Amar Deep Tiwari, Yadu Pokhrel, Farshid Felfelani, Ahmed Elkouk, Julien Boulange, Simon N. Gosling, Naota Hanasaki, Aristeidis Koutroulis, Vimal Mishra, Hannes Müller Schmied, Yusuke Satoh, Sebastian Ostberg, Tobias Stacke, Jiabo Yin
{"title":"全球水模式对历史陆地储水干旱的低估","authors":"Amar Deep Tiwari, Yadu Pokhrel, Farshid Felfelani, Ahmed Elkouk, Julien Boulange, Simon N. Gosling, Naota Hanasaki, Aristeidis Koutroulis, Vimal Mishra, Hannes Müller Schmied, Yusuke Satoh, Sebastian Ostberg, Tobias Stacke, Jiabo Yin","doi":"10.1029/2025gl115164","DOIUrl":null,"url":null,"abstract":"Enhanced drought modeling is crucial for realistic prediction and effective management of water resources, especially with climate change anticipated to exacerbate drought frequency and severity. Global water models (GWMs) simulate historical and future terrestrial water storage (TWS) with continuous spatial and temporal coverage. However, a global evaluation of TWS simulations by GWMs focused on drought is lacking. Here we evaluate, for the first time, GWMs' capability to represent TWS droughts by comparing simulations with Gravity Recovery and Climate Experiment satellite data. We find notable underestimation of drought severity and coverage by GWMs, across diverse regions, including North America, South America, Africa, and Northern Asia. When examined without trend removal, the underestimation of TWS droughts is more pronounced in recent years (2016–2019) compared to 2002–2015, especially in northern latitudes. This underrepresentation highlights the necessity to improve GWMs to simulate TWS droughts. Our results imply that previously reported future TWS projections could have underestimated droughts.","PeriodicalId":12523,"journal":{"name":"Geophysical Research Letters","volume":"102 1","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Underestimation of Historical Terrestrial Water Storage Droughts in Global Water Models\",\"authors\":\"Amar Deep Tiwari, Yadu Pokhrel, Farshid Felfelani, Ahmed Elkouk, Julien Boulange, Simon N. Gosling, Naota Hanasaki, Aristeidis Koutroulis, Vimal Mishra, Hannes Müller Schmied, Yusuke Satoh, Sebastian Ostberg, Tobias Stacke, Jiabo Yin\",\"doi\":\"10.1029/2025gl115164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Enhanced drought modeling is crucial for realistic prediction and effective management of water resources, especially with climate change anticipated to exacerbate drought frequency and severity. Global water models (GWMs) simulate historical and future terrestrial water storage (TWS) with continuous spatial and temporal coverage. However, a global evaluation of TWS simulations by GWMs focused on drought is lacking. Here we evaluate, for the first time, GWMs' capability to represent TWS droughts by comparing simulations with Gravity Recovery and Climate Experiment satellite data. We find notable underestimation of drought severity and coverage by GWMs, across diverse regions, including North America, South America, Africa, and Northern Asia. When examined without trend removal, the underestimation of TWS droughts is more pronounced in recent years (2016–2019) compared to 2002–2015, especially in northern latitudes. This underrepresentation highlights the necessity to improve GWMs to simulate TWS droughts. Our results imply that previously reported future TWS projections could have underestimated droughts.\",\"PeriodicalId\":12523,\"journal\":{\"name\":\"Geophysical Research Letters\",\"volume\":\"102 1\",\"pages\":\"\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geophysical Research Letters\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1029/2025gl115164\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geophysical Research Letters","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1029/2025gl115164","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Underestimation of Historical Terrestrial Water Storage Droughts in Global Water Models
Enhanced drought modeling is crucial for realistic prediction and effective management of water resources, especially with climate change anticipated to exacerbate drought frequency and severity. Global water models (GWMs) simulate historical and future terrestrial water storage (TWS) with continuous spatial and temporal coverage. However, a global evaluation of TWS simulations by GWMs focused on drought is lacking. Here we evaluate, for the first time, GWMs' capability to represent TWS droughts by comparing simulations with Gravity Recovery and Climate Experiment satellite data. We find notable underestimation of drought severity and coverage by GWMs, across diverse regions, including North America, South America, Africa, and Northern Asia. When examined without trend removal, the underestimation of TWS droughts is more pronounced in recent years (2016–2019) compared to 2002–2015, especially in northern latitudes. This underrepresentation highlights the necessity to improve GWMs to simulate TWS droughts. Our results imply that previously reported future TWS projections could have underestimated droughts.
期刊介绍:
Geophysical Research Letters (GRL) publishes high-impact, innovative, and timely research on major scientific advances in all the major geoscience disciplines. Papers are communications-length articles and should have broad and immediate implications in their discipline or across the geosciences. GRLmaintains the fastest turn-around of all high-impact publications in the geosciences and works closely with authors to ensure broad visibility of top papers.