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

Overview of attention for article published in Progress in Earth and Planetary Science, December 2018

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In the top 25% of all research outputs scored by Altmetric
Among the highest-scoring outputs from this source (#21 of 556)
High Attention Score compared to outputs of the same age (92nd percentile)
High Attention Score compared to outputs of the same age and source (89th percentile)

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The most recent citing publications are shown below. View all 60 publications that cite this research output on Dimensions.

Predicting the spatiotemporal characteristics of atmospheric rivers: A novel data-driven approach

Article in Global and Planetary Change (December 2023)

Three-dimensional temporal-spatial attention for tropical cyclone forecast

Conference proceeding in Proceedings of SPIE (October 2023)

Recent global nonhydrostatic modeling approach without using a cumulus parameterization to understand the mechanisms underlying cloud changes due to global warming

Article in Progress in Earth and Planetary Science (August 2023)