A novel framework for estimating probable maximum tropical cyclone parameters for ocean basins with sparse records

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Authors: Diljit Dutta, Jaya Bhatt, Prof. V.V. Srinivas
Cited by: 0
References: 81

Abstract

A Probable Maximum Tropical Cyclone (PMTC) is a hypothetical steady-state tropical cyclone with the highest possible maximum sustained wind speed ( V max ) that can reasonably occur in an ocean basin. Its estimate is desirable for designing critical coastal infrastructures (e.g., nuclear plants) to ensure their safety from cyclone hazards. PMTC parameters ( V max and pressure drop from the cyclone's center to periphery Δ P ) are often determined by frequency analysis of V max and Δ P from historical tropical cyclones (TCs), which becomes challenging when data are sparse. This paper proposes a novel framework to arrive at effective estimates of the PMTC parameters in ocean basins with sparse cyclone records. It involves estimating the V max of PMTC using Bethlahmy method, and validating it by comparing with the theoretical maximum V max (i.e., ) corresponding to the maximum potential intensity of TC. The is determined by (i) developing a quantile regression relationship between V max of historical TCs and the corresponding genesis region's sea surface temperature (SST), and (ii) extrapolating the relationship to the end of the 21 st century, considering SST projected for the highest emission climate change scenario. Subsequently, the Δ P corresponding to the estimated V max of PMTC is determined using a newly developed wind-pressure relationship. The potential of the framework over existing methods in yielding reliable PMTC parameters is demonstrated through application to two sub-basins (Arabian Sea, Bay of Bengal) in the North Indian Ocean. The results were consistent across cyclones corresponding to different El Niño–Southern Oscillation phases, which further highlights the framework's efficacy.

Fields of Study & Subjects

Tropical and Extratropical Cyclones Research Climate variability and models Ocean Waves and Remote Sensing

Publication details

Journal / source
Weather and Climate Extremes
Volume
52
Pages
100891–100891
Publication date
15 March 2026
Language
EN