Diagnosing modeling errors in global terrestrial water storage interannual variability

Detalhes bibliográficos
Autor(a) principal: Lee, Hoontaek
Data de Publicação: 2023
Outros Autores: Jung, Martin, Carvalhais, Nuno, Trautmann, Tina, Kraft, Basil, Reichstein, Markus, Forkel, Matthias, Koirala, Sujan
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/158087
Resumo: Funding Information: Hoontaek Lee acknowledges support from the Max Planck Institute for Biogeochemistry (MPI-BGC) and the International Max Planck Research School for Global Biogeochemical Cycles (IMPRS-gBGC). We also thank Uli Weber at MPI-BGC for the collection and preparation of the data used in the model simulations and analysis. Publisher Copyright: © Copyright:
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spelling Diagnosing modeling errors in global terrestrial water storage interannual variabilityWater Science and TechnologyEarth and Planetary Sciences (miscellaneous)SDG 13 - Climate ActionFunding Information: Hoontaek Lee acknowledges support from the Max Planck Institute for Biogeochemistry (MPI-BGC) and the International Max Planck Research School for Global Biogeochemical Cycles (IMPRS-gBGC). We also thank Uli Weber at MPI-BGC for the collection and preparation of the data used in the model simulations and analysis. Publisher Copyright: © Copyright:Terrestrial water storage (TWS) is an integrative hydrological state that is key for our understanding of the global water cycle. The TWS observation from the GRACE missions has, therefore, been instrumental in the calibration and validation of hydrological models and understanding the variations in the hydrological storage. The models, however, still show significant uncertainties in reproducing observed TWS variations, especially for the interannual variability (IAV) at the global scale. Here, we diagnose the regions dominating the variance in globally integrated TWS IAV and the sources of the errors in two data-driven hydrological models that were calibrated against global TWS, snow water equivalent, evapotranspiration, and runoff data. We used (1) a parsimonious process-based hydrological model, the Strategies to INtegrate Data and BiogeochemicAl moDels (SINDBAD) framework and (2) a machine learning, physically based hybrid hydrological model (H2M) that combines a dynamic neural network with a water balance concept. While both models agree with the Gravity Recovery and Climate Experiment (GRACE) that global TWS IAV is largely driven by the semi-arid regions of southern Africa, the Indian subcontinent and northern Australia, and the humid regions of northern South America and the Mekong River basin, the models still show errors such as the overestimation of the observed magnitude of TWS IAV at the global scale. Our analysis identifies modeling error hotspots of the global TWS IAV, mostly in the tropical regions including the Amazon, sub-Saharan regions, and Southeast Asia, indicating that the regions that dominate global TWS IAV are not necessarily the same as those that dominate the error in global TWS IAV. Excluding those error hotspot regions in the global integration yields large improvements in the simulated global TWS IAV, which implies that model improvements can focus on improving processes in these hotspot regions. Further analysis indicates that error hotspot regions are associated with lateral flow dynamics, including both sub-pixel moisture convergence and across-pixel lateral river flow, or with interactions between surface processes and groundwater. The association of model deficiencies with land processes that delay the TWS variation could, in part, explain why the models cannot represent the observed lagged response of TWS IAV to precipitation IAV in hotspot regions that manifest as errors in global TWS IAV. Our approach presents a general avenue to better diagnose model simulation errors for global data streams to guide efficient and focused model development for regions and processes that matter the most.DCEA - Departamento de Ciências e Engenharia do AmbienteRUNLee, HoontaekJung, MartinCarvalhais, NunoTrautmann, TinaKraft, BasilReichstein, MarkusForkel, MatthiasKoirala, Sujan2023-09-21T22:14:35Z2023-04-142023-04-14T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article33application/pdfhttp://hdl.handle.net/10362/158087eng1027-5606PURE: 72082967https://doi.org/10.5194/hess-27-1531-2023info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:40:22Zoai:run.unl.pt:10362/158087Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:56:58.554325Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Diagnosing modeling errors in global terrestrial water storage interannual variability
title Diagnosing modeling errors in global terrestrial water storage interannual variability
spellingShingle Diagnosing modeling errors in global terrestrial water storage interannual variability
Lee, Hoontaek
Water Science and Technology
Earth and Planetary Sciences (miscellaneous)
SDG 13 - Climate Action
title_short Diagnosing modeling errors in global terrestrial water storage interannual variability
title_full Diagnosing modeling errors in global terrestrial water storage interannual variability
title_fullStr Diagnosing modeling errors in global terrestrial water storage interannual variability
title_full_unstemmed Diagnosing modeling errors in global terrestrial water storage interannual variability
title_sort Diagnosing modeling errors in global terrestrial water storage interannual variability
author Lee, Hoontaek
author_facet Lee, Hoontaek
Jung, Martin
Carvalhais, Nuno
Trautmann, Tina
Kraft, Basil
Reichstein, Markus
Forkel, Matthias
Koirala, Sujan
author_role author
author2 Jung, Martin
Carvalhais, Nuno
Trautmann, Tina
Kraft, Basil
Reichstein, Markus
Forkel, Matthias
Koirala, Sujan
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv DCEA - Departamento de Ciências e Engenharia do Ambiente
RUN
dc.contributor.author.fl_str_mv Lee, Hoontaek
Jung, Martin
Carvalhais, Nuno
Trautmann, Tina
Kraft, Basil
Reichstein, Markus
Forkel, Matthias
Koirala, Sujan
dc.subject.por.fl_str_mv Water Science and Technology
Earth and Planetary Sciences (miscellaneous)
SDG 13 - Climate Action
topic Water Science and Technology
Earth and Planetary Sciences (miscellaneous)
SDG 13 - Climate Action
description Funding Information: Hoontaek Lee acknowledges support from the Max Planck Institute for Biogeochemistry (MPI-BGC) and the International Max Planck Research School for Global Biogeochemical Cycles (IMPRS-gBGC). We also thank Uli Weber at MPI-BGC for the collection and preparation of the data used in the model simulations and analysis. Publisher Copyright: © Copyright:
publishDate 2023
dc.date.none.fl_str_mv 2023-09-21T22:14:35Z
2023-04-14
2023-04-14T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/158087
url http://hdl.handle.net/10362/158087
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1027-5606
PURE: 72082967
https://doi.org/10.5194/hess-27-1531-2023
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 33
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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