Ocean Salinity validation of mission requirements review / improvements:

Points of ReflexionESL teams

Mission Requirements:

The so-called GODAE requirements:

0.1-0.2 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 requirementÞHow 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)ÞL2 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°CÞWe shall not expect the same retrieval accuracy in warm seas than in the cold ones.ÞThe 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)Þ this is not true at L2!ÞAt 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 errorsThis 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 requirementsMetrics shall be provided separatly 1) for the absolute SMOS SSS2) For the relative SMOS SSS (anomalies)=> could use the mean SMOS SSS as a reference3) 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 hasno 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..)

Þ TSG data shall be used to showcase such capability in complement to ARGOÞ 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. MartinMet 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)

Þprovide ‘specific’ validation metrics based only on well-mixed upper ocean layer cases (TBD) in addition to the general metric

Þ tripple co-location (ARGO+TSG+SMOS+Aquarius)

Courtesy M. MartinMet Office0.1

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+SMAP2) Science Applications (sea ice melting, water cycle, circumpolar

fronts monitoring, pCO2, bio geo-chemistry…)

Potential Study 2: Impact of satellite SSS into GCM through assimilationÞ Foster on Pionering works (Mercator, Univ of Hamburg,

UKMetoffice, NOAA)Þ 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., 2015. Suitability of satellite sea surface salinity data for assessing and correcting ocean forecasts. Forecasting Research Technical Report 599, Met Office, UK. Available fromhttp://www.metoffice.gov.uk/learning/library/publications/science/weather-science-technical-reports.

Potential Study 3: Spicyness & surface Density monitoringÞ SSS+SST= surface density: major source for the surface

thermo-haline circulationÞ Equation of state density=function (sst, sss)

ÞProposed a Sea surface thermohaline circulation regulator mechanism associated with freshening induced by rainstorm

ÞVerification and testing the idea against observation presents considerable Difficulty and wasn’t attempted

ÞNow that SSS from space is available, this fondamental process of the ocean surface could be revisited

Rain