A quantitative precipitation forecast model using convective-cloud tracking in satellite thermal infrared images and adaptive regression: a case study along East Coast of India

Abstract

The current work addresses issues related to quantitative estimation of precipitation caused by convective clouds, using thermal infrared images, and adaptive regression modeling. The developed methodology has been implemented on the Indian sector during the period 22–25 October 2013. The importance of the developed methodology lies in the fact that the information obtained from it can facilitate further studies intended for the prediction of flood events. This study is the continuation of existing work of identification of convective clouds and the analysis of the Mesoscale Convective Systems (MCS). In the current work, forecast of rainfall in terms of millimeter has been proposed. The entire work has been carried out on thermal infrared (TIR) images obtained from geostationary satellites and the results have been validated by actual rainfall data measured by rain gauges. The results obtained from the developed methodology were found to be fairly close to actual values.

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Acknowledgements

The authors are especially indebted to Meteorological and Oceanographic Satellite Data Archival Centre (MOSDAC), Indian Space Research Organization, Government of India, for availing the images of Indian subcontinent from the Indian Meteorological Satellite, Kalpana-1, for performing the study. Special thanks to National Climate Centre (NCC), Indian Meteorological Department, Pune, India for providing rainfall data to validate the developed model.

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Correspondence to Sanjay Goswami.

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Goswami, B., Bhandari, G. & Goswami, S. A quantitative precipitation forecast model using convective-cloud tracking in satellite thermal infrared images and adaptive regression: a case study along East Coast of India. Model. Earth Syst. Environ. (2020). https://doi.org/10.1007/s40808-020-00968-7

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Keywords

  • Quantitative precipitation forecast
  • Convective cloud
  • Mesoscale convective system
  • Thermal infrared images
  • Tracking
  • Clustering
  • Meteorology
  • Satellite image processing