feff02256baf91c876f7a7906e4f
created_at: 2023-04-19 13:23:24
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"[...] mitigation policies. {3.5, 4.2.1.2, 5.2.2, 5.2.3, 5.2.4, 5.2.5, 6.1.4, 7.2, Table SM7.5} Risks are not indicated beyond 3degC because SSP1 does not exceed this level \r of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation \r protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi\u0002round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and \r underlying literature can be found in Chapter 7 Supplementary Material."


id: fd3cf3ab4fcb983314f0d0913c14f668
created_at: 2023-04-19 13:23:24
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"Figure SPM.3: Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and \r enhancing food security. | This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are \r implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. Magnitude \r of potential: For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker \r level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr\u00021\r ). The threshold for the 'large' magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by \r [...]"


id: 5d505bd30eabc654ffd020139c1b3b6
created_at: 2023-04-19 13:23:24
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"[...] climate change and a carbon-based economy between 2010 and 2030. The threshold for the 'large' magnitude category represents 25% of this total. For desertification \r and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10-60 million km2. The threshold for the 'large' magnitude \r category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. \r The threshold for the 'large' magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the \r magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are \r [...]"


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"[...] green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable \r intensification rather than through injudicious application of additional external inputs such as agrochemicals. Levels of confidence: Confidence in the magnitude \r category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. \r High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low \r confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude \r of response. Cost ranges: Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, \r [...]"


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"[...] cost estimates are not provided for best practice implementation. One coin indicates low cost (<USD10 tCO2-eq-1 or <USD20 ha-1), two coins indicate medium cost \r (USD10-USD100 tCO2-eq-1 or USD20 -USD200 ha-1), and three coins indicate high cost (>USD100 tCO2-eq-1 or USD200 ha-1). Thresholds in USD ha-1 are chosen to be \r comparable, but precise conversions will depend on the response option. Supporting evidence: Supporting evidence for the magnitude of the quantitative potential \r for land management-based response options can be found as follows: for mitigation Table's 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Table's \r 6.21 to 6.28; for combating desertification Table's 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence \r [...]"


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"[...] in Chapter 4; for enhancing food security Table's 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter \r 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table's 6.6, 6.55, 6.56 and 6.58, \r Section 6.3.5.1.3, and Box 6.1c."


id: 7a12a0402d945338258dce84a42adfb8
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"Figure SPM.4: Pathways linking socioeconomic development, mitigation responses and land | Future scenarios provide a framework for understanding the \r implications of mitigation and socioeconomics on land. The Shared Socioeconomic Pathways (SSPs) span a range of different socioeconomic assumptions (Box SPM.1). \r They are combined with Representative Concentration Pathways (RCPs)36 which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, \r forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). \r This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation \r bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of 'permanent meadows and pastures'. \r [...]"


id: 88e00f0ba8c8103bb59c531ed8415ffd
created_at: 2023-04-19 13:23:24
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"[...] Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and \r unmanaged forest. Natural land includes other grassland, savannah, and shrubland. Panel A: This panel shows integrated assessment model (IAM)37 results for SSP1, \r SSP2 and SSP5 at RCP1.9.38 For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 \r and SSP5 results are from five, four and two IAMs respectively. Panel B: Land use and land cover change are indicated for various SSP-RCP combinations, showing \r multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter \r 1, Cross-Chapter Box 9 in Chapter 6}"


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content:
"Myles Allen (UK), Mustafa Babiker (Sudan), Yang Chen (China), Heleen de Coninck \r (Netherlands/EU), Sarah Connors (UK), Renee van Diemen (Netherlands), Opha Pauline \r Dube (Botswana), Kristie L. Ebi (USA), Francois Engelbrecht (South Africa), Marion Ferrat \r (UK/France), James Ford (UK/Canada), Piers Forster (UK), Sabine Fuss (Germany), Tania \r Guillen Bolanos (Germany/Nicaragua), Jordan Harold (UK), Ove Hoegh-Guldberg (Australia), \r Jean-Charles Hourcade (France), Daniel Huppmann (Austria), Daniela Jacob (Germany), \r Kejun Jiang (China), Tom Gabriel Johansen (Norway), Mikiko Kainuma (Japan), Kiane de \r Kleijne (Netherlands/EU), Elmar Kriegler (Germany), Debora Ley (Guatemala/Mexico), \r Diana Liverman (USA), Natalie Mahowald (USA), Valerie Masson-Delmotte (France),\r J. B. Robin Matthews (UK), Richard Millar (UK), Katja Mintenbeck (Germany), Angela Morelli \r (Norway/Italy), Wilfran Moufouma-Okia (France/Congo), Luis Mundaca (Sweden/Chile), \r [...]"


