• K Mohankumar

      Articles written in Journal of Earth System Science

    • Spatial variability and rainfall characteristics of Kerala

      Anu Simon K Mohankumar

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      Geographical regions of covariability in precipitation over the Kerala state are exposed using factor analysis. The results suggest that Kerala can be divided into three unique rainfall regions, each region having a similar covariance structure of annual rainfall. Stations north of 10‡N (north Kerala) fall into one group and they receive more rainfall than stations south of 10‡N (south Kerala). Group I stations receive more than 65% of the annual rainfall during the south-west monsoon period, whereas stations falling in Group II receive 25–30% of annual rainfall during the pre-monsoon and the north-east monsoon periods. The meteorology of Kerala is profoundly influenced by its orographical features, however it is difficult to make out a direct relationship between elevation and rainfall. Local features of the state as reflected in the rainfall distribution are also clearly brought out by the study.

    • Assimilation of Doppler weather radar observations in a mesoscale model for the prediction of rainfall associated with mesoscale convective systems

      S Abhilash Someshwar Das S R Kalsi M Das Gupta K Mohankumar J P George S K Banerjee S B Thampi D Pradhan

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      Obtaining an accurate initial state is recognized as one of the biggest challenges in accurate model prediction of convective events. This work is the first attempt in utilizing the India Meteorological Department (IMD) Doppler radar data in a numerical model for the prediction of mesoscale convective complexes around Chennai and Kolkata. Three strong convective events both over Chennai and Kolkata have been considered for the present study. The simulation experiments have been carried out using fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) mesoscale model (MM5) version 3.5.6. The variational data assimilation approach is one of the most promising tools available for directly assimilating the mesoscale observations in order to improve the initial state. The horizontal wind derived from the DWR has been used alongwith other conventional and non-conventional data in the assimilation system. The preliminary results from the three dimensional variational (3DVAR) experiments are encouraging. The simulated rainfall has also been compared with that derived from the Tropical Rainfall Measuring Mission (TRMM) satellite. The encouraging result from this study can be the basis for further investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present study indicates that Doppler radar data assimilation improves the initial field and enhances the Quantitative Precipitation Forecasting (QPF) skill.

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