The Determination of Surface Salinity with the European SMOS Space Mission

The European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission aims at obtaining global maps of soil moisture and sea surface salinity from space for large-scale and climatic studies. It uses an L-band (1400–1427 MHz) Microwave Interferometric Radiometer by Aperture Synthesis to measure brightness temperature of the earth’s surface at horizontal and vertical polarizations ( h and v). These two parameters will be used together to retrieve the geophysical parameters. The retrieval of salinity is a complex process that requires the knowledge of other environmental information and an accurate processing of the radiometer measurements. Here, we present recent results obtained from several studies and field experiments that were part of the SMOS mission, and highlight the issues still to be solved

Issues in the balancing of the SMOS ocean salinity trieval cost function

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SMOS: ESA'S Water Mission

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Review of the CALIMAS Team Contributions to European Space Agency's Soil Moisture and Ocean Salinity Mission Calibration and Validation

Camps, Adriano ... et al.-- 38 pages, 22 figuresThis work summarizes the activities carried out by the SMOS (Soil Moisture and Ocean Salinity) Barcelona Expert Center (SMOS-BEC) team in conjunction with the CIALE/Universidad de Salamanca team, within the framework of the European Space Agency (ESA) CALIMAS project in preparation for the SMOS mission and during its first year of operation. Under these activities several studies were performed, ranging from Level 1 (calibration and image reconstruction) to Level 4 (land pixel disaggregation techniques, by means of data fusion with higher resolution data from optical/infrared sensors). Validation of SMOS salinity products by means of surface drifters developed ad-hoc, and soil moisture products over the REMEDHUS site (Zamora, Spain) are also presented. Results of other preparatory activities carried out to improve the performance of eventual SMOS follow-on missions are presented, including GNSS-R to infer the sea state correction needed for improved ocean salinity retrievals and land surface parameters. Results from CALIMAS show a satisfactory performance of the MIRAS instrument, the accuracy and efficiency of the algorithms implemented in the ground data processors, and explore the limits of spatial resolution of soil moisture products using data fusion, as well as the feasibility of GNSS-R techniques for sea state determination and soil moisture monitoringThis work has been performed under research grants TEC2005-06863-C02-01/TCM, ESP2005-06823-C05, ESP2007-65667-C04, AYA2008-05906-C02-01/ESP and AYA2010-22062-C05 from the Spanish Ministry of Science and Innovation, and a EURYI 2004 award from the European Science FoundationPeer Reviewe

Potential synergetic use of GNSS-R signals to improve the sea-state correction in the sea surface salinity estimation: Application to the SMOS mission

It is accepted that the best way to monitor sea surface salinity (SSS) on a global basis is by means of L-band radiometry. However, the measured sea surface brightness temperature (TB) depends not only on the SSS but also on the sea surface temperature (SST) and, more importantly, on the sea state, which is usually parameterized in terms of the 10-m-height wind speed (U10) or the significant wave height. It has been recently proposed that the mean-square slope (mss) derived from global navigation satellite system (GNSS) signals reflected by the sea surface could be a potentially appropriate sea-state descriptor and could be used to make the necessary sea state TB corrections to improve the SSS estimates. This paper presents a preliminary error analysis of the use of reflected GNSS signals for the sea roughness correction and was performed to support the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) mission; the orbit and parameters for the SMOS instrument were assumed. The accuracy requirement for the retrieved SSS is 0.1 practical salinity units after monthly averaging over 2◦ × 2◦ boxes. In this paper, potential improvements in salinity estimation are hampered mainly by the coarse sampling and by the requirements of the retrieval algorithm, particularly the need for a semiempirical model that relates TB and mss.Postprint (published version

North Atlantic salinity as a predictor of Sahel rainfall

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Science Advances 2 (2016): e1501588, doi:10.1126/sciadv.1501588.Water evaporating from the ocean sustains precipitation on land. This ocean-to-land moisture transport leaves an imprint on sea surface salinity (SSS). Thus, the question arises of whether variations in SSS can provide insight into terrestrial precipitation. This study provides evidence that springtime SSS in the subtropical North Atlantic ocean can be used as a predictor of terrestrial precipitation during the subsequent summer monsoon in Africa. Specifically, increased springtime SSS in the central to eastern subtropical North Atlantic tends to be followed by above-normal monsoon-season precipitation in the African Sahel. In the spring, high SSS is associated with enhanced moisture flux divergence from the subtropical oceans, which converges over the African Sahel and helps to elevate local soil moisture content. From spring to the summer monsoon season, the initial water cycling signal is preserved, amplified, and manifested in excessive precipitation. According to our analysis of currently available soil moisture data sets, this 3-month delay is attributable to a positive coupling between soil moisture, moisture flux convergence, and precipitation in the Sahel. Because of the physical connection between salinity, ocean-to-land moisture transport, and local soil moisture feedback, seasonal forecasts of Sahel precipitation can be improved by incorporating SSS into prediction models. Thus, expanded monitoring of ocean salinity should contribute to more skillful predictions of precipitation in vulnerable subtropical regions, such as the Sahel.L.L. is supported by the Postdoctoral Scholar Program at the Woods Hole Oceanographic Institution (WHOI), with funding provided by the Ocean and Climate Change Institute (OCCI). R.W.S. is supported by NASA grants NNX12AF59G and NNX14AH38G and NSF grant OCE-1129646. C.C.U. is supported by NSF grant AGS-1355339. K.B.K. is supported by the Alfred P. Sloan Foundation and the James E. and Barbara V. Moltz Fellowship administered by the WHOI OCCI

A new empirical model of sea surface microwave emissivity for salinity remote sensing

SMOS (Soil Moisture and Ocean Salinity) is a European Space Agency mission that aims at generating global ocean salinity maps with an accuracy of 0.1 psu, at spatial and temporal resolution suitable for climatic studies. The satellite sensor is an L-band (1400-1427 MHz) aperture synthesis interferometric radiometer. Sea surface salinity (SSS) can be retrieved since the brightness temperature of sea water is dependent on the frequency, angle of observation, dielectric constant of sea water, sea surface temperature and sea surface state. This paper presents a new empirical sea water emissivity model at L-band in which surface roughness effects are parameterized in terms of wind speed and significant wave height. For the SMOS mission these parameters can be obtained from external measurements and model diagnostics. An analysis has been done on the effect on SSS retrieval of different sources for this auxiliary information. Copyright 2004 by the American Geophysical UnionThis study was funded by ESA-ESTEC under WISE (14188/00/NL/DC) and EuroSTARRS (15950/02/NL/SF) contracts, and by the Spanish National Program on Space Research under grant ESP2001-4523-PEPeer Reviewe