Open AccessImpact of TMI SST on the Simulation of a Heavy Rainfall Episode over Mumbai on 26 July 2005
Author(s) -
S. K. Deb,
C. M. Kishtawal,
P. K. Pal,
P. C. Joshi
Publication year - 2008
Publication title -
monthly weather review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.862
H-Index - 179
eISSN - 1520-0493
pISSN - 0027-0644
DOI - 10.1175/2008mwr2291.1
Subject(s) - weather research and forecasting model , environmental science , mesoscale meteorology , climatology , convective available potential energy , meteorology , atmospheric research , numerical weather prediction , sea surface temperature , convection , atmospheric sciences , geology , geography
In this study the simulation of a severe rainfall episode over Mumbai on 26 July 2005 has been attempted with two different mesoscale models. The numerical models used in this study are the Brazilian Regional Atmospheric Modeling System (BRAMS) developed originally by Colorado State University and the Advanced Research Weather Research Forecast (WRF-ARW) Model, version 2.0.1, developed at the National Center for Atmospheric Research. The simulations carried out in this study use the Grell–Devenyi Ensemble cumulus parameterization scheme. Apart from using climatological sea surface temperature (SST) for the control simulations, the impact of the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) SST on the simulation of rainfall is evaluated using these two models. The performances of the models are compared by examining the predicted parameters like upper- and lower-level circulations, moisture, temperature, and rainfall. The strength of convective instability is also derived by calculating the convective available potential energy. The intensity of maximum rainfall around Mumbai is significantly improved with TMI SST as the surface boundary condition in both the models. The large-scale circulation features, moisture, and temperature are compared with those in the National Centers for Environmental Prediction analyses. The rainfall prediction is assessed quantitatively by comparing the simulated rainfall with the rainfall from TRMM products and the observed station values reported in Indian Daily Weather Reports from the India Meteorological Department.