Editing IPCC:AR6/WGI/TS (section)

=== TS.1.4 From Global to Regional Climate Information for Impact and Risk Assessment ===

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'''The AR6 WGI Report has an expanded focus on regional information supported by the increased availability of coordinated regional climate model ensemble projections and improvements in the sophistication and resolution of global and regional climate models (''high confidence''). Multiple lines of evidence can be used to construct climate information on a global to regional scale and can be further distilled in a co-production process to meet user needs (''high confidence''). To better support risk assessment, a common risk framework across all three Working Groups has been implemented in AR6, and low-likelihood but high-impact outcomes are explicitly addressed in WGI by using physical climate storylines (see Core Concepts Box).''' '''Climatic impact-drivers are physical climate system conditions (e.g., means, events, extremes) that affect an element of society or ecosystems. They are the WGI contribution to the risk framing without anticipating whether their impact provides potential opportunities or is detrimental (i.e., as for hazards). Many global and regional climatic impact-drivers have a direct relation to global warming levels (''high confidence''). Links to chapters 1.4.4, 1.5.2–1.5.4, Cross-Chapter Box 1.3, 4.8, 10.1, 10.5.1, Box 10.2, Cross-Chapter Box 10.3, 11.2.4, 11.9, Box 11.2, Cross-Chapter Box 11.1, 12.1–12.3, 12.6, Cross-Chapter Boxes 12.1 and 12.2, Atlas.1.3.3–1.3.4, Atlas.1.4, Atlas.1.4.4'''

Climate change is a global phenomenon, but manifests differently in different regions. The impacts of climate change are generally experienced at local, national and regional scales, and these are also the scales at which decisions are typically made. Robust climate change information is increasingly available at regional scales for impact and risk assessments. Depending on the climate information context, geographical regions in AR6 may refer to larger areas, such as sub-continents and oceanic regions, or to typological regions, such as monsoon regions, coastlines, mountain ranges or cities, as used in Section TS.4. A new set of standard AR6 WGI reference regions has also been included in this Report (Figure TS.6, bottom panels). Links to chapters 1.4.5, 10.1, 11.9, 12.1–12.4, Atlas.1.3.3–1.3.4

[[File:7883996611279b2ba154dd86af2f0d1b IPCC_AR6_WGI_TS_Figure_6.png]]

'''Figure TS.6 |''' '''A graphical abstract for key aspects of the Technical Summary.''' ''The intent of this figure is to summarize many different aspects of the Technical Summary related to observed and projected changes in global temperature and associated regional changes in climatic impact-drivers relevant for impact and risk assessment.'' Top left: a schematic representation of the likelihood for equilibrium climate sensitivity (ECS), consistent with the AR6 assessment (see [[IPCC:Wg1:Chapter:Chapter-7|Chapter 7]] and Section TS.3). ECS values above 5°C and below 2°C are termed low-likelihood, high warming (LLHW) and low-likelihood, low warming, respectively (Box TS.3). Top right: Observed (see Cross-Section Box TS.1) and projected global surface temperature changes, shown as global warming levels (GWLs) relative to 1850–1900, using the assessed 95% (top), 50% (middle) and 5% (bottom) likelihood time series (see [[IPCC:Wg1:Chapter:Chapter-4|Chapter 4]] and Section TS.2). Bottom panels show maps of Coupled Model Intercomparison Project Phase 6 (CMIP6) median projections of two climatic impact-drivers (CIDs, see Section TS.1.4) at three different GWLs (columns for 1.5, 2 and 4°C) for the AR6 land regions (see Chapters 1, 10, and [[IPCC:Wg1:Chapter:Atlas|Atlas]] and Section TS.4). The heat warning index is the number of days per year averaged across each region at which a heat warning for human health at level ‘danger’ would be issued according to the U.S. National Oceanic and Atmospheric Administration (NOAA) (NOAA HI41, see [[IPCC:Wg1:Chapter:Chapter-12|Chapter 12]] and Annex VI). The maps of extreme rainfall changes show the percentage change in the amount of rain falling on the wettest day of a year (Rx1day, relative to 1995–2014, see Chapter 11) averaged across each region when the respective GWL is reached. Additional CIDs are discussed in Section TS.4. Links to chapters 1.4.4, Box 4.1, 7.5, 11.4.3, 12.4

