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

=== 10.1.4 Distillation of Regional Climate Information ===

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Regional climate information is synthesized from different lines of evidence from a number of sources (Sections 10.2–10.4) taking into account the context of a user vulnerable to climate variability and change at regional scales ( [[#Baztan--2017|Baztan et al., 2017]] ) and the values of all relevant actors ( [[#Corner--2014|Corner et al., 2014]] ; [[#Bessette--2017|Bessette et al., 2017]] ) in a process called distillation ( [[#10.5|Section 10.5]] ). Distillation, understood as the process of synthesizing information about climate change from different lines of evidence obtained from a variety of sources and taking into account the user context and the values of all relevant actors, allows the connection of global climate change to the local and regional scales, where adaptation responses and policy decisions take place. Climate information is translated into the user context in a co-production process that introduces further user-relevant elements leading to user-relevant climate information (Figure 10.1; [[#Pettenger--2016|Pettenger, 2016]] ; [[#Verrax--2017|Verrax, 2017]] ) for a specific demand like, for instance, guiding climate-resilient development ( [[#Kruk--2017|Kruk et al., 2017]] ; [[#Parker--2019|Parker and Lusk, 2019]] ).

The approaches adopted in the distillation of regional climate information are diverse and range from the simple delivery of data as information to co-production with the user using as many lines of evidence as possible ( [[#Lourenço--2016|Lourenço et al., 2016]] ). The availability and selection of the sources and the approach followed has implications for the usefulness of the information. For instance, it is well-established that it is invalid to take a time series from a gridcell of a model simulation as equivalent to an observational estimate of a point within the cell, due to the lack of representativeness ( [[#10.3|Section 10.3]] ), and consequently the information building solely on this type of data source is of limited use. Relevant decisions are made during the distillation process, such as what method is most suitable to a specific user context and the question being addressed. The information may be provided in the form of summarized raw data, a set of user-oriented indicators, a set of figures and maps with either a brief description, in the form of a storyline, or formulated as rich and complex climate adaptation plans. The information typically includes a description of the sources and assumptions, estimates of the associated uncertainty and its sources, and guidance to prevent possible misunderstandings in its communication.

The choices made for the distillation have typically been part of a linear supply chain, starting from the access to climate data that are transformed into maps or derived climate data products, and finally formulating statements that are communicated and delivered to a broad range of users ( [[#Hewitt--2012|Hewitt et al., 2012]] ; [[#Hewitson--2017|Hewitson et al., 2017]] ). This methodology has proven to be valuable in many cases, but it is equally fraught with dangers of not communicating important assumptions, not estimating the impact of relevant uncertainties, and possibly causing misunderstandings in the handover to the user community. This has led to the emergence of new pathways to generate user-oriented climate information, many in the context of emerging climate services ( [[#Buontempo--2018|Buontempo et al., 2018]] ; [[#Hewitt--2020|Hewitt et al., 2020]] ), which are assessed in [[#10.5|Section 10.5]] and in Chapter 12.

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