1. QWG8, Boutin et al. SMOS and Aquarius: SSS and Wind Effect J. Boutin, X. Yin, N. Martin (LOCEAN, Paris), E. Dinnat (Chapman University/NASA/GSFC), S. Yueh (NASA/JPL) Coll. G. Reverdin (LOCEAN), G. Alory (LEGOS), F. Gaillard (LPO) ESA Expert Support Lab.(ARGANS, ICM, Ifremer, ACRI-st, CLS) ESA/CNES SMOS CAL/VAL project (GLOSCAL) NASA ROSES project (Intercalibration of SMOS and Aquarius)

2. QWG8, Boutin et al. Overview of this presentation SMOS – Aquarius – ARGO maps SMOS & Aquarius wind dependencies Comparisons of SMOS SSS wrt in situ measurements (ship and ARGO) Influence of using SSMI WS intead of ECMWF

3. QWG8, Boutin et al. Data Improvements with respect to previous versions: -Reduced coastal bias; OTT (systematic bias in the Field of View) every 2 weeks and separetely for ascending and descending orbits; improved wind correction ; improved RFI & outlier sorting SSS averages weighted by the variance of the error of the retrieved SSS (Boutin et al., TGRS, 2012), and restricted to wind speed between 3 and 12m/s USE ONLY ASCENDING ORBITS SATELLITE SSS -SMOS SSS reprocessed by ESA v5.5 (wind-model 1) -AQUARIUS level 3 maps v1.2.3 IN SITU SSS -Optimal Interpolation of ARGO SSS: IFREMER In Situ Analysis System (ISAS) (Gaillard et al. 2009) -ARGO SSS (upper SSS between 10m and 0.5m depth) (CORIOLIS GDAAC) -Ships of Opportunity (Delayed mode data delivered by SSS observatory (http://www.legos.obs-mip.fr/observations/sss/))

4. QWG8, Boutin et al. Ascending vs Descending SSS: Sept 2011 SSS Ascending orbitsSSS Descending orbits SSS error Ascending orbitsSSS error Descending orbits Descending OTTs not enough to remove stripes especially in September => Sun alias? Galactic noise?

5. QWG8, Boutin et al. Sept-Dec 2011 SMOS v5.5 (Ascending Orbits) Aquarius v1.2.3 ARGO OI SMOS - AQUARIUS – ARGO SSS – Sept-Dec 2011

6. QWG8, Boutin et al. SMOS-Aquarius SMOS-ARGO OI Aquarius-ARGO OI Sept-Dec 2011 SMOS features: -issues close to land (image reconstruction) -Large RFI (N. Atl., Asian coasts) -Ice edge Aquarius features: -Underestimates in Southern Ocean -Overestimates close to islands (e.g. S. Pac ). SMOS & Aquarius features: -Better resolution of Amazone Plume -Lower SSS in rainy regions -Lower SSS in Indian Ocean +1 +1 +1

7. QWG8, Boutin et al. SMOS & AQUARIUS WIND DEPENDENCIES Aquarius Tb-wind : -empirical wrt SSMI wind speed + NCEP wind direction (Yueh) -empirical wrt NCEP wind (Dinnat) SMOS Tb-wind : -Adjusted rough & foam models wrt SSMI wind speed (Yin et al, TGRS, 2012) -Adjusted rough & foam models wrt ECMWF wind speed (Yin et al, TGRS, 2012) -Empirical model wrt ECMWF wind speed (Tenerelli, 2011) -Empirical model wrt ECMWF wind speed (Guimbard et al, 2012) Given the uncertainty about the absolute bias between model and data (need for OTT correction for SMOS) all the curves have been adjusted at 7m/s

8. QWG8, Boutin et al. Very similar SMOS and Aquarius Tb-Wind omnidirectional dependencies 3<WS<12 m/s Above 15m/s SMOS  T higher than Aquarius  T (especially in H polarization) Aquarius (SSMI WS); Aquarius (NCEP WS); SMOS (SSMI WS); *,*,* SMOS (ECMWF WS) Omnidirectional Tb-Wind dependencies 28.7° 37.8° 45.6°  Th (K)  Tv (K) 7 777 77 00 000 0 217 WS (m/s) 2172 2 2 2 WS (m/s)

9. QWG8, Boutin et al. Tb dependency with Wind Direction 020 WS (m/s) 0200 28.7° 37.8° 45.6° 0.9 0.6 0.3 0 -0.3  T (K) 0.9 0.6 0.3 0 -0.3 0.9 0.6 0.3 0 -0.3 Aquarius SMOS model 1 V1 V2 H1 H2 Tb=Tbwind + Tb1 cos(Phi) + Tb2 cos(2Phi) TbV1 TbV2 TbH1 TbH2 Much larger dependency in Aquarius than in SMOS functions at high WS! SMOS and Aquarius Tb wind dependencies better agree for wind speed between 3 and 12m/s => confirm the relevance of SMOS L2 wind speed range flagging

