2024-03-29T12:51:38Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1674042021-07-13T06:05:28Zcom_10261_123com_10261_8col_10261_376
DIGITAL.CSIC
author
Hoareau, Nina
author
Portabella, Marcos
author
Lin, Wenming
author
Ballabrera-Poy, Joaquim
author
Turiel, Antonio
funder
Ministerio de Economía, Industria y Competitividad (España)
funder
Ministerio de Ciencia, Innovación y Universidades (España)
2018-07-05T12:21:21Z
2018-07-05T12:21:21Z
2018-04
IEEE Transactions on Geoscience and Remote Sensing 56(9): 5160-5168 (2018)
0196-8904
http://hdl.handle.net/10261/167404
10.1109/TGRS.2018.2810442
http://dx.doi.org/10.13039/501100010198
The triple collocation (TC) technique allows the simultaneous calibration of three independent, collocated data sources, while providing an estimate of their accuracy. In this paper, the TC is adapted to validate different salinity data products along the tropical band. The representativeness error (the true variance resolved by the relatively high-resolution systems but not by the relatively low-resolution system) is accounted for in the validation process. A method based on the intercalibration capabilities of TC is used to estimate the representativeness error for each triplet, which is found to impact between 15% and 50% the error estimation of the different products. The method also sorts the different products in terms of their resolving spatiotemporal scales. Six salinity products (sorted from smaller to larger scales) used were: the in situ data from the Global Tropical Moored Buoy Array (TAO), the GLORYS2V3 ocean reanalysis output provided by Copernicus, the satellite-derived Aquarius Level 3 version 4 (AV4) and Soil Moisture and Ocean Salinity (SMOS) objectively analyzed (SOA) maps, and the climatology maps provided by the World Ocean Atlas (WOA). This calibration study is limited to the year 2013, a year when all the products were available. This validation approach aims to assess the quality of the different salinity products at the satellite-resolved spatiotemporal scales. The results show that, at the AV4 resolved scales, the Aquarius product has an error of 0.17, and outperforms TAO, GLORYS2V3, and the SOA maps. However, at the SOA resolved scales (which are coarser than those of the Aquarius product because of the large OA correlation radii used), the SMOS product has an error of 0.20, slightly lower than that of GLORYS2V3, Aquarius, and TAO. The WOA products show the highest errors. Higher order calibration may lead to a more accurate assessment of the quality of the climatological products
eng
openAccess
Error Characterization of Sea Surface Salinity Products Using Triple Collocation Analysis
artículo
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
URL
https://digital.csic.es/bitstream/10261/167404/3/Hoareau_et_al_2018_postprint.pdf
File
MD5
95b796b5c86f6142da4d14f626bf24eb
3511764
application/pdf
Hoareau_et_al_2018_postprint.pdf