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"[...] Maike Nicolai (Germany), Chukwumerije Okereke (UK/Nigeria), Minal Pathak (India), Antony \r Payne (UK), Roz Pidcock (UK), Anna Pirani (Italy), Elvira Poloczanska (UK/Australia), Hans\u0002Otto Portner (Germany), Aromar Revi (India), Keywan Riahi (Austria), Debra C. Roberts \r (South Africa), Joeri Rogelj (Austria/Belgium), Joyashree Roy (India), Sonia I. Seneviratne \r (Switzerland), Priyadarshi R. Shukla (India), James Skea (UK), Raphael Slade (UK), Drew \r Shindell (USA), Chandni Singh (India), William Solecki (USA), Linda Steg (Netherlands), \r Michael Taylor (Jamaica), Petra Tschakert (Australia/Austria), Henri Waisman (France), \r Rachel Warren (UK), Panmao Zhai (China), Kirsten Zickfeld (Canada)."


id: 2eb1a1f2f79676f62f6c06e4172acef
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 5493
content:
"Figure SPM.1 | Panel a: Observed monthly global mean surface temperature (GMST, grey line up to 2017, from the HadCRUT4, GISTEMP, Cowtan-Way, and \r NOAA datasets) change and estimated anthropogenic global warming (solid orange line up to 2017, with orange shading indicating assessed likely range). Orange \r dashed arrow and horizontal orange error bar show respectively the central estimate and likely range of the time at which 1.5degC is reached if the current rate \r of warming continues. The grey plume on the right of panel a shows the likely range of warming responses, computed with a simple climate model, to a stylized \r pathway (hypothetical future) in which net CO2 emissions (grey line in panels b and c) decline in a straight line from 2020 to reach net zero in 2055 and net non\u0002CO2 radiative forcing (grey line in panel d) increases to 2030 and then declines. The blue plume in panel a) shows the response to faster CO2 emissions reductions \r [...]"


id: 502b76af91f27fca42178ef7f310f3e5
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 11390
content:
"[...] (blue line in panel b), reaching net zero in 2040, reducing cumulative CO2 emissions (panel c). The purple plume shows the response to net CO2 emissions declining \r to zero in 2055, with net non-CO2 forcing remaining constant after 2030. The vertical error bars on right of panel a) show the likely ranges (thin lines) and central \r terciles (33rd - 66th percentiles, thick lines) of the estimated distribution of warming in 2100 under these three stylized pathways. Vertical dotted error bars in \r panels b, c and d show the likely range of historical annual and cumulative global net CO2 emissions in 2017 (data from the Global Carbon Project) and of net \r non-CO2 radiative forcing in 2011 from AR5, respectively. Vertical axes in panels c and d are scaled to represent approximately equal effects on GMST. {1.2.1, 1.2.3, \r 1.2.4, 2.3, Figure 1.2 and Chapter 1 Supplementary Material, Cross-Chapter Box 2 in Chapter 1}"


id: 3fedde9bd2983f135adf1aec6b089a9b
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 8440
content:
"10 Here, impacts on economic growth refer to changes in gross domestic product (GDP). Many impacts, such as loss of human lives, cultural heritage and ecosystem services, are difficult \r to value and monetize.\r 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 people, mountain glaciers and biodiversity hotspots. \r RFC2 Extreme weather events: risks/impacts to human health, livelihoods, assets and ecosystems from extreme weather events such as heat waves, heavy rain, \r drought and associated wildfires, and coastal flooding. \r RFC3 Distribution of impacts: risks/impacts that disproportionately affect particular groups due to uneven distribution of physical climate change hazards, \r exposure or vulnerability. \r [...]"


id: 7c224090d5bd0f718d55b6fbf47da9dc
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 19049
content:
"[...] RFC4 Global aggregate impacts: global monetary damage, global-scale degradation and loss of ecosystems and biodiversity. \r RFC5 Large-scale singular events: are relatively large, abrupt and sometimes irreversible changes in systems that are caused by global warming. Examples \r include disintegration of the Greenland and Antarctic ice sheets."


id: 40303d38e7e8dc56475aeb0308ab0d4
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 8481
content:
"Figure SPM.3a | Global emissions pathway characteristics. The main panel shows global net anthropogenic CO2 emissions in pathways limiting global warming \r to 1.5degC with no or limited (less than 0.1degC) overshoot and pathways with higher overshoot. The shaded area shows the full range for pathways analysed in this \r Report. The panels on the right show non-CO2 emissions ranges for three compounds with large historical forcing and a substantial portion of emissions coming \r from sources distinct from those central to CO2 mitigation. Shaded areas in these panels show the 5-95% (light shading) and interquartile (dark shading) ranges \r of pathways limiting global warming to 1.5degC with no or limited overshoot. Box and whiskers at the bottom of the figure show the timing of pathways reaching \r global net zero CO2 emission levels, and a comparison with pathways limiting global warming to 2degC with at least 66% probability. Four illustrative model pathways \r [...]"


