The role of land surface schemes in non-hydrostatic RegCM on the simulation of Indian summer monsoon

This study evaluates the performance of a non-hydrostatic Regional Climate Model (RegCM) with two land surface parameterizations namely Biosphere-Atmosphere Transfer (BAT) scheme and Community Land Model (CLM) scheme on the simulation of summer monsoon over India. The initial and boundary conditions are taken from ERA-Interim (ERA-I) reanalysis available at 0.75o spatial grid. The RegCM is designed with 25km horizontal resolution and 23 vertical levels and it integrated for the period 1st January 1982 to 30th September 2016. We used the NOAA Optimum Interpolation Weekly sea surface temperatures, the topography and land-use data from the United States Geological Survey, and Global Land Cover Characterization. Our results reveal that the summer monsoon precipitation anomaly is reasonably well simulated with BAT and CLM schemes compared to those of India Meteorological Department (IMD) observations. The spatial distributions of temperature anomaly over India with BAT compared to CRU shows cold bias over most of the Indian sub-continent, whereas the CLM shows large warm bias over central India and monsoon trough region. The low-level and upper-level winds are in good agreement with ERA-I. Further, the analysis of extreme monsoon events (i.e., excess and deficit seasons) reveals that CLM depicts less bias in simulating the excess and deficit precipitation regions as compared to those of BAT. Conversely, BAT simulates temperature well over India in both excess and deficit monsoon seasons. The Taylor's diagram analysis, Added Value Index based on Mean Square Error, and Modified Brier Skill Score are also applied for the extreme rainfall seasons. Our quantitative analysis demonstrates that the CLM have resolved better rainfall features with more skills with respect to that of BAT. The results suggest that CLM have added value in Indian Summer Monsoon (ISM) regional climate simulation than the BAT, particularly on simulation of the rainfall characteristics during extreme rainfall seasons.