Sensitivity of Indian summer monsoon simulation to physical parameterization schemes in the WRF model

J. V. Ratnam, Swadhin K. Behera, R Krishnan, Takeshi Doi, Satyaban B. Ratna

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A set of 17 experiments, using various combinations of physical parameterization schemes in the Weather Research and Forecasting (WRF) model, were carried out to choose a combination suitable for simulating the Indian summer monsoon. The model experiments, forced with the ERA-Interim reanalysis data, were at 30 km horizontal resolution. The WRF model experiments were initialized on 1 May of each year and integrated until 30 September to cover the entire monsoon season for the years 1982 to 2013. The results indicate that the simulated Indian summer monsoon precipitation and 2 m air temperature are sensitive to the physical parameterization schemes in the WRF model and that choosing the correct combination of physical parameterization schemes is essential for simulating the Indian summer monsoon realistically. Our analysis shows that a model setup with the Kain-Fritsch cumulus scheme, a radiation package with the Dudhia shortwave and Rapid Radiative Transfer Model longwave schemes, the Yonsei State University planetary boundary layer scheme, the WRF Single-Moment 3-class microphysics scheme, the revised MM5 Monin-Obukhov surface layer scheme, and the Unified Noah land surface model is suitable for simulating the precipitation realistically. The model setup with a combination of these physical parameterization schemes was found to have smaller biases and root mean square errors in the simulated precipitation, along with a realistic simulation of intraseasonal and interannual variability of precipitation. The results of this study will be useful to researchers and forecasters using the WRF model to improve the Indian summer monsoon simulations/forecasts over the Indian region.
Original languageEnglish
Pages (from-to)43-66
Number of pages24
JournalClimate Research
Issue number1
Publication statusPublished - 2 Nov 2017


  • Regional climate model
  • Intra-seasonal variability
  • Inter-annual variability

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