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

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...

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Bibliographic Details
Published in:Modeling earth systems and environment 2021-06, Vol.7 (2), p.1097-1105
Main Authors: Goswami, Barnali, Bhandari, Gupinath, Goswami, Sanjay
Format: Article
Language:English
Subjects:
Atmospheric precipitations
Chemistry and Earth Sciences
Clouds
Computer Science
Convective clouds
Earth and Environmental Science
Earth Sciences
Earth System Sciences
Ecosystems
Environment
Flood predictions
Gauges
Hydrologic data
Infrared imagery
Infrared tracking
Math. Appl. in Environmental Science
Mathematical Applications in the Physical Sciences
Mathematical models
Meteorological satellites
Methodology
Original Article
Physics
Precipitation
Rain
Rain gauges
Rainfall
Satellite imagery
Satellite tracking
Statistics for Engineering
Synchronous satellites
Weather forecasting
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Summary: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.
ISSN:2363-6203
2363-6211
DOI:10.1007/s40808-020-00968-7