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Revised cloud processes to improve the simulation and prediction skill of Indian summer monsoon rainfall in climate forecast system model


The performance of six-class weather research forecasting (WRF) single moment (WSM6) cloud microphysical scheme in the National Centre for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) at T126 (~ 100 km) horizontal resolution in the simulation and prediction skill of the Indian summer monsoon (ISM) is investigated with 34 years of hindcast runs with 10 ensemble members. The results reveal that the revised version of CFSv2 (EXPT) shows relative improvement in summer monsoon precipitation, its variability, rainfall annual cycle, rainfall probability distribution function, synoptic and intraseasonal variance, etc. over ISM region compared to standard CFSv2 (CTRL). Robust representation of cloud hydrometeors in the WSM6 microphysics scheme leads to better large-scale precipitation distribution compared to CTRL simulation which resulted in realistic northward propagation of rainfall bands in the EXPT. The interannual variability of rainfall in EXPT simulation suggests improved prediction skill of summer monsoon than CTRL run and comparable to higher resolution (T382; ~ 38 km) version of CFSv2. The above improvements are mainly attributed to the better simulation of vertical and spatial distribution of cloud hydrometeors in the EXPT simulation. Further, the cold bias in sea surface temperature (SST) in CTRL simulation is replaced with slightly warm bias in EXPT run which has resulted in wet bias in precipitation over the tropical oceanic region. Introduction of more physically based cloud physics parameterization helps to improve the cloud hydrometeor, cloud variability, and the rainfall variability.

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Data availability

The datasets generated during and/or analysed during the current study are available in the “Pratyush” high performance computing system at IITM, Pune, India and can be made available by request to the corresponding author.


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The Indian Institute of Tropical Meteorology (Pune, India) is fully funded by the Ministry of Earth Sciences, Government of India, NewDelhi. Authors are thankful to Director, IITM for encouragement for carrying out the research. We would like to thank ECMWF for providing ERA5 data set ( OLR data are accessed from NOAA. We thank IMD for providing the long term rainfall data. We would like to thank GSFC/DAAC, NASA for providing TRMM (http://precip.gsfc.nasa. gov/) gridded data set. SST data is obtained from the Met Office Hadley Centre, is also acknowledge. All model runs are carried out on Pratyush High Performance Computing (HPC) system at Indian Institute of Tropical Meteorology (IITM), Pune, India. Authors would like to thank anonymous reviewers for their fruitful comments and suggestions which have immensely helped in improving the quality of the manuscript.


The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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PM and RPMK conceptualized the work. Material preparation, data collection and analysis were performed by MG and ST. The first draft of the manuscript was written by MG, ST, and RPMK. Review and editing done by PM. All authors read and approved the final manuscript.

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Correspondence to Parthasarathi Mukhopadhyay.

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The authors have no relevant financial or non-financial interests to disclose. However, due to conflict of interest, this paper may not be sent for review to IITM reviewers.

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Krishna, R.P.M., Ganai, M., Tirkey, S. et al. Revised cloud processes to improve the simulation and prediction skill of Indian summer monsoon rainfall in climate forecast system model. Clim Dyn (2023).

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  • Climate forecast system model
  • WSM6 microphysics scheme
  • Indian summer monsoon
  • Hindcast simulation
  • Seasonal prediction