Ocean Salinity validation of mission requirements review / improvements: Points of Reflexion ESL teams Mission Requirements: The so-called GODAE requirements: psu in 200x200 km 10 days or 1°X1° monthly Points on verification of the requirements and associated metrics of validation 1)Level 2 versus Level 3 requirements The SMOS mission requirements over the ocean is a Level 3 product requirement  How does this translate to the Level 2 products ? in terms of requirements is not an easy question : 0.6 to 1.5 pss ? (today based on a theoretical error estimation)  L2 SSS errors are not uncorrelated, they are across-track location dependent, etc, etc.. We need to re-define the L2 requirement in view of our knowledge gain during 5 years of experience 2) Cold versus Warm water requirements: From the physical perspective, measurements sensitivity to SSS drops by a factor 3 from sst=30°C to sst=5°C  We shall not expect the same retrieval accuracy in warm seas than in the cold ones.  The arguments to have a global requirement was the increase number of obs at high latitude (so lost of sensitivity is compensated by gain in number of obs)  this is not true at L2!  At L3, it is conditioned by the actual number of measurements n with independent errors ( what is n ?) that can be averaged to reduce individual measurement errors This do not apply at L2 for which no averages are done, so, we shall refine the L2 requirements to be (at least) sst dependent COLD WATER: -0.3 K/psu Warm WATER: -1 K/psu

3) Absolute versus Relative Requirements: L3 & ESL team works revealed that SMOS data-after being biased corrected are almost reaching the mission requirements When monthly systematic biases are removed, RMSD (SMOS-ISAS) ~0.2 but ISAS is not the truth (it is smoothed over ~300km) and it is affected by ARGO undersampling...) – Doing similar exercise with ship SSS averaged over 0.25° in SPURS region, we found 0.15 (Hernandez et al. 2014)! So in term of anomalies, we are almost reaching the mission requirements =>This shall be reflected in the metrics of ocean SMOS product validation with respect the mission requirements Metrics shall be provided separatly 1)for the absolute SMOS SSS 2)For the relative SMOS SSS (anomalies)=> could use the mean SMOS SSS as a reference 3)Shall we provide the user with an SSS anomaly product in the L2 ? (Boutin et al.)

4) Better Characterizing SMOS Space & time resolution capabilities: Main validation metrics is based on ARGO float data (or OA Argo data) which has no spatial content at scales <300 km => Need to emphasize the higher-resolution capability of SMOS with respect e.g. ARGO & Aquarius (demonstrations on fronts, eddies, TIW, etc..)  TSG data shall be used to showcase such capability in complement to ARGO  Spectral scale content analyses and metrics shall be defined and used for mission achivements illustration (e.g. meso-scale, metrics for the front monitoring capability) Courtesy M. Martin Met Office

5) Problem of representativness of in situ data  Vertical and Horizontal mis-matches => rely and recall conclusions from the SISS group & paper (Little support from ESA to SMOS team involvment in SISS would be nice)  Better account for Geophysical SSS variability & model capabilities (see plot below)  provide ‘specific’ validation metrics based only on well-mixed upper ocean layer cases (TBD) in addition to the general metric  tripple co-location (ARGO+TSG+SMOS+Aquarius) Courtesy M. Martin Met Office 0.1

Representative & Visual Metrics of validation: Characterizing the regional dependencies of the results

Characterizing the Spatial Averaging Impacts

ARGO versus Foam model SMOS ¼° versus Foam model SMOS 1/2° versus Foam model SMOS 1° versus Foam model

Characterizing the Temporal Averaging Impacts

Science studies on SMOS ocean: Perspectives Potential Study 1: High latitudes seas: 1) Improving the retrieval and understanding of the physics of measurements (roughness & sst effects, sea ice contamination, glints, gain in number of obs,…) + Potential of synergies: SMOS+Aquarius+SMAP 2) Science Applications (sea ice melting, water cycle, circumpolar fronts monitoring, pCO2, bio geo-chemistry…)

Potential Study 2: Impact of satellite SSS into GCM through assimilation  Foster on Pionering works (Mercator, Univ of Hamburg, UKMetoffice, NOAA)  Process studies (salt transport by meso-scale, frontal activities, etc..) (+ need for a strong interaction with L2/L3 experts for discussions on biases, anomalies, error production... ) Martin, M., Suitability of satellite sea surface salinity data for assessing and correcting ocean forecasts. Forecasting Research Technical Report 599, Met Office, UK. Available fromhttp:// technical-reports. technical-reports

Potential Study 3: Spicyness & surface Density monitoring  SSS+SST= surface density: major source for the surface thermo-haline circulation  Equation of state density=function (sst, sss)  Proposed a Sea surface thermohaline circulation regulator mechanism associated with freshening induced by rainstorm  Verification and testing the idea against observation presents considerable Difficulty and wasn’t attempted  Now that SSS from space is available, this fondamental process of the ocean surface could be revisited Rain