Global and regional climate models are important sources of climate information at the regional scale. Since AR5, a more comprehensive assessment of past and future evolution of a range of climate variables on a regional scale has been enabled by the increased availability of coordinated ensemble regional climate model projections and improvements in the level of sophistication and resolution of global and regional climate models. This has been complemented by observational, attribution and sectoral-vulnerability studies informing, for instance, about impact-relevant tolerance thresholds. Links to chapters 10.3.3, 11.9, 12.1, 12.3, 12.6, Atlas.3–Atlas.11

Multiple lines of evidence derived from observations, model simulations and other approaches can be used to construct climate information on a regional scale as described in detail in Sections TS.4.1.1 and TS.4.1.2. Depending on the phenomena and specific context, these sources and methodologies include theoretical understanding of the relevant processes, drivers and feedbacks of climate at regional scale; trends in observed data from multiple datasets; and the attribution of these trends to specific drivers. Furthermore, simulations from different model types (including global and regional climate models, emulators, statistical downscaling methods, etc.) and experiments (e.g., CMIP, CORDEX, and large ensembles of single-model simulations with different initial conditions), attribution methodologies and other relevant local knowledge (e.g., indigenous knowledge) are utilized (see Box TS.11). Links to chapters 1.5.3, 1.5.4, Cross-Chapter Box 7.1, 10.2–10.6, 11.2, Atlas.1.4, Cross-Chapter Box 10.3

From the multiple lines of evidence, climate information can be distilled in a co-production process that involves users, related stakeholders and producers of climate information, considering the specific context of the question at stake, the underlying values and the challenge of communicating across different communities. The co-production process is an essential part of climate services, which are discussed in Section TS.4.1.2. Links to chapters 10.5, 12.6, Cross-Chapter Box 12.2

With the aim of informing decision-making at local or regional scales, a common risk framework has been implemented in AR6. Methodologies have been developed to construct more impact- and risk-relevant climate change information tailored to regions and stakeholders. Physical storyline approaches are used in order to build climate information based on multiple lines of evidence, and which can explicitly address physically plausible, but low-likelihood, high-impact outcomes and uncertainties related to climate variability for consideration in risk assessments (Figure TS.6). Links to chapters Cross-Chapter Box 1.3, 4.8, Box 9.4, 10.5, Box 10.2, Box 11.2, 12.1–12.3, 12.6, Glossary

The climatic impact-driver framework developed in AR6 supports an assessment of changing climate conditions that are relevant for sectoral impacts and risk assessment. Climatic impact-drivers (CIDs) are physical climate system conditions (e.g., means, extremes, events) that affect an element of society or ecosystems and are thus a potential priority for providing climate information. For instance, the heat index used by the U.S. National Oceanic and Atmospheric Administration (NOAA HI) for issuing heat warnings is a CID index that can be associated with adverse human health impacts due to heat stress (see Figure TS.6). Depending on system tolerance, CIDs and their changes can be detrimental (i.e., hazards in the risk framing), beneficial, neutral, or a mixture of each across interacting system elements, regions and sectors (aligning with WGII Sectoral Chapters 2–8). Each sector is affected by multiple CIDs, and each CID affects multiple sectors. Climate change has already altered CID profiles and resulted in shifting magnitude, frequency, duration, seasonality and spatial extent of associated indices (''high confidence'') (see regional details in Section TS.4.3). Links to chapters 12.1–12.4, Table 12.1, Table 12.2, Annex VI

Many global- and regional-scale CIDs, including extremes, have a direct relation to global warming levels (GWLs) and can thus inform the hazard component of ‘Representative Key Risks’ and ‘Reasons for Concern’ assessed by AR6 WGII. These include heat, cold, wet and dry hazards, both mean and extremes; cryospheric hazards (snow cover, ice extent, permafrost) and oceanic hazards (marine heatwaves) (''high confidence'') (Figure TS.6). Establishing links between specific GWLs with tipping points and irreversible behaviour is challenging due to model uncertainties and lack of observations, but their occurrence cannot be excluded, and their likelihood of occurrence generally increases at greater warming levels (Box TS.1, Section TS.9). Links to chapters 11.2.4, Box 11.2, Cross-Chapter Boxes 11.1 and 12.1

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