10. QWG8, Boutin et al. Comparisons of SMOS reprocessed SSS(v5) and in situ SSS ARGO Ship: –Indian Ocean (Lavender) –Atlantic Ocean: Rio Blanco Colibri and Toucan

11. QWG8, Boutin et al. Comparisons with ARGO in selected regions far from land (Aug-Sept 2010 & 2011) Atl subtrop Ind. S Pac S Pac trop N 32 40 32 (SMOS SSS weighted averaged over 100km-10days around ARGO) SMOS – ARGO SSS in tropical Pacific 0.1 fresher than in other regions: rain? SSSsmos SSSargo

12. QWG8, Boutin et al. Indian Ocean: SMOS–Lavender Ship SSS 19 Sep – 1 Oct 2010 Sept 2010 - SMOS SSS (Asc orbits) SMOS – ARGO OI SSS Next slides: SMOS SSS averaged over 10 days and 100km around Lavender time and location

13. QWG8, Boutin et al. Ship SMOS 10d-100km ARGO OI ARGO OI much smoother than Ship SSS: monthly & ~1 ARGO meas./10days, 2° SMOS (40km resolution) better sees small scale variability, but still some deficiencies (distance to coast?, RFI, islands…) On average: SSS ARGO_OI -SSS TSG = 0.2 (0.23) SSS SMOS -SSS TSG = 0.0 (0.37) SSS latitudinal profiles – Ship-ARGO OI-SMOS

14. QWG8, Boutin et al. Atlantic Ocean SSS: SMOS and Rio Blanco Ship (Aug-Sep 2010) 40 30 -40 50 Distance to coast SSS ITCZ High noise close to land but qualitative agreement SMOS SSS fresher than ship in ITCZ Latitude Ship SMOS 10d-100km

15. QWG8, Boutin et al. Comparison of Toucan and Colibri ship and SMOS v5 reprocessed SSS Leslie David (master trainee), Gilles Reverdin, Jacqueline Boutin (LOCEAN)

16. QWG8, Boutin et al. SPURS region Toucan and Colibri Ship of Opportunity trajectories (2010-2011)

17. QWG8, Boutin et al. 32 38 ARGO interpolation SMOS Ascending 10days-100km Colibri Ship SSS Latitude (°) 5N 35N 18-22 October 2011

18. QWG8, Boutin et al.

19. Mean and std of difference (SMOS-Ship SSS) over the whole period 2010-2011and July-Aug-Sept Coast/RFI Biases? Std ~0.2-0.3 (except north of 25N in winter- Spring; RFIs?) (all sections except 19-Oct-2010, 11-Jul-2010 et 14-Mar-2011 ) 10N 15N 20N Latitude 30N 35N -0.2 0.2 1 Bias and std(diff) Black /grey: all months Colors: July-Aug-Sept

20. QWG8, Boutin et al. RFI sorting needs to be improved!! 35.5 38.5 16N 34N June 2011

21. QWG8, Boutin et al. Conclusion SMOS SSS: In tropical-subtropical regions, far from land, in non rainy region, precision at 100x100km 2 -10days ~0.3 SMOS SSS freshening wrt in situ SSS (~5m depth) in rainy conditions: true salinity effect? Needs for surface drifters for validation (needs for a lot of matchups!!!) Ship TSG: very useful for validating ‘small scale’ (<200km) variability (gradients) seen by SMOS Still issues (sun aliases, land vicinity, ice edge, RFI sorting …): image reconstruction still in progress SMOS and Aquarius wind models Tb-wind SMOS and Aquarius very similar: 3-12m/s but Aquarius lower above 12m/s; Aquarius azimuth dependency much larger at high wind speed

22. QWG8, Yin et al. Issues about wind speed uncertainties and SMOS retrieved SSS Yin X. 1, Boutin J. 1, Martin N. 1, Vergely J. 2, Spurgeon P. 3 1. LOCEAN/IPSL, UMR CNRS/UPMC/IRD/MNHN, France 2. ACRI-ST, France 3. ARGANS, United Kingdom

23. QWG8, Yin et al. Outline Impact of wind speed uncertainties on SMOS retrieved SSS 1) SSMI versus ECMWF wind speed 2) Difference in retrieved SSS using two different prior wind speeds 3) The eastern equatorial Pacific Ocean Conclusions and perspectives

24. QWG8, Yin et al. Wind speed retrieved from SMOS data August 2010, ECWMF wind speed used as prior. -300 300 WS (retrieved-prior) Distance to the track (km) Latitude 40N 50S Incidence angle 60 0 Eta Distance to the track (km) In the centered swath (within +-300km), wind speed is adjusted with SMOS data; in the border of the swath (outside of +-300km), wind speed can not be adjusted with SMOS data (not enough incidence angles).

