期刊信息/Journal information
：中国气象局上海台风研究所
：LEI Xiaotu;YU Jixin
：季刊
：2225-6032
：tcrr@mail.typhoon.gov.cn
：200030
：中国上海市浦西路166号热带气旋研究与评论编辑部
Tropical Cyclone Research and Review/Journal 热带气旋研究与评论（英文版）
Tropical Cyclone Research and Review is an international journal focusing on tropical cyclone foreca...展开全部>>
收录年代
Application of stream function in tracking a quasi-closed circulation and its characteristics in developing and non-developing tropical cyclones over the North Indian Ocean
R.Emmanuel;Medha Deshpande;Anandh T.S.;Ralf Toumi;Ganadhi Mano Kranthi;S.T.Ingle;P.185-202
Research progress on the influence of water vapor on tropical cyclone intensity
Yubin Yu;Dajun Zhao;Huan Tang;Yuhao Zheng;P.219-229
Response of aquatic organisms as an eco-biotic indicator with response to cyclonic intervention in the large river system:A case study of river Ganga,India,during cyclone YAAS
Basanta Kumar Das;Nitish Kumar Tiwari;Trupti Rani Mohanty;Shreya Roy;Archisman Ray;Supriti Bayen;Subhadeep Das Gupta;Kausik Mondal;Himanshu Sekhar Swain;Raju Baitha;Mitesh Hiradas Ramteke;Canciyal Johnson;Thangjam Nirupada Chanu;Manisha Bhor;P.249-269
From vulnerability to resilience:Addressing the causes,impacts,and solutions for recurrent flash floods in the Philippines
Alice T.Rivera;Jim Boy G.Dela Vega;P.301-310
On the physics of a new time-dependent theory of tropical cyclone intensification
Roger K.Smith;Michael T.Montgomery;P.297-300
Analysis of tropical cyclone eye over the North Indian Ocean during 2013-2023
Sunil Kumar;Shashi Kant;Amrit Kumar;P.287-296
The influence of El Nino-Southern Oscillation(ENSO)on the characteristics of tropical cyclones in Indonesia waters
Kadek Krisna Yulianti;Nining Sari Ningsih;Rima Rachmayani;Eko Prasetyo;P.270-286
Challenges in forecasting super typhoon Yagi(2024)
Yumei Li;Johnny CL.Chan;Xun Li;Wen Feng;Yu Zhang;P.317-322
Typhoon science meets artificial intelligence:A roundtable on bridging physics-based and data-driven paradigms
Zeyi Niu;Zhe-Min Tan;Hui Yu;Jian-Feng Gu;Guomin Chen;Wei Huang;P.311-316
Forecasting the frequency and magnitude of hurricanes in the Yucatan Peninsula,Mexico,in the period from 2025 to 2034 using convolutional neural networks(CNNs),Long Short-Term Memory networks(LSTMs)and statistical models
Hermes De Gracia;Jorge Celeron;Consuelo Diaz;Aristeo Hernandez;Victoria Serrano;P.237-248
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