Cloud‐Top Cooling Rate Based Rapidly Developing Convection Detection Using FY‐2F Satellite Images

Rapidly developing convection (RDC) serves as a precursor to severe weather events. Timely detection of RDC (DRDC) through satellite remote sensing technology is critical for advancing nowcasting capabilities. With the operational deployment of the rapid scanning mode on China’s FengYun‐2F (FY‐2F) meteorological satellite, it provides multichannel rapid scanning data with a temporal resolution of 6 min and a spatial resolution of 5 km, making it possible to detect RDC operationally using satellites. Leveraging the characteristics of FY‐2F multichannel data, this study proposes a novel method for RDC detection. The method employs multichannel identification of the cloud‐top cooling rate (CTC) combined with a three‐test CTC filter. After filtering, local brightness temperature (Tb) minima are identified for each RDC, and a flood‐fill algorithm is applied to surrounding pixels to delineate rapidly developing convective bodies. This study introduces the innovative application of multichannel RDC identification and a CTC filter that incorporates three tests. Experimental validation using August 2014 scanning data (106° E–113° E, 27° N–31° N) demonstrates robust performance, with a probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) of 0.88, 0.16, and 0.76, respectively, confirming the method’s accuracy in identifying RDC.

Authors

Institutions

Publication Details

Journal
Advances in Meteorology
Published
2026-01-01
DOI
https://doi.org/10.1155/adme/5676585
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cloud‐Top Cooling Rate Based Rapidly Developing Convection Detection Using FY‐2F Satellite Images

Q. C. Zhang, H. Lü, Jia Liu, Yang Zhang
Advances in Meteorology
Meteorological Phenomena and Simulations
article

Cloud‐Top Cooling Rate Based Rapidly Developing Convection Detection Using FY‐2F Satellite Images

Q. C. Zhang, H. Lü, Jia Liu, Yang Zhang
article en

Abstract

Rapidly developing convection (RDC) serves as a precursor to severe weather events. Timely detection of RDC (DRDC) through satellite remote sensing technology is critical for advancing nowcasting capabilities. With the operational deployment of the rapid scanning mode on China’s FengYun‐2F (FY‐2F) meteorological satellite, it provides multichannel rapid scanning data with a temporal resolution of 6 min and a spatial resolution of 5 km, making it possible to detect RDC operationally using satellites. Leveraging the characteristics of FY‐2F multichannel data, this study proposes a novel method for RDC detection. The method employs multichannel identification of the cloud‐top cooling rate (CTC) combined with a three‐test CTC filter. After filtering, local brightness temperature (Tb) minima are identified for each RDC, and a flood‐fill algorithm is applied to surrounding pixels to delineate rapidly developing convective bodies. This study introduces the innovative application of multichannel RDC identification and a CTC filter that incorporates three tests. Experimental validation using August 2014 scanning data (106° E–113° E, 27° N–31° N) demonstrates robust performance, with a probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) of 0.88, 0.16, and 0.76, respectively, confirming the method’s accuracy in identifying RDC.

Advances in MeteorologyVol. 2026(1)
Zhengzhou University (CN), Shangqiu Institute of Technology (CN), Shangqiu Normal University (CN)
Science and Technology Department of Henan Province
Openalex Percentile: Top 97%
Meteorological Phenomena and Simulations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.