4th Land Cyclone in 80 Years Forming Over Arabian Sea as Gujarat Faces Heavy Rains
A deep depression over the Saurashtra and Kutch regions is poised to become a cyclone, marking a rare meteorological event over the Arabian Sea, according to the India Meteorological Department (IMD). This would be only the fourth time in 80 years that a weather system has transitioned from land to a cyclone after moving out to sea.
Highlights:
- Rare Phenomenon: Deep depression over Gujarat coast to intensify into a cyclone in the Arabian Sea.
- Severe Weather: Coastal Gujarat to experience gusty winds and heavy rain; fishermen advised to avoid the sea until August 31.
- Historical Significance: This is only the fourth time in 80 years that a land depression has transitioned to a cyclone over the Arabian Sea.
As of Thursday, the deep depression had moved slowly westwards at a speed of approximately three kilometers per hour and was concentrated around noon, as per the IMD's latest weather bulletin. This system is expected to continue its west-southwestward trajectory, emerging into the Arabian Sea near the Kutch coast, and intensifying into a cyclonic storm by August 30.
"This event is particularly significant because it is the first time in nearly five decades that we are witnessing such a transition," noted IMD scientist Soma Sen Roy. Previous instances of land depressions transforming into cyclones over the Arabian Sea occurred in 1944, 1964, and 1976.
The IMD has issued warnings for heavy to extremely heavy rainfall across the western coast, especially in Gujarat, with gusty winds reaching speeds of up to 65 kmph expected over Saurashtra, Kutch, and parts of south Gujarat. Coastal areas of north Maharashtra are also likely to experience strong winds and rain over the next two days.
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Given the severe weather conditions, fishermen have been advised to stay away from the sea along the Gujarat and north Maharashtra coasts until Saturday. This rare meteorological event offers a valuable opportunity for researchers to enhance predictive models and understand the dynamics of such unusual weather patterns.