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  • 标题:Colorado River water supply is predictable on multi-year timescales owing to long-term ocean memory
  • 本地全文:下载
  • 作者:Yoshimitsu Chikamoto ; S.-Y. Simon Wang ; Matt Yost
  • 期刊名称:Communications Earth & Environment
  • 电子版ISSN:2662-4435
  • 出版年度:2020
  • 卷号:1
  • 期号:1
  • 页码:1-11
  • DOI:10.1038/s43247-020-00027-0
  • 语种:English
  • 出版社:Nature Research
  • 摘要:Skillful multi-year climate forecasts provide crucial information for decision-makers and resource managers to mitigate water scarcity, yet such forecasts remain challenging due to unpredictable weather noise and the lack of dynamical model capability. Here we demonstrate that the annual water supply of the Colorado River is predictable up to several years in advance by a drift-free decadal climate prediction system using a fully coupled climate model. Observational analyses and model experiments show that prolonged shortages of water supply in the Colorado River are significantly linked to sea surface temperature precursors including tropical Pacific cooling, North Pacific warming, and southern tropical Atlantic warming. In the Colorado River basin, the water deficits can reduce crop yield and increase wildfire potential. Thus, a multi-year prediction of severe water shortages in the Colorado River basin could be useful as an early indicator of subsequent agricultural loss and wildfire risk. Sea surface temperature anomalies in the Atlantic and Pacific Oceans can help predict water shortages in the Colorado River basin, according to analyses of decadal climate predictions and observations.
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