Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data
| Autor: | Scanlon, Bridget R., Zhang, Zizhan, Save, Himanshu, Sun, Alexander Y., Schmied, Hannes Müller, Van Beek, Ludovicus P.H., Wiese, David N., Wada, Yoshihide, Long, Di, Reedy, Robert C., Longuevergne, Laurent, Döll, Petra, Bierkens, Marc F.P., Hydrologie, Landscape functioning, Geocomputation and Hydrology |
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| Přispěvatelé: | Jackson School of Geosciences (JSG), University of Texas at Austin [Austin], Bureau of Economic Geology [Austin] (BEG), University of Texas at Austin [Austin]-University of Texas at Austin [Austin], Center for Space Research [Austin] (CSR), Centrum voor Wiskunde en Informatica (CWI), Centrum Wiskunde & Informatica (CWI)-Netherlands Organisation for Scientific Research, Goethe-Universität Frankfurt am Main, Universiteit Utrecht, Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Géosciences Rennes (GR), Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Hydrologie, Landscape functioning, Geocomputation and Hydrology |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Irrigation
010504 meteorology & atmospheric sciences global hydrological models 0208 environmental biotechnology Drainage basin terrestrial total water storage anomalies 02 engineering and technology Structural basin 01 natural sciences Global hydrological models land surface models global mean sea level GRACE satellites Land surface models [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology General Sea level 0105 earth and related environmental sciences geography Multidisciplinary geography.geographical_feature_category Terrestrial total water storage anomalies Amazon rainforest Water storage 15. Life on land Radiative forcing 020801 environmental engineering Water resources PNAS Plus 13. Climate action Climatology Physical Sciences Environmental science Global mean sea level Environmental Sciences |
| Zdroj: | Proceedings of the National Academy of Sciences of the United States of America Proceedings of the National Academy of Sciences of the United States of America, National Academy of Sciences, 2018, 115 (6), pp.E1080-E1089. ⟨10.1073/pnas.1704665115⟩ Proceedings of the National Academy of Sciences of the United States of America, 115(6):E1080-E1089 Proceedings of the National Academy of Sciences of the United States of America, 115(6), E1080. National Academy of Sciences Proceedings of the National Academy of Sciences of the United States of America, 2018, 115 (6), pp.E1080-E1089. ⟨10.1073/pnas.1704665115⟩ |
| ISSN: | 0027-8424 1091-6490 |
| DOI: | 10.1073/pnas.1704665115⟩ |
| Popis: | Significance We increasingly rely on global models to project impacts of humans and climate on water resources. How reliable are these models? While past model intercomparison projects focused on water fluxes, we provide here the first comprehensive comparison of land total water storage trends from seven global models to trends from Gravity Recovery and Climate Experiment (GRACE) satellites, which have been likened to giant weighing scales in the sky. The models underestimate the large decadal (2002–2014) trends in water storage relative to GRACE satellites, both decreasing trends related to human intervention and climate and increasing trends related primarily to climate variations. The poor agreement between models and GRACE underscores the challenges remaining for global models to capture human or climate impacts on global water storage trends. Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002–2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤−0.5 km3/y) and increasing (≥0.5 km3/y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km3/y, whereas most models estimate decreasing trends (−71 to 11 km3/y). Land water storage trends, summed over all basins, are positive for GRACE (∼71–82 km3/y) but negative for models (−450 to −12 km3/y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated. |
| Databáze: | OpenAIRE |
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