Deep learning approach for detecting tropical cyclones and their precursors in the simulation by a cloud-resolving global nonhydrostatic atmospheric model

D Matsuoka, M Nakano, D Sugiyama… - Progress in Earth and …, 2018 - Springer
We propose a deep learning approach for identifying tropical cyclones (TCs) and their
precursors. Twenty year simulated outgoing longwave radiation (OLR) calculated using a …

A novel data-driven tropical cyclone track prediction model based on CNN and GRU with multi-dimensional feature selection

J Lian, P Dong, Y Zhang, J Pan, K Liu - Ieee Access, 2020 - ieeexplore.ieee.org
Strong tropical cyclones have made a drastic effect on human life and natural environment.
As large amounts of meteorological data and monitoring data continue to accumulate …

DeepFR: A trajectory prediction model based on deep feature representation

W Qin, J Tang, S Lao - Information Sciences, 2022 - Elsevier
Mining key information from trajectory data can effectively help people in their life. In the
case of hurricanes, trajectory prediction can avoid losses caused by disasters. Deep …

[HTML][HTML] Cyclone trajectory and intensity prediction with uncertainty quantification using variational recurrent neural networks

A Kapoor, A Negi, L Marshall, R Chandra - Environmental Modelling & …, 2023 - Elsevier
Cyclone track forecasting is a critical climate science problem involving time-series
prediction of cyclone location and intensity. Machine learning methods have shown much …

A typhoon trajectory prediction model based on multimodal and multitask learning

W Qin, J Tang, C Lu, S Lao - Applied Soft Computing, 2022 - Elsevier
Artificial intelligence technology has been widely used in various fields in recent years. In
the case of typhoons, trajectory prediction technology can reduce the loss of human life and …

Globenet: Convolutional neural networks for typhoon eye tracking from remote sensing imagery

S Hong, S Kim, M Joh, S Song - arxiv preprint arxiv:1708.03417, 2017 - arxiv.org
Advances in remote sensing technologies have made it possible to use high-resolution
visual data for weather observation and forecasting tasks. We propose the use of multi-layer …

Comparison of different forecasting tools for short-range lightning strike risk assessment

A Bouchard, M Buguet, A Chan-Hon-Tong, J Dezert… - Natural Hazards, 2023 - Springer
Thunderstorms, the main generator of lightning on earth, are characterized by the presence
of extreme atmospheric conditions (turbulence, hail, heavy rain, wind shear, etc.) …

Forecasting tropical cyclone tracks in the northwestern Pacific based on a deep-learning model

L Wang, B Wan, S Zhou, H Sun… - Geoscientific Model …, 2023 - gmd.copernicus.org
Tropical cyclones (TCs) are one of the most severe meteorological disasters, making rapid
and accurate track forecasts crucial for disaster prevention and mitigation. Because TC …

Tropical cyclone track prediction with an encoding-to-forecasting deep learning model

P Dong, J Lian, H Yu, J Pan, Y Zhang… - Weather and …, 2022 - journals.ametsoc.org
Recently, with the accumulation of remote sensing data, the traditional tropical cyclone (TC)
track prediction methods (eg, dynamic methods and statistical methods) have limitations in …

Cyclone track prediction with matrix neural networks

Y Zhang, R Chandra, J Gao - 2018 International Joint …, 2018 - ieeexplore.ieee.org
Although machine learning and statistical methods have been extensively used to study
cyclones, the prediction of cyclone trajectories remains a challenging problem. Matrix neural …