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Assessing the performance of WRF ARW model in simulating heavy rainfall events over the Pune region: in support of operational applications

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Abstract

This study evaluates the impact of the Planetary Boundary layer (PBL) on rainfall simulated by the Weather Research and Forecasting (WRF) model during extreme rainfall event cases over an urban city. This is accomplished by producing a heavy rainfall event forecast using the WRF model with five varying PBL scenarios (ACM2, YSU, MYJ, QNSE, MYNN) but otherwise identical model configuration. The study examined the role of PBL in modulating rainfall characteristics by investigating the impacts of PBL on forecast skills with particular reference to rainfall. The PBL scheme plays a crucial role and can significantly alter the spatial pattern and magnitudes of rainfall simulated by the model. Results showed that the QNSE boundary layer scheme substantially improved the magnitudes and spatial pattern of rainfall simulated by the model. The model’s ability was cross-checked with this setup to capture the other two heavy rainfall events over Pune city and was found satisfactory. The current model setup could capture the spatial distribution and the magnitude of rainfall compared with satellite data and observation over point locations. These findings are highly relevant to highlight the dependency of the model on parameterization schemes to forecast extreme rainfall events accurately.

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Acknowledgements

The NCEP FNL data used to provide initial and boundary conditions for the model simulation are downloaded from http://dss.ucar.edu/datasets/ds083.2/. The authors thank the India Meteorological Department for providing the Automatic Weather Station (AWS) and Rain-gauge data. The CMORPH-derived rainfall data are retrieved from https://climatedataguide.ucar.edu/climate-data. PARAM Shivay and PARAM Shakti supercomputer facilities have been used for model simulation. The work was primarily funded by the project (Sanction Number MeitY/R&D/HPC/2(1)/2014) from the Ministry of Electronics and Information Technology (MeITy), under the National Supercomputing Mission program of Government of India.

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  1. Centre for Development of Advanced Computing, Pune, Maharashtra, 411008, India

    Vineeth Krishnan Valappil, Sumita Kedia, Arun K. Dwivedi, Sagar S. Pokale, Sahidul Islam & Manoj K. Khare

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Valappil, V.K., Kedia, S., Dwivedi, A.K. et al. Assessing the performance of WRF ARW model in simulating heavy rainfall events over the Pune region: in support of operational applications. Meteorol Atmos Phys 135, 16 (2023). https://doi.org/10.1007/s00703-023-00952-7

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