In this study, the Weather Research and Forecasting (WRF) model was used to assess the importance of very high resolution sea surface temperature (SST) on seasonal rainfall prediction. Two different SST datasets available from the National Centers for Environmental Prediction (NCEP) global model analysis and merged satellite product from Group for High Resolution SST (GHRSST) are used as a lower boundary condition in the WRF model for the Indian Summer Monsoon (ISM) 2010. Before using NCEP SST and GHRSST for model simulation, an initial verification of NCEP SST and GHRSST are performed with buoy measurements. It is found that approximately 0.4 K root mean square difference (RMSD) in GHRSST and NCEP SST when compared with buoy observations available over the Indian Ocean during 01 May to 30 September 2010. Our analyses suggest that use of GHRSST as lower boundary conditions in the WRF model improve the low level temperature, moisture, wind speed and rainfall prediction over ISM region. Moreover, temporal evolution of surface parameters such as temperature, moisture and wind speed forecasts associated with monsoon is also improved with GHRSST forcing as a lower boundary condition. Interestingly, rainfall prediction is improved with the use of GHRSST over the Western Ghats, which mostly not simulated in the NCEP SST based experiment.
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The authors would like to thank Director, SAC. Authors are also thankful to Dr. Neeraj Agarwal for his motivation to use GHRSST in WRF model. Authors are thankful to NCAR for WRF model. The NCEP global model analyses are obtained from Data Support Section of the Computational and Information Systems Laboratory (CISL) at NCAR. TRMM data are obtained from http://daac.gsfc.nasa.gov/data/datasets. Authors are also thankful to Tropical Atmosphere Ocean project office of NOAA/PMEL to provide RAMA (Research Moored Array for African-Asian-Australian Monsson Analysis and Prediction) Buoy observations. www.pmel.noaa.gov/tao/data_deliv/deliv-nojava-rama.html.