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

== Atlas.2 The Online ‘Interactive Atlas’ ==

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The WGI Interactive Atlas is a new AR6 product developed as part of the Atlas in consultation with other chapters to facilitate flexible synthesis information for regions, and to support the Technical Summary (TS) and the Summary for Policymakers (SPM), as well as the handshake with WGII. It includes multiple lines of evidence to support the assessment of observed and projected climate change by offering information for regions using both time slices across scenarios and GWLs. Coordination has been established with other chapters (particularly the regional chapters), adopting their methodological recommendations (Chapter 10) and using common datasets and agreed extreme indices and climatic impact-drivers (CIDs) to support and expand their assessment (Chapters 11 and 12).

The Interactive Atlas includes two components. The first component (Regional Information) allows for flexible spatial and temporal analysis ( [[#Atlas.1.3|Atlas.1.3]] ) with a predefined granularity (predefined climatological and typological regions, and user-defined seasons) through a wide range of maps, graphs and tables generated in an interactive manner building on a collection of global and regional observational datasets and climate projections (including CMIP5, CMIP6 and CORDEX; [[#Atlas.1.4|Atlas.1.4]] ). In particular, the Interactive Atlas provides trends and changes for observations and projections in the form of interactive maps for predefined historical and future periods of analysis, the former including the recent past and paleoclimate (Cross-Chapter Box 2.1) and the latter including future time slices (near, medium and long term) across scenarios (RCPs and SSPs; see Cross-Chapter Box 1.4) and GWLs (1.5°C, 2°C, 3°C and 4°C; see Cross-Chapter Box 11.1). It also provides regional information (aggregated spatial values) for a number of predefined (reference and typological) regions in the form of time series, annual cycle plots, scatter plots (e.g., temperature versus precipitation), table summaries, and ensemble and seasonal stripe plots. This allows for a comprehensive analysis (and intercomparison, particularly using GWLs as a dimension of integration) of the different datasets at a global and regional scale.

The second component of the Interactive Atlas (Regional Synthesis) provides synthesis information about changes in CIDs in several categories such as heat and cold, wet and dry, or coastal and oceanic, supporting exploration of the regional assessment findings summarised in the TS and the SPM.

The Interactive Atlas can be consulted online at http://interactive-atlas.ipcc.ch . Figure Atlas.8 illustrates the main functionalities available: the controls at the top of the window allow the interactive selection of the dataset, variable, period (reference and baseline) and season which define a particular product of interest (e.g., annual temperature change from CMIP6 for a global warming level of 2°C under SSP3-7.0 relative to 1850–1900 in this illustrative case). Regionally aggregated information can be obtained interactively by clicking on one or several sub-regions on the map and by selecting one of the several options available for visuals (time series, annual cycle plots, scatter and stripe plots) and tables.

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[[File:452c2c21fe51b0729f10669c0f95a9d0 IPCC_AR6_WGI_Atlas_Figure_8.png]]

'''Figure Atlas.8|''' '''Screenshots from the Interactive Atlas (regional information). (a)''' The main interface includes a global map and controls to define a particular choice of dataset, variable, period (reference and baseline), and season (in this example, annual temperature change from CMIP6 for a global warming level of 2°C under SSP3-7.0 relative to 1850–1900). '''(b–e)''' Various visuals for the regionally averaged information for the selected reference regions.

A major goal during the development of the Interactive Atlas has been ensuring transparency and reproducibility of results, and promoting open science and Findability, Accessibility, Interoperability, and Reuse (FAIR) principles ( [[#Wilkinson--2016|Wilkinson et al., 2016]] ) described in [[#Atlas.2.3|Atlas.2.3]] . As a result, full metadata are provided in the Interactive Atlas for each of the products, and the scripts used to generate the intermediated products (e.g., extreme indices and CIDs) and figures are available online in a public repository ( [[#Iturbide--2021|Iturbide et al., 2021]] ), which also includes simple notebooks illustrating key parts of the code suitable for reusability. These scripts are based on the climate4R open-source framework ( [[#Iturbide--2019|Iturbide et al., 2019]] ) and full metadata have been generated for all final products using the METACLIP framework ( [[#Bedia--2019|Bedia et al., 2019]] ), which builds on standards and describes provenance of the datasets as well as the post-processing workflow.

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=== Atlas.2.1 Why an Online Interactive Atlas in AR6? ===

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The idea of an online interactive Atlas was first discussed in the IPCC Expert Meeting on Assessing Climate Information for the Regions ( [[#IPCC--2018a|IPCC, 2018a]] ). The meeting stressed the need for the AR6 regional Atlas to go beyond the AR5 experience in supporting and expanding the assessment of key variables/indices and datasets conducted in all chapters, ensuring traceability, and facilitating the ‘handshake’ between WGI and WGII. One of the main limitations of previous products, including the AR5 WGI Atlas ( [[#IPCC--2013a|IPCC, 2013a]] ), is their static nature with inherent limited options and flexibility to provide comprehensive regional climate information for different regions and applications. For instance, the use of standard seasons limits the assessment in many cases, such as regions affected by monsoons or seasonal rainband migrations or other phenomena-driven seasons. The limited number of variables which can be treated on a printed Atlas also prevents the inclusion of relevant extreme indices and CIDs. The development of an online Interactive Atlas for AR6 was proposed as a solution to overcome these obstacles, facilitating the flexible exploration of key variables/indices and datasets assessed in all chapters through a wide range of maps, graphs and tables generated in an interactive manner, and thus also providing support to the TS and SPM. One of the main concerns raised by this new online interactive product was the potential danger of having an unmanageable number of final products impossible to assess following the IPCC review process. This was addressed by designing the Interactive Atlas with limited and predefined functionality and granularity, thus facilitating the review process and including use of open-source tools and code for traceability and reproducibility of results.

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=== Atlas.2.2 Description of the Interactive Atlas: Functionalities and Datasets ===

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The Interactive Atlas builds on the work done in the context of the Spanish National Adaptation Plan (PNACC – AdapteCCa; [http://escenarios.adaptecca.es h ttp://escenarios .adaptecca.es] ) to develop an interactive online application centralizing and providing key regional climate change information to assist the Spanish climate change impact and adaptation community. The functionalities included in the AR6 WGI Interactive Atlas are an evolution of those implemented in AdapteCCa and have been adapted and extended to cope with the particular requirements of the datasets and functionalities it includes. In particular, the Interactive Atlas allows analysis of global and regional information on past trends and future climate changes through a wide range of maps, graphs and tables generated in an interactive manner, and building on six basic products (Figure Atlas.8):

# Global maps of ensemble mean values averaged over time slices across scenarios and GWLs, with robustness represented using the approaches described in Cross-Chapter Box Atlas.1.
# Temporal series, displaying all individual ensemble members and the multi-model median, with robustness represented as ranges across the ensemble (25th–75th and 10th–90th percentile ranges). The selected reference period of analysis is also displayed as context information, either a time slice (near, mid- or long term) or a GWL (defined for a given model as the first 20-year period where its average surface temperature change first reaches the GWL relative to its 1850–1900 temperature).
# Annual cycle plots representing individual models, the multi-model median and ranges across the ensemble.
# Stripe and seasonal stripe plots, providing visual information on changes across the ensemble (different models in rows with the multi-model median on the top) and across seasons (months in rows, using the signal from the multi-model mean), respectively.
# Two-variable scatter plots (e.g., temperature versus precipitation) and GWL plots representing regional/global changes of a particular variable versus global mean warming.
# Tables with summary information.

The first of these products provides spatial information about the ensemble mean, while the latter five convey (spatially) aggregated information of the multi-model ensemble for particular region(s) selected by the user from a number of predefined alternatives (see [[#Atlas.1.3.3|Atlas.1.3.3]] and [[#Atlas.1.3.4|Atlas.1.3.4]] for reference and typological regions, respectively).

The Interactive Atlas includes both atmospheric (daily mean, minimum and maximum temperatures, precipitation, snowfall and wind) and oceanic (sea surface temperature, pH, sea ice, and sea level rise) essential variables assessed in the Atlas chapter and Chapters 4, 8 and 9, as well as some derived extreme indices used in [[IPCC:Wg1:Chapter:Chapter-11|Chapter 11]] and a selection of CIDs used in [[IPCC:Wg1:Chapter:Chapter-12|Chapter 12]] (see Annex VI):

* Maximum of maximum temperatures (TXx) – see Chapter 11.
* Minimum of minimum temperatures (TNn) – see Chapter 11.
* Maximum 1-day precipitation (Rx1day) – see Chapter 11.
* Maximum 5-day precipitation (Rx5day) – see Chapter 11.
* Consecutive dry days (CDD) – see Chapter 11.
* Standardized Precipitation Index (SPI-6) – see Chapters 11 and 12.
* Frost days (FD), both raw and bias adjusted – see Chapters 11 and 12.
* Heating degree days (HD) – see Chapter 12.
* Cooling degree days (CD) – see Chapter 12.
* Days with maximum temperature above 35°C (TX35), both raw and bias adjusted – see Chapter 12.
* Days with maximum temperature above 40°C (TX40), both raw and bias adjusted – see Chapter 12.

