数据说明
Sea Level Anomaly (SLA)
上传时间：2019-05-22 14:10:36 浏览次数：作者与来源：admin
Sea Level Anomaly (SLA) is the temporal mean of the SSH above the ellipsoid over a period N. Changes in SLA will influence the frequency and impact of extreme sea level events which engender lots of negative impact. (WANG Yangjun et. al, 2016)
Unit: m
Resolution: 0.25 degree, Daily
Duration: January 1, 1993 - present
Source: Copernicus Marine Environment Monitoring Service (CMEMS)
Version: -
Processing: Original daily mean products are shown, and all the daily data in a month are averaged to get the monthly data.
This product is processed by the SL-TAC multimission altimeter data processing system and combination of data from Sentinel-3A, Jason-3, HY-2A, Saral/AltiKa, Cryosat-2, OSTM/Jason-2, Jason-1, Topex/Poseidon, Envisat, GFO, ERS-1/2.All altimeter fields are interpolated at crossover locations and dates.
Sea Level Anomaly (SLA) is deduced from the SSH using a Mean Sea Surface (MSS):
SLAN = SSH - MSSN
Where Sea Surface Heights (SSH) observations from the altimeters and altimetry gives access to the SSH above the reference ellipsoid, the Mean Sea Surface (MSS) is the temporal mean of the SSH over a period N (see figure 1).
Known issues
1. It mainly traduces errors induced by the constellation sampling capability and consistency with the spatial/temporal scales considered, as described in Le Traon et al (1998) or Ducet et al (2000) .
2. The sea level anomaly is the sea surface height above mean sea surface, it is referenced to the [1993, 2012] period.
3. The data scale factor need to be multiplied when using the data.
Reference
Ducet N, Traon P Y L, Reverdin G. Global high-resolution mapping of ocean circulation from TOPEX/Poseidon and ERS-1/2. Journal of Geophysical Research Atmospheres, 2000, 105(C8):19477-19498. DOI: 10.1029/2000JC900063
Traon P Y L, Nadal F, Ducet N. An Improved Mapping Method of Multi-Satellite Altimeter Data. Journal of atmospheric and oceanic technology, 1998,15(2):522-534. DOI: 10.1175/1520-0426(1998)015<0522:AIMMOM>2.0.CO;2
WANG Yanjun, HOU Taiping, ZHANG Ren .et al.Prediction modeling of extreme sea level based on dynamic extreme value theory and Copula function. The ocean engineering, 2016, 34(4):62-70.
All the contents of this page are quoted from Copernicus Marine Environment Monitoring Service. All project documentation and related publications can be found at website: http://marine.copernicus.eu/services-portfolio/access-to-products/?option=com_csw&view=details&product_id=SEALEVEL_GLO_PHY_L4_REP_OBSERVATIONS_008_047, andhttp://marine.copernicus.eu/documents/PUM/CMEMS-SL-PUM-008-032-051.pdf
Unit: m
Resolution: 0.25 degree, Daily
Duration: January 1, 1993 - present
Source: Copernicus Marine Environment Monitoring Service (CMEMS)
Version: -
Processing: Original daily mean products are shown, and all the daily data in a month are averaged to get the monthly data.
This product is processed by the SL-TAC multimission altimeter data processing system and combination of data from Sentinel-3A, Jason-3, HY-2A, Saral/AltiKa, Cryosat-2, OSTM/Jason-2, Jason-1, Topex/Poseidon, Envisat, GFO, ERS-1/2.All altimeter fields are interpolated at crossover locations and dates.
Sea Level Anomaly (SLA) is deduced from the SSH using a Mean Sea Surface (MSS):
SLAN = SSH - MSSN
Where Sea Surface Heights (SSH) observations from the altimeters and altimetry gives access to the SSH above the reference ellipsoid, the Mean Sea Surface (MSS) is the temporal mean of the SSH over a period N (see figure 1).
Known issues
1. It mainly traduces errors induced by the constellation sampling capability and consistency with the spatial/temporal scales considered, as described in Le Traon et al (1998) or Ducet et al (2000) .
2. The sea level anomaly is the sea surface height above mean sea surface, it is referenced to the [1993, 2012] period.
3. The data scale factor need to be multiplied when using the data.
Reference
Ducet N, Traon P Y L, Reverdin G. Global high-resolution mapping of ocean circulation from TOPEX/Poseidon and ERS-1/2. Journal of Geophysical Research Atmospheres, 2000, 105(C8):19477-19498. DOI: 10.1029/2000JC900063
Traon P Y L, Nadal F, Ducet N. An Improved Mapping Method of Multi-Satellite Altimeter Data. Journal of atmospheric and oceanic technology, 1998,15(2):522-534. DOI: 10.1175/1520-0426(1998)015<0522:AIMMOM>2.0.CO;2
WANG Yanjun, HOU Taiping, ZHANG Ren .et al.Prediction modeling of extreme sea level based on dynamic extreme value theory and Copula function. The ocean engineering, 2016, 34(4):62-70.
All the contents of this page are quoted from Copernicus Marine Environment Monitoring Service. All project documentation and related publications can be found at website: http://marine.copernicus.eu/services-portfolio/access-to-products/?option=com_csw&view=details&product_id=SEALEVEL_GLO_PHY_L4_REP_OBSERVATIONS_008_047, andhttp://marine.copernicus.eu/documents/PUM/CMEMS-SL-PUM-008-032-051.pdf
