Validating SMOS ocean surface salinity in the Atlantic with Argo and operational ocean model data

Banks, C.J., Gommenginger, C.P., Srokosz, M.A. and Snaith, H.M. (2012) Validating SMOS ocean surface salinity in the Atlantic with Argo and operational ocean model data IEEE Transactions on Geoscience and Remote Sensing, 50, (5), pp. 1688-1702. (doi:10.1109/TGRS.2011.2167340).


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This paper provides an assessment of synoptic measurements of sea surface salinity (SSS) from the European Space Agency Soil Moisture and Ocean Salinity (SMOS) satellite. Due to the complex nature of the response of L-band signals to SSS, SMOS provides three values of SSS at each grid point from three different forward models. To meet oceanographic requirements for SSS retrieval accuracy, SMOS Level 2 SSS products are averaged over time and space. This paper reports on validation studies in the Atlantic based on monthly Level 3 products on a $1^{circ}times 1^{circ}$ grid for September 2010. Outside coastal regions, large-scale SSS patterns from SMOS are in general agreement with climatology, Argo, and ocean model output. During September 2010, SSS from descending passes provides reasonable quantitative estimates, while SSS from ascending passes overestimates SSS by over 1 practical salinity unit (psu). The daily mean difference in SSS between ascending and descending passes varies during August–December 2010, reaching a maximum in September. Differences in SMOS SSS from the three models are an order of magnitude smaller than differences between ascending and descending passes. Gridded SMOS SSS data are compared against output from the U.K. Met Office Forecasting Ocean Assimilation Model (FOAM)-Nucleus for European Modelling of the Ocean (NEMO). Basic checks confirm that SSS from FOAM-NEMO is unbiased against Argo and that FOAM-NEMO SSS is a useful independent data source to validate and rapidly identify departures in SMOS SSS. Over the whole Atlantic, SMOS SSS variability against FOAM-NEMO is around 0.9 psu, decreasing to 0.5 psu over the subtropical North Atlantic.

Item Type: Article
Digital Object Identifier (DOI): doi:10.1109/TGRS.2011.2167340
ISSNs: 0196-2892 (print)
Keywords: Microwave radiometry, remote sensing, sea surface
Organisations: National Oceanography Centre, Marine Physics and Ocean Climate
ePrint ID: 208145
Date :
Date Event
May 2012Published
Date Deposited: 16 Jan 2012 15:11
Last Modified: 18 Apr 2017 00:35
Further Information:Google Scholar

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