1. EXTENDING THE LAND SEA CONTAMINATION CHARACTERIZATION TO THE EXTENDED ALIAS- FREE FIELD OF VIEW Joe Tenerelli (CLS) and Nicolas Reul (IFREMER) SMOS Quality Working Group #15 ESA ESRIN 6-8 October 2014

2. REMINDER OF THE PROBLEM There is a significant bias in the retrieved surface salinity around all of the continents, and this bias seems to be stable over the entire mission. By significant I mean that the biases can exceed 2 pss, while the range of SSS over the global oceans is 30-40 pss (away from river plumes and freshwater lenses). We will call this bias land-sea contamination, or LSC.

3. AN EXAMPLE OF LSC AROUND AUSTRALIA BASED UPON ARGO MEASUREMENTS FROM 2010-2013

4. AN EXAMPLE OF LSC AROUND SOUTH AMERICA BASED UPON ARGO MEASUREMENTS FROM 2010-2013

5. GLOBAL LSC IN TERMS OF FIRST STOKES PARAMETER ASCENDING PASSES FOR MAY 2011: FIRST STOKES PARAMETER BIAS The LSC is global:

6. ASCENDING PASSES FOR MAY 2011: RETIEVED SALINITY BIAS GLOBAL LSC IN TERMS OF RETRIEVED SALINITY The LSC is global:

7. ASCENDING PASSES FOR MAY 2011: RETIEVED SALINITY BIAS Note: In this presentation SMOS SSS is retrieved using the first Stokes parameter and a simple linear retrieval algorithm. GLOBAL LSC IN TERMS OF RETRIEVED SALINITY

8. LSC IS SCENE-DEPENDENT scene-dependent change as the distribution of land over the front half space changes The biases are also scene-dependent and therefore change as the distribution of land over the front half space changes:

9. THE LSC CORRECTION

10. KEY POINTS OF THE EMPIRICAL LSC CORRECTION latitude-longitude grid: 0.5x0.5 deg lat-lon grid Director cosine grid: 0.025x0.025 director cosine units rather than 0.1x0.1 director cosine units Two lookup tables are calculated: One for RFI-flagged snapshots and another for non-RFI-flagged (nominal) snapshots. 41,469 half-orbits are used to compute the mission average land contamination. Biases in all four Stokes parameters are computed. Final correction is weighted by a function that approaches zero as the fraction of land in the front half space approaches 0.2% and approaches one as the fraction approaches 1%. The correction also approaches zero as the ice fraction approached 0.02%.

11. DISCRETIZATION

12. PROCESSING STEPS (1) Successive snapshots (‘scene’) (Tx,Ty,Uxy,Vxy) on hex grid Flag scene for RFI: Tx > 500 K or Ty > 500 K or Uxy > 200 K Compute bias relative to forward model (ref. SSS is WOA-2009) for all four Stokes parameters in instrument polarization basis Grid biases onto ISEA-4H9 grid and identify (xi,eta) bins Accumulate data into daily maps on 0.5°x0.5° lat-lon grid; remove gridpoints with no measurements; introduce linear indexing for retained gridpoints Accumulate data into monthly maps; keep track of pointwise measurement counts Create separate monthly files for each variable Average the monthly Stokes parameter bias maps over the full period (Jan 2010-June 2014) RFI-flagged RFI-free

13. PROCESSING STEPS (2) Remove gridpoints with fewer than 10 passes entering into the average For each (xi,eta) cell, remove average bias over all (lat,lon) cells with no land or ice in the front half-space; removes impact of the choice of OTT Apply linear weighting function to biases which ramps down from 1 at FHS land fraction of 1% to 0 at land fraction of 0.2%. Apply similar weighting function that ramps to 0 as the ice fraction approaches 0.02%. Set correction to zero south of 60°S latitude Merge all Stokes parameter biases (single precision) into a single file for each pass direction and for RFI and non-RFI- flagged scenes. Each file is 2.45 GB in size with about 88 million gridpoints in each.

