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The selection of the dataset determines the dimensions of analysis available in the C3S Atlas (Figure 3b), which are different for observations/reanalysis and for climate projections.  For observational and reanalysis datasetsIn both cases, the C3S Atlas allows analyzing climatologies (or changes) and trends for a number of pre-defined periods (see Figure 4). In particular, the “climatology and changes” choice allows selecting a number of predefined reference historical periods: 1850-1900 (commonly used as a reference of pre-industrial conditions), 1961-1990, 1981-2010 and 1991-2020 (three 30-year periods recommended by WMO to define climate normals) and 1986-2005 and 1995-2014 (the 20-year common periods used in IPCC AR5 and AR6, respectively, to define modern climatic conditions). The choice menu allows selecting “climatology”, for aggregated values of the selected variable on the reference period (mean, minimum/maximum or accumulated values, depending on the particular variable), or “changes”, for differences between the values of the reference period and a selected baseline one (see Figure 4, top). The particular choice of climatology or change can be selected in the quantity selector.

The “Trends” choice allows selecting two periods (1950-2020 and 1991-2020) as references for analysing long-term and modern trends, respectively. In this case the only option of the quantity selector is “trend” (see Figure 4, bottom). 

“season” selector allows selecting the particular month or season of interest to display the variables/indices (note that they are originally defined with either monthly or annual aggregation, and the latter are not available for particular seasons; see the Atlas dataset documentation for full details). The aggregation of the monthly time series to obtain the seasonal/annual time series of interest is performed using the mean, with the exception of the extreme indices Minimum/Maximum of daily minimum temperature and Maximum of 1-day/5-day accumulated precipitation, which are aggregated using the corresponding minimum or maximum (i.e. seasonal/annual extremes are the extremes of the corresponding monthly values), and the "count" indices Days with maximum temperature above 35/40 ºC (both raw and bias adjusted) and frost days, which are aggregated using the sum (i.e. seasonal/annual counts are the sum of the monthly counts).

For observational and reanalysis datasets, the C3S Atlas allows analyzing climatologies (or changes) and trends for a number of pre-defined periods (see Figure 4). In particular, the “climatology and changes” choice allows selecting a number of predefined reference historical periods: 1850-1900 (commonly used as a reference of pre-industrial conditions), 1961-1990, 1981-2010 and 1991-2020 (three 30-year periods recommended by WMO to define climate normals) and 1986-2005 and 1995-2014 (the 20-year common periods used in IPCC AR5 and AR6, respectively, to define modern climatic conditions). The choice menu allows selecting “climatology”, for mean aggregated values of the monthly/seasonal/annual time series of the selected variable on the reference period or “changes”, for differences between the climatologies of the reference period and a selected baseline (see Figure 4, top). The particular choice of climatology or change can be selected in the quantity selector.

The “Trends” choice allows selecting two periods (1950-2020 and 1991-2020) as references for analysing long-term and modern trends of the monthly/seasonal/annual time series, respectively. In this case the only option of the quantity selector is “trend” (see Figure 4, bottom)In both cases, the products can be defined for particular months or seasons of interest (or annual) in the “season” selector. 

Figure 4. Dimensions of analysis for observational and reanalysis datasets (e.g. for ERA5 in this case) showing climatology (for the 1991-2020 period) and changes (for the 1991-2020 period, relative to 1961-1990; note that the solid red bar indicates the range between the reference and baseline) in the top, and trends (for the modern 1991-2020 period) in the bottom. Note that the inset maps are included only for illustrative purposes to visualize the climate products corresponding to the particular dimensions of analysis. These dimensions characterize recent historical changes and trends.

For the climate projection datasets, besides the historical periods which are common with observations and reanalysis, the “climatology and changes” dimensionallows exploring future periods (long-, medium- and long-term, defined as 2021-40, 2041-60 and 2081-2100, respectively) across different emission scenarios (RCPs or SSPs depending on the dataset), as illustrated in Figure 5 (top). The choice menu allows selecting “climatology” (left), for mean aggregated values of the selected variable on the reference period (mean, minimum/maximum or accumulated values, depending on the particular variable), or “changes” (right), for differences between the values of the reference period and a selected baseline one.

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A particular choice of the selection panel (variable, dataset, period and dimension of analysis) determines a climate product (e.g. mean temperature (°C) - CMIP6 - change - warming 2°C - annual - relative to 1850-1900, see Figure 1) which is graphically represented in the display panel in the form of a map. The map represents gridbox information for the full spatial extent of the dataset (global or regional, with different spatial resolutions, from 2º to 0.05º depending on the selected dataset; see the Atlas dataset documentation  for details). The map shows the temporally aggregated (using the mean , minimum/maximum or accumulated, depending on the variable) values for the reference period (or changes relative to a baseline) over the season of interest, and is dynamically updated when changing any choice in the selection panel; note that for projection datasets the map represents the ensemble mean values (individual information on the members of the ensemble is available only for regional products). 

