Data/hora: 08/06/2024 10:38:28

Provedor de dados: | 5
País: | France
Título: | A New Method of De-Aliasing Large-Scale High-Frequency Barotropic Signals in the Mediterranean Sea
Autores: | Hu, Denghui; Xu, Yongsheng.
Data: | 2020-07
Ano: | 2020
Palavras-chave: | Tide gauge; EOF analysis; De-aliasing; Altimeter.
Resumo: | With the development of satellite observation technology, higher resolution and shorter return cycle have also placed higher demands on satellite data processing. The non-tide high-frequency barotropic oscillation in the marginal sea produces large aliasing errors in satellite altimeter observations. In previous studies, the satellite altimeter aliasing correction generally relied on a few bottom pressure data or the model data. Here, we employed the high-frequency tide gauge data to extract the altimeter non-tide aliasing correction in the west Mediterranean Sea. The spatial average method and EOF analysis method were adopted to track the high-frequency oscillation signals from 15 tide gauge records (TGs), and then were used to correct the aliasing errors in the Jason-1 and Envisat observations. The results showed that the EOF analysis method is better than the spatial average method in the altimeter data correction. After EOF correction, 90% of correlation (COR) between TG and sea level of Jason-1 has increased ~5%, and ~3% increase for the Envisat sea level; for the spatial average correction method, only ~70% of Jason-1 and Envisat data at the TGs location has about 2% increase in correlation. The EOF correction reduced the average percentage of error variance (PEL) by ~30%, while the spatial average correction increased the average percentage of PEL by ~20%. After correction by the EOF method, the altimeter observations are more consistent with the distribution of strong currents and eddies in the west Mediterranean Sea. The results prove that the proposed EOF method is more effective and accurate for the non-tide aliasing correction
Tipo: | Text
Idioma: | Inglês

Identificador:

https://archimer.ifremer.fr/doc/00641/75262/75467.pdf

DOI:10.3390/rs12132157

https://archimer.ifremer.fr/doc/00641/75262/

Editor: | MDPI AG
Formato: | application/pdf
Fonte: | Remote Sensing (2072-4292) (MDPI AG), 2020-07 , Vol. 12 , N. 13 , P. 2157 (13p.)

Fonte:

info:eu-repo/semantics/openAccess

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