Tropical Cyclones (TCs) have devastating effects on several coastal regions worldwide. Accurate estimation of TC characteristics such as wind direction, wind speed, eye, rainfall bands, and radius of maximum wind helps to understand the evolution of TCs throughout their life cycle and plays an essential role in mitigating TC impact. Existing literature has focused on TC wind direction, intensity, cloud shape, and eye, but there has been limited research on the estimation of the Radius of Maximum Wind (RMW). An accurate estimate of RMW helps in identifying the regions where TC’s strongest wind and most intense cooling of the ocean occur. In this study, our objective is to formulate a method to determine the value of the RMW over the North Indian Ocean (NIO), this region has been chosen as it has the Bay of Bengal and the Arabian Sea which are one of the six globally prominent areas prone to TCs. Our study is on the relationship between the center of the TC, the estimated pressure drop at the center, and the RMW, using historical observations and mathematical correlations. We validate the accuracy of our developed method using three statistical measures: error percentage, t-test, and root mean square error. Our findings indicate that our method exhibits a mean absolute error percentage ranging from approximately \(6\%\) to \(32\%\), whereas the formulation of RMW from other studies has a mean absolute error range of \(13\%\) to \(128\%\) concerning IMD best track data.

热带气旋 (TC) 对全球多个沿海地区造成破坏性影响。准确估算TC的风向、风速、风眼、降雨带、最大风半径等特征，有助于了解TC全生命周期的演变过程，对减轻TC影响具有重要作用。现有文献主要集中在热带气旋风向、强度、云形和风眼方面，但对最大风半径（RMW）估计的研究有限。准确估计 RMW 有助于确定 TC 风力最强和海洋冷却最强烈的区域。在本研究中，我们的目标是制定一种方法来确定北印度洋 (NIO) 上空的 RMW 值，选择该地区是因为它拥有孟加拉湾和阿拉伯海，是全球六个海域之一易发生 TC 的突出区域。我们的研究是利用历史观测和数学相关性来研究 TC 中心、中心的估计压降和 RMW 之间的关系。我们使用三种统计指标来验证我们开发的方法的准确性：误差百分比、t 检验和均方根误差。我们的研究结果表明，我们的方法的平均绝对误差百分比范围约为\(6\%\)到\(32\%\)，而其他研究中的 RMW 公式的平均绝对误差范围为\(13\ %\)至\(128\%\)有关 IMD 最佳轨迹数据。