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Skill of regional and global model forecast over Indian region

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Abstract

The global model analysis and forecast have a significant impact on the regional model predictions, as global model provides the initial and lateral boundary condition to regional model. This study addresses an important question whether the regional model can improve the short-range weather forecast as compared to the global model. The National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) and the Weather Research and Forecasting (WRF) model are used in this study to evaluate the performance of global and regional models over the Indian region. A 24-h temperature and specific humidity forecast from the NCEP GFS model show less error compared to WRF model forecast. Rainfall prediction is improved over the Indian landmass when WRF model is used for rainfall forecast. Moreover, the results showed that high-resolution global model analysis (GFS4) improved the regional model forecast as compared to low-resolution global model analysis (GFS3).

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Acknowledgments

The authors would like to thank Dr. A. S. Kiran Kumar, director, SAC for the constant encouragement and guidance. The authors are also thankful to the NCAR for the WRF model and to NASA for the valuable data from TRMM website http://disc2.nascom.nasa.gov/Giovanni/tovas. The authors are grateful for the comments and suggestions by anonymous reviewers that helped to improve the quality of this paper.

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Correspondence to Prashant Kumar.

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Kumar, P., Kishtawal, C.M. & Pal, P.K. Skill of regional and global model forecast over Indian region. Theor Appl Climatol 123, 629–636 (2016). https://doi.org/10.1007/s00704-014-1361-2

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  • DOI: https://doi.org/10.1007/s00704-014-1361-2

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