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Besides the global map displaying spatial information, the C3S Atlas allows exploring exploring regionally aggregated information for a number of predefined regions, displayed in the “region set” selector (labeled as (1) in Figure 1); a single (or multiple) regions can be selected by clicking on the map (the button (2) allows selecting all the regions, e.g. to produce global averaged information for global datasets). Predefined regions include 1) the IPCC AR6 reference regions (used in the AR6 WGI report for regional climate change assessment), 2) the EUCRA regions (which are used in the European Climate Risk Assessment) and 3) European countries (including those countries covered by the regional European datasets: E-OBS and CORDEX-EUR). The regional information displayed by the C3S Atlas for these predefined regions is pre-computed and can be explored interactively by clicking in the “regional information” button at the bottom of the panel (see Figure 6), which is visible when a region is selected. 

The user can also select customized regions which can be defined using the “user defined” option in the regions selector. This option allows defining a new region by clicking on the “pencil” button and drawing a polygonal line. This creates an offline job which is executed by a queue system passing through different states (such as pending and running), until completion. Jobs are displayed at the bottom of the display panel as shown in Figure 6 (bottom) and regional products can be explored when the job is completed, clicking on the “eye” icon labeled as (1) in the figure.

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Figure 6. Display panel showing a global map for the default selection (mean temperature changes for 2º global warming) and the selection of (top) predefined and (bottom) customized regions. The panel on the top shows the predefined Mediterranean region selected (from the IPCC AR6 reference regions) with the button “regional information” to display the different graphical products for regional information. The bottom panel shows the definition of a customized region created over Iberia drawing a polygonal; in this case the option is first “create a job” to launch a job to compute the requested information. All jobs will be available from the “job” button appearing in the right toolbar of buttons; regional information would be displayed when clicking in the “eye” icon in the corresponding job in the list. 

Different aspects of regional information are displayed using different graphical products  (see Figure 7): 1) time series, 2) climate stripes, 3) annual cycle plots, and 4) seasonal climate stripes; all these graphical elements are dynamically updated when changing the choices in the selection panel.

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Figure 7. Different graphical products for regional information of mean temperature changes for 2º global warming: over the predefined IPCC AR6 Mediterranean region: time series, climate stripes, annual cycle plot, and seasonal climate stripes, from top to bottom. All graphical regional information products allow exporting the results in PDF and PNG formats, and also export (in CSV files) the underlying data (numbers). The inset in the bottom represents the map information, highlighting the selected region(s).

The time series panel displays the annual/seasonal values year by year, along the historical or historical and future climate periods. For observations/renalysis, the time-series panel displays the regionally aggregated annual/seasonal series. For climate projections, the time-series displays the regionally aggregated annual/seasonal series for the raw values or the changes (anomalies relative to the selected baseline in this case) for all the model simulations forming the ensemble, as well as the ensemble median. A gray shading indicates the particular period selected, as represented in the map; in the case of global warming levels, the shading area exhibits different grey shading intensities according to the overlaps of 20-year periods where the warming level is first reached by the different models (higher shade intensity indicates years with higher overlap). Detailed (percentile) information is provided by hovering the pointer over the individual lines. 

The climate stripes plot is inspired by the “warming stripes” graphics (introduced by Ed Hawkins, https://www.ShowYourStripes.info), which are simple and compelling visual representations of the change in temperature using a series of coloured stripes chronologically ordered; stripes reflect a minimalist style, conceived to use colour alone to avoid technical distractions when conveying information to non-scientists. Climate stripes are implemented in the C3S  Atlas using chronologically ordered vertical bars along the 1950-2100 period (spanning historical and projected simulations) to represent annual/seasonal raw values or changes (anomalies relative to the selected baseline in this case) of the selected variable and scenario. The stripes are divided vertically to represent each of the simulations/models (for climate projections) forming the ensemble (with the ensemble median at the top). Colors blue/brown to red/green indicate negative to positive changes (or minimum to maximum values).

Note that, for the sake of simplicity, this functionality is only available in the standard Robinson projection (the application switches the projection automatically when selecting this option). Similarly to the pre-defined regional values, the calculation of the regional mean is performed using the underlying data model (grids with regular lat-lon coordinates, that will be soon available from the CDS catalogue), applying a cosine latitude weighting.

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Figure 6. Display panel showing a global map for the default selection (mean temperature changes for 2º global warming) and the selection of (top) predefined and (bottom) customized regions. The panel on the top shows the predefined Mediterranean region selected (from the IPCC AR6 reference regions) with the button “regional information” to display the different graphical products for regional information. The bottom panel shows the definition of a customized region created over Iberia drawing a polygonal; in this case the option is first “create a job” to launch a job to compute the requested information. All jobs will be available from the “job” button appearing in the right toolbar of buttons; regional information would be displayed when clicking in the “eye” icon in the corresponding job in the list. The details of the job, including the machine-readable definition of the selected region (in WKT format) are available when clicking in the the "?" icon.

Different aspects of regional information are displayed using different graphical products (see Figure 7) building on the time series of the selected season computed  as described in Sec. 2.2 (season selector): 1) time series, 2) climate stripes, 3) annual cycle plots, and 4) seasonal climate stripes; all these graphical elements are dynamically updated when changing the choices in the selection panel.

