Estimation of the Area and Precipitation Associated with a Tropical Cyclone Biparjoy by using Image Processing
Shikha Verma, Kuldeep Srivastava, Akhilesh Tiwari, Shekhar Verma

TL;DR
This study uses satellite image processing to estimate the precipitation and affected area of Cyclone Biparjoy, providing valuable data for disaster management and climate impact assessment.
Contribution
It introduces a remote sensing-based method to quantify cyclone-induced precipitation and area coverage, enhancing predictive capabilities for tropical cyclone impacts.
Findings
Biparjoy caused an average of 53.14 mm/day rainfall across India.
The cyclone affected an area of approximately 412,000 square kilometers.
Localized intensity varied significantly across different Indian states.
Abstract
The rainfall associated with Topical Cyclone(TC) contributes a major amount to the annual rainfall in India. Due to the limited research on the quantitative precipitation associated with Tropical Cyclones (TC), the prediction of the amount of precipitation and area that it may cover remains a challenge. This paper proposes an approach to estimate the accumulated precipitation and impact on affected area using Remote Sensing data. For this study, an instance of Extremely Severe Cyclonic Storm, Biparjoy that formed over the Arabian Sea and hit India in 2023 is considered in which we have used the satellite images of IMERG-Late Run of Global Precipitation Measurement (GPM). Image processing techniques were employed to identify and extract precipitation clusters linked to the cyclone. The results indicate that Biparjoy contributed a daily average rainfall of 53.14 mm/day across India and…
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Taxonomy
TopicsPrecipitation Measurement and Analysis
