Classification of Middle Tropospheric Systems over the Arabian Sea and Western India
Pradeep Kushwaha, Jai Sukhatme, Ravi S. Nanjundiah

TL;DR
This study classifies Middle Tropospheric Cyclones over the Arabian Sea and Western India using machine learning, revealing four dominant formation patterns linked to large-scale environmental factors, aiding prediction of extreme rainfall events.
Contribution
Introduces an unsupervised machine learning approach to classify MTCs and identifies their formation mechanisms and environmental dependencies.
Findings
Four main weather patterns leading to MTC formation identified.
Type 2a MTCs have the highest rain rate of 60 mm/day.
Formation patterns are linked to Boreal Summer Intraseasonal Oscillation phases.
Abstract
The formation of Middle Tropospheric Cyclones (MTCs) that are responsible for a large portion of annual precipitation and extreme rainfall events over western India is studied using an unsupervised machine learning algorithm and cyclone tracking. Both approaches reveal four dominant weather patterns that lead to the genesis of these systems; specifically, re-intensification of westward moving synoptic systems from Bay of Bengal (Type 1, 51%), in-situ formation with a coexisting cyclonic system over the Bay of Bengal that precedes (Type 2a, 31%) or follows (Type 2b, 10%) genesis in the Arabian Sea, and finally in-situ genesis within a northwestward propagating cyclonic anomaly from the south Bay of Bengal (Type 2c, 8%). Thus, a large fraction of rainy middle tropospheric synoptic systems in this region form in association with cyclonic activity in the Bay of Bengal. The four variants…
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Taxonomy
TopicsTropical and Extratropical Cyclones Research · Climate variability and models · Meteorological Phenomena and Simulations
