Guideline for Online IPCC Interactive Atlas

Information about the IPCC Sixth Assessment Report (AR6) Interactive Atlas

Content

The guideline for the online IPCC Interactive Atlas consists of a Part 1 and 2. The Sixth IPCC Assessment Report (AR6) Working Group 1 (WG1) introduces a new product – The Interactive Atlas. The Interactive Atlas takes advantage of interactive web applications to allow flexible exploration of key climate variables and products underpinning the IPCC assessments.

The purpose of this guideline is to demonstrate and familiarize users with the Interactive Atlas and its functionalities. Part 1 is a brief introduction of the interface, datasets and variables that are included in the Interactive Atlas. Part 2 provides examples from the Atlas through figures and screenshots that represent the many options for customising data and data visualisation for different users.

A detailed description of the Interactive Atlas can be found here: www.ipcc.ch. The Interactive Atlas can be consulted online at: https://interactive-atlas.ipcc.ch

PART 1: from page 3-16 PART 2: from page 17-28 1. Introduction 1. Introduction 2. Interactive Atlas 2. Examples 3. Regional Information Example 1: Global and Regional Temperatures 3.1 Spatial and temporal analysis Example 2: Temperatures CMIP6 and CMIP5 Example 3: Stereographic plot of CORDEX data 3.2 Functionalities, datasets, and Example 4: Sea Surface Temperature change variables Example 5: Global and Regional Precipitation 3.3 Reproducibility Example 6: Seasonal and extreme Precipitation Example 7: Spatial and Temporal Snowfall 4. Regional Synthesis Example 8: Regional Sea Ice Concentration 4.1 Climate Impact Drivers Example 9: Regional Sea Level Change 5. References Example 10: Climatic Impact-Drivers

Miljødirektoratet IPCC Focal Point Norway Grensesvingen 7, 0661 Oslo, Norway

Consultency work is performed by IPCC AR6 Lead Author Professor Sebastian H. Mernild, affiliated with Southern Danish University, Denmark, The Nansen Center and University of Bergen, Norway, on behalf of Miljødirektoratet.

M- 3000 I 2021

PART 1: General information about the IPCC AR6 WG1 Interactive Atlas

1. Introduction The primary purpose of the IPCC (Intergovernmental Panel on Climate Change) is to provide a policy relevant, non-prescriptive assessment of the state of knowledge on climate change and its impacts. IPCC assessments are based on quantitative observational and model-generated data used in activities supporting the development of climate policies.

The Interactive Atlas enables multiple observational and model-generated datasets and spatial and temporal analyses to be combined. This information supports statements on the characteristics of the climate system, here illustrated in the Interactive Atlas through regional information and regional synthesis.

The functionality of the Interactive Atlas is aimed at supporting the knowledge assessment and provides an expert knowledge base from which to build targeted storylines and climate messages.

2. Interactive Atlas

The Interactive Atlas enables multiple observational and model-generated datasets and spatial and temporal analyses to be combined to support statements on the characteristics of the climate system, here illustrated through regional information and regional synthesis (See Figure 1).

The Interactive Atlas builds on open tools and therefore is an important step towards making IPCC assessments more reproducible and reusable.

The Interactive Atlas under Regional Information and Regional Synthesis provides an online region- by-region assessment in time and space of new knowledge on changes in climate variables. It demonstrates the diversity in these changes across defined regions (see Figure 2), in the evidence base for generating information on what changes have already occurred (based on observations), and what further changes each region is likely to face (based on simulations) in the future based on different emission scenarios.

Front cover for the Interactive Atlas. Highlighting the different tools: Regional Information, Regional Synthesis, and Documentation besides a globe illustrating for example the expected regional warming at different global warming levels.

Figure 1: Regional Information includes the ability to generate maps and aggregated products i.e., time series, scatter plots, tables, climate stripes, etc. for observed and projected climate change for time periods, emissions scenarios or global warming levels. The regional synthesis provides qualitative information about changes in climatic impact-drivers (CIDs) in several categories such as heat and cold, wet and dry, or coastal and oceanic. Documentation provides additional information regarding the Interactive Atlas.

