Improvement of the regional climate model with soil moisture initialization on simulations of Indian summer monsoon

The influence of initializing soil moisture data in a nonhydrostatic regional climate model (RegCM) for the simulations of Indian summer monsoon (ISM) for the period 1982 to 2018 was analysed. Gridded global atmospheric reanalysis soil moisture dataset of Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2) and the model-based soil moisture estimate dataset of Climate Prediction Center (CPC), are used for the model initialization. All experiments were performed at a 25 km horizontal resolution over the ISM region, employing initial and boundary conditions from the ERA interim analysis. The results were compared with a control experiment (CTL) simulated with Community Land Model version 4.5 (CLM4.5) scheme. The results indicate that the simulations initialized with soil moisture data exhibit better performance compared to the control run. Land surface characteristics, including soil moisture, latent heat flux, and surface net radiation, are relatively better represented in the MERRA-2–initialized simulations compared with the CPC-initialized and control runs. The JJAS rainfall simulated using MERRA2 dataset has reduced bias compared with CPC and CTL datasets when evaluated against IMD gridded rainfall with a correlation of 0.8 whilst CTL simulations demonstrate a correlation of less than 0.7. The results are validated using quantile-quantile distributions, Taylor diagram metrics, and mean absolute error percentage performance metrics. The MERRA-2–initialized simulations exhibit relatively better performance for rainfall, soil moisture, soil temperature, and latent heat flux, showing average improvements of about 10% compared with the CPC-initialized run and about 15% compared with the control experiment. Overall, the results suggest that soil-moisture initialization contributes to improved simulation of the ISM in a regional climate modeling framework.