Issued by: CSIC and Predictia

Date: 15/02/2024

Service contract: 2022/C3S2_381_Contractor/SC1

Table of Contents

Introduction

The Copernicus Interactive Climate Atlas (referred to as C3S Atlas hereafter) is a web application of the Copernicus Climate Change Service (C3S) allowing for flexible temporal and spatial exploration and analysis of recent past trends and projected future changes for a wide range of key climate variables and for multiple datasets (commonly used as alternative lines of evidence for climate change assessment). 

The C3S Atlas is organized in three main panels (information, selection and display), as shown in Figure 1. The information panel (a) displays the information (title and full description) of the current selection. The selection panel (b) allows selecting the particular dataset, variable/index and dimension of analysis. The display panel (c) shows different interactive climatic products associated with the current selection, such as maps showing spatial information for the full geographical extent (as in Figure 1), or time series, stripes and other products displaying regional information for pre-defined (or customized) regions (not shown in the figure). In the following sections we describe these elements in detail.

Figure 1. Main screen of the C3S Atlas displaying the three main panels: (a) information, (b) selection and (c) display (note that the User Guide –this document– is available from the op right link). The default configuration displays an interactive map with the spatial information of the climate change signal (relative to the pre-industrial period 1850-1900) for mean temperature for a 2º global warming level obtained from the CMIP6 ensemble of global climate projections (labeled as “Mean temperature (°C) - CMIP6 - Change - Warming 2°C - Annual - rel. to 1850-1900” in the information panel).

The Information Panel

The information panel in Figure 1(a) displays the information (variable, dataset and dimension of analysis) for the current selection. This is used as the title of the corresponding graphical climate products displayed in panel (c). A full description with comprehensive information is provided by clicking on the "i" information button on the right side of the information panel. For instance, Figure 2 shows the information displayed for the default configuration of the C3S Atlas corresponding to “Mean temperature (°C) - CMIP6 - Change - Warming 2°C - Annual - rel. to 1850-1900”. The panel shows detailed information about the selected variable and dataset (the CMIP6 ensemble of global climate change projections in this case), as well as additional information on the different choices (global warming level, baseline periods, etc.).

Figure 2. Comprehensive description of the selected climate product available from the "i" information button on the right side of the information panel. This figure shows the information corresponding to the default selection displayed in Figure 1 (only the initial part is shown).

The Selection Panel

The selection panel includes the different choices required to define the climatic product of interest and is organized in three main modules, as shown in Figure 3: (a) selection of variable/index and dataset, (b) selection of the dimension of analysis and (c) palette of color and range of displayed values (including autofit/reset options to adapt/restore the ranges according to the current view).

The two main choices of the C3S Atlas are the particular variable/index and dataset of interest, and can be selected from the “choice” buttons in the top of the selection panel (Figure 3a, panels a.1 and a.2); note that the default choices are “mean temperature” and “CMIP6”. The C3S Atlas includes information for 30 variables and (extreme) indices organized in different categories (heat and cold, wet and dry, wind and radiation, snow and ice, ocean, and circulation) to simplify the selection (Figure 3a.1 illustrates the available indices filtered by the heat and cold category). These variables/indices are computed for a number of datasets from the C3S Climate Data Store (CDS) which are commonly used as complementary lines of evidence in climate change studies. In particular, the datasets are organized in three categories (panel 3a.2): Observations, reanalysis and climate projections; in particular E-OBS for gridded observations, ERA5 and ERA5-Land for global atmospheric and land reanalysis, ORAS5 for global ocean reanalysis, CMIP5 and CMIP6 for global climate projections, and CORDEX-EUR-11 and CORDEX-CORE for regional climate projections (see the Atlas dataset documentation for specific details on the variables and datasets available, as well as the harmonization and calculation of the underpinning dataset).

Figure 3. Elements of the selection panel of the C3S Atlas showing the particular choices of the default  configuration: (a) variable/index and dataset, (b) dimension of analysis and (c) palette of color and range of values displayed (including autofit/reset options to adapt/restore the ranges according to the current view). The variable and dataset selectors in panels (a.1) and (a.2) are illustrated in the right panels, the latter filtering for the particular category of heat and cold.

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 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 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). 

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” dimension allows 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 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.

An additional dimension of analysis is the policy-relevant “Global Warming Levels” (GWL) used extensively in the IPCC AR6 report. In particular the C3S Atlas allows selecting 1.5°, 2°, 3° and 4°, as shown in Figure 5 (bottom). Global warming levels have been computed following the methodology used in the IPCC AR6 WGI Atlas; in particular a single scenario (RCP8.5 or SSP5-8.5, depending on the datasets) was used to define the 20-year periods when models first reach the particular global warming levels (1.5°C, 2°C, 3°C and 4°C, relative to the pre-industrial 1850-1900 period). Note that similar GWL results are obtained for different scenarios (e.g. 2°C changes produced using SSP1-2.6 and SSP5-8.5; see AR6 WGI Cross-Chapter Box 11.1). 

Figure 5. Dimensions of analysis for projection datasets. The top panels correspond to the climatology (left) and changes (right) relative to 1850-1900 (right) of mean temperature corresponding to a long-term future period (2081-2100) for a high emissions SSP3-7.0 scenario. The panels in the bottom show the same information, but for a 2º global warming level. 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 future climate change from different dimensions of analysis (which allows visualizing the differences between the regional temperatures for the end of the century under a high emission scenario and for a 2º global warming).

Note also that for the climate projection datasets, some of the historical past periods (in particular the more recent periods) are not fully covered by the historical scenario data (e.g. the historical simulations for CMIP5/CORDEX and CMIP6 end in 2005 and 2014, respectively). A pragmatic approximation to deal with this issue is to use scenario data to fill the missing segments, for example for 2006–2020 use the first years of RCP8.5-driven transient projections, which are the most common scenarios available and in which the emissions are close to those observed (this approach is used, for instance, in the IPCC WGI AR6 Atlas chapter and Chapter 12).

Finally, the colorbar on the bottom (Figure 3c) is interactive and allows user-defined selection of color palettes and color ranges. The colors are displayed on a continuous scale and the minimum/maximum values can be adjusted by clicking and dragging the labels, or using the autofit tool. The box next to the colorbar shows the legend for the methods representing robustness/uncertainty (significance for observations/reanalysis trends, and robustness for model projection changes).

The Display Panel

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). 

Figure 1(c) shows the different controls available in the display panel (labeled with numbers). The tools button bar on the right allows to interact and modify the figure and export the content:  (3-4) zooming in (+) and out (-), (5) going back to the initial graphical configuration, (6) changing the projection (Robinson, Pacific-centric Robinson, stereographic North and South, and 3D globe); note that the 3D globe is computational demanding and is not available for some systems, (7) obtaining gridbox information (pin), (8) displaying or hiding robustness information, (9) exporting the graphics in PNG format, (10) exporting the underpinning data as GeoTIFF/NetCDF files (including both the signal and the robustness information), and (11) obtaining a permalink for referring to the particular configuration of the C3S Atlas (both the choices and the particular configuration of the graphic).

Besides the global map displaying spatial information, the C3S Atlas allows 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.

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.

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).

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 (\) 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). 

This document has been produced in the context of the Copernicus Climate Change Service (C3S).

The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation Agreement signed on 11/11/2014 and Contribution Agreement signed on 22/07/2021). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose.

The users thereof use the information at their sole risk and liability. For the avoidance of all doubt , the European Commission and the European Centre for Medium - Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view

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