The future change information behind the 'Human dynamics of climate change' poster

Global projections of temperature change

The information below gives more detail about the projections used to create the map, and links to find out more.

A detailed technical summary of the future projections used in the 'Human dynamics of climate change' poster is available for download, along with the poster itself and supplementary information, to the right of this page. The technical report explains more of the science behind the data and the process of creating the poster.

The 'Human dynamics of climate change' poster shows future projections of a number of climate variables. The climate models used in these projections are a sub-set of the Global Climate Models (GCMs) used in the Intergovernmental Panel on Climate Change Fifth Assessment Report ( IPCC AR5). These are: HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, GFDL-ESM2M and NorESM1-M. The climate impacts models have been driven by all, or a selection of, these five GCMs and are those included in the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) database (coordinated by the Potsdam Institute for Climate Impact Research); also used in the IPCC AR5 reports. The use of ISI-MIP data ensures consistency across the sectors through common background scenarios and driving GCM data, and allows a systematic approach in order to build a coherent picture of the future climate.

An ensemble of multiple GCMs is used to give an indication of the uncertainty in climate model projections, but because only a limited sub-set of the total range available is applied in this study, the full range of uncertainty for all available models may be larger than the results shown here indicate. The impacts models add further uncertainty, and this is reflected in the range of results from across the models; for some impacts model projections disagree on even the direction (increase or decrease) of change.

The data is displayed on the poster as scaled icons, and in some cases the spatial pattern of change is also shown on the map behind; this is the mean change across the ensemble of models. The icons indicate the average impact across climatological regions, so that each of the impacts layers can be compared for consistent regions. The size of the icon is determined by the median value across the model ensemble for each region, and the tables included in the supplementary information contain these median values and the interquartile range for each impact shown. You can download  the supplementary in the panel to the right of this page.

The projections show change for the end of the 21st century (2071-2100), with respect to a present-day baseline (1981-2010), under a 'business as usual' greenhouse gas concentration scenario (RCP8.5) and a 'middle of the road' socio-economic scenario (SSP2) for population change. Individual impacts studies occasionally use slightly different years for the baseline and future periods (for example the crop yield projections shown here use a baseline of 1980-2010, and 2070-2099 for the future period), but these differences have little impact on the results. You can find more detail in the technical report PDF in the panel to the right of this page.

All the impacts are generated from published work. A short description of each of the impacts layers, along with links to the original paper, is included below. More detail on the projections is available in the technical report, along with data from an alternative 'aggressive mitigation' greenhouse gas concentration scenario (RCP2.6).

Water run-off

Water run-off is the surface and sub-surface water running into rivers. This is the water available for use from precipitation, taking into account losses due to evaporation. The water run-off projections come from Davie et al. (2013) and show the percentage change in water run-off. The data is shown as regionally averaged scaled icons, with the spatial pattern on the map for more detail. See the technical report in the panel to the right of this page for maps of this data and the icon values and ranges, for both 'business as usual' (RCP8.5) and 'aggressive mitigation' (RCP2.6) greenhouse gas concentration scenarios.

Water demand for irrigation

Water demand for irrigation is a measure of the amount of water crops need to fully meet their water requirements as a result of the warmer climate. The water demand for irrigation projections come from Wada et al. (2013) and show the percentage change in water demand for irrigation. There is a low representation of CO2 fertilisation (20 of the 25 models used in the study do not include CO2 fertilisation), and the effects of population growth are not included. The data is shown as regionally averaged scaled icons, with the spatial pattern on the map for more detail. See the technical report in the panel to the right of this page for maps of this data and the icon values and ranges, for both 'business as usual' (RCP8.5) and 'aggressive mitigation' (RCP2.6) greenhouse gas concentration scenarios.

Crop yield

The crop yield projections combine results from Rosenzweig et al. (2013) of change in average yield for rainfed crops over present-day rainfed land, with similar projections for irrigated crops over present-day irrigated land, where irrigated crops are assumed to be supplied with sufficient water. The median percentage change in average yield across the model runs for wheat, maize, rice and soybean is shown as scaled regional icons, for larger producing regions of each crop (regions that produce more than 1% of the present-day (year 2000) global total). See the technical report in the panel to the right of this page for maps of this data and the icon values and ranges, for both 'business as usual' (RCP8.5) and 'aggressive mitigation' (RCP2.6) greenhouse gas concentration scenarios.

Drought

The drought projections come from Prudhomme et al. (2013) and show the percentage change in the number of days in drought conditions. Drought conditions are here defined as days when the daily run-off is less than the 10th percentile of the daily run-off that occurs in the baseline period (1976-2005) for that day. The data is shown as regionally averaged scaled icons with the spatial pattern on the map for more detail. See the technical report in the panel to the right of this page for maps of this data and the icon values and ranges, for both 'business as usual' (RCP8.5) and 'aggressive mitigation'  (RCP2.6) greenhouse gas concentration scenarios.

Temperature of warmest days

The data on the change in temperature of the warmest days of the year shows the projected change in the 95th percentile of daily maximum temperature (the temperature reached or exceeded only 5% of the time). These values were calculated directly from the ensemble of projections from the five Global Climate Models (GCMs) used to generate the other impacts on the map, specifically for inclusion on it. For the projected change in the temperature of the warmest days, only the scaled icons are shown, as the background map already displays the spatial pattern of change in drought. See the technical report in the panel to the right of this page for maps of this data and the icon values and ranges, for both 'business as usual' (RCP8.5) and 'aggressive mitigation' (RCP2.6) greenhouse gas concentration scenarios.

