Roberto Sabia

SMOS first data analysis for sea surface salinity determination

Soil Moisture and Ocean Salinity (SMOS), launched on 2 November 2009, is the first satellite mission addressing sea surface salinity (SSS) measurement from space. Its unique payload is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS), a new two-dimensional interferometer designed by the European Space Agency (ESA) and operating at the L-band frequency. This article presents a summary of SSS retrieval from SMOS observations and shows initial results obtained one year after launch. These results are encouraging, but also indicate that further improvements at various data processing levels are needed and hence are currently under investigation.

The emissivity of foam-covered water surface at L-band: theoretical modeling and experimental results from the FROG 2003 field experiment

Sea surface salinity can be measured by microwave radiometry at L-band (1400-1427 MHz). This frequency is a compromise between sensitivity to the salinity, small atmospheric perturbation, and reasonable pixel resolution. The description of the ocean emission depends on two main factors: (1) the sea water permittivity, which is a function of salinity, temperature, and frequency, and (2) the sea surface state, which depends on the wind-induced wave spectrum, swell, and rain-induced roughness spectrum, and by the foam coverage and its emissivity. This study presents a simplified two-layer emission model for foam-covered water and the results of a controlled experiment to measure the foam emissivity as a function of salinity, foam thickness, incidence angle, and polarization. Experimental results are presented, and then compared to the two-layer foam emission model with the measured foam parameters used as input model parameters. At 37 psu salt water the foam-induced emissivity increase is /spl sim/0.007 per millimeter of foam thickness (extrapolated to nadir), increasing with increasing incidence angles at vertical polarization, and decreasing with increasing incidence angles at horizontal polarization.

Determination of the Sea Surface Salinity Error Budget in the Soil Moisture and Ocean Salinity Mission

The Soil Moisture and Ocean Salinity mission will provide sea surface salinity maps over the oceans, beginning in late 2009. In this paper an ocean salinity error budget is described, an analysis needed to identify the magnitude of the error sources associated with the retrieval. Instrumental, external noise sources, and geophysical errors have been analyzed, stressing their relative impact. This paper includes results from previous studies, addressing the impact of multisource auxiliary sea surface temperature and wind speed data on the final salinity error. It provides, moreover, a sensitivity analysis to the uncertainty of the auxiliary salinity field. Salinity retrieval has been addressed in a wide set of configurations of the inversion algorithm.

SMOS REFLEX 2003: L-band emissivity characterization of vineyards

The goal of the Soil Moisture and Ocean Salinity mission over land is to infer surface soil moisture from multiangular L-band radiometric measurements. As the canopy affects the microwave emission of land, it is necessary to characterize different vegetation layers. This paper presents the Reference Pixel L-Band Experiment (REFLEX), carried out in June-July 2003 at the Vale/spl grave/ncia Anchor Station, Spain, to study the effects of grapevines on the soil emission and on the soil moisture retrieval. A wide range of soil moisture (SM), from saturated to completely dry soil, was measured with the Universitat Polite/spl grave/cnica de Catalunyas L-band Automatic Radiometer (LAURA). Concurrently with the radiometric measurements, the gravimetric soil moisture, temperature, and roughness were measured, and the vines were fully characterized. The opacity and albedo of the vineyard have been estimated and found to be independent on the polarization. The /spl tau/--/spl omega/ model has been used to retrieve the SM and the vegetation parameters, obtaining a good accuracy for incidence angles up to 55/spl deg/. Algorithms with a three-parameter optimization (SM, albedo albedo, and opacity) exhibit a better performance than those with one-parameter optimization (SM).

