Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 8
Articles | Volume 16, issue 8
https://doi.org/10.5194/gmd-16-2167-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-2167-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 8
Methods for assessment of models
 | 
20 Apr 2023
Methods for assessment of models |  | 20 Apr 2023

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

Liang Wang, Bingcheng Wan, Shaohui Zhou, Haofei Sun, and Zhiqiu Gao

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Latest update: 23 Nov 2024
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Short summary
The past 24 h TC trajectories and meteorological field data were used to forecast TC tracks in the northwestern Pacific from hours 6–72 based on GRU_CNN, which we proposed in this paper and which has better prediction results than traditional single deep-learning methods. The historical steering flow of cyclones has a significant effect on improving the accuracy of short-term forecasting, while, in long-term forecasting, the SST and geopotential height will have a particular impact.
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