Diurnal Variation of Cloud Physical Properties for Tropical Cyclones Over North Atlantic in 2019–2023

Abstract Diurnal cloud variations critically modulate tropical cyclone (TC) precipitation and intensity, yet remain poorly understood due to the lack of continuous observations. This study examined diurnal characteristics in North Atlantic TCs (2019–2023) based on retrieved cloud properties from GOES infrared measurements using ResUnet—a machine learning framework (ResUnet‐GOES). Results revealed distinct diurnal cycles: while average cloud top heights (CTHs) within the TC inner region (0–200 km) exhibited dual peaks at 05 and 14 local standard time (LST), cloud optical thickness (COT) and cloud water path (CWP) maximized singularly at 05 LST, contrasting with maxima in cloud effective radius (CER) at 16 LST. Notably, regarding deep convective clouds (DCCs) within the TC inner region, the average CTH, CWP, and coverage increased synchronously at night and peaked in early morning, providing the micro‐physical evidence for the early morning peak in TC precipitation. These diurnal signatures may serve as reliable indicators for diagnosing TC convective variability.

Authors

Institutions

Publication Details

Journal
Geophysical Research Letters
Published
2025-06-30
DOI
https://doi.org/10.1029/2025gl115566
Citations
1
Primary Topic
Tropical and Extratropical Cyclones Research
Type
article
Field-Weighted Citation Impact
1.30

Funders

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

Diurnal Variation of Cloud Physical Properties for Tropical Cyclones Over North Atlantic in 2019–2023

Huiling Ouyang, Feng Zhang, Wenwen Li, Zhijun Zhao et al.
1 citations
Geophysical Research Letters
Tropical and Extratropical Cyclones Research
1.30
article

Diurnal Variation of Cloud Physical Properties for Tropical Cyclones Over North Atlantic in 2019–2023

Huiling Ouyang, Feng Zhang, Wenwen Li, Zhijun Zhao, Cuiping Liu
article en
1 citations

Abstract

Abstract Diurnal cloud variations critically modulate tropical cyclone (TC) precipitation and intensity, yet remain poorly understood due to the lack of continuous observations. This study examined diurnal characteristics in North Atlantic TCs (2019–2023) based on retrieved cloud properties from GOES infrared measurements using ResUnet—a machine learning framework (ResUnet‐GOES). Results revealed distinct diurnal cycles: while average cloud top heights (CTHs) within the TC inner region (0–200 km) exhibited dual peaks at 05 and 14 local standard time (LST), cloud optical thickness (COT) and cloud water path (CWP) maximized singularly at 05 LST, contrasting with maxima in cloud effective radius (CER) at 16 LST. Notably, regarding deep convective clouds (DCCs) within the TC inner region, the average CTH, CWP, and coverage increased synchronously at night and peaked in early morning, providing the micro‐physical evidence for the early morning peak in TC precipitation. These diurnal signatures may serve as reliable indicators for diagnosing TC convective variability.

Geophysical Research LettersVol. 52(13)
University of Shanghai for Science and Technology (CN), Fudan University (CN), NOAA Oceanic and Atmospheric Research (US)
National Natural Science Foundation of China, Fudan University, Shanghai Municipal Education Commission
Openalex Percentile: Top 21%
Tropical and Extratropical Cyclones Research
1.30
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.