Mayurbhanj district in Odisha bears brunt of low-pressure-induced rainfall

District tops vulnerability index of low pressure rains, finds IIT-BBS study

Published: 14th November 2022 09:29 AM  |   Last Updated: 14th November 2022 09:29 AM   |  A+A-

heavy rainfall image

Image used for representational purpose only. (File Photo | PTI)

By Express News Service

BHUBANESWAR: Mayurbhanj district in Odisha is the most vulnerable to low-pressure system (LPS) induced rainfall, followed by Kalahandi, Ganjam and Puri, found a study carried out by IIT-Bhubaneswar.

The study ‘Role of cloud microphysics and energetics in regulating different phases of the monsoon low-pressure systems over the Indian region’ was carried out by researcher Vivekananda Hazra and associate professor of School of Earth, Ocean and Climate Sciences IIT-Bhubaneswar, Sandeep Pattnaik and published in the quarterly journal of Royal Meteorological Society also found a possible clue on how some of the low-pressure systems during monsoon intensified into a deep depression.

As many as 26 low-pressure systems, 12 related to depressions and 14 related to deep depressions, formed over the Bay of Bengal and moved north-westwards towards the Indian mainland during the 2001-2017 period were taken into consideration for the model sensitivity experiment.

A total of 130 simulations were carried out and from the experiment in which we came to know that Mayurbhanj is on top among all districts in the vulnerability index (VI) of rainfall due to the low-pressure system, said Prof Pattnaik, the corresponding author of the research.

“We found that the track of depression and deep depression during monsoon has majorly remained towards North Odisha and West Bengal for which Mayurbhanj has been in the VI. The hilly terrain and the impact of the vegetation could be the other reasons that have put the district in the first layer of vulnerability. More study is required to ascertain these factors,” he said.

Similarly, the track from Puri to Srikakulam also puts Puri, Ganjam and Kalahandi vulnerable to system-induced rainfall, he said.

The IIT faculty said they found that thermodynamically, deep depressions are more efficient at converting latent energy into kinetic energy compared to depressions. This helps the process of intensification by generating more kinetic energy associated with large water vapour consumption.

As operational forecasting agencies face a significant challenge to make accurate predictions of these severe weather events, the findings of the study are expected to help with the localised forecast, policy planning, disaster preparedness, mitigation, and adaptation, the IIT professor said.


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