Machine learning in tropical cyclone forecast modeling: A review
Tropical cyclones have always been a concern of meteorologists, and there are many
studies regarding the axisymmetric structures, dynamic mechanisms, and forecasting …
studies regarding the axisymmetric structures, dynamic mechanisms, and forecasting …
A review on the application of machine learning methods in tropical cyclone forecasting
Z Wang, J Zhao, H Huang, X Wang - Frontiers in Earth Science, 2022 - frontiersin.org
At present, there is still a bottleneck in tropical cyclone (TC) forecasting due to its complex
dynamical mechanisms and various impact factors. Machine learning (ML) methods have …
dynamical mechanisms and various impact factors. Machine learning (ML) methods have …
Improvement of typhoon intensity forecasting by using a novel spatio-temporal deep learning model
Typhoons can cause massive casualties and economic damage, and accurately predicting
typhoon intensity has always been a hot topic both in theory and practice. In consideration …
typhoon intensity has always been a hot topic both in theory and practice. In consideration …
[HTML][HTML] Recent advances in research and forecasting of tropical cyclone track, intensity, and structure at landfall
This review prepared for the fourth International Workshop on Tropical Cyclone Landfall
Processes (IWTCLP-4) summarizes the most recent (2015-2017) theoretical and practical …
Processes (IWTCLP-4) summarizes the most recent (2015-2017) theoretical and practical …
Moisture sources for precipitation associated with major hurricanes during 2017 in the North Atlantic basin
A Pérez‐Alarcón, P Coll‐Hidalgo… - Journal of …, 2022 - Wiley Online Library
Abstract The 2017 North Atlantic tropical cyclone season was among the most active in the
last two decades, with 17 named storms, of which six reached the major hurricane (MH) …
last two decades, with 17 named storms, of which six reached the major hurricane (MH) …
Tropical cyclone intensity change prediction based on surrounding environmental conditions with deep learning
X Wang, W Wang, B Yan - Water, 2020 - mdpi.com
Tropical cyclone (TC) motion has an important impact on both human lives and
infrastructure. Predicting TC intensity is crucial, especially within the 24 h warning time. TC …
infrastructure. Predicting TC intensity is crucial, especially within the 24 h warning time. TC …
A climatology of southwest Indian Ocean tropical systems: Their number, tracks, impacts, sizes, empirical maximum potential intensity, and intensity changes
MD Leroux, J Meister, D Mekies… - Journal of Applied …, 2018 - journals.ametsoc.org
Abstract A 17-yr “climatology” of tropical-system activity, track, size, and 24-h intensity
change in the southwest Indian Ocean (SWIO) is developed and analyzed in comparison …
change in the southwest Indian Ocean (SWIO) is developed and analyzed in comparison …
Tropical cyclone intensity prediction by inter-and intra-pattern fusion based on multi-source data
Tropical cyclones (TCs) are one of the most destructive natural disasters, which can bring
huge life and economic losses to the global coastal areas. Accurate TC intensity prediction …
huge life and economic losses to the global coastal areas. Accurate TC intensity prediction …
Rapid decay of slowly moving Typhoon Soulik (2018) due to interactions with the strongly stratified northern East China Sea
Typhoon Soulik decayed rapidly via two‐way interaction with the northern East China Sea,
the extratropical shelf region, before landing on the Korean Peninsula on 23 August 2018. In …
the extratropical shelf region, before landing on the Korean Peninsula on 23 August 2018. In …
Predicting rapid intensification of tropical cyclones in the western North Pacific: a machine learning and net energy gain rate approach
SH Kim, W Lee, HW Kang, SK Kang - Frontiers in Marine Science, 2024 - frontiersin.org
In this study, a machine learning (ML)-based Tropical Cyclones (TCs) Rapid Intensification
(RI) prediction model has been developed by using the Net Energy Gain Rate Index (NGR) …
(RI) prediction model has been developed by using the Net Energy Gain Rate Index (NGR) …