Multi-Factor Intensity Estimation for Tropical Cyclones in the Western North Pacific Based on the Deviation Angle Varian
- PDF / 2,212,196 Bytes
- 14 Pages / 611.98 x 792 pts (letter) Page_size
- 3 Downloads / 168 Views
Volume 34
OCTOBER 2020
Multi-Factor Intensity Estimation for Tropical Cyclones in the Western North Pacific Based on the Deviation Angle Variance Technique Wei ZHONG1, Meng YUAN2*, Hexin YE1, and Xia LUO1 1 College of Meteorology and Oceanology, National University of Defense Technology, Nanjing 211101 2 Submarine College of Navy, Qingdao 266199 (Received January 13, 2020; in final form June 7, 2020)
ABSTRACT In this paper, the infrared cloud images from Fengyun series geostationary satellites and the best track data from the China Meteorological Administration (CMA-BST) in 2015–2017 are used to investigate the effects of two multifactor models, generalized linear model (GLM) and long short-term memory (LSTM) model, for tropical cyclone (TC) intensity estimation based on the deviation angle variance (DAV) technique. For comparison, the typical singlefactor Sigmoid function model (SFM) with the map minimum value of DAV is also used to produce TC intensity estimation. Sensitivity experiments regarding the DAV calculation radius and different training data groups are conducted, and the estimation precision and optimum calculation radius for DAV in the western North Pacific (WNP) are analyzed. The results show that the root-mean-square-error (RMSE) of the single-factor SFM is 8.79–13.91 m s−1 by using the individual years as test sets and the remaining two years as training sets with the optimum calculation radius of 550 km. However, after selecting and using the high-correlation multiple factors from the same test and training data, the RMSEs of GLM and LSTM models decrease to 5.93–8.68 and 4.99–7.00 m s−1 respectively, with their own optimum calculation radii of 350 and 400 km. All the sensitivity experiments indicate that the SFM results are significantly influenced by the DAV calculation radius and characteristics of the training set data, while the results of multi-factor models appear more stable. Furthermore, the multi-factor models reduce the optimum radius within the process of DAV calculation and improve the precision of TC intensity estimation in the WNP, which can be chosen as an effective approach for TC intensity estimation in marine areas. Key words: deviation angle variance (DAV) technique, tropical cyclone (TC), intensity estimation Citation: Zhong, W., M. Yuan, H. X. Ye, et al., 2020: Multi-factor intensity estimation for tropical cyclones in the western North Pacific based on the deviation angle variance technique. J. Meteor. Res., 34(5), 1038–1051, doi: 10.1007/s13351-020-9216-5.
1.
Introduction
Tropical cyclone (TC) is one of the most catastrophic weather systems in the world (Zhang and Guo, 2008). As the majority of meteorological observations are on the land, whereas the genesis and development of TCs mostly occur over the ocean, it is difficult for us to directly acquire the information on the TC structure, intensity, trajectory, and variation, due to the shortage of observations and limits in data extraction techniques. Therefore, the detection and forecast of TCs have always been the mos
Data Loading...
