Case Study of a Convective Cluster Over the Rain Shadow Region of Western Ghats Using Multi-platform Observations and WRF Model
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Unique observational features of a convective cluster, occurred on 12-Sept-2015, over the rain shadow region in the leeward side of Western Ghats have been presented in this study. The synoptic environment had preconditioned the formation of a convergence zone over the study area. Moisture transport from the Arabian Sea was responsible for the moistening in the lower layers. Boundary layer convective thermals contributed to middle level moistening and subsequent onset of the cloud cluster was accompanied by a sudden surge of moist and warm air into the middle troposphere, and subsequent lifting of freezing level (FL) and wet bulb temperature zero (WBT0) levels. Sudden changes in the FL and WBT0 levels in association with the gust front prior to the initiation of the cloud system has been documented with high-resolution measurements using microwave radiometer and wind profiler. Thermodynamical parameters from radiometer illustrate the percussive conditions for formation of the cloud system. The cloud cluster had resulted in 25.50 mm rainfall, attributing to ~ 91% of convective rain. Intense fall velocity (10–12 ms−1) was noted up to ~ 7 km during the convective rain and the fall velocity was reduced to ~ 7 ms−1 (below the melting layer) during the stratiform counterpart. The cloud system was forecasted using WRF model (version 3.6.1), which was reproduced reasonably well as in the observations and the model output has been analyzed to understand the morphology of the system. The features such as formation of a cold pool, initiation of convective rainfall from the system were well forecasted by the model. Microphysical characteristics of the cloud cluster have also been examined. Riming was the dominant microphysical process within the convective regime. A major contribution to precipitation was from melting of ice hydrometeors especially graupel and snow was noted. Deep warm layer and associated production of supercooled liquid by the lifting of liquid water above the freezing level in updrafts exceeding 15 ms−1 was important for the production of a mixed-phase cloud system. Vapor deposition and aggregation process was noted in the stratiform/anvil counterpart, which also contained mixed phase hydrometeors, primarily of snow.
KeywordsConvective cluster Western Ghats rain shadow region cloud microphysics cloud simulation
The authors would like to thank the Director, IITM for the support and providing necessary facilities to carry out the research work and Ministry of Earth Sciences, Government of India for funding the CAIPEEX project. We heartily thank all the members associated with CAIPEEX campaign for their effort in collecting the data. We also thank Dr. Kaustav Chakravarty, IITM for providing the disdrometer data, ‘Radar and Satellite Meteorology’ division, IITM for providing the X-Band Radar Data and ‘Thunderstorm Dynamics’ group, IITM for providing the Lightning Location Network (LLN) data. We would also like to thank European Centre for Medium-range Weather Forecast (ECMWF) for providing ERA-Interim reanalysis dataset, NOAA National Centers for Environmental Information (NCEI) for providing Global Land One-kilometer Base Elevation (GLOBE) digital elevation data set, National Centers for Environmental Prediction (NCEP) for providing the NCEP GFS data (used in WRF simulation), Indian Space Research Organisation (ISRO) for maintaining MOSDAC website and providing INSAT-3D data, National Aeronautics and Space Administration (NASA) for providing IMERG data product through Precipitation Measurement Mission and India Meteorological Department (IMD) for providing AWS data. We would like to acknowledge the National Center for Atmospheric Research (NCAR) for providing Thunderstorm Identification Tracking Analysis and Nowcasting (TITAN) software. We would also like to acknowledge the High-Performance Computing (HPC) facility at IITM for model simulation. We sincerely thank the three anonymous reviewers from the journal for their insightful comments and valuable suggestions, which has helped us to improve the quality of the manuscript. In this study, Python Programming Language and NCL (NCAR Command Language) software are used for generating the plots.
