Abstract
Human-induced climate change impacts the hydrological cycle and thus the availability of water resources. However, previous assessments of observed warming-induced changes in dryness have not excluded natural climate variability and show conflicting results due to uncertainties in our understanding of the response of evapotranspiration. Here we employ data-driven and land-surface models to produce observation-based global reconstructions of water availability from 1902 to 2014, a period during which our planet experienced a global warming of approximately 1 °C. Our analysis reveals a spatial pattern of changes in average water availability during the driest month of the year over the past three decades compared with the first half of the twentieth century, with some regions experiencing increased and some decreased water availability. The global pattern is consistent with climate model estimates that account for anthropogenic effects, and it is not expected from natural climate variability, supporting human-induced climate change as the cause. There is regional evidence of drier dry seasons predominantly in extratropical latitudes and including Europe, western North America, northern Asia, southern South America, Australia and eastern Africa. We also find that the intensification of the dry season is generally a consequence of increasing evapotranspiration rather than decreasing precipitation.
| Original language | English |
|---|---|
| Pages (from-to) | 477-481 |
| Number of pages | 5 |
| Journal | Nature Geoscience |
| Volume | 13 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 1 2020 |
Funding
R.S.P., L.G. and S.I.S. acknowledge partial support from the European Research Council (ERC) DROUGHT-HEAT project funded by the European Community’s Seventh Framework Programme (grant agreement FP7-IDEAS-ERC-617518) and from the European Union’s Horizon 2020 Research and Innovation Program (grant agreement 821003 (4C)). D.M.L. was supported in part by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computing Scientific Focus Area (RUBISCO SFA), which is sponsored by the Regional and Global Climate Modeling (RGCM) Program in the US Department of Energy Office of Science. J.M. was also supported by the RUBISCO SFA. Oak Ridge National Laboratory is managed by UT‐BATTELLE for DOE under contract number DE‐AC05‐00OR22725. D.P. acknowledges the European Union’s Horizon 2020 research and innovation program under Grant Agreement 641816 (CRESCENDO) that partially funded the CMCC simulations. H.K. acknowledges Grant-in-Aid for Specially Promoted Research 16H06291 and 18KK0117 from Japan Society for the Promotion of Science. The LS3MIP simulation of the Institut Pierre Simon Laplace (IPSL) was performed at the Très Grand Centre de Calcul (TGCC) under the allocation 2018-R0040110492 (project gencmip6) provided by GENCI (Grand Equipement National de Calcul Intensif). We acknowledge the World Climate Research Program’s Working Group on Coupled Modelling, which is responsible for the Coupled Model Intercomparison Project (CMIP), and we thank the climate modelling groups for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank U. Beyerle, J. Sedlacek and L. Brunner for downloading and processing the CMIP5 and LS3MIP data.