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Figure 7. Different graphical products for regional information of mean temperature changes for 2º global warming: over the predefined IPCC AR6 Mediterranean region: time series, climate stripes, annual cycle plot, and seasonal climate stripes, from top to bottom. All graphical regional information products allow exporting the results in PDF and PNG formats, and also export (in CSV files) the underlying data (numbers). The inset in the bottom represents the map information, highlighting the selected region(s).

The time series panel displays the annual/seasonal values year by year, along the historical or historical and future climate periods. For observations/renalysis, the time-series panel displays the regionally aggregated annual/seasonal series. For climate projections, the time-series displays the regionally aggregated annual/seasonal series for the raw values or the changes (anomalies relative to the selected baseline in this case) for all the model simulations forming the ensemble, as well as the ensemble median. A gray shading indicates the particular period selected, as represented in the map; in the case of global warming levels, the shading area exhibits different grey shading intensities according to the overlaps of 20-year periods where the warming level is first reached by the different models (higher shade intensity indicates years with higher overlap). Detailed (percentile) information is provided by hovering the pointer over the individual lines. 

The climate stripes plot is inspired by the “warming stripes” graphics (introduced by Ed Hawkins, https://www.ShowYourStripes.info), which are simple and compelling visual representations of the change in temperature using a series of coloured stripes chronologically ordered; stripes reflect a minimalist style, conceived to use colour alone to avoid technical distractions when conveying information to non-scientists. Climate stripes are implemented in the C3S  Atlas using chronologically ordered vertical bars along the 1950-2100 period (spanning historical and projected simulations) to represent annual/seasonal raw values or The annual cycle plot displays the regionally aggregated monthly climatologies for the selected variable and period. For climate projections it displays the regionally aggregated monthly climatologies of the selected period for the raw values or the changes (anomalies relative to the selected baseline in this case) for all the simulations forming the ensemble, as well as the ensemble median. Detailed (percentile) information is provided by hovering the pointer over the individual months. 

The seasonal stripe plot is like the climate stripes panel but including monthly values vertically instead of model results, displaying results for the ensemble multi-model median.

Robustness and Uncertainty

The representation of robustness in the C3S Atlas is based on the same approaches used in the IPCC WGI AR6 report (Cross-Chapter Box Atlas.1). For observation/reanalysis trends, robustness is defined using the significance of the linear trends as obtained from standard hypothesis testing (and obscuring regions with non-significant trends using "x"). 

of the selected variable and scenario. The stripes are divided vertically to represent each of the simulations/models (for climate projections) forming the ensemble (with the ensemble median at the top). Colors blue/brown to red/green indicate negative to positive changes (or minimum to maximum values).

The annual cycle plot displays the regionally aggregated monthly climatologies for the selected variable and period. For climate projections it displays the regionally aggregated monthly climatologies of the selected period for the raw values or the changes (anomalies relative to the selected baseline in this case) for all the simulations forming the ensemble, as well as the ensemble median. Detailed (percentile) information is provided by hovering the pointer over the individual months. 

The seasonal stripe plot is like the climate stripes panel but including monthly values vertically instead of model results, displaying results for the ensemble multi-model median.

Robustness and Uncertainty

The representation of robustness in the C3S Atlas is based on the same approaches used in the IPCC WGI AR6 report (Cross-Chapter Box Atlas.1). For observation/reanalysis trends, robustness is defined using the significance of the linear trends as obtained from standard hypothesis testing (and obscuring regions with non-significant trends using "x"). 

For future climate changes, robustness is defined based on three categories: No overlay indicates that the change is robust and likely emerges from internal variability (at least 80% of the models agree on the sign of change and at least 66% of the models show a change greater than the internal-variability threshold); diagonal lines (\) For future climate changes, robustness is defined based on three categories: No overlay indicates that the change is robust and likely emerges from internal variability (at least 80% of the models agree on the sign of change and at least 66% of the models show a change greater than the internal-variability threshold); diagonal lines (\) indicate no change or no robust change (fewer than 66% of the models show change greater than the internal-variability threshold); crossed lines (X) indicate conflicting signals where at least 66% of the models show change greater than the internal-variability threshold but fewer than 80% of all models agree on the sign of change.

Note that robustness results are computed at a gridbox level and are not representative of regionally aggregated results over larger regions (less influenced by local variability). 

Application updates

The first version of the C3S Atlas was launched on 20 February 2024. Since then, the following periodic updates including different fixes (typos and not-substantial changes, improvements and errors/bugs) have been implemented in the different versions described below (in chronological order with new versions on the top).

not representative of regionally aggregated results over larger regions (less influenced by local variability). 

Application updates

The first version of the C3S Atlas was launched on 20 February 2024. Since then, the following periodic updates including different fixes (typos and not-substantial changes, improvements and errors/bugs) have been implemented in the different versions described below (in chronological order with new versions on the top).

Known-problems and update plans: We are working in the following known problems to include fixes in the coming versions:

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• Optimize layouts of exported PDF/PNG figures.
• Unavailable options (e.g. variables not available for a particular dataset) will been disabled (grayed out) instead of hiding them.

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