EGUsphere

Copernicus Publications

Göttingen, Germany

10.5194/egusphere-2026-5436

Improving Reconstructed HY-1D/COCTS SST for Upwelling Events in the Gulf of Lion through Wind-Informed Cloud Detection

Zhuomin

¹ ² ³ ⁴ Alvera-Azcárate

Aida

https://orcid.org/0000-0002-0484-4791

⁴ Barth

Alexander

https://orcid.org/0000-0003-2952-5997

⁴ Bensoussan

Nathaniel

⁵ Guan

Lei

² ³ ⁶ Xu

National Satellite Meteorological Center, China Meteorological Administration, Beijing, 100081, China

Key Laboratory of Ocean Observation and Information of Hainan Province, Sanya Oceanographic Institution, Ocean University of China, Sanya, 572024, China

College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao, 266100, China

GeoHydrodynamics and Environment Research (GHER), University of Liège, Liège, 4000, Belgium

Laboratoire d'Océanographie Physique et Spatiale (LOPS), IUEM, University of Brest, CNRS, Ifremer, IRD, 29280, Plouzané, France

SANYA Oceanographic Laboratory, Sanya, 572024, China

25 09 2026

2026 1 25

2026

This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/

This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-5436/

The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-5436/egusphere-2026-5436.pdf

Sea surface temperature (SST) is essential for understanding ocean dynamics and air-sea interactions. SST from the Haiyang-1D (HY-1D) Chinese Ocean Color and Temperature Scanner (COCTS) has been obtained based on the algorithm derived using an atmospheric radiative transfer model. In the Gulf of Lion of the Mediterranean Sea, northwest winds prevail in summer and autumn, which favors upwelling events. This study aims to improve reconstructed HY-1D/COCTS SST for characterizing strong upwelling events in the Gulf of Lion. The study covers the period from May to November 2021(summer and autumn). The research area is 41°N–44°N and 3°E–8°E and the spatial resolution of COCTS SST is 1 km. Owing to persistent cloud cover, 61.92% of all pixels are missing. First, to better utilize COCTS SST, we apply Data Interpolating Empirical Orthogonal Functions (DINEOF) to reconstruct COCTS SST. The validation results for reconstructed COCTS SST show that DINEOF provides accurate statistical results on cloud pixels. We analyze the performance of the reconstructed COCTS SST in 8 sporadic upwelling events using the in situ data as reference. The hourly in situ data from 3 sites located in/nearby distinct upwelling areas from the Gulf of Lion (Marseille-Toulon area). The results show that the reconstructed COCTS SST characterizes most SST cooling events caused by upwelling, but not as intense as the in situ SST. Second, to overcome this limitation, we propose a wind-informed cloud detection procedure that takes into account wind speed and direction in order to improve the classification of upwelling-influenced pixels. The COCTS SST obtained by this improved cloud mask is subsequently reconstructed using DINEOF.  The improved reconstructed COCTS SST has higher consistency with the in situ SST in the upwelling area. The results show the difficulty of cloud masking in areas with strong upwelling events and that the improved reconstructed HY-1D/COCTS SST, enabled by wind-informed cloud detection, have the potential to accurately describe such events.