The growing societal engagement with climate change means that IPCC reports are increasingly used directly by civil society, businesses, industries, the financial sector, health practitioners, the media, and educators at all levels. The Interactive Atlas should effectively be considered a tiered set of products with information relevant to a range of audiences.

3. Regional Information

3.1 Spatial and temporal analysis

The Interactive Atlas allows for flexible spatial and temporal analysis with a predefined granularity (predefined climatological and typological regions and user-defined seasons) through a wide range of temporal and spatial maps, graphs, scatter plots (e.g., temperature vs. precipitation), and tables generated in an interactive manner building on a collection of global and regional observational datasets and climate models including available future emissions scenarios. This allows for a comprehensive analysis – and intercomparison, particularly using Global Warming Levels as a dimension of integration – of the different datasets at a global and regional scale (see Figure 3). As an example, the Interactive Atlas provides: 1) ranges of observations of mean precipitation and air temperature change and trends for the period 1980–2014 (see Box 1); and 2) and ranges of regional mean precipitation change and ranges of regional warming change for different global warming levels of 1.5ºC, 2ºC, 3ºC, and 4ºC based on available emissions scenarios from different climate models CMIP5, CMIP6, and CORDEX (see Box 2). The global warming levels are expressed as changes in global mean temperature relative to the 1850–1900 period.

Figure 2: Screenshots from the Interactive Atlas. (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 SSP3-7.0 for the long-term 2081–2100 period relative to 1995–2014). (b–e) Various visuals and summary tables for the regionally averaged information for the selected reference regions. The visual communication of climate information can take many forms. The Interactive Atlas incorporates new visuals, for example ‘stripes’ (Royal Meteorological Society, 2019), facilitating the communication of key messages e.g., warming and consistency across models.

Box 1: Observations used in the Interactive Atlas. The Interactive Atlas provides trends and changes for observations – surface air temperature and precipitation – in the form of interactive maps for a predefined historical period 1980–2014. Specifically, for air temperature the Interactive Atlas uses output from three gridded global temperature datasets: 1) Climatic Research Unit CRU TS4.0 (version 4.03), 2) Berkeley surface temperature dataset (BEST, here referred to as BERKELEY), 3) EWEMBI (EartH2Observe, WFDEI and ERA-Interim data Merged and Bias-adjusted for ISIMIP), and two gridded global precipitation datasets: 1) Global Precipitation Climatology Centre (GPCC, v2018), and 2) Global Precipitation Climatology Project (GPCP; monthly version 2.3). Although the ultimate source of these datasets is surface station reported values (GPCP also includes satellite information), each has access to different numbers of stations and lengths of records.

Figure 3: The different regions, both land and ocean regions, used as the standard for the regional analysis of atmospheric variables in the Interactive Atlas.

Box 2: Explanation of CMIP5, CORDEX and CMIP6 climate models and scenarios.

For further information see chapter 1 in the IPCC AR6 WG1 report: https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Chapter_01.pdf pdf

CMIP5: A set of coordinated climate model experiments: These experiments comprise the fifth phase of the Coupled Model Intercomparison Project (CMIP5) using different Representative Concentration Pathway (RCP). A Representative Concentration Pathway is a greenhouse gas concentration (not emissions) trajectory. The pathways describe different climate futures, all of which are considered possible depending on the volume of greenhouse gases (GHG) emitted. The different Representative Concentration Pathways – RCP2.6, RCP4.5, RCP6, and RCP8.5 – are labelled after a possible range of radiative forcing values in the year 2100 (2.6, 4.5, 6.0, and 8.5 W/m2, respectively). For further information regarding the RCP’s see https://cicero.oslo.no/en/posts/news/a-guide-to-representative-concentration- pathways.

