Convective Cloud Detection and Tracking Using the New-Generation Geostationary Satellite Over South China-Reference-Cited by-同舟云学术

Convective Cloud Detection and Tracking Using the New-Generation Geostationary Satellite Over South China

Published:2023 Issue: Volume:61 Page:1-12
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Yang Yikun¹^ORCID,Zhao Chuanfeng¹^ORCID,Sun Yue²,Chi Yulei²,Fan Hao²

Affiliation:

1. Department of Atmospheric and Oceanic Sciences, School of Physics and the China Meteorological Administration Tornado Key Laboratory, Peking University, Beijing, China

2. Faculty of Geographical Science, Beijing Normal University, Beijing, China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10195250.pdf?arnumber=10195250

Reference63 articles.

1. A long-term tropical mesoscale convective systems dataset based on a novel objective automatic tracking algorithm

2. Detection of convective initiation using Meteosat SEVIRI: implementation in and verification with the tracking and nowcasting algorithm Cb-TRAM

3. Mesoscale Convective Systems in the Asian Monsoon Region From Advanced Himawari Imager: Algorithms and Preliminary Results

4. Classifying clouds around the globe with the CloudSat radar: 1-year of results

5. Full‐Tracking Algorithm for Convective Thunderstorm System From Initiation to Complete Dissipation

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Evolution Characteristics of Convective Clouds With Relatively Small Scales Over South China;Journal of Geophysical Research: Atmospheres;2024-08-06

2. Using Machine Learning to Predict Cloud Turbulent Entrainment‐Mixing Processes;Journal of Advances in Modeling Earth Systems;2024-08

3. Methodology for Severe Convective Cloud Identification Using Lightweight Neural Network Model Ensembling;Remote Sensing;2024-06-07

4. Observational evidence and mechanisms of aerosol effects on precipitation;Science Bulletin;2024-05

5. Convective Cloud Detection From Himawari-8 Advanced Himawari Imager Data Using a Dual-Branch Deformable Convolutional Network;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024