id: 863dcdab6eb385f64f9a33c60e5735c
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 20774
content:
"[...] are highlighted in the main panel and are labelled P1, P2, P3 and P4, corresponding to the LED, S1, S2, and S5 pathways assessed in Chapter 2. Descriptions and \r characteristics of these pathways are available in Figure SPM.3b. {2.1, 2.2, 2.3, Figure 2.5, Figure 2.10, Figure 2.11}"


id: fd575dcd4dc66a47db5547b5af756c93
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 41925
content:
"Figure SPM.3b | Characteristics of four illustrative model pathways in relation to global warming of 1.5degC introduced in Figure SPM.3a. These pathways were \r selected to show a range of potential mitigation approaches and vary widely in their projected energy and land use, as well as their assumptions about future \r socio-economic developments, including economic and population growth, equity and sustainability. A breakdown of the global net anthropogenic CO2 emissions \r into the contributions in terms of CO2 emissions from fossil fuel and industry; agriculture, forestry and other land use (AFOLU); and bioenergy with carbon capture \r and storage (BECCS) is shown. AFOLU estimates reported here are not necessarily comparable with countries' estimates. Further characteristics for each of these \r pathways are listed below each pathway. These pathways illustrate relative global differences in mitigation strategies, but do not represent central estimates, \r [...]"


id: 4d4d518bf5dce6769202d7566d743a42
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 10882
content:
"[...] national strategies, and do not indicate requirements. For comparison, the right-most column shows the interquartile ranges across pathways with no or limited \r overshoot of 1.5degC. Pathways P1, P2, P3 and P4 correspond to the LED, S1, S2 and S5 pathways assessed in Chapter 2 (Figure SPM.3a). {2.2.1, 2.3.1, 2.3.2, \r 2.3.3, 2.3.4, 2.4.1, 2.4.2, 2.4.4, 2.5.3, Figure 2.5, Figure 2.6, Figure 2.9, Figure 2.10, Figure 2.11, Figure 2.14, Figure 2.15, Figure 2.16, Figure 2.17, Figure 2.24,\r Figure 2.25, Table 2.4, Table 2.6, Table 2.7, Table 2.9, Table 4.1} "


id: 43c5af6bc7e3536068953d2d10889a1f
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 9148
content:
"Figure SPM.4 | Potential synergies and trade-offs between the sectoral portfolio of climate change mitigation options and the Sustainable Development Goals \r (SDGs). The SDGs serve as an analytical framework for the assessment of the different sustainable development dimensions, which extend beyond the time frame \r of the 2030 SDG targets. The assessment is based on literature on mitigation options that are considered relevant for 1.5degC. The assessed strength of the SDG \r interactions is based on the qualitative and quantitative assessment of individual mitigation options listed in Table 5.2. For each mitigation option, the strength of \r the SDG-connection as well as the associated confidence of the underlying literature (shades of green and red) was assessed. The strength of positive connections \r (synergies) and negative connections (trade-offs) across all individual options within a sector (see Table 5.2) are aggregated into sectoral potentials for the whole \r [...]"


id: 3deb9064ebe0d774431984ce8914e77e
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 8063
content:
"[...] mitigation portfolio. The (white) areas outside the bars, which indicate no interactions, have low confidence due to the uncertainty and limited number of studies \r exploring indirect effects. The strength of the connection considers only the effect of mitigation and does not include benefits of avoided impacts. SDG 13 (climate \r action) is not listed because mitigation is being considered in terms of interactions with SDGs and not vice versa. The bars denote the strength of the connection, \r and do not consider the strength of the impact on the SDGs. The energy demand sector comprises behavioural responses, fuel switching and efficiency options in \r the transport, industry and building sector as well as carbon capture options in the industry sector. Options assessed in the energy supply sector comprise biomass \r and non-biomass renewables, nuclear, carbon capture and storage (CCS) with bioenergy, and CCS with fossil fuels. Options in the land sector comprise agricultural \r [...]"


id: 2d3e266afca3c6a6699cb5fb6451037d
created_at: 2023-04-19 13:23:24
updated_at: 2023-04-19 13:23:24
content_type: text
index: climate_gpt_v2
vector_id: 5246
content:
"[...] and forest options, sustainable diets and reduced food waste, soil sequestration, livestock and manure management, reduced deforestation, afforestation and \r reforestation, and responsible sourcing. In addition to this figure, options in the ocean sector are discussed in the underlying report. {5.4, Table 5.2, Figure 5.2}"


# meta_document

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