CORDEX: Coordinated Regional Climate Downscaling Experiment is a framework to evaluate regional climate model performance through a set of experiments aiming at producing regional climate projections. In CORDEX the different Representative Concentration Pathways – RCP2.6, RCP4.5, RCP6, and RCP8.5 – are used.

CMIP6: These experiments comprise the sixth phase of the Coupled Model Intercomparison Project (CMIP6). In the lead up to the IPCC AR6, the climate modelling community has developed a new set of emissions scenarios driven by different socioeconomic assumptions: these are the “Shared Socioeconomic Pathways” (SSPs). A number of these SSP scenarios have been selected to drive climate models for CMIP6. These updated scenarios are called SSP1-2.6, SSP2-4.5, SSP4-6.0, and SSP5-8.5, each of which result in similar 2100 radiative forcing levels as their predecessor in AR5. For further information see: https://www.carbonbrief.org/explainer-how-shared-socioeconomic-pathways-explore-future- climate-change

Regionally aggregated information can be obtained interactively from one or several regions on the map (Figures 3 and 4) and by selecting one of the several options available for visuals e.g., time series, annual-cycle plots, scatter and stripe plots and tables based on different datasets (Figure 5). The use of predefined spatial and temporal aggregations in the Interactive Atlas imposes constraints on the ability to make specific or tailored assessments. However, it provides essential background and uncertainty information to generate broad assessments and provide confidence statements.

Full metadata are provided in the Interactive Atlas for each of the products, and the scripts used (based on the climate4R open-source framework) to generate the intermediated products and figures are available online in a public repository (Atlas GitHub, 2020).

A detailed description of the Interactive Atlas can be found here: www.ipcc.ch. The Interactive Atlas can be consulted online at: https://interactive-atlas.ipcc.ch/. The Interactive Atlas does provide access to a collection of observational and modelling datasets, presented in a form that supports the distillation of messages on observed and projected climate trends at the regional scale. Access to the repository of underlying datasets enables further processing for particular purposes, however, 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.

The Interactive Atlas implements FAIR principles promoting open science and Findability, Accessibility, Interoperability, and Reuse (FAIR) principles (Wilkinson et al. 2016).

Figure 4: Interactive Atlas front cover page of the Regional Information with explanation of the different tool bottoms: (upper left) choose different sets of regions over which to aggregate data and display information on significance of observed trends, or uncertainty information for projections, and (lower left) legend; and (right) zoon in and out on the map; select between different map projections: Robinson, Stereographic North and South; select all regions; show metadata; download figures as GeoTIFF or PNG and share on Facebook, Twitter, and review codes; highlight information at a specific location; duplicate map; and full screen.

Figure 5: An illustration of the different dataset available in the Interactive Atlas: Model projections, model historical data, observations, and paleoclimate.

3.2 Functionalities, datasets, and variables

The Interactive Atlas allows for analysing global and regional information for past trends and future climate changes through a wide range of functionalities (see Figure 4). This includes maps, graphs and tables generated in an interactive manner and building on six basic products:

1. Global maps for time-slices across different scenarios and Global Warming Levels. 2. Temporal series, displaying all individual ensemble members and the multi-model mean, 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 Global Warming Level (defined for a given model as the first 20-year period where the average surface temperature in that model reaches the Global Warming Level relative to its 1850–1900 temperature). 3. Annual cycle plots representing individual models, the multi-model mean and ranges across the ensemble. 4. Stripe and seasonal stripe plots, providing visual information on changes across the

ensemble and across seasons, respectively. 5. Two-variable scatter plots (e.g., temperature versus precipitation). 6. Tables with summary information.

The Interactive Atlas provides trend analyses for two baseline periods (1961–2015 and 1980–2015, selected according to data availability). Further, 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 scenarios for both CMIP5 and CORDEX and for different variables (see Figures 5–7). 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, or for different Global Warming Levels 1.5°C, 2°C, 3°C, or 4°C, with changes relative to a number of baselines 1850–1900 (pre-industrial; baseline used in the calculation of global warming levels), and 1995–2014 (recent past; AR6 20-year baseline) (see Figure 7). Note, that instead of blending the information from the different scenarios, the Interactive Atlas allows comparison of the Global Warming Level spatial patterns and timings across the different scenarios.

