Cargando…

Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data

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 w...

Descripción completa

Detalles Bibliográficos
Autores principales: Scanlon, Bridget R., Zhang, Zizhan, Save, Himanshu, Sun, Alexander Y., Müller Schmied, Hannes, van Beek, Ludovicus P. H., Wiese, David N., Wada, Yoshihide, Long, Di, Reedy, Robert C., Longuevergne, Laurent, Döll, Petra, Bierkens, Marc F. P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819387/
https://www.ncbi.nlm.nih.gov/pubmed/29358394
http://dx.doi.org/10.1073/pnas.1704665115
_version_ 1783301200468246528
author Scanlon, Bridget R.
Zhang, Zizhan
Save, Himanshu
Sun, Alexander Y.
Müller Schmied, Hannes
van Beek, Ludovicus P. H.
Wiese, David N.
Wada, Yoshihide
Long, Di
Reedy, Robert C.
Longuevergne, Laurent
Döll, Petra
Bierkens, Marc F. P.
author_facet Scanlon, Bridget R.
Zhang, Zizhan
Save, Himanshu
Sun, Alexander Y.
Müller Schmied, Hannes
van Beek, Ludovicus P. H.
Wiese, David N.
Wada, Yoshihide
Long, Di
Reedy, Robert C.
Longuevergne, Laurent
Döll, Petra
Bierkens, Marc F. P.
author_sort Scanlon, Bridget R.
collection PubMed
description 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 km(3)/y) and increasing (≥0.5 km(3)/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 km(3)/y, whereas most models estimate decreasing trends (−71 to 11 km(3)/y). Land water storage trends, summed over all basins, are positive for GRACE (∼71–82 km(3)/y) but negative for models (−450 to −12 km(3)/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.
format Online
Article
Text
id pubmed-5819387
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher National Academy of Sciences
record_format MEDLINE/PubMed
spelling pubmed-58193872018-02-21 Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data Scanlon, Bridget R. Zhang, Zizhan Save, Himanshu Sun, Alexander Y. Müller Schmied, Hannes van Beek, Ludovicus P. H. Wiese, David N. Wada, Yoshihide Long, Di Reedy, Robert C. Longuevergne, Laurent Döll, Petra Bierkens, Marc F. P. Proc Natl Acad Sci U S A PNAS Plus 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 km(3)/y) and increasing (≥0.5 km(3)/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 km(3)/y, whereas most models estimate decreasing trends (−71 to 11 km(3)/y). Land water storage trends, summed over all basins, are positive for GRACE (∼71–82 km(3)/y) but negative for models (−450 to −12 km(3)/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. National Academy of Sciences 2018-02-06 2018-01-22 /pmc/articles/PMC5819387/ /pubmed/29358394 http://dx.doi.org/10.1073/pnas.1704665115 Text en Copyright © 2018 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle PNAS Plus
Scanlon, Bridget R.
Zhang, Zizhan
Save, Himanshu
Sun, Alexander Y.
Müller Schmied, Hannes
van Beek, Ludovicus P. H.
Wiese, David N.
Wada, Yoshihide
Long, Di
Reedy, Robert C.
Longuevergne, Laurent
Döll, Petra
Bierkens, Marc F. P.
Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data
title Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data
title_full Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data
title_fullStr Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data
title_full_unstemmed Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data
title_short Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data
title_sort global models underestimate large decadal declining and rising water storage trends relative to grace satellite data
topic PNAS Plus
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819387/
https://www.ncbi.nlm.nih.gov/pubmed/29358394
http://dx.doi.org/10.1073/pnas.1704665115
work_keys_str_mv AT scanlonbridgetr globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata
AT zhangzizhan globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata
AT savehimanshu globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata
AT sunalexandery globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata
AT mullerschmiedhannes globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata
AT vanbeekludovicusph globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata
AT wiesedavidn globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata
AT wadayoshihide globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata
AT longdi globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata
AT reedyrobertc globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata
AT longuevergnelaurent globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata
AT dollpetra globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata
AT bierkensmarcfp globalmodelsunderestimatelargedecadaldecliningandrisingwaterstoragetrendsrelativetogracesatellitedata