Multisensor observations of the Amazon‐Orinoco river plume interactions with hurricanes

An analysis is presented for the spatial and intensity distributions of North Atlantic extreme atmospheric events crossing the buoyant Amazon-Orinoco freshwater plume. The sea surface cooling amplitude in the wake of an ensemble of storm tracks traveling in that region is estimated from satellite products for the period 1998-2012. For the most intense storms, cooling is systematically reduced by approximate to 50% over the plume area compared to surroundings open-ocean waters. Historical salinity and temperature observations from in situ profiles indicate that salt-driven vertical stratification, enhanced oceanic heat content, and barrier-layer presence within the plume waters are likely key oceanic factors to explain these results. Satellite SMOS surface salinity data combined with in situ observations are further used to detail the oceanic response to category 4 hurricane Igor in 2010. Argo and satellite measurements confirm the haline stratification impact on the cooling inhibition as the hurricane crossed the river plume. Over this region, the SSS mapping capability is further tested and demonstrated to monitor the horizontal distribution of the vertical stratification parameter. SMOS SSS data can thus be used to consistently anticipate the cooling inhibition in the wake of TCs traveling over the Amazon-Orinoco plume region.

Characterization of the SMOS Instrumental Error Pattern Correction Over the Ocean

The Soil Moisture and Ocean Salinity (SMOS) mission was launched on November 2nd, 2009 aiming at providing sea surface salinity (SSS) estimates over the oceans with frequent temporal coverage. The detection and mitigation of residual instrumental systematic errors in the measured brightness temperatures are key steps prior to the SSS retrieval. For such purpose, the so-called ocean target transformation (OTT) technique is currently used in the SMOS operational SSS processor. In this paper, an assessment of the OTT is performed. It is found that, to compute a consistent and robust OTT, a large ensemble of measurements is required. Moreover, several effects are reported to significantly impact the OTT computation, namely, the apparent instrument (temporal) drift, forward model imperfections, auxiliary data (used by forward model) uncertainty and external error sources, such as galactic noise and Sun effects (among others). These effects have to be properly mitigated or filtered during the OTT computation, so as to successfully retrieve SSS from SMOS measurements.

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 Agencys 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 2deg times 2degboxes. 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.

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

This 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 monitoring.

Salinity from Space Unlocks Satellite-Based Assessment of Ocean Acidification

Approximately a quarter of the carbon dioxide (CO2) that we emit into the atmosphere is absorbed by the ocean. This oceanic uptake of CO2 leads to a change in marine carbonate chemistry resulting in a decrease of seawater pH and carbonate ion concentration, a process commonly called ‘Ocean Acidification’. Salinity data are key for assessing the marine carbonate system, and new space-based salinity measurements will enable the development of novel space-based ocean acidification assessment. Recent studies have highlighted the need to develop new in situ technology for monitoring ocean acidification, but the potential capabilities of space-based measurements remain largely untapped. Routine measurements from space can provide quasi-synoptic, reproducible data for investigating processes on global scales; they may also be the most efficient way to monitor the ocean surface. As the carbon cycle is dominantly controlled by the balance between the biological and solubility carbon pumps, innovative methods to exploit existing satellite sea surface temperature and ocean color, and new satellite sea surface salinity measurements, are needed and will enable frequent assessment of ocean acidification parameters over large spatial scales.

A first estimation of SMOS-based ocean surface T-S diagrams

A first estimation of satellite-based ocean surface T-S diagrams is performed by using SMOS Sea Surface Salinity (SSS) and OSTIA Sea Surface Temperature (SST) and comparing them with in situ measurements interpolated fields obtained by the Argo-buoys for the North Atlantic and over the entire year 2011. The key objectives at the base of this study are: (1) To demonstrate the feasibility of generating routinely satellite-derived surface T-S diagrams, obviating the lack of extensive sampling of the surface open ocean, (2) To display the T-S diagrams variability and the distribution/dynamics of SSS, altogether with SST and the relative density with respect to in situ measurements, and (3) To assess the SMOS SSS data added value in detecting geophysical signals not sensed/resolved by the Argo measurements. To perform the latter analysis, the satellite-Argo mismatches have been overlapped with geophysical parameters of precipitation rates, surface heat and freshwater fluxes and wind speed data. Ongoing and future efforts focus on enlarging the study area and the temporal frame of the analysis and aim at developing a method for the systematic identification of surface water masses formation areas by remotely sensed data.