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A First Look at Decadal Hydrological Predictability by Land Surface Ensemble Simulations
Author(s) -
Yuan Xing,
Zhu Enda
Publication year - 2018
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2018gl077211
Subject(s) - predictability , environmental science , climatology , hindcast , pacific decadal oscillation , climate model , forecast skill , water resources , climate change , sea surface temperature , geology , oceanography , ecology , physics , quantum mechanics , biology
The prediction of terrestrial hydrology at the decadal scale is critical for managing water resources in the face of climate change. Here we conducted an assessment by global land model simulations following the design of the fifth Coupled Model Intercomparison Project (CMIP5) decadal hindcast experiments, specifically testing for the sensitivity to perfect initial or boundary conditions. The memory for terrestrial water storage (TWS) is longer than 6 years over 11% of global land areas where the deep soil moisture and aquifer water have a long memory and a nonnegligible variability. Ensemble decadal predictions based on realistic initial conditions are skillful over 31%, 43%, and 59% of global land areas for TWS, deep soil moisture, and aquifer water, respectively. The fraction of skillful predictions for TWS increases by 10%–16% when conditioned on Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation indices. This study provides a first look at decadal hydrological predictability, with an improved skill when incorporating low‐frequency climate information.