25. QWG8, Yin et al. Data 1. SMOS Brightness temperature (last reprocessing: L1c v504) 1) August 2010, 436 ascending orbits over global ocean 2) September 2011, 418 ascending orbits over global ocean 2. ECMWF wind speed collocated with SSMI wind speed, August 2010 and September 2011 collocation radii of ±0.5 hour and ±50 km 3. SSS 1) SMOS SSS retrieved with ECWMF wind as prior. Roughness model fitted from ECMWF wind speed (Yin et al., TGRS SMOS special issue, 2012) is used. ( ESA reprocessing v550) 2) SMOS SSS retrieved with SSMI wind as prior, processed by LOCEAN. Roughness model fitted from SSMI wind speed (Yin et al., TGRS SMOS special issue, 2012) is used. 3) ARGO optimal interpolation (ISAS) (Gaillard et al. 2009) used as reference

26. QWG8, Yin et al. For the orbit 20100809T142544_20100809T151945, the ECMWF and SSMI wind speeds are quite different around 17S. One example of differences between ECMWF, SSMI and retrieved WS from SMOS data

27. QWG8, Yin et al. Latitude TB simulations with SSMI Wind 5 points running mean of SMOS TB TB simulations with ECMWF Wind No matter whether SSMI or ECWMF wind is used as prior, retrieved wind speed is closer to SSMI wind speed but still a little bit lower. TB simulations with SSMI Wind are closer to SMOS TB _____ECMWF prior WS ---------SSMI prior WS Retrieved WS (ECMWF prior) Retrieved WS (SSMI prior)

28. QWG8, Yin et al. August 2010 monthly average SMOS SSS (+-300km) 3-12m/s (both ECWMF and SSMI) Similar spatial distribution The same for September 2011, not shown here. SMOS SSS with SSMI wind speed SMOS SSS with ECMWF wind speed ARGO OI SSS

29. QWG8, Yin et al. August 2010 monthly average SMOS SSS – ISAS/ARGO SSS 3-12m/s 1. In the eastern equatorial Pacific ocean, differences between SMOS SSS with SSMI WS and ARGO OI SSS are often lower than those with ECMWF WS. 2. In the eastern part of Pacific and Atlantic ocean, SSMI WS are lower than ECMWF WS. Also, the retrieved SSS with SSMI WS are lower than those with ECMWF WS. Similar patterns in September 2011, not shown here. SMOS– ARGO OI SSS, SSMI prior wind speed SMOS– ARGO OI SSS, ECMWF prior wind speed 1 -1 1 -1 1 -1 1 -1 SMOS SSS (SSMI) – SMOS SSS (ECMWF) WS (SSMI) – WS (ECMWF)

30. QWG8, Yin et al. Retrieved WS(ECMWF) Retrieved WS(SSMI) rWS(ECMWF)- ECMWF WS rWS(SSMI)- SSMI WS -Monthly averaged August 2010- 1. In the eastern equatorial Pacific ocean, SSMI WS are much lower than ECMWF WS. 2. Retrieved WS with ECMWF WS are trying to get close to SSMI WS but not close enough.

31. QWG8, Yin et al. Conclusions and Perspectives 1. In the centered part of the swath (within +-300km), wind speed is adjusted with SMOS data; In the border of the swath (outside of +-300km), wind speed can not be adjusted with SMOS data. 2. In the centered part of the swath (+-300km), the difference between SMOS SSS and ARGO OI SSS is lower than the border, since wind speed is corrected (partly) with SMOS data. 3. Locally (eastern equatorial Pacific), SSMI wind speeds used as prior in the retrieval perform better (SMOS retrieval scheme not able to completely correct for the differences between SSMI and ECMWF WS, but it decreases SSS bias locally). 4. Origin of differences in eastern equatorial Pacific? 5. Work in progress….

32. QWG8, Yin et al. Sensitivity of L-band Tb (h- & v-pol) to θ, wind speed and SSS Incidence angle From Dinnat et al. 2003 Incidence angle (°)  Tv/  WS >0 and with incidence angle  Tv/  SSS<0 and abs() with incidence angle  Th/  WS>0 and with incidence angle  Th/  SSS<0 and abs() with incidence angle (at nadir, 20°C,  Tb/  WS ~0.2K/m/s,  Tb/  SSS~-0.5K/psu => a bias of 5m/s on WS  ~ a bias of -2psu on SSS)

33. SMOS SSS (ESA level 2 retrieval) is retrieved through a least square minimisation of the difference between SMOS and modeled Tb. Retrieval of SSS (  =100psu), SST (  =1°C), WS(  =1.5m/s on wind components) through the minimisation of: => estimate of SSS error (Levenberg & Marquard algorithm) SMOS SSS and WS retrieval method

34. QWG8, Yin et al. SSS v5 Descending August & September 2010 & 2011 August 2010 September 2011 August 2011 September2010 Descending OTTs not enough to remove stripes Larger stripes in September than in August => Sun alias? Galactic noise? Less outliers in the northern Atlantic in 2011 than in 2010  Decrease of RFIs