Figure 6: An illustration of the different variables (mean change and trends) available in the Interactive Atlas: Atmosphere variables, Ocean variables, and Socio-economic variables (Drivers).

Figure 7: An illustration of the different time periods (Near Term: 2021–2040, Medium Term 2041–2060, and Long Term 2081–2100) and global warming levels (1,5°C, 2,0°C, 3,0°C, and 4,0°C), SSP scenarios, baseline periods (AR5: 1986–2005, AR6: 1995–2014, preindustrial (1850– 1900), WMO: 1961–2010 and 1981–2010) available in the Interactive Atlas.

The Interactive Atlas includes specific variables (see Figure 6) and both atmospheric (for example daily mean, minimum and maximum temperatures, precipitation, snowfall, and wind) and oceanic (for example sea surface temperature, sea level rise, oxygen, and pH), and drivers (socio-economic variables), and for different seasons (see Figure 8). Below is a list of examples of variables, where the last five variables from the atmospheric group refer to particular regions:

Atmosphere: • Mean temperature (T) • Minimum Temperature (TN) • Maximum Temperature (TX) • Maximum of maximum temperatures (TXx: annual maximum daily maximum temperature) • Minimum of minimum temperatures (TNn: annual minimum daily minimum temperature) • Total precipitation (PR) • Snowfall

• Surface wind • Maximum 1-day precipitation (RX1day: annual maximum precipitation amount in a day) • Maximum 5-day precipitation (RX5day: annual maximum five-day precipitation) • Consecutive Dry Days (CDD: mean number of dry days) • Standardized Precipitation Index (SPI) • Frost days (FD) • Heating Degree Days (HD) • Cooling Degree Days (CD) • Days with maximum temperature above 35°C (TX35) • Days with maximum temperature above 40°C (TX40)

Ocean: • Sea Surface Temperature (SST) • pH at surface (pH) • Sea level rise (SLR) • Sea ice concentration

3.3 Reproducibility

All final products visualized in the Interactive Atlas can be exported in a variety of formats, including PNG image files and PDF if including vector information. Moreover, in the case of the global maps, the final data underlying these products can be downloaded in 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-Data Distributing Center (DCC) under a more flexible license which facilitates reusability.

Figure 8: An illustration of the different seasons available in the Interactive Atlas: Annual, December to February, March to May, June to August, September to November, and Customized seasons.

4. Regional Synthesis

4.1. Climate Impact Drives

Also, in the Interactive Atlas Climate Impact Drivers (CID) are illustrated on regional scale (Figure 9). The displayed hexagons can be set up to six CIDs summarized on a quasi-geographical representation of the reference regions. This nice representation combines synthesis information for trends and projections in a single view. The information presented on regional observations is where there is evidence for increasing or decreasing trends and if there is additional evidence on attribution of these trends. The information presented on projected regional climate changes is where there is evidence for increases or decreases at either high, medium, or low confidence.

Figure 9: Interactive Atlas front cover page of the Regional Synthesis combining different parameters with Climate Impact Drivers. Here, illustrated specifically in the hexagon diagram is the mean air temperature, mean precipitation, and mean wind speed.

5. References Atlas GitHub (2020). Atlas GitHub. doi:10.5281/zenodo.3595626.

Royal Meteorological Society (2019). Warming Stripes show the changing climate across the globe. Available at: https://www.rmets.org/news/warming-stripes-show-changing-climate-across-globe [Accessed December 19, 2019].

Wilkinson, M. D., Dumontier, M., Aalbersberg, Ij. J., Appleton, G., Axton, M., Baak, A., et al. (2016). The 19 FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3, 160018. 20 doi:10.1038/sdata.2016.18.

