Soil-moisture memory in the regional climate model COSMO-CLM during the Indian summer monsoon season

被引：19

作者：

Asharaf, Shakeel ^{[1
]}

Ahrens, Bodo ^{[1
,2
]}

机构：

[1] Goethe Univ Frankfurt, Inst Atmospher & Environm Sci, D-60438 Frankfurt, Germany

[2] Biodivers & Climate Res Ctr BiK F, Frankfurt, Germany

来源：

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES | 2013年 / 118卷 / 12期

关键词：

Soil moisture; RCM; Autocorrelation; Constant greenhouse gases simulation; GRIDDED PRECIPITATION DATASET; DENSE NETWORK; LAND; VARIABILITY; SENSITIVITY; SIMULATION;

D O I：

10.1002/jgrd.50429

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

Soil moisture memory over the Indian subcontinent was investigated on the basis of a 101year long simulation with the regional climate model (RCM) COSMO-CLM (COSMO model in Climate Mode). The RCM was driven by lateral boundary conditions derived from a preindustrial control run of the coupled global ocean-atmosphere model ECHAM5/MPIOM. To prevent an external atmospheric forcing, the simulation was done with constant greenhouse gas concentrations. This provides an estimate of the internal variability of the (modeled) climate system. The analysis, which was performed for the Indian summer monsoon season (ISM), shows that simulated memory lengths (a) increase with soil depth, and (b) are longer in the western region than in the eastern region (14 and 9 days, respectively, at 34cm soil layer depth). Also, the meridionally averaged (20 degrees N-30 degrees N) variance of subsequent precipitation explained by soil-moisture rises from east to west. This enhanced explained variance value in the western region reveals the potential usefulness of improved soil moisture initialization in subseasonal rainfall forecasting.

引用

页码：6144 / 6151

页数：8

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