- Arnaud, Y., Desbois, M., & Maizi, J. (1992). Automatic tracking and characterization of african convective systems on meteosat pictures. Journal of Applied Meteorology, 31, 443–453. https://doi.org/10.1175/1520-0450(1992)031<0443:ATACOA>2.0.CO;2.CrossRefGoogle Scholar
- Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., et al. (2011). The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137, 553–597. https://doi.org/10.1002/qj.828.CrossRefGoogle Scholar
- Dixon, M., & Wiener, G. (1993). TITAN: Thunderstorm identification, tracking, analysis, and nowcasting—a radar-based methodology. Journal of Atmospheric and Oceanic Technology. https://doi.org/10.1175/1520-0426(1993)010%3c0785:ttitaa%3e2.0.co;2.CrossRefGoogle Scholar
- Dudhia, J. (1989). Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. Journal of the Atmospheric Sciences, 46, 3077–3107. https://doi.org/10.1175/1520-0469(1989)046%3c3077:NSOCOD%3e2.0.CO;2.CrossRefGoogle Scholar
- Gunnell, Y. (1997). Relief and climate in south Asia: The influence of the western ghats on the current climate pattern of peninsular India. International Journal of Climatology, 17, 1169–1182. https://doi.org/10.1002/(SICI)1097-0088(199709)17:11<1169::AID-JOC189>3.0.CO;2-W. CrossRefGoogle Scholar
- Hagos, S., Feng, Z., Burleyson, C. D., Lim, K.-S. S., Long, C. N., Wu, D., et al. (2014). Evaluation of convection-permitting model simulations of cloud populations associated with the Madden-Julian Oscillation using data collected during the AMIE/DYNAMO field campaign. Journal of Geophysical Research Atmospheres, 119(21), 12052–12068. https://doi.org/10.1002/2014JD022143.CrossRefGoogle Scholar
- Huffman, G. J., Stocker, E. F., Bolvin, D. T., Nelkin, E. J., & Jackson T. (2019). GPM IMERG final precipitation L3 half hourly 0.1 degree × 0.1 degree V06, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC). https://doi.org/10.5067/gpm/imerg/3b-hh/06. Accessed 09 June 2019.
- Kain, J. S. (2004). The Kain–Fritsch convective parameterization: An update. Journal of Applied Meteorology, 43, 170–181. https://doi.org/10.1175/1520-0450(2004)043%3c0170:TKCPAU%3e2.0.CO;2.CrossRefGoogle Scholar
- Maheskumar, R. S., Narkhedkar, S. G., Morwal, S. B., Padmakumari, B., Kothawale, D. R., Joshi, R. R., et al. (2014). Mechanism of high rainfall over the Indian west coast region during the monsoon season. Climate Dynamics, 43, 1513–1529. https://doi.org/10.1007/s00382-013-1972-9.CrossRefGoogle Scholar
- Mathon, V., Laurent, H., & Lebel, T. (2002). Mesoscale convective system rainfall in the Sahel. Journal of Applied Meteorology, 41, 1081–1092. https://doi.org/10.1175/1520-0450(2002)041%3c1081:MCSRIT%3e2.0.CO;2.CrossRefGoogle Scholar
- Patwardhan, S. K., & Asnani, G. C. (2000). Meso-scale distribution of summer monsoon rainfall near the Western Ghats (INDIA). International Journal of Climatology, 20, 575–581. https://doi.org/10.1002/(SICI)1097-0088(200004)20:5<575::AID-JOC509>3.0.CO;2-6.CrossRefGoogle Scholar
- Rao, Y. P. (1976). Southwest Monsoon. Google Scholar
- Segele, Z. T., Leslie, L. M., & Lamb, P. J. (2013). Weather research and forecasting model simulations of extended warm-season heavy precipitation episode over the US southern great plains: Data assimilation and microphysics sensitivity experiments. Tellus Series A Dynamic Meteorology and Oceanography, 65, 1–28. https://doi.org/10.3402/tellusa.v65i0.19599.CrossRefGoogle Scholar
- Tewari, M., Chen, F., Wang, W., Dudhia, J., LeMone, M. A., Mitchell, K., Ek, M., Gayno, G., Wegiel, J., & Cuenca, R. H. (2004). Implementation and verification of the unified noah land surface model in the WRF model. In 20th conference on weather analysis and forecasting/16th conference on numerical weather prediction, American Meteorological Society, Seattle, WA, US, pp. 11–15.Google Scholar
- Utsav, B., Deshpande, S. M., Das, S. K., & Pandithurai, G. (2017). Statistical characteristics of convective clouds over the western ghats derived from weather radar observations. Journal of Geophysical Research Atmospheres, 122, 10050–10076. https://doi.org/10.1002/2016JD026183.CrossRefGoogle Scholar
- Wu, D., Zhao, K., Kumjian, M. R., Chen, X., Huang, H., Wang, M., Didlake, A. C. Jr., Duan, Y., & Zhang, F. (2018). Kinematics and microphysics of convection in the outer rainband of typhoon nida (2016) revealed by polarimetric radar. Monthly Weather Review, 146(7), 2147–2159. https://doi.org/10.1175/MWR-D-17-0320.1.CrossRefGoogle Scholar