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Monu Yadav

Publications and source records attributed to Monu Yadav.

5 recordsLinked to original sources

Evaluation of the Radius of Maximum Wind over the North Indian Basin with the help of Tropical Cyclone characteristics

Tropical Cyclones (TCs) have devastating effects on several coastal regions worldwide. Precautionary knowledge about TC characteristics such as wind direction, wind speed, epicenter position, condensed vapor pressure measure, and radius of maximum can be highly valuable in disaster management and economic planning. Existing literature has focused on TC wind direction, intensity, cloud shape, and epicenter position, but there has been limited research on estimation of the Radius of Maximum Wind (RMW). Accurate estimation of RMW is crucial as errors can significantly impact wind and storm surge assessments and forecasts. In this study, our objective is to determine the RMW over the North Indian Ocean (NIO). We chose this region due to its location surrounded by the Bay of Bengal and Arabian Sea, making it 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. To address missing parameters in the best track database of the Indian Meteorological Department, we employ a local regression model. We validate the accuracy of our developed method using two statistical measures: error percentage and T-test. Numerous TC cases are discussed in the paper over the NIO. Our findings indicates that the suggested method exhibits an error percentage ranging from approximately $-63\%$ to $50\%$ when compared to the best track data provided by the Indian Meteorological Department (IMD). In contrast, the error percentages for two other references \cite{bib21, bib22} with the same best track data range from approximately $-26\%$ to $200\%$. Moreover, the T-test results demonstrate that our method outperforms than the other approaches in terms of statistical significance.

physics.ao-ph

Analysis of the Impact of North Indian Ocean Cyclonic Disturbance on Human and Economic Losses

This paper explores the features of cyclonic disturbances (CDs) in the North Indian Ocean (NIO) by utilizing data from 1990 to 2022. It investigates the occurrence rate of these disturbances and their effects on human and economic losses throughout the mentioned period. The analysis demonstrates a rising trend in the occurrence of CDs in the NIO. While there has been a slight decline in CD-related fatalities since 2015, but there has been a considerable increase in economic losses. These findings can be attributed to enhanced government initiatives in disaster prevention and mitigation in recent years, as well as rapid economic growth in regions prone to CDs. The study sheds light on the significance of addressing the impact of CDs on both human lives and economic stability in the NIO region.

physics.ao-ph

Detecting Tropical Cyclone from the basic overview of life cycle of Extremely Severe Cyclonic Storm, Tauktae

The Extremely Severe Cyclonic Storm (ESCS) Tauktae, which made landfall on the Gujarat coast on May 17, 2021, is discussed in the current study. The analysis is based on INSAT-3D and passive microwave (PMW) images, focusing on the cyclone's eye characteristics and intensity. The satellite images and products are utilized to determine the cyclone's intensity and the specific characteristics of its eye. The study showcases the variations in intensity and eye features of the cyclone throughout its life span, providing insights into the process of tropical cyclone intensification. The paper is structured to cover the methods for analysis, an overview of ESCS Tauktae's life cycle, the regulation of intensity based on Dvorak's technique, intensity estimation using ADT9.0 and comparison with SATCON method and Indian Meteorological Department (IMD) provided best track data. Furthermore, the formation of Tauktae's eye, timeframes for eye scenes, comparison with sea surface temperature data, and concluding thoughts are also discussed.

physics.ao-ph

Analyze the SATCON Algorithm's Capability to Estimate Tropical Storm Intensity across the West Pacific Basin

A group of algorithms for estimating the current intensity (CI) of tropical cyclones (TCs), which use infrared and microwave sensor-based images as the input of the algorithm because it is more skilled than each algorithm separately, are used to create a technique to estimate the TC intensity which is known as SATCON . In the current study, an effort was undertaken to assess how well the SATCON approach performed for estimating TC intensity throughout the west pacific basin from year 2017 to 2021. To do this, 26 TCs over the west pacific basin were analysed using the SATCON-based technique, and the estimates were compared to the best track predictions provided by the Regional Specialized Meteorological Centre (RSMC), Tokyo. The maximum sustained surface winds (Vmax) and estimated central pressures (ECP) for various ``T" numbers and types of storm throughout the entire year as well as during the pre-monsoon (March-July) and post-monsoon (July-February) seasons have been compared. When compared to weaker and very strong TCs, the ability of the SATCON algorithm to estimate intensity is determined to be rather excellent for mid-range TCs. We demonstrate that SATCON is more effective in the post-monsoon across the west pacific basin than in the pre-monsoon by comparing the algorithm results.

physics.ao-ph

Identification of storm eye from Satellite image data using fuzzy logic with machine learning

This research presents a study of a unique technique for identifying storm eye that is based on fuzzy logic and image processing with the help of cloud images. Fuzzy logic is a term that refers to complicated systems with unclear behaviour caused by a number of different circumstances. It provides the ability to model the dynamic behavior of the storm and determines the location of the best eye in an area of interest. After that, image processing is applied to enable accurate eye positioning based on the search results. The experimental results are analyzing the storm eye position with approxiamtely $98\%$ accurate compared to the India meteorological department provided best track data and Cooperative Institute for Meteorological Satellite Studies provided Advances Dvorak Technique data. As a result, the identification of storm's eye location using this technique can be found to improve significantly. Using the present technique, it is possible to determine the eye entirely automatically, which replacing the manual method that has been employed in the past.

math.OC