SMAP SSS provided by REMSS: v1.0 vs v2.0

Outliers distribution is very homogeous in both versions

Fig. 1: Outliers distribution (red dots) is homogeneous in both versions. The nearest points to the coast are also excluded from statistics.

Since last September, Remote Sensing Systems (REMSS) is producing version 2.0 of the Level 2 and Level 3 Sea Surface Salinity products from SMAP. One year ago, we published in this blog a brief study on the validation of  version 1.0 of the 8-day L3 SSS maps provided by REMSS (see Preliminary validation of 8-day SMAP L3 Salinity product V1.0 for more information). Now, in order to assess the improvements of this new version, we present a small comparison between these two versions of the 8-day SSS L3 maps. Part of this study was included in the V2.0 Release Notes document. The validation has been made using as reference field the 7-day global ocean 0.25-degree SSS FOAM product generated by Met Office and distributed by Copernicus.

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Preliminary SMOS SSS in the Mediterranean

Experimental SMOS SSS maps of the Mediterranean Sea are being computed at BEC using a new methodological approach to cope with land and RFI contamination. Three different products are being analysed: monthly binned maps at a 1×1 deg grid; optimal interpolated maps at 0.25×0.25 deg; and daily products at 0.25×0.25 deg through fusion with Reynolds SST.  The preliminary assessment of the monthly product shows an RMS with respect to ARGO of 0.35 psu. These maps will be available soon in our CP34-BEC data distribution system, so keep watching!
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Using Argo to validate remote sensing missions

With its more than 3500 automatic profilers, the Argo array is one of the most important component of the Global in-situ Ocean Observing System. The array provides measurements of temperature and salinity profiles down to 2000 m. These data are rapidly expanding the historical database of the ocean sub-surface (specially in the case of ocean salinity) and are providing novel information about the ocean’s vertical structure and its variability. Moreover, these data allow real-time monitoring, model-constraining and contribute to calibration and verification efforts.

Number of available profiles from January 2005 to December 2014: Shown are the total number of profiles, the delayed mode profiles as for Apri 27, 2015 and the number of delayed mode profiles with salinity.

Figure 1: Number of Argo profiles from January 2005 to December 2014: Shown are the total number of profiles, the delayed mode profiles as for April 27, and the number of delayed mode profiles with salinity.

The Euro-Argo ( research infrastructure, designed to coordinate the European contribution to Argo, is part of the European Strategy Forum on Research Infrastructures (ESFRI). Euro-Argo is expected to provide additional 50 floats per year and support about the 25% of
the Argo array.

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Barcelona World Race 2014-2015

The 2014-15 edition of the Barcelona World Race (BWR) has had an active ocean observation contribution that will provide new data about the ocean water dynamics and its environmental quality.

In addition to contribute to the build-up of the Argo system by deploying eight Argo profilers during January 2015, the One Planet, One Ocean & Pharmaton ship carried a Sea Bird SBE37-SI MicroCAT instrument to collect continuous (every minute) sea surface temperature and salinity measurements.

Photography by Mireia Perelló from

The One Planet, One Ocean & Pharmaton. Photography by Mireia Perelló from

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New study on the detection of cold-core rings in the Gulf Stream area using remote sensing platforms

The Gulf Stream plays a major role in the meridional transport of heat and salt across the North Atlantic Ocean. The Gulf Stream acts as a barrier between the cold (10-18 °C) and relatively fresh (salinity around 30-32 in the practical salinity scale) waters of the Labrador Current and the warm (23 °C), salty (36), clear, and unproductive waters of the Sargasso Sea. After leaving Cape Hatteras, the Gulf Stream forms large-amplitude meanders that may loop back onto themselves and break off the stream forming detached rings. Warm-core anti-cyclonic rings bring significant amounts of warm tropical water to the continental slope and shelf seas north of the Gulf Stream. Similarly, cold-core cyclonic rings bring cold, nutrient-rich shelf water, to the biologically barren Sargasso Sea waters. Detection of cold-core rings from satellite data has been quite elusive so far as the surface temperature signature rapidly disappears.

Figure 1

Sea Surface salinity on August 23, 2015 according to various SSS products with superimposed OSCAR velocities. The plot on (a) correspond to the one-degree binned Aquarius L3 map. The other three maps show the fusion of the map shown in (s) with: AVISO SSH (b); SMOS SSS (c); and AVHRR SST (d).

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SMOS in a Massive Open Online Course

The Barcelona World Race Ocean Campus has organised five courses on Instructure Canvas platform to provide the 2014-2015 round the world regatta followers with basic knowledge about the science of oceanography and other subjects like meteorology, telemedecine, chronobiology or nutrition. One of these MOOCs is “Oceanography: a key to a better understanding of our world” that includes a module on ocean remote sensing instructed by Jordi Font. This free course will start on April 20th and does not require previous knowledge in oceanography. Feel free to join us in this worldwide adventure!

A blending algorithm using SST data to improve SMOS SSS maps

Data fusion is a process for combining two, or more, sources of information to improve the representation of a given system. In a recent paper, data fusion has been used to remove noise from SMOS sea surface salinity (SSS) products, by fusing SMOS data with sea surface temperature (SST) fields.

Our approach is justified by the correspondence between the singularity exponents of SSS and SST. The singularity exponent is a non-dimensional measure of the regularity or irregularity of a field in a given point. The value of the singularity exponent increases with the smoothness of a field. The correspondence between the singularity exponents of SST and SSS implies the existence of a local functional dependence between these two variables. This correspondence can be illustrated using data of a numerical simulation (OFES, Ocean General Circulation Model for the Earth Simulator).

Figure 1 shows two conditioned histograms. The one in the top illustrates the histogram of SSS conditioned by each given value of SST. The conditioned histogram looks like a superposition of narrow lines. It indicates that, while strong local SSS-SST correlations exist, these relations do change from one region to the other. On the contrary, the conditioned histogram of SSS singularity exponents conditioned by the value of the singularity exponents of SST indicates that a unique correlation exists all over the world ocean. In fact, the slope of the maximum probability line is close to one, indicating an almost perfect identity between the singularity exponents of SST and SSS.


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Data assimilation of SMOS SSS data to create Level 4 salinity maps. A case study

Many approaches can be used to reduce the amount of noise present in a given set of data (observed or retrieved). In the SMOS processing chain, weighted averages are used to reduce the noise present in the sea surface salinity (SSS) data retrieved from brightness temperature measurements. This is the rationale of the existence of the higher production levels (Levels 3 and 4) of sea surface salinity and soil moisture.

Differences between SMOS level 3 (right) or FREE-run(left) and Argo data (2011). All 2011 match ups are shown in these plots.

Figure 1: Differences between SMOS level 3 (right) or FREE-run(left) and Argo data (2011). All 2011 match ups are shown in these plots.

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