Part 2: Guideline for IPCC Interactive Atlas – examples of functionalities and visualizations

1. Introduction

Here, in Part 2 of the guidelines several examples of the functionalities and visualizations of the Interactive Atlas are presented. It provides examples on specific parameters relevant e.g., on global scale, for Northern Europe, and the Arctic region visualized in different ways. The first nine examples are related to topics regarding ‘Regional Information’, where the last example is related to ‘Regional Synthesis’. Front cover for the Interactive Atlas. Highlighting the different tools: Regional Information, Regional Synthesis, and Documentation besides a globe illustrating for example the expected regional warming at different global warming levels.

Example 1: Global and Regional Temperatures Figures 2a-b illustrate the spatial distribution of mean annual and seasonal (December to February) temperatures. They emphasize a distinct difference between polar regions, equatorial regions, and high mountain regions, including on seasonal scale.

Figure 2a: CMIP6 mean annual temperature (1995–2014). Below the globe a specific description of the Interactive Atlas setup is shown. Here, CMIP6 – Mean Temperature (T) deg C- AR6 (1995- 2014) Historical Annual (mean of 35 models).

Figure 2b: CMIP6 mean seasonal temperature December to February (1995–2014).

Example 2: Difference in CMIP6 and CMIP5 temperatures This example illustrates a dual plot of the spatial distribution of the mean annual temperature based on CMIP6 and CMIP5 simulations. Point information (grid cell information) of the capital of Oslo is highlighted to emphasize the difference between CMIP6 and CMIP5 (Figure 3a). Further, Figure 3b illustrates a dual plot of the annual (left) and seasonal (December to February) (right) maximum temperature change (point information for Longyearbyen is highlighted).

Figure 3a: Dual plot of the CMIP6 mean annual temperature (1995–2014) (left), and CMIP5 (right). Point information is shown as example for the capital of Oslo.

Figure 3b: Dual plot of the CMIP6 annual (left) and seasonal (December to February; right) maximum temperature change (1981–2010). Point information is shown near the city of Longyearbyen on Svalbard. The shaded areas e.g., Southeast of Greenland are due to low model agreement.

Example 3: Stereographic plot of CORDEX data

This example illustrates a dual plot of the spatial distribution of ‘CORDEX Arctic’ mean annual temperature both at a 1.5 global warming level (left) and a 3.0 global warming level (right). Here, illustrated as a stereographic plot, where point information is shown for a location in Northwest Svalbard (Figure 4a). Figure 4b illustrates a time series of the 3.0 global warming level for the entire Arctic region.

Figure 4a: Stereographic dual plot of CORDEX Arctic mean temperature change at a 1.5 global warming level (left) and a 3.0 global warming level (right). Point information is shown for a location in Northwest Svalbard.

Figure 4b: Stereographic plot of CORDEX Arctic mean temperature change at a 3.0 global warming level including the time series specifically for the Arctic region. The Arctic region is highlighted on the stereographic map (see shaded color).

Example 4: CMIP6 Sea Surface Temperature change

This example illustrates the CMIP6 Sea Surface Temperature (SST) change. Here, illustrated based on the SSP5 8.5 scenario towards 2081–2100, using 1981–2010 as baseline (Figure 5a). On Figure 5b the SST simulations are, however, highlighted only for the interval between 3.5–4.0 degree (intervals are selected by clicking on the temperature legend).

Figure 5a: CMIP6 Sea Surface Temperature (SST) change.

Figure 5b: CMIP6 Sea Surface Temperature (SST) change highlighted for the interval 3.5–4.0 degree.

Example 5: Global and Regional Precipitation This example illustrates the CMIP6 spatial distribution of total annual precipitation (mm/day) including locations of major river basins (Figure 6a). Figure 6b is a snapshot of Northern Europe and the North Atlantic region, highlighting the interval between 4.0–5.0 mm/day. This indicates that both Western Norway and Southeast Greenland are rain rich regions.

