A Deep Learning Nowcasting Model for Convective Cell Occurrence in Taiwan-Reference-Cited by-同舟云学术

A Deep Learning Nowcasting Model for Convective Cell Occurrence in Taiwan

Published:2024 Issue:0 Volume:20 Page:130-137
ISSN:1349-6476
Container-title:SOLA
language:en
Short-container-title:SOLA

Author:

Pan Yu-Tai¹,Chen Buo-Fu¹,Chen Dian-You¹,Chang Chia-Tung¹,Huang Treng-Shi²

Affiliation:

1. Center for Weather and Climate Disaster Research, National Taiwan University

2. Central Weather Administration

Publisher

Meteorological Society of Japan

Link

https://www.jstage.jst.go.jp/article/sola/20/0/20_2024-018/_pdf

Reference24 articles.

1. Ashesh, A., C. Chang, B. Chen, H. Lin, B. Chen, and T. Huang, 2022: Accurate and clear quantitative precipitation nowcasting based on a deep learning model with consecutive attention and rain-map discrimination. Artif. Intell. Earth Syst., 1, e210005, doi:10.1175/AIES-D-21-0005.1.

2. Ayzel, G., T. Scheffer, and M. Heistermann, 2020: RainNet v1.0: A convolutional neural network for radar-based precipitation nowcasting. Geosci. Model Dev., 13, 2631-2644, doi:10.5194/gmd-13-2631-2020.

3. Bell, M. M., and co-authors, 2023: Overview of the Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP) 2022. Third Symp. Mesoscale Proc., 103rd Amer. Meteor. Soc. Ann. Meeting, Denver, CO, Amer. Meteor. Soc., 8-12 Jan 2023, P301.

4. Chang, P.-L., and co-authors, 2021: An operational multi-radar multi-sensor QPE system in Taiwan. Bull. Amer. Meteor. Soc., 102, E555-E577, doi:10.1175/BAMS-D-20-0043.1.

5. Chung, K.-S., and I.-A. Yao, 2020: Improving radar echo Lagrangian extrapolation nowcasting by blending numerical model wind information: Statistical performance of 16 typhoon cases. Mon. Wea. Rev., 148, 1099-1120, doi:10.1175/MWR-D-19-0193.1.