  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
the Arabian Sea, with the Indian boundary receiving 11.59 mm/day, covering an
extensive 411.76 thousand square kilometers. The localized intensity and
variability observed in states like Gujarat, Rajasthan, Madhya Pradesh, and
Uttar Pradesh highlight the need for tailored response measures, emphasizing
the importance of further research to enhance predictive models and disaster
readiness, crucial for building resilience against the diverse impacts of
tropical cyclones.