Figure 6a: CMIP6 total annual precipitation (mm/day) (1995–2014), including as an example locations of major river basins.

Figure 6b: Northern Europe and North Atlantic CMIP6 total annual precipitation (mm/day) (1995–2014), including locations of major river basins. Highlighted is the interval between 4.0–5.0 mm/day.

Example 6: Seasonal and extreme variabilities in Precipitation This example illustrates a dual plot of the spatial distribution of CMIP6 total precipitation from June to August (left) and from December to February (right) for Northern Europe and North Atlantic for the period 1995–2014. Higher precipitation values occur e.g., for Western Norway (Figure 7a). Figure 7b illustrates the maximum 1-day precipitation (annual maximum precipitation amount in a day) (left), and the maximum 5-day precipitation (annual maximum five-day precipitation) (right).

Figure 7a: Dual plot Northern Europe CMIP6 total precipitation (mm/day) (1995–2014) for June to August (left), and December to February (right).

Figure 7b: Dual plot Northern Europe CMIP6 maximum 1-day precipitation (annual maximum precipitation amount in a day) (1995–2014) (left), and maximum 5-day precipitation (annual maximum five-day precipitation) (right).

Example 7: Spatial and Temporal Variability in Snowfall This example illustrates the CMIP6 spatial distribution of snowfall (mm/day) for the customized period November to March (Figure 8a) indicating most snowfall in the Arctic and high mountain regions on the Northern Hemisphere (Figure 8a). Figure 8b is a zoom showing Northern Europe and the North Atlantic region, showing most snowfall in Southeast Greenland and Western Norway. Further, for the region Northern Europe a time series is illustrated together with a point information for Western Norway.

Figure 8a: CMIP6 Snowfall (mm/day) (1995–2014) for the customized period November to March.

Figure 8b: CMIP6 Snowfall (mm/day) (1995–2014) for the customized period November to March. Including time series for the region Northern Europe and point information for Central Western Norway.

Example 8: Regional Sea Ice Concentration

This example illustrates a dual plot of the spatial distribution of CMIP6 spatial distribution of Sea Ice Concentration (%) for March (end-of-winter) (left) and September (end-of-summer) (right) (Figure 9). The figure illustrates that sea ice concentration and extent is lower in September compared to March.

Figure 9: CMIP6 Sea Ice Concentration (%) (1995–2014) for March (left), and September (right).

Example 9: Regional Sea Level Change

This example illustrates CMIP6 Sea Level Rise (SLR) changes. Here, illustrated for the majority of the Northern Hemisphere based on the SSP5 8.5 scenario towards 2081–2100, using 1981–2010 as baseline (Figure 10). A relative drop in SLR will occur e.g., around Svalbard and Northern Greenland. This is because the gravitational attraction that the ice sheet exerts on the surrounding water diminishes as the ice melts. Consequently, water migrates away from the ice sheet. For example, along the east coast of US and Canada an increase in sea level will take place. Further, as the ice sheet melts further, the land underneath the ice sheet pops up; it rebounds.

Figure 10: CMIP6 Sea Level Rise (SLR) (meter). Here, illustrated based on SSP5-8.5 towards 2081–2100, using 1981–2010 as baseline.

Example 10: Climatic Impact-Drivers

This example illustrates Climatic Impact-Drivers on regional scale (on Figures 11a-b each region is illustrated by a hexagon). Here, different parameters can be combined to illustrate e.g., confidence level and trends (Figures 11a-b). As an example, Figure 11a plots mean air temperature with mean precipitation, and Figure 11b plots extreme heat with heavy precipitation events . Figure 11c illustrates heavy precipitation in map view showing level of confidence of increase or decrease.

Figure 11a: Mean air temperature plotted together with mean precipitation.

Figure 11b: Extreme heat plotted together with heavy precipitation.

Figure 11c: Heavy precipitation plotted in map view showing level of confidence of increase or decrease.