Coupled Land‐Atmosphere Regional Model Reduces Dry Bias in Indian Summer Monsoon Rainfall Simulated by CFSv2. Issue 5 (11th March 2018)

• Record Type: Journal Article
• Authors: Devanand, Anjana; Roxy, Mathew Koll; Ghosh, Subimal
• Is Part Of: Geophysical research letters. Volume 45:Issue 5(2018)
• Page Start: 2476
• Page End: 2486
• Publication Date: 2018-03-11
• Subjects: regional modeling -- dry bias -- Indian monsoon; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1002/2018GL077218
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Global climate models including the Climate Forecast System version 2, the operational model used for prediction of Indian summer monsoon rainfall by the India Meteorological Department, has dry precipitation bias, mostly over densely populated Ganga basin. This restricts the use of model output in hydrological simulations/forecasts. We use regional atmospheric Weather Research and Forecasting model coupled with land surface models, driven by the boundary conditions from Climate Forecast System version 2. We find significant reduction in the dry bias of Indian summer monsoon rainfall with regional land‐atmosphere model and this attributes to (a) improved moisture transport from Western and Upper Indian Ocean to Ganga Basin and (b) improved precipitation recycling over the Ganga basin. We find that the smoothened topography in the global model allows advection of cold dry subtropical air into the Indian monsoon region, contributing to the cold temperature and dry precipitation bias. These results have important implications for monsoon simulations in developing operational hydroclimatic prediction system in India. Plain Language Summary: The operational monsoon prediction model for India, Climate Forecast System version 2, has significant dry bias in precipitation over the Ganga basin, and this restricts the use of model output for hydrologic prediction. We attribute such bias to the lack of representation of land surface processes and characteristics in the model. We show that an improved representation of land characteristics in a regional coupled atmospheric‐land model improves not only the land‐atmosphere interactions but also the moisture contributions from distant oceanic sources. This finally results into improved simulations of monsoon. Key Points: There is a reduction of the precipitation dry bias over Ganga basin in Indian monsoon simulations using a coupled land‐atmosphere regional model Reduction of bias comes from improvement in local recycling and atmospheric moisture transport from the Western and Upper Indian Ocean Better land surface process representation in climate models is necessary to capture the monsoon rainfall over the Ganga basin