A. Montuori 1, M. Portabella 2, S. Guimbard 2, C. Gabarrò 2, M. Migliaccio 1 1 Dipartimento per le Tecnologie (DiT), University of Naples Parthenope, Italy.

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A. Montuori 1, M. Portabella 2, S. Guimbard 2, C. Gabarrò 2, M. Migliaccio 1 1 Dipartimento per le Tecnologie (DiT), University of Naples Parthenope, Italy 2 SMOS Barcelona Expert Centre (SMOS-BEC), Institute of Marine Sciences, Barcelona, Spain

 SMOS Mission Overview  SMOS Bayesian-based Cost Function:  General Formulation  Sensitivity Analysis  Multiple-minima Assessment  Effects of constraints  SMOS Bayesian-based minimization procedure Assessment:  Levenberg-Marquardt (LM) procedure (Monte-Carlo simulations)  Optimization for both SSS and wind speed (U 10 ) retrieval purposes

SMOS makes global observations of soil moisture over Earth's landmasses and salinity over the oceans. L-band full-polarized Microwave Imaging Radiometer using Aperture Synthesis (MIRAS). Data Product Generation System (DPGS) provides consistent SSS, SST and SSR (e.g. U 10 ) retrievals through the SMOS Level 2 Salinity Prototype Processor (L2PP) by processing geolocated TBs provided at the SMOS Level 1C (L1C) after the image reconstruction step. Assessment of the Operational SMOS Bayesian-based inversion procedure to develope a parallel simplified version of the SMOS DPGS inversion scheme for the optimal retrieval of SSS and wind speed at sea (U 10 ).

Klein and Swift, 1997 Guimbard et al., 2012 Zine et. al, 2008 p = polarization  = incidence angle SSS = Sea Surface Salinity SST = Sea Surface Temperature U 10 = Wind Speed at 10m N obs = Number of observables

SSS=35psu, SST=20°C, U 10 =5m/s σ SSS =2psu, σ SST =2°C, σ u10 =2.5m/s

Contour Plot of Cost Function True Value Estimated Value Contour Plot of Cost Function True Value Estimated Value SSS=35psu, SST=20°C, U 10 =5m/s σ SSS =2psu, σ SST =2°C, σ u10 =2.5m/s Contour Plot of Cost Function True Value Estimated Value

 Un-constrained cost function (OBS term)  SST constrained cost function (OBS + SST Background) SST Estim - SST True

 Retrieved - True  Retrieved - Prior SSS-U10-SST constrained cost function configuration SSS=35psu, SST=20°C, U 10 =5m/s σ SSS =0.3psu, σ SST =1°C, σ u10 =2m/s

 Retrieved - True  Retrieved - Prior SSS-U10-SST constrained cost function configuration SSS=33psu, SST=0°C, U 10 =14m/s σ SSS =0.3psu, σ SST =1°C, σ u10 =2m/s

 Levenber-Marquardt (Monte-Carlo Simulations approach)  Optimization for SSS and U 10 retrieval:  SST constrained of fixed to an auxiliary a priori value  SSS un-constrained for SSS retrieval  Optimization for SSS and U 10 retrieval:  SST constrained of fixed to an auxiliary a priori value  SSS un-constrained for SSS retrieval

(σ SSS =100psu)

(σ SSS =0.3psu) (σ SSS =100psu)(σ SSS =0.3psu) (σ SSS =100psu)(σ SSS =0.3psu) (σ SSS =100psu)(σ SSS =0.3psu)

SSS (psu) retrieval – DPGS Configuration μ (DPGS / Prior)RMSE (DPGS / Prior)STD (DPGS / Prior) AFEAFAFEAFAFEAF Warm & Low0.01 / / / / / / 0.36 Warm & High0.02 / / / / / / 0.55 Cold & Low-0.07 / / / / / / 1.07 Cold & High0.05 / / / / / / 1.83 U 10 (m/s) retrieval – Fully constrained Configuration μ (DPGS / Prior)RMSE (DPGS / Prior)STD (DPGS / Prior) AFEAFAFEAFAFEAF Warm & Low0.04 / / / / / / 0.91 Warm & High0.03 / / / / / / 0.64 Cold & Low-0.05 / / / / / / 0.72 Cold & High-0.06/ / / / / / 0.49

SSS (psu) retrieval – DPGS Configuration μ (DPGS / Prior)RMSE (DPGS / Prior)STD (DPGS / Prior) AFEAFAFEAFAFEAF Warm & Low-0.01 / / / / / / 0.41 Warm & High0.03 / / / / / / 0.54 Cold & Low0.01 / / / / / / 1.21 Cold & High0.05 / / / / / / 1.79 U 10 (m/s) retrieval – Fully constrained Configuration μ (DPGS / Prior)RMSE (DPGS / Prior)STD (DPGS / Prior) AFEAFAFEAFAFEAF Warm & Low0.04 / / / / / / 0.88 Warm & High-0.04 / / / / / / 0.69 Cold & Low0.08 / / / / / / 0.83 Cold & High0.01 / / / / / / 0.55

 Internal SMOS Bayesian-based processing chain for SSS and U 10 retrieval purposes has been developed.  Low sensitivities of SMOS TB measurements with respect to geophysical parameter changes, especially for SST.  Unique absolute minimum value for all the cost function configurations  Unique triplet solution of SSS-U 10 -SST.  Fixing or constraining SST to an auxiliary value improves the retrieval of SSS and U 10.  Successful assessment of LM minimization procedure for the retrieval of SSS and U 10 by means of realistically simulated SMOS TB measurements.  SSS optimal retrieval  DPGS [SST-U 10 ] configuration.  U 10 optimal retrieval  Fully [SST-SSS-U 10 ] constrained configuration.  Future test with both real SMOS TB data.