search for




 

Atlantic storm modeling using the empirical orthogonal functions of sea surface temperatures
Journal of the Korean Data & Information Science Society 2021;32:1363-71
Published online November 30, 2021;  https://doi.org/10.7465/jkdi.2021.32.6.1363
© 2021 Korean Data and Information Science Society.

Sangwan Kim1 · Yongku Kim2

12Department of Statistics, Kyungpook National University
Correspondence to: 1 Graduate Student, Department of Statistics, Kyungpook National University, Daegu 41566, Korea
2 Corresponding author: Associate professor, Department of Statistics, Kyungpook National University, Daegu 41566, Korea. E-mail: kim.1252@knu.ac.kr
This research was supported by Kyungpook National University Research Fund, 2021.
Received September 25, 2021; Revised October 9, 2021; Accepted October 12, 2021.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Recently, both the numbers and intensities of Atlantic tropical storms show an upward trend under the global warming condition. Statistical models play a very important role in understanding how the climate factors such as the cycle of El Ni~no/La Ni~na, the pattern of the northern hemisphere jet stream and tropical Atlantic sea surface temperatures in uence tropical storm activity. This paper proposes a hierarchical and statistical model which predicts the number of the Atlantic tropical storms using sea surface temperatures. Especially, Atlantic sea surface temperatures are incorporated into the model through empirical orthogonal functions. The proposed model is illustrated using the climate data during 1900-2002.
Keywords : Atlantic tropical storm, empirical orthogonal function, sea surface temperature, statistical modeling.