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)versus that of USGS (United States Geological Survey)vegetation dataset on the simulation of the Indian summer monsoon.The present study has been conducted for ﬁve monsoon seasons (1998 –2002),giving emphasis over the two contrasting southwest monsoon seasons of 1998 (normal)and 2002 (deﬁcient).
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 131, 2022
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