14. DISCRETIZATION

15. EXAMPLE BIAS OVER EAF-FOV

16. MEASUREMENT COUNT FOR THE AVERAGING non-RFI-flagged snapshots

17. EXAMPLE MAP OF THE FIRST STOKES BIAS non-RFI-flagged snapshots

18. MEASUREMENT COUNTS FOR THE AVERAGING RFI-flagged snapshots

19. EXAMPLE MAP OF THE FIRST STOKES BIAS RFI-flagged snapshots

20. EVALUATION OF THE CORRECTION 1.Global perspective for May 2011 2.Impact in areas with stable SSS: Australia and South America in May 2011 using ISAS as the reference 3.Comparison with ARGO data around Australia and South America over the period 2010-2013 4.Impact in areas with strongly varying SSS: Panama and the Amazon plume regions

21. EVALUATION OF THE CORRECTION 1.Global perspective for May 2011 2.Impact in areas with stable SSS: Australia and South America in May 2011 using ISAS as the reference 3.Comparison with ARGO data around Australia and South America over the period 2010-2013 4.Impact in areas with strongly varying SSS: Panama and the Amazon plume regions

22. INITIAL EVALUATION OF THE CORRECTION USING THE MONTH OF MAY 2011 AND THE ISAS MONTHLY MAP FIRST STOKES PARAMETER DIVIDED BY TWO BEFORE CORRECTION

23. INITIAL EVALUATION OF THE CORRECTION USING THE MONTH OF MAY 2011 AND THE ISAS MONTHLY MAP FIRST STOKES PARAMETER DIVIDED BY TWO AFTER CORRECTION

24. INITIAL EVALUATION OF THE CORRECTION USING THE MONTH OF MAY 2011 AND THE ISAS MONTHLY MAP DESCENDING-ASCENDING BIAS BEFORE CORRECTION

25. INITIAL EVALUATION OF THE CORRECTION USING THE MONTH OF MAY 2011 AND THE ISAS MONTHLY MAP DESCENDING-ASCENDING BIAS AFTER CORRECTION

26. EVALUATION OF THE CORRECTION 1.Global perspective for May 2011 2.Impact in areas with stable SSS: Australia and South America in May 2011 using ISAS as the reference 3.Comparison with ARGO data around Australia and South America over the period 2010-2013 4.Impact in areas with strongly varying SSS: Panama and the Amazon plume regions

27. INITIAL EVALUATION OF THE CORRECTION USING THE MONTH OF MAY 2011 AND THE ISAS MAPS First consider two areas with stable surface salinity whose distribution is well-measured by ARGO floats.

28. INITIAL EVALUATION OF THE CORRECTION USING THE MONTH OF MAY 2011 AND THE ISAS MAPS First consider two areas with stable surface salinity whose distribution is well-measured by ARGO floats.

29. INITIAL EVALUATION OF THE CORRECTION USING THE MONTH OF MAY 2011 AND THE ISAS MAPS First consider two areas with stable surface salinity whose distribution is well-measured by ARGO floats.

30. INITIAL EVALUATION OF THE CORRECTION USING THE MONTH OF MAY 2011 AND THE ISAS MAPS

31. CORRECTION REDUCES VARIATION OF BIAS WITH LAND FRACTION OUTSIDE THE FUNDAMENTAL HEXAGON

32. INITIAL EVALUATION OF THE CORRECTION USING THE MONTH OF MAY 2011 AND THE ISAS MAPS CORRECTION REDUCES VARIATION OF BIAS WITH LAND FRACTION OUTSIDE THE FUNDAMENTAL HEXAGON

33. INITIAL EVALUATION OF THE CORRECTION USING THE MONTH OF MAY 2011 AND THE ISAS MAPS

34. BIAS APPEARS AS SOON AS LAND APPEARS OUTSIDE THE FUNDAMENTAL HEXAGON

35. INITIAL EVALUATION OF THE CORRECTION USING THE MONTH OF MAY 2011 AND THE ISAS MAPS BIAS APPROACHES 2.5 PSU AS THE LAND FRACTION APPROACHES 0.9.

36. INITIAL EVALUATION OF THE CORRECTION USING THE MONTH OF MAY 2011 AND THE ISAS MAPS

38. CORRECTION SEEMS TO REDUCE THE ABSOLUTE ERROR TO