This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.3390/rs13152995. This is version 3 of this Preprint.
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Abstract
Sea surface salinity (SSS) satellite measurements are validated using in situ observations usually made by surfacing Argo floats. Validation statistics are computed using matched values of SSS from satellites and floats. This study explores how the matchup process is done using a high-resolution numerical ocean model, the MITgcm. One year of model output is sampled as if the Aquarius and Soil Moisture Active Passive (SMAP) satellites flew over it and Argo floats popped up into it. Statistical measures of mismatch between satellite and float are computed, RMS difference (RMSD) and bias. The bias is small, less than 0.002 in absolute value, but negative with float values being greater than satellites. RMSD is computed using an “all salinity difference” method that averages level 2 satellite observations within a given time and space window for comparison with Argo floats. RMSD values range from 0.08 to 0.18 depending on the space-time window and the satellite. This range gives an estimate of the representation error inherent in comparing single point Argo floats to area-average satellite values. The study has implications for future SSS satellite missions and the need to specify how errors are computed to gauge the total accuracy of retrieved SSS values.
DOI
https://doi.org/10.31223/X5Q61C
Subjects
Oceanography
Keywords
ocean modelling, Surface salinity, representation error, satellite validation, matchups
Dates
Published: 2021-06-16 06:17
Last Updated: 2021-08-20 17:43
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License
CC BY Attribution 4.0 International
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Conflict of interest statement:
None
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