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  Validation of multisource altimeter SWH measurements for climate data analysis in China's offshore waters

Xu, J., Wu, H., Zhi, X., Koldunov, N. V., Zhang, X., Xu, Y., et al. (2024). Validation of multisource altimeter SWH measurements for climate data analysis in China's offshore waters. Remote Sensing, 16: 2162. doi:10.3390/rs16122162.

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 Creators:
Xu, Jingwei, Author
Wu, Huanping, Author
Zhi, Xiefei, Author
Koldunov , Nikolay V., Author
Zhang, Xiuzhi, Author
Xu, Ying, Author
Zhang, Yangyang, Author
Guo, Maohua, Author
Kong, Lisha, Author
Fraedrich, Klaus F.1, Author           
Affiliations:
1MPI for Meteorology, Max Planck Society, ou_913545              

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Free keywords: merged long-term multisource altimeter data; significant wave height; Haiyang-2 series satellites; CFOSAT; validation; variance; China’s offshore waters
 Abstract: Climate data derived from long-term, multisource altimeter significant wave height (SWH) measurements are more valuable than those obtained from a single altimeter source. Such data facilitate exploration of long-term air–sea momentum transfer and more comprehensive investigation of weather system dynamics processes over the ocean. Despite the deployment of the first satellite in the Chinese Haiyang-2 (HY-2) series more than 12 years ago, validation and integration of SWH data from China’s offshore waters, derived using Chinese altimeters, have been limited. This study constructed a high-resolution, long-term, multisource gridded SWH climate dataset using along-track data from the HY-2 series, CFOSAT, Jason-2, Jason-3, and Cryosat-2 altimeters. Validation against observations from 31 buoys covering China’s offshore waters indicated that the SWH variances from HY-2A, HY-2B, HY-2C, CFOSAT, and Jason-3 altimeters correlated well with observations, with a temporal correlation coefficient of approximately 0.95 (except HY-2A, correlation: 0.89). These SWH measurements generally showed a robust linear relationship with the buoy data. Additionally, cross-calibration between Jason-3 and the HY-2A, HY-2B, HY-2C, and CFOSAT altimeters also demonstrated a typically linear relationship for SWH > 6.0 m. Using this relationship, the SWH data were linearly corrected and integrated into a 10 d mean, long-term, multisource altimeter gridded SWH dataset. Compared with in situ observations, the merged 10 d mean SWHs are more accurate and closely match the observations, with temporal correlation coefficients improving from 0.87 to 0.90 and bias decreasing from 0.28 to 0.03 m. The merged gridded SWHs effectively represent the local spatial distribution of SWH. This study revealed the importance of observational data in the process of merging and recalibrating long-term multisource altimeter SWH datasets, particularly before their application in specific ocean regions.

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Language(s): eng - English
 Dates: 2024-06-042024-05-082024-06-122024-07-14
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.3390/rs16122162
 Degree: -

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Project name : Research on 8-42d Subseasonal Multi-mode Integrated Forecasting Based on Statistical Methods and Machine Learning
Grant ID : 42275164, 41005057
Funding program : -
Funding organization : National Natural Science Foundation of China
Project name : -
Grant ID : -
Funding program : (2023CFO018)
Funding organization : Key Laboratory of Space Ocean Remote Sensing and Application
Project name : China Special Fund for Meteorological Research in the Public Interest
Grant ID : GYHY 201406008
Funding program : -
Funding organization : -
Project name : S1 (Diagnosis and Metrics in Climate Models
Grant ID : -
Funding program : Collaborative Research Centre TRR 181 Energy Transfer in Atmosphere and Ocean program ( 27476265)
Funding organization : DFG
Project name : Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
Grant ID : -
Funding program : -
Funding organization : -

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Title: Remote Sensing
Source Genre: Journal
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Publ. Info: Basel : Molecular Diversity Preservation International (MDPI)
Pages: - Volume / Issue: 16 Sequence Number: 2162 Start / End Page: - Identifier: ISSN: 2072-4292
CoNE: https://pure.mpg.de/cone/journals/resource/2072-4292