Deriving Overlapped Cloud Motion Vectors Based on Geostationary Satellite and Its Application on Monitoring Typhoon Mulan

Abstract Accurate cloud motion vector retrieval in multi‐layer clouds faces persistent challenges due to ambiguous height assignment. We developed a novel overlapped cloud motion vectors (OCMVs) retrieval method using Himawari‐8 observations. Multi‐layer cloud top heights (CTHs) were retrieved based...

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Main Authors: Cuiping Liu, Wei Han, Feng Zhang, Jiaqi Jin, Qiong Wu, Wenwen Li, Chloe Yuchao Gao
Format: Article
Language:English
Published: Wiley 2025-07-01
Series:Geophysical Research Letters
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Online Access:https://doi.org/10.1029/2025GL116397
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author Cuiping Liu
Wei Han
Feng Zhang
Jiaqi Jin
Qiong Wu
Wenwen Li
Chloe Yuchao Gao
author_facet Cuiping Liu
Wei Han
Feng Zhang
Jiaqi Jin
Qiong Wu
Wenwen Li
Chloe Yuchao Gao
author_sort Cuiping Liu
collection DOAJ
description Abstract Accurate cloud motion vector retrieval in multi‐layer clouds faces persistent challenges due to ambiguous height assignment. We developed a novel overlapped cloud motion vectors (OCMVs) retrieval method using Himawari‐8 observations. Multi‐layer cloud top heights (CTHs) were retrieved based on multi‐spectral radiance using neural networks and were assigned to upper ice and lower water cloud layers. Subsequently, CTHs from the two layers were used as respective tracers for deriving OCMVs based on the optical flow algorithm. Applied to Typhoon Mulan (2022), OCMVs showed strong vertical wind shear within the inner region, further depicting the kinematic structure of Typhoon Mulan. The vortex center of lower water OCMVs provided more valuable information on determining typhoon center than that of single‐layer CMVs. Additionally, the OCMVs demonstrated good consistency with dropsonde observations, exhibiting Root‐Mean‐Square‐Errors (RMSEs) of wind direction at ∼18.5°and wind speed at ∼5.2 m/s.
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institution DOAJ
issn 0094-8276
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language English
publishDate 2025-07-01
publisher Wiley
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series Geophysical Research Letters
spelling doaj-art-b637e96b40d342969e220a89b17c36f12025-08-20T02:56:24ZengWileyGeophysical Research Letters0094-82761944-80072025-07-015213n/an/a10.1029/2025GL116397Deriving Overlapped Cloud Motion Vectors Based on Geostationary Satellite and Its Application on Monitoring Typhoon MulanCuiping Liu0Wei Han1Feng Zhang2Jiaqi Jin3Qiong Wu4Wenwen Li5Chloe Yuchao Gao6Key Laboratory of Polar Atmosphere‐Ocean‐Ice System for Weather and Climate of Ministry of Education / Shanghai Key Laboratory of Ocean‐Land‐Atmosphere Boundary Dynamics and Climate Change Department of Atmospheric and Oceanic Sciences & Institutes of Atmospheric Sciences Fudan University Shanghai ChinaChina Meteorological Administration Earth System Modeling and Prediction Centre Beijing ChinaKey Laboratory of Polar Atmosphere‐Ocean‐Ice System for Weather and Climate of Ministry of Education / Shanghai Key Laboratory of Ocean‐Land‐Atmosphere Boundary Dynamics and Climate Change Department of Atmospheric and Oceanic Sciences & Institutes of Atmospheric Sciences Fudan University Shanghai ChinaShanghai Qi Zhi Institute Shanghai ChinaSchool of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai ChinaEngineering Research Center of Optical Instrument and System the Ministry of Education Shanghai Key Laboratory of Modern Optical System University of Shanghai for Science and Technology Shanghai ChinaKey Laboratory of Polar Atmosphere‐Ocean‐Ice System for Weather and Climate of Ministry of Education / Shanghai Key Laboratory of Ocean‐Land‐Atmosphere Boundary Dynamics and Climate Change Department of Atmospheric and Oceanic Sciences & Institutes of Atmospheric Sciences Fudan University Shanghai ChinaAbstract Accurate cloud motion vector retrieval in multi‐layer clouds faces persistent challenges due to ambiguous height assignment. We developed a novel overlapped cloud motion vectors (OCMVs) retrieval method using Himawari‐8 observations. Multi‐layer cloud top heights (CTHs) were retrieved based on multi‐spectral radiance using neural networks and were assigned to upper ice and lower water cloud layers. Subsequently, CTHs from the two layers were used as respective tracers for deriving OCMVs based on the optical flow algorithm. Applied to Typhoon Mulan (2022), OCMVs showed strong vertical wind shear within the inner region, further depicting the kinematic structure of Typhoon Mulan. The vortex center of lower water OCMVs provided more valuable information on determining typhoon center than that of single‐layer CMVs. Additionally, the OCMVs demonstrated good consistency with dropsonde observations, exhibiting Root‐Mean‐Square‐Errors (RMSEs) of wind direction at ∼18.5°and wind speed at ∼5.2 m/s.https://doi.org/10.1029/2025GL116397overlapped cloud motion vectorsmulti‐layer cloudoptical flowtyphoon Mulan
spellingShingle Cuiping Liu
Wei Han
Feng Zhang
Jiaqi Jin
Qiong Wu
Wenwen Li
Chloe Yuchao Gao
Deriving Overlapped Cloud Motion Vectors Based on Geostationary Satellite and Its Application on Monitoring Typhoon Mulan
Geophysical Research Letters
overlapped cloud motion vectors
multi‐layer cloud
optical flow
typhoon Mulan
title Deriving Overlapped Cloud Motion Vectors Based on Geostationary Satellite and Its Application on Monitoring Typhoon Mulan
title_full Deriving Overlapped Cloud Motion Vectors Based on Geostationary Satellite and Its Application on Monitoring Typhoon Mulan
title_fullStr Deriving Overlapped Cloud Motion Vectors Based on Geostationary Satellite and Its Application on Monitoring Typhoon Mulan
title_full_unstemmed Deriving Overlapped Cloud Motion Vectors Based on Geostationary Satellite and Its Application on Monitoring Typhoon Mulan
title_short Deriving Overlapped Cloud Motion Vectors Based on Geostationary Satellite and Its Application on Monitoring Typhoon Mulan
title_sort deriving overlapped cloud motion vectors based on geostationary satellite and its application on monitoring typhoon mulan
topic overlapped cloud motion vectors
multi‐layer cloud
optical flow
typhoon Mulan
url https://doi.org/10.1029/2025GL116397
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