S C Kar
Articles written in Journal of Earth System Science
Volume 111 Issue 3 September 2002 pp 351-364
Oceansat-1 was successfully launched by India in 1999, with two payloads, namely Multi-frequency Scanning Microwave Radiometer (MSMR) and Ocean Color Monitor (OCM) to study the biological and physical parameters of the ocean. The MSMR sensor is configured as an eight-channel radiometer using four frequencies with dual polarization. The MSMR data at 75 km resolution from the Oceansat-I have been assimilated in the National Centre for Medium Range Weather Forecasting (NCMRWF) data assimilation forecast system. The operational analysis and forecast system at NCMRWF is based on a T80L18 global spectral model and Spectral Statistical Interpolation (SSI) scheme for data analysis. The impact of the MSMR data is seen globally, however it is significant over the oceanic region where conventional data are rare. The dry-nature of the control analyses have been removed by utilizing the MSMR data. Therefore, the total precipitable water data from MSMR has been identified as a very crucial parameter in this study. The impact of surface wind speed from MSMR is to increase easterlies over the tropical Indian Ocean. Shifting of the positions of westerly troughs and ridges in the south Indian Ocean has contributed to reduction of temperature to around 30‡S.
Volume 118 Issue 5 October 2009 pp 413-440
The change in the type of vegetation fraction can induce major changes in the local effects such as local evaporation,surface radiation,etc.,that in turn induces changes in the model simulated outputs.The present study deals with the effects of vegetation in climate modeling over the Indian region using the MM5 mesoscale model.The main objective of the present study is to investigate the impact of vegetation dataset derived from SPOT satellite by ISRO (Indian Space Research Organization)
The study reveals mixed results on the impact of vegetation datasets generated by ISRO and USGS on the simulations of the monsoon.Results indicate that the ISRO data has a positive impact on the simulations of the monsoon over northeastern India and along the western coast.The MM5- USGS has greater tendency of overestimation of rainfall.It has higher standard deviation indicating that it induces a dispersive effect on the rainfall simulation.Among the ﬁve years of study,it is seen that the RMSE of July and JJAS (June –July –August –September)for All India Rainfall is mostly lower for MM5-ISRO.Also,the bias of July and JJAS rainfall is mostly closer to unity for MM5-ISRO.The wind ﬁelds at 850 hPa and 200 hPa are also better simulated by MM5 using ISRO vegetation.The synoptic features like Somali jet and Tibetan anticyclone are simulated closer to the veri ﬁcation analysis by ISRO vegetation.The 2 m air temperature is also better simulated by ISRO vegetation over the northeastern India,showing greater spatial variability over the region. However,the JJAS total rainfall over north India and Deccan coast is better simulated using the USGS vegetation.Sensible heat ﬂux over north-west India is also better simulated by MM5-USGS.
Volume 120 Issue 5 October 2011 pp 795-805
The northeast (NE) monsoon season (October, November and December) is the major period of rainfall activity over south peninsular India. This study is mainly focused on the prediction of northeast monsoon rainfall using lead-1 products (forecasts for the season issued in beginning of September) of seven general circulation models (GCMs). An examination of the performances of these GCMs during hindcast runs (1982–2008) indicates that these models are not able to simulate the observed interannual variability of rainfall. Inaccurate response of the models to sea surface temperatures may be one of the probable reasons for the poor performance of these models to predict seasonal mean rainfall anomalies over the study domain. An attempt has been made to improve the accuracy of predicted rainfall using three different multi-model ensemble (MME) schemes,