The essential variables are computed for observations and reanalysis datasets as described in [[#Atlas.1.4.1|Atlas.1.4.1]] and [[#Atlas.1.4.2|Atlas.1.4.2]] (note that the Atlas does not include observational datasets for extremes). Trend analyses are available for two alternative baseline periods (1961–2015 and 1980–2015, selected according to data availability). This expands the information available in [[IPCC:Wg1:Chapter:Chapter-2|Chapter 2]] for global observational datasets, including new periods of analysis and new regional observational datasets which provide further insight into observational uncertainty. The Interactive Atlas also includes paleoclimate information from the Paleoclimate Model Intercomparison Projects PMIP3/4 for temperature and precipitation for the Last Glacial Maximum, Last Interglacial, mid-Holocene and mid-Pliocene periods (see Cross-Chapter Box 2.1).

Both essential variables and indices/CIDs are computed for CMIP5, CMIP6 and CORDEX model projections ( [[#Atlas.1.4.3|Atlas.1.4.3]] and [[#Atlas.1.4.4|Atlas.1.4.4]] ). The calculations are performed on the original model grids and results are interpolated to the reference regular grids at horizontal resolutions of 2° (CMIP5), 1° (CMIP6) and 0.5° (CORDEX) ( [[#Iturbide--2021|Iturbide et al., 2021]] ). Information is available for the historical, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios for CMIP6, and historical, RCP2.6, RCP4.5 and RCP8.5 for CMIP5 and CORDEX, as documented in the supplementary material Tables Atlas.SM.1–2 (for CMIP5/CMIP6) and Tables Atlas.SM.3–14 (for the different CORDEX domains). All products (maps, graphs and tables) are available for different reference periods of analysis, either time slices (2021–2040, 2041–2060 and 2081–2100 for near-, mid- and long-term future periods, respectively; see [[#Atlas.1.3.1|Atlas.1.3.1]] ), or GWLs (1.5°C, 2°C, 3°C or 4°C; see [[#Atlas.1.3.2|Atlas.1.3.2]] ), with changes relative to a number of alternative baselines (including 1850–1900 pre-industrial, and 1995–2014 recent past; see [[#Atlas.1.3.1|Atlas.1.3.1]] ). Note that instead of blending the information from the different scenarios, the Interactive Atlas allows comparison of the GWL spatial patterns and timings across the different scenarios (Cross-Chapter Box 11.1).

Some of the above indices (in particular, TX35 and TX40) are highly sensitive to model biases and the application of bias-adjustment techniques is recommended to alleviate this problem (see Cross-Chapter Box 10.2). Bias adjustment is performed as explained in [[#Atlas.1.4.5|Atlas.1.4.5]] .

The Interactive Atlas implements the approaches for representing robustness in maps at the grid-box level described in Cross-Chapter Box Atlas.1. These approaches are not necessarily informative for assessing trends and climate change signals over larger spatial scales where signals are less affected by small-scale variability leading to an increase in robustness. For regional analysis, the Interactive Atlas allows the analysis of aggregated region-wide signals and assessing their robustness at a regional scale, thus complementing the previous approach for grid-box robustness representation. For example, Figure Atlas.9 shows large hatched areas for maximum five-day precipitation in the South Asia region. When aggregated spatially, the region exhibits a robust wetting signal, with most ensemble members agreeing on the sign. This highlights that signals may not have emerged at the station or grid-box scale but have clearly at aggregated scales, particularly for variables with high variability (e.g., extreme precipitation or cold extremes; see Cross-Chapter Box Atlas.1).

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[[File:1fefb0fff696d8c6351018051f5fe4de IPCC_AR6_WGI_Atlas_Figure_9.png]]

'''Figure Atlas.9''' '''|''' '''Analysing robustness and uncertainty in climate change signals across spatial scales using the Interactive Atlas.''' The left panel shows projected annual relative changes for maximum five-day precipitation from CMIP6 for 2081–2100 relative to a 1995-2014 baseline under the SSP3-7.0 scenario, through a map of the ensemble-mean changes (panel top) and information on the regional aggregated signal over the South Asia reference region as a time series (panel bottom). This shows non-robust changes (diagonal lines) at the grid-box level (due to the large local variability), but a robust aggregated signal over the region. The right panel shows projected surface wind-speed changes from CMIP6 models for 2041–2060 relative to a 1995–2014 baseline under the SSP5-8.5 scenario, again with the ensemble-mean changes in the map (panel top) and a regionally aggregated time series over Central Africa for each model (panel bottom). This shows conflicting changes (crossed lines) at the grid-box level due to signals of opposite sign in the individual models displayed in the time series.

The advanced approach for representing robustness includes a new category for identifying conflicting signals, where models are projecting significant changes but of opposite signs. This is demonstrated in Figure Atlas.9 which shows a region of central Africa where models have significant changes in surface winds with some projecting increases and others decreases. This is clearly demonstrated in the time series below the map which shows these wind-speed changes aggregated over the CAF reference region for each of the CMIP6 models and the opposing signals in many of these.

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=== Atlas.2.3 Accessibility, Reproducibility and Reusability (FAIR Principles) ===

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The accessibility and reproducibility of scientific results have become a major concern in all scientific disciplines ( [[#Baker--2016|Baker, 2016]] ). During the design and development of the Interactive Atlas, special attention was paid to these issues in order to ensure the transparency of the products feeding into the Interactive Atlas (which are all publicly available). Accessibility is implemented in collaboration with the IPCC Data Distribution Centre (DDC), since all products underpinning the Interactive Atlas, including the intermediate products required for the indices and CIDs (monthly aggregated data), are curated and distributed by the IPCC-DDC and include full provenance information as part of their metadata. Atlas products are generated using the open-source climate4R framework ( [[#Iturbide--2019|Iturbide et al., 2019]] ) for data processing (e.g., regridding, aggregation, index calculation, bias adjustment), evaluation and quality control (when applicable). Full metadata are generated for all final products using the METACLIP framework ( [[#Bedia--2019|Bedia et al., 2019]] ), based on the Resource Description Framework (RDF) standard to describe the datasets and data-processing workflow.

In summary, a number of actions have been conducted in order to implement open access, reproducibility and reusability of results, including:

* Use of standards and open-source tools.
* Open access to raw data and derived Atlas products via the IPCC-DDC.
* Provision of full provenance metadata describing the product generation workflow.
* Access to code through an online repository ( [[#Iturbide--2021|Iturbide et al., 2021]] ), including the scripts needed for calculating the intermediate datasets and for reproducing some of the figures of the Atlas chapter.
* Provision of annotated (Jupyter) notebooks describing key elements of the code to provide guidance and facilitate reusability.

All final products visualized in the Interactive Atlas can be exported in a variety of formats, including PNG and PDF for bitmap and vector information, respectively. Moreover, in the case of the global maps, the final data underlying these products can be downloaded in NetCDF and GIS format (GeoTIFF), thus facilitating reusability of the information. Note that the images are final IPCC products (covered by the IPCC terms of use), whereas the underlying data are distributed by the IPCC-DDC under a more flexible license which facilitates reusability. Moreover, a comprehensive provenance metadata description has been generated, including all details needed for reproducibility, from the data sources to the different post-processes applied to obtain the final product. In these cases, there is also the possibility to download a PNG file augmented with attached metadata information (in JSON format). This metadata information (including the source code generating the product) can be accessed and interpreted automatically using specific JSON software/libraries. However, for the sake of simplicity, a human-readable version of the metadata is accessible directly from the Interactive Atlas, describing the key information along the workflow.

Provenance is defined as a ‘record that describes the people, institutions, entities, and activities involved in producing, influencing, or delivering a piece of data or a thing’. This information can be used to form assessments about their quality, reliability or trustworthiness. In the context of the outcomes of the Interactive Atlas, having an effective way of dealing with data provenance is a necessary condition to ensure not only the reproducibility of results, but also to build trust on the information provided. However, the relative complexity of the data and the post-processing workflows involved may prevent a proper communication of data provenance with full details for reproducibility. Therefore, a special effort was made in order to build a comprehensive provenance metadata model for the Interactive Atlas products.

