Editing IPCC:AR6/WGI/Chapter-10 (section)

=== 10.1.1 Introduction ===

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This chapter assesses the foundations for the distillation of regional climate change information from multiple lines of evidence. The AR5, SR1.5 and SRCCL reports underlined the relevance of assessing regional climate information that is useful and relevant to the decision scale (Box 10.1). To respond to this need, the AR6 WGI Report includes four regional chapters of which this is the first. Chapter 10 assesses the sources and methodologies used by the Chapters 11, 12 and [[IPCC:Wg1:Chapter:Atlas|Atlas]] to construct regional information. Chapter 10 builds on the assessment of methodologies considered to construct global climate change information in Chapters 2 to 4 and on the processes assessed in Chapters 5 to 9. Additionally, this chapter assesses the methodologies for the co-production of regional climate information, the role of the different actors involved in the process and the relevance of the user context and values.

Regional climate change refers to a change in climate in a given region ( [[#10.1.2.1|Section 10.1.2.1]] ) identified by changes in the mean or higher moments of the probability distribution of a climate variable and persisting for a few decades or longer. It can also refer to a change in temporal properties such as persistence and frequency of occurrence of weather and climate extreme events. Regional climate change may be caused by natural internal processes such as atmospheric internal variability and local climate response to low-frequency modes of climate variability (Technical Annex IV), as well as by changes in external forcings such as modulations of the solar cycle, orbital forcing, volcanic eruptions, and persistent anthropogenic changes in the composition of the atmosphere or in land use and land cover (Cross-Chapter Box 3.2; [[#IPCC--2018a|IPCC, 2018a]] ), in addition to the interactions and feedbacks between them. Process interaction in space is pervasive, which means that small spatial scales often have an influence on the larger scales ( [[#Palmer--2013|Palmer, 2013]] ; [[#Sandu--2016|Sandu et al., 2016]] ). Depending on the context, a region may refer to a large area such as a monsoon region, but may also be confined to smaller areas such as coastlines, mountain ranges or human settlements like cities. Users (understood as anyone incorporating climate information into their activity) often request climate information for these range of scales since their operating and adaptation decision scales range from the local to the sub-continental level.

Given the many types of regional climates, the broad range of spatial and temporal scales ( [[#10.1.2|Section 10.1.2]] ), and the diversity of user needs, a variety of methodologies and approaches have been developed to construct regional climate change information. The sources include global and regional climate model simulations, statistical downscaling and bias adjustment methods. A commonly used source is long-term (end-of-century) model projections of regional climate change, as well as near-term (next 10 years) climate predictions ( [[#Kushnir--2019|Kushnir et al., 2019]] ; [[#Rössler--2019a|Rössler et al., 2019a]] ). Regional observations, with their associated challenges, are a key source for the regional climate information construction process (Q. [[#Li--2020|]] [[#Li--2020|Li et al., 2020]] ). High-quality observations that enable monitoring of the regional aspects of climate are used to adjust inherent model biases and are the basis for assessing model performance. Process understanding and attribution of observed changes to large- and regional-scale anthropogenic and natural drivers and forcings are also important sources.

All these sources are used, when available, to distil regional climate information from multiple lines of evidence (Figure 10.1). The resulting climate information can then be integrated, following a co-production process involving both the user and the producer, into a user context that often is already taken into account when constructing the regional climate information. In fact, the distillation process leading to the climate information can consider the specific context of the question at stake, the values of both the user and the producer, and the challenge of communicating across different communities ( [[#10.5|Section 10.5]] ).

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'''Figure 10.1''' '''|''' '''Diagram of the processes leading to the construction of regional climate information (blue) and user-relevant regional climate information (brown).''' The chapter sections and the other chapters of the Report involved in each step are indicated in rectangles. WGII stands for Working Group II. Literature refers to scientific and technical literature, and climate experts refers to climate scientists, practitioners and local communities, as defined in [[#10.5|Section 10.5]] .

The chapter (Figure 10.2) starts with an introduction of the concepts used in the distillation of regional climate information ( [[#10.1|Section 10.1]] ). [[#10.2|Section 10.2]] addresses the aspects associated with the access to and use of observations, while different modelling approaches are introduced and assessed in [[#10.3|Section 10.3]] . [[#10.3|Section 10.3]] also addresses the performance of models in simulating relevant climate characteristics as needed to estimate the credibility of future projections. [[#10.4|Section 10.4]] assesses the interplay between anthropogenic causes and internal variability at regional scales, and its relevance for the attribution of regional climate changes and the emergence of regional climate change signals. [[#10.5|Section 10.5]] tackles the issue of how regional climate information is distilled from different sources taking into account the context and the values of both the producer and the user. [[#10.6|Section 10.6]] illustrates the distillation approach using three comprehensive examples. Finally, [[#10.7|Section 10.7]] lists some limitations to the assessment of regional climate information.

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'''Figure 10.2''' '''|''' '''Visual guide to Chapter 10.'''

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