Prof. Mohanty presented a seminar on “Numerical Modeling of Land Surface Processes for Improved-Simulation of Extreme Weather Events over the Indian Region”
The Indian monsoon region (IMR) is recognized as one of the major ‘hot spots’ for soil moisture variations that significantly influence precipitation. During pre-monsoon season (April- May), due to land falling tropical cyclones and severe thunderstorms the Indian region receives rainfall which alters the surface moisture significantly. On the other side, the monsoon depressions also produce heavy rainfall along its long-inland path. The climatological land surface parameters (such as soil moisture and temperature) cannot reflect these local changes in surface moisture and limits the mesoscale model performance. Further, these observations are a few over the Indian region. Therefore, we hypothesize that the mesoscale model performance can be improved by incorporating more realistic land surface conditions such as soil moisture/soil temperature (SM/ST) profiles (with depth) as surface initial conditions to the model.
The SM/ST gridded profiles (with depth) are modeled at 4 km horizontal resolution using High Resolution Land Data Assimilation System (HRLDAS) and investigated its role/credibility on simulation of extreme weather events such as severe thunderstorms and monsoon depressions (MDs) over the IMR. All forcing fields for HRLDAS are obtained from the MERRA analyses except the rain rate which is taken from the TRMM-3B42V6 analyses. The MERRA-based 2m temperature and TRMM rainfall are in acceptable agreement with the observed data over the IMR. The time series of HRLDAS-based top layer SM was in good agreement with observed data. A set of two experiments were conducted using WRF model considering surface conditions from climatological SM/ST (known as CNTL experiment) and HRLDAS-based SM/ST (LDAS). Both the offline LDAS and WRF systems are executed on the same grid structure/domain to facilitate incorporation of soil fields initialized from LDAS when assimilating into WRF initial conditions without any interpolation.
Model simulations have been improved significantly in intensity and time of occurrence of rainfall associated with pre-monsoon severe thunderstorms with updated soil moisture and temperature profiles. Simulation of monsoon depressions with LDAS fields improved the track and rainfall over the land. The track errors are significantly reduced with the incorporation of HRLDAS-based SM/ST profiles at different depths yielding an improvement of approximately 26%, 25%, and 24% at 24, 48, and 72 hour forecast length, respectively.
At the end, we like to present and discuss on our collaborative efforts with HRD and NCEP in prediction of recent devastating cyclone Phailin successfully which crossed east coast of India, Odisha in October, 2013. This is the first step in our plan for next two years for improvement in prediction of intensity in terms of rainfall and storm surges associated with deadly land falling tropical cyclones in the Bay of Bengal.
A video recording of the presentation is available on the anonymous ftp site: