Abstract
Soil moisture is one of the key components of land surface processes and a potential source of atmospheric predictability that has received little attention in regional scale studies. In this study, an attempt was made to investigate the impact of soil moisture on Indian summer monsoon simulation using a regional model. We conducted seasonal simulations using a regional climate model (RegCM4) for two different years, viz., 2002 (deficit) and 2011 (normal). The model was forced to initialize with the high-resolution satellite-derived soil moisture data obtained from the Climate Change Initiative (CCI) of the European Space Agency (ESA) by replacing the default static soil moisture. Simulated results were validated against high-resolution surface temperature and rainfall analysis datasets from the India Meteorology Department (IMD). Careful examination revealed significant advancement in the RegCM4 simulation when initialized with soil moisture data from ESA-CCI despite having regional biases. In general, the model exhibited slightly higher soil moisture than observation, RegCM4 with ESA setup showed lower soil moisture than the default one. Model ability was relatively better in capturing surface temperature distribution when initialized with high-resolution soil moisture data. Rainfall biases over India and homogeneous regions were significantly improved with the use of ESA-CCI soil moisture data. Several statistical measures such as temporal correlation, standard deviation, equitable threat score (ETS), etc. were also employed for the assessment. ETS values were found to be better in 2011 and higher in the simulation with the ESA setup. However, RegCM4 was still unable to enhance its ability in simulating temporal variation of rainfall adequately. Although initializing with the soil moisture data from the satellite performed relatively better in a normal monsoon year (2011) but had limitations in simulating different epochs of monsoon in an extreme year (2002). Thus, the study concluded that the simulation of the Indian summer monsoon was improved by using RegCM4 initialized with high-resolution satellite soil moisture data although having limitations in predicting temporal variability. The study suggests that soil moisture initialization has a critical impact on the accurate prediction of atmospheric circulation processes and convective rainfall activity.
Highlights
The strong impact of land surface processes is well recognized in modulating the weather and climate system in subseasonal to seasonal and even longer time scale
We focused on the soil moisture initialization in the seasonal simulation of Indian summer monsoon (ISM) using RegCM4
The analysis was started with the discussion about the model simulated surface temperature and its validation with the India Meteorology Department (IMD) observation
Summary
The strong impact of land surface processes is well recognized in modulating the weather and climate system in subseasonal to seasonal and even longer time scale. Land surface acts as an interface between the biosphere and the overlying atmosphere It interacts with the atmosphere through the exchange of mass, momentum and energy and is considered as the lower boundary of the atmosphere at approximately 30% of the Earth’s surface [1]. It is well understood that the Earth’s surface is the reservoir of our main energy resources from solar radiation. When releasing the energy through the planetary boundary layer, the Earth’s surface works like a separator. It redistributes the net incoming radiative energy into various fluxes such as sensible, latent and other ground fluxes.
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