Multi-Factor Intensity Estimation for Tropical Cyclones in the Western North Pacific Based on the Deviation Angle Variance Technique  

作　　者：Wei ZHONG Meng YUAN Hexin YE Xia LUO 

机构地区：[1]College of Meteorology and Oceanology,National University of Defense Technology,Nanjing 211101 [2]Submarine College of Navy,Qingdao 266199

出　　处：《Journal of Meteorological Research》2020年第5期1038-1051,共14页气象学报（英文版）

基　　金：Supported by the National Key Research and Development Program of China(2018YFC1507402);National Natural Science Foundation of China(42075011)。

摘　　要：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.

关 键 词：deviation angle variance(DAV)technique tropical cyclone(TC) intensity estimation 

分 类 号：P732.3[天文地球—海洋科学]