Flood hazard

The inland flooding projections come from Dankers et al. (2013) and show the change in frequency of a 1-in-30 year flood event. The flood icons on the map show the area within a region that is projected to increase or decrease in flood frequency (only the strongest signal is shown), while the background spatial pattern shows the level of confidence in the model runs in this change (increase or decrease). See the technical report in the panel to the right of this page for maps of this data and the icon values and ranges, for both 'business as usual' (RCP8.5) and 'aggressive mitigation' (RCP2.6).

Coastal flooding

The coastal flooding projections come from Hinkel et al. (2014) and show the annual number of people flooded per year due to sea level rise per country. This assumes the level of population change in the 'middle of the road' socio-economic scenario (SSP2), with no additional adaptation to the changes, under a 'medium' ice melting scenario of sea level rise (see methods in Hinkel et al. (2014) for details of these assumptions). The 'medium' ice melting scenario projects sea levels to rise by 78cm in 2100 with respect to a 1985-2005 baseline, with a range of 65cm - 117cm from the 'low' and 'high' ice melting scenarios respectively. Icons are shown on the map for the top ten countries with the highest absolute number of people flooded per year, and the top ten countries with the highest number of people flooded per year relative to the projected population. See the technical report in the panel to the right of this page for tables of the data used to compute the icons, along with alternative 'high' and 'low' ice melting scenarios, for both 'business as usual' (RCP 8.5) and 'aggressive mitigation' (RCP 2.6) greenhouse gas concentration scenarios, and the difference that adaptation can make in considerably reducing the number of people flooded.

Sea surface temperature

As with the change in temperature of the warmest days, the change in sea surface temperature data was also calculated for this map from the driving Global Climate Model (GCM) data. The projections show the change in the sea surface temperature, and are displayed on the map as the spatial pattern of change over the sea, and also as scaled icons averaged over fishing regions, so that the values directly relate to the fish catch values in those regions. See the technical report in the panel to the right of this page for maps of this data and the icon values and ranges, for both 'business as usual' (RCP8.5) and 'aggressive mitigation' (RCP2.6) greenhouse gas concentration scenarios.

Population change

The population change data shows the change in population between 2010 and 2085, as a percentage of the 2010 population levels. These changes are calculated from the population data in the 'middle of the road' socio-economic scenario (SSP2), used throughout the poster.

References

Dankers, R., Arnell, N. W., Clark, D. B., Falloon, P. D., Fekete, B. M., Gosling, S. N., Heinke, J., Kim, H., Masaki, Y., Satoh, Y., Stacke, T., Wada, Y. and Wisser, Dankers, R., Arnell, N. W., Clark, D. B., Falloon, P. D., Fekete, B. M., Gosling, S. N., Heinke, J., Kim, H., Masaki, Y., Satoh, Y., Stacke, T., Wada, Y. and Wisser, D. (2013), First look at changes in flood hazard in the Inter-Sectoral Impact Model Intercomparison Project ensemble, PNAS, 111, 9, 3257-3261 

Davie, J., Falloon, P. D., Kahana, R., Dankers, R., Betts, R., Portmann, F. T., Wisser, D., Clark, D. B., Ito, A., Masaki, Y., Nishina, K., Fekete, B., Tessler, Z., Wada, Y., Liu, W., Tang, Q., Hagemann, S., Stacke, T., Pavlick, R., Schaphoff, S., Gosling, S. N., Franssen, W. and Arnell, N. (2013), Comparing projections of future changes in runoff from hydrological and biome models is ISI-MIP, Earth Syst. Dynam., 4, 359-374

Hinkel, J., Lincke, D., Vafeidis, A. T., Perrette, M., Nicholls, R. J., Tol, R. S. J., Marzeion, B., Fettweis, X., Ionescu, C. and Levemann, A.(2014), Coastal flood damage and adaptation cost under 21st century sea-level rise, PNAS, 111, 9, 3292-3297

Prudhomme, C., Giuntoli, I., Robinson, E. L., Clark, D. B., Arnell, N. W., Dankers, R., Fekete, B. M., Franssen, W., Gerten, D., Gosling, S. N., Hagemann, S., Hannah, D. M., Kim, H., Masaki, Y., Satoh, Y., Stacke, T., Wada, Y. and Wisser, D. (2013), Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment, PNAS, 111, 3262-3267 

Rosenzweig, C., Elliott, J., Deryng, D., Ruane, A. C., Müller, C., Arneth, A., Boote, K. J., Folberth, C., Glotter, M., Khabarov, N., Neumann, K., Piontek, F., Pugh, T. A. M., Schmid, E., Stehfest, E., Yang, H. and Jones, J. W. (2013), Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison, PNAS, 111, 9, 3268-3273 )

Wada, Y., Wisser, D., Eisner, S., Flörke, M., Gerten, D., Haddeland, I., Hanasaki, N., Masaki, Y., Portmann, F. T., Stacke, T., Tessler, Z. and Schewe, J. (2013), Multimodel projections and uncertainties of irrigation water demand under climate change, Geophys. Res. Lett., 40, 4626-4632 

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Last updated: 12 September 2014

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