Provenance frameworks are typically based on RDF (Resource Description Framework), a family of World Wide Web Consortium (W3C) specifications originally designed as a metadata model ( [[#Candan--2001|Candan et al., 2001]] ). It is an abstract model that has become a general method for conceptual description of information for the Web, using a variety of syntax notations and serialization formats. METACLIP ( [[#Bedia--2019|Bedia et al., 2019]] ) exploits RDF through specific vocabularies, written in the Web Ontology Language (OWL), describing different aspects involved in climate product generation, from the data source to the post-processing workflow, extending international standard vocabularies such as PROV-O ( [[#Moreau--2015|Moreau et al., 2015]] ). The METACLIP vocabularies are publicly available in the METACLIP repository (Bedia and Martin, 2021).

METACLIP emphasizes the delivery of ‘final products’ (understood as any piece of information that is stored in a file, such as a plot or a map) with a full semantic description of its origin and meaning attached. METACLIP ensures ‘machine readability’ through reuse of well-defined, standard metadata vocabularies, providing semantic interoperability and the possibility of developing database engines supporting advanced provenance analytics. Therefore, this framework has been adopted to generate provenance information and attach it as metadata to the products generated by the Interactive Atlas. A specific vocabulary (‘ipcc_terms’) is created alongside the inclusion of new products in the Interactive Atlas and uses the controlled vocabularies existing from CMIP and CORDEX experiments. As an example, Figure Atlas.10 shows the semantic vocabularies needed to encode the information of the typical workflow for computing (from bias-adjusted data) any of the climate indices (extreme or CIDs) included in the Interactive Atlas.

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[[File:21269b047c37dcec9b45d1d7a6944874 IPCC_AR6_WGI_Atlas_Figure_10.png]]

'''Figure Atlas.10''' '''|''' '''Schematic representation of theInteractive Atlas workflow, from database description, subsetting and data transformation to final graphical product generation (maps and plots).''' Product-dependent workflow steps are depicted with dashed borders. METACLIP specifically considers the different intermediate steps consisting of various data transformations, bias adjustment, climate index calculation and graphical product generation, providing a semantic description of each stage and the different elements involved. The different controlled vocabularies describing each stage are indicated by the colours, with gradients indicating several vocabularies involved, usually meaning that specific individual instances are defined in ‘ipcc_terms’ extending generic classes of ‘datasource’. These two vocabularies, dealing with the primary data sources have specific annotation properties linking their own features with the CMIP5, CMIP6 and CORDEX Data Reference Syntax, taking as reference their respective controlled vocabularies. All products generated by the Interactive Atlas provide a METACLIP provenance description, including a persistent link to a reproducible source code under version control.

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=== Atlas.2.4 Guidance for Users ===

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==== Atlas.2.4.1 Purpose of the Interactive Atlas ====

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The primary purpose of the IPCC is to provide a policy-relevant, non-prescriptive assessment of the state of knowledge on climate change and its impacts. This purpose is different from the provision of information targeted to implement climate policies, which is the focus of climate services and national climate change assessment communities. IPCC assessments are based on quantitative observational and model-generated data that are also used in many activities supporting the development of climate policies. However, the functionality of the Interactive Atlas is primarily aimed at supporting the knowledge assessment.

Much of the assessment in this report is based on multiple lines of evidence (Cross-Chapter Box 10.3). The Interactive Atlas facilitates combining multiple observational and model-generated datasets and spatial and temporal analyses that combine to support statements on the characteristics of the climate system. The use of predefined spatial and temporal aggregations imposes constraints on the ability to make specific or tailored assessments but does provide essential background and uncertainty information to generate broad findings and provide confidence statements on these. Also, the inclusion of a selection of extremes and climatic impact-drivers (CIDs) is a new element in the Interactive Atlas and facilitates broader application, including the handshake with WGII. Below, some guidelines on the use, interpretation and limitations of the Interactive Atlas are given.

