Premium
Soil‐moisture memory in the regional climate model COSMO‐CLM during the Indian summer monsoon season
Author(s) -
Asharaf Shakeel,
Ahrens Bodo
Publication year - 2013
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/jgrd.50429
Subject(s) - environmental science , climatology , monsoon , forcing (mathematics) , precipitation , climate model , water content , atmospheric sciences , moisture , monsoon of south asia , initialization , atmosphere (unit) , climate change , meteorology , geography , geology , oceanography , programming language , geotechnical engineering , computer science
Soil moisture memory over the Indian subcontinent was investigated on the basis of a 101 year 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 34 cm soil layer depth). Also, the meridionally averaged (20°N–30°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.