SMOS-MODE Cost Action


Working Groups

Working Group 1: Satellite salinity retrieval

Chair: Marcos Portabella

Co-Chair: Jacqueline Boutin

- Monitoring of the SMOS instrument performance and stability, and definition of an optimal calibration strategy. Detection of systematic instrumental errors. This will be performed by means of consistency tests, mainly at Level 1, which will also provide the basis for the consolidation and improvement of the existing TB bias mitigation techniques.

- Characterization of external perturbing sources such as Solar, Galactic and Cosmic reflections, signal rotation in the ionosphere, coastline and ice borders contaminations. The characterization of these noise sources will support the choice of an optimal data selection and filtering strategy.

- Detection of radiofrequency interferences (RFI). Investigation of the effect of human activities in the satellite radiometer data quality at the radio frequency band ranging from 1400 to 1427 MHz (L-band). This will include mapping of the affected areas along with proposing methods for flagging RFI-contaminated data.

- Characterization of the sea surface emissivity (or brightness temperature) sensitivity to geophysical parameters such as sea surface roughness, fractional foam coverage, precipitation rates and sea surface temperature. Characterization of the intrinsic SSS variability and cross-correlations between various geophysical conditions.

- Improvement of existing empirical forward models. With the upcoming availability of real data, the pre-launch semi-empirical model used in the ocean salinity Level 2 operational processor will be reviewed and improved, in particular the empirically-derived roughness term. The benefits of developing a fully empirical forward model (in which other geophysical parameters besides roughness, i.e. SSS and SST, are also empirically modelled) will also be assessed at a later stage.

- Definition of the optimal retrieval processing chain by duly estimating error modelling (both instrumental and geophysical), developing a comprehensive quality control, and assessing the inversion cost function. The latter activity will include the review of existing formulations as well as the derivation and testing of new ad-hoc formulations.

- Evaluation of adequate spatio-temporal averaging methodologies. Filtering and averaging of the data is needed to reduce the level of noise of the salinity measurements, even if at the detriment of the spatial and temporal resolution of the estimates. The main focus is to develop optimal averaging strategies to derive unbiased SMOS SSS Level 3 products from single-pass Level 2 SMOS salinity data by comparing simple averaging, weighted average, and optimal interpolation techniques. Error estimates of Level 2 and Level 3 SMOS products will be given by applying the usual statistical methods used in geo-statistics.

- Geographical characterization of the quality of the SSS retrievals. The resulting SSS values will be analyzed over specific identified monitoring/validation areas, and also at challenging regions characterized by cold surface waters (reduced sensitivity of the microwave radiometer), freshwater input from rivers or melting sea ice. These analyses will also be performed in several atmospherical conditions (e.g., different wind speed regimes), as well as in the regions of low spatio-temporal changes in surface salinity.

- Intercomparison and fusion with Aquarius/SAC-D data (the US/Argentinean dedicated salinity mission, due to launch in 2010) should they become available during the project.

- Sea-Ice characteristic retrievals.


Working Group 2: Oceanographic exploitation

Chair: Yianna Samuel-Rhoads

Co-Chair: Aida Alvera-Azcarate

- Systematic collocation of SMOS data with meaningful satellite datasets such as, among others, the scatterometer wind fields, the AMSR-E passive microwave radiometry data, and wide-swath ASAR images.

- Validation of SMOS SSS products against in-situ measurements. Specific comparisons are foreseen against moored buoys, profilers (among them, the Argo floats network), drifters and gliders, as well as from oceanographic cruises transects and from VOS (Voluntary Observatory Ships). These data will be arranged in specific match-up datasets, to properly organize the spatiotemporal collocation of the SMOS and in-situ measurements. Of particular relevance will be the spatial structures analysis observed by thermosalinographs onboard both research vessels and ships of the VOS program. Besides, the usefulness of the near-surface SSS data from Argo floats for SMOS surface salinity product validation will be assessed.

- Validation versus ocean models and climatology. Model outputs are being obtained from available prediction systems such as NEMO/OPA, MFS and HYCOM (Hybrid Coordinate Ocean Model). Besides, MICOM (Miami Isopycnic Coordinate Ocean Model) together with the TOPAZ data assimilation system will be used to examine the importance of the SSS fields to improve the knowledge of the hydrographic structure of high latitude water masses and the thermohaline circulation. Moreover, departures from climatological products will be studied, as well as zonal averages and scatter per each ocean basin.

- Deployment of Air/Sea Interaction Profilers (ASIP). The ASIPs are autonomous profiling instruments capable of measuring the upward salinity vertical distribution up to the ocean-atmosphere interface. It should provide insights in the current knowledge of the near-surface salinity structure, providing might exist a significant ocean surface salinity gradient (known as the skin effect), which can decouple the validation measurement (usually at 1 m depth) from the remote measurement (at 0.5 cm depth).

- Improvement of the ocean forecasting capabilities based on advanced downscaling and assimilation techniques. The 3DVar and Ensemble data assimilation schemes and the SEEK filter will be used to examine the importance of SMOS SSS in determining the ocean circulation  structures and the water masses distribution in several basins. Besides, comparison with satellite sea surface salinity will be used as a measurement of the forecast skill.

- Sea-Ice and other ocean applications.