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==== Atlas.2.4.2 Guidelines for the Interactive Atlas ====

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===== Atlas.2.4.2.1 Quantitative Support for Assessments =====

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Many assessment statements make use of evidence derived from observed changes, model projections, and process-oriented attribution of changes to human interventions. The Interactive Atlas shows a small subset of available observations that document climate change, namely surface air temperature and total precipitation (and thus not including observations of other atmospheric and Earth system components used as part of the evidence base for the report). Only datasets that have (near) global or large regional gridded spatial coverage and go back multiple decades are used. For each variable multiple datasets are included, but some of these have overlapping native ground-station observations and so are not independent ( [[#Atlas.1.4.1|Atlas.1.4.1]] ). The datasets show patterns of substantial spatial and temporal variability, and the empirical evidence of a non-stationary climatology needs to be filtered from this information. Issues with quality, representativity and mutual consistency lead to constraints on their use for attribution of causes of trends (see [[IPCC:Wg1:Chapter:Chapter-10#10.4.1.2|Section 10.4.1.2]] for examples). The practice of attributing trends and extreme events to human causes gives confidence that these trends are expected to continue in the (near) future, provided the human drivers of climate change remain unchanged. However, large internal variability at decadal time scales can be misinterpreted as an anthropogenic influence on the likelihood of extreme events, and in that case extrapolation of trends cannot be expected to be a reliable predictor for the future ( [[#Schiermeier--2018|Schiermeier, 2018]] ).

The Interactive Atlas gives access to a specific set of climate variables from a large number of climate model simulations, particularly the (global) CMIP5, CMIP6 and (regional) CORDEX archives. The global model outputs generally give a relatively coarse picture of climate change, which is an important line of evidence for the detection and attribution of climate change, but is rarely directly applicable for local climate change assessment or support of policy design ( [[#van%20den%20Hurk--2018|van den Hurk et al., 2018]] ). To provide additional detail, downscaling global projections with regional climate models (RCMs) or statistical downscaling can be undertaken but also adds a source of uncertainty as it involves additional modelling ( [[IPCC:Wg1:Chapter:Chapter-10#10.3|Section 10.3]] ).

The information displayed in the Interactive Atlas allows a number of sources of uncertainty to be quantified. ‘Observational uncertainty’ is represented by the use of multiple (albeit often not completely independent) observational datasets. ‘Uncertainty due to internal variability’ cannot be quantified directly since multiple realizations from historic and future projections are not accessible (the Interactive Atlas uses a single realization of each model). The use of a large collection of model systems allows for an elaborate quantification of ‘model uncertainty’. In addition, a comparison of CMIP5 and CMIP6 supports evidence of progress in model quality since AR5, while the evaluation of the added value of RCMs reveals model uncertainty related to spatial resolution ( [[IPCC:Wg1:Chapter:Chapter-10#10.3|Section 10.3]] ). Finally, the assessment of ‘scenario uncertainty’ is supported by the inclusion of multiple emissions scenarios for both CMIP5, CORDEX and CMIP6.

The communication of uncertainty has a profound influence on the perception of information that is exchanged during the communication process. An assessment of uncertainty communication and the barriers to climate information construction is given in [[IPCC:Wg1:Chapter:Chapter-10#10.5.4|Section 10.5.4]] .

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===== Atlas.2.4.2.2 Insights From Physical Understanding =====

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The detailed technical findings in IPCC reports also serve as an important benchmark resource for the research community. The Interactive Atlas complements the IPCC assessment report as a repository of scientific information on global and regional climate and its representation in coordinated model ensemble experiments. Regional climate is governed by a mixture of drivers, such as circulation patterns, seasonal monsoons, annual cycles of snow and regional land–atmosphere feedbacks. Global warming may affect regional climate characteristics by altering the dynamics of their drivers. The Interactive Atlas allows the comparison of different levels of global warming on specific regional climate features but is not designed for advanced analysis of the relationship between drivers and regional climate characteristics. For this, tailored analysis protocols need to be applied, such as the aggregation of climate change information from ensembles of regional climate projections, and stratification according to drivers of regional climate such as patterns of atmospheric circulation ( [[#Lenderink--2014|Lenderink et al., 2014]] ). The analysis of complex regional climate characteristics resulting from compound drivers also require additional expert knowledge and data processing ( [[#Thompson--2016|Thompson et al., 2016]] ). [[IPCC:Wg1:Chapter:Chapter-12#12.6.2|Section 12.6.2]] assesses various categories of climate services, including tailored analysis of regional climate processes.

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===== Atlas.2.4.2.3 Construction of Storylines =====

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Communicating the full extent of available information on future climate for a region, including a quantification of uncertainties, can act as a barrier to the uptake and use of such information ( [[#Lemos--2012|Lemos et al., 2012]] ; [[#Daron--2018|Daron et al., 2018]] ). To address the need to simplify and increase the relevance of information for specific contexts, recent studies have adopted narrative and storyline approaches (see Sections 1.4.4 and 10.5.3 for definitions and further discussion on these concepts; [[#Hazeleger--2015|Hazeleger et al., 2015]] ; [[#Shepherd--2018|Shepherd et al., 2018]] ). The use of region-specific climate storylines, including a role for local mechanisms, drivers and societal impacts generally requires detailed information that is typically not provided by the Interactive Atlas. However, background information and basic (scenario) assumptions can be derived from the Interactive Atlas which can be considered to provide an expert knowledge base from which to build targeted storylines and climate information.

