RSRW DATA, CSP AND CYCLONE TRACK PREDICTION

Authors:

Indrajit Ghosh,Sukhen Das,Nabajit Chakravarty,

DOI NO:

https://doi.org/10.26782/jmcms.2022.02.00005

Keywords:

CSP,Radial velocity,Cross-radial velocity,RSRW,Cyclone eye,Tropical cyclone,

Abstract

Tropical cyclones are gradually becoming an increasing menace to the coastal human civilization throughout the World. This is due to their increased frequency and intensity of occurrence nowadays. With the global increase of sea surface temperature a marked increase in the percentage of their formation from depression happening especially in the tropical oceans of the World. The Coromandel Coast of India is not an exception to these. To mitigate their devastation effect on mankind we need to study the details of their dynamics governing equations and hence develop suitable solutions. In this paper the numerical value of a stability parameter, viz. CSP is determined employing the RSRW data of one tropical cyclone that has hit the Coromandel Coast of India in 2010. CSP is a dimensionless parameter that we obtained from the analytic solution of cyclone dynamics governing equations.

Refference:

I. Baisya H, Pattanaik S, Chakraborty T (2020) A coupled modeling approach to understand ocean coupling and energetics of tropical cyclones in the Bay of Bengal basin. Atmospheric Research, 246, 105092. https://doi.orgII/10.1016/j.atmosres.2020.105092.
II. Emanuel K (2005) Increasing destructiveness of tropical cyclones over the past 30 years. Nature, 436, 686-688. https://doi:10.1038/nature03096.
III. Ghosh I, Chakravarty N (2018) Tropical cyclones: expressions for velocity components and stability parameter. Natural Hazards, 94, 1293-1304. https://doi:10.1007/s11069-018-3477-7.
IV. Goff CG, Chan JCH, Goff J, Gadd P (2016) Late holocene record of environmental changes, cyclones and tsunamis in a coastal lake, Mangania, Cook Islands Arc. 25, 333-349. https://doi:10.1111/iar.12153.
V. Köhle MP, Promper C, Glade T (2016) A common methodology for risk assessment and mapping of climate change related hazards- implications for climate change adaptation policies. MDPI Article Climate, 4, 8. https://doi:10.3390/cli4010008.
VI. Lala S, Chakravarty N, Das MK (2014) Mathematical explanation of earlier dissipation of the energy of tilted cyclone. Journal of Climatology & Weather Forecasting, 2, 113. https://doi.org/10.4172/2332-2594.1000115.
VII. Nott JF (2003) Intensity of prehistoric tropical cyclones. Journal of Geophysical Research, 108, D7 4212. https://doi.org/10.1029/2002JD002726.
VIII. Posada R, Ortega GE, Sanchez JL, Lopez L (2012) Verification of the MM5 model using radiosonde data from Madrid-Barajas Airport. Atmospheric Research, 122, 174-182. https://doi.org/10.1016/j.atmosres.2012.10.018
IX. Rezapour M (2015) A new methodology of classification of tropical cyclones: the importance of rainfall. https://espace.library.uq.edu.au/view/UQ:384798/s42713083-final-thesis.pdf. Accessed 2015.
X. Ritchie l, Vigh JL (2010) Tropical cyclone structure and intensity change: Inner core impacts Rapporteur Report, topic 1.2 conference paper. https://doi:10.13140/2.1.1825.8247
XI. Shevtsov BM, Ekaterina P, Holzworth RH (2015) Relation of tropical cyclone structure with thunder storm activity. Conference paper. https://doi:10.1117/12.2203348.
XII. Stern DP, Vigh JL, Zhang F (2015) Revisiting the relationship between eyewall contraction and intensification. Journal of Atmospheric Science, 72, 1283-1306. https://doi:10.1175/ JAS-D-14-0261.1
XIII. Tapiador FJ (2008) Hurricane footprints in global climate models. Entropy, 10, 613-620. https://doi:10.3390/e10040613.
XIV. Zehnder JA (2019) Tropical cyclone. https://www.britannica.com/science/tropicalcyclone (2018). Accessed 2020.

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