Do Climate Forecast System (CFSv2) forecasts improve seasonal soil moisture prediction?

被引：65

作者：

Mo, Kingtse C. ^{[1
]}

Shukla, Shraddhanand ^{[2
,3
]}

Lettenmaier, Dennis P. ^{[2
]}

Chen, Li-Chuan ^{[4
]}

机构：

[1] NOAA, Climate Predict Ctr, NCEP, NWS, College Pk, MD 20740 USA

[2] Univ Washington, Dept Civil & Environm Engn, Seattle, WA 98195 USA

[3] Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA

[4] Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, Cooperat Inst Climate & Satellites, College Pk, MD 20742 USA

来源：

GEOPHYSICAL RESEARCH LETTERS | 2012年 / 39卷

关键词：

UNITED-STATES; HYDROLOGIC PREDICTION; PREDICTABILITY; PERSISTENCE; SKILL;

D O I：

10.1029/2012GL053598

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

We investigated whether seasonal soil moisture forecasts derived from a land surface model forced by seasonal climate forecast model outputs are more skillful than benchmark forecasts derived from the same land surface model but with forcings taken from resampled climatological precipitation, temperature and low level winds. For most forecast leads and over the western United States, soil moisture forecasts based on seasonal climate forecasts are no more skillful than the benchmark. For relatively short (one month) leads, the climate model-based forecasts are more skillful than the benchmark along a swath from the Gulf States to the Tennessee and Ohio Valleys and the Southwest monsoon region, where the climate model has skillful precipitation forecasts. Citation: Mo, K. C., S. Shukla, D. P. Lettenmaier, and L.-C. Chen (2012), Do Climate Forecast System (CFSv2) forecasts improve seasonal soil moisture prediction?, Geophys. Res. Lett., 39, L23703, doi:10.1029/2012GL053598.

引用

页数：6

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