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===== Atlas.2.4.2.4 Visual Information =====

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The visual communication of climate information can take many forms. Besides the standard visual products typically used for communicating global and regional climate information to practitioners (e.g., maps, time series or scatter plots), the Interactive Atlas incorporates new visuals, for example, ‘stripes’ ( [[#RMetS--2019|RMetS, 2019]] ), facilitating the communication of key messages (e.g., warming and consistency across models) to a less technical audience. The various tabular and graphical representation alternatives included as options in the Interactive Atlas (Figure Atlas.8) facilitate exploring the information interactively from different perspectives and in different levels of detail, thus favouring communication with the large and diverse audience of IPCC products.

To support the use of visuals provided in the Interactive Atlas for application to different audiences, new insights since AR5 have emerged from a range of scientific disciplines, including the cognitive and psychological sciences ( [[#Harold--2016|Harold et al., 2016]] ). Studies have used interviews and online surveys to assess interpretations of visuals used to communicate climate information and uncertainties ( [[#Daron--2015|Daron et al., 2015]] ; [[#Lorenz--2015|Lorenz et al., 2015]] ; [[#McMahon--2015|McMahon et al., 2015]] ; [[#Retchless--2016|Retchless and Brewer, 2016]] ). They commonly find wide-ranging interpretations and varied understandings of climate information amongst respondents due to the choice of visuals. In addition, [[#Taylor--2015|Taylor et al. (2015)]] found that preferences for a particular visualization approach do not always align with the approaches that achieve greatest accuracy in interpretation. Choosing appropriate visuals for a particular purpose and audience can be informed by testing and evaluation with target groups.

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===== Atlas.2.4.2.5 Dedicated Climate Change Assessment Programmes =====

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Communication aimed at informing the general public about assessed scientific findings on climate change have a different purpose and format than if intended to inform a specific target audience to support adaptation or mitigation policies ( [[#Whetton--2016|Whetton et al., 2016]] ). The growing societal engagement with climate change means IPCC reports are increasingly used directly by businesses, the financial sector, health practitioners, civil society, the media, and educators at all levels. The IPCC reports could effectively be considered a tiered set of products with information relevant to a range of audiences.

The Interactive Atlas does provide access to a collection of observational and modelling datasets, presented in a form that supports the distillation of information on observed and projected climate trends at the regional scale. Access to the repository of underlying datasets enables further processing for particular purposes. As noted above, it is not the intention nor the ambition of this IPCC assessment and the Interactive Atlas component to provide a climate service for supporting targeted policies. For this an increasing number of dedicated climate change assessment programmes have been carried out, aiming at mapping climate change information relevant for adaptation and mitigation decision support.

For instance, [[#EEA--2018|EEA (2018)]] provides an overview of European national climate change scenario programmes. Most of these use CMIP5 (or earlier) global climate change ensembles driven by an agreed set of greenhouse gas (GHG) emissions scenarios, followed by downscaling using RCMs and/or statistical methods, in order to generate regionally representative hydro-meteorological indicators of climate change. In some cases, output of selected downscaled global and regional models is provided to users ( [[#Whetton--2012|Whetton et al., 2012]] ; [[#Daron--2018|Daron et al., 2018]] ). Uptake by users is strongly dependent on providing justification of the selection or for the downscaling procedure and if further steps are needed to tailor the information to local scales ( [[#Lemos--2012|Lemos et al., 2012]] ). More comprehensive programmes provide probabilistic climate information by careful analysis and interpretation of ensembles of model outputs ( [[#Lowe--2018|Lowe et al., 2018]] ). The information is generally tailored to professional practitioners with expertise to interpret and process this probabilistic data. This top-down probabilistic information chain is not always able to highlight the essential climate change information for users, and alternative bottom-up approaches are encouraged ( [[#Frigg--2013|Frigg et al., 2013]] ). [[IPCC:Wg1:Chapter:Chapter-12#12.6.2|Section 12.6.2]] assesses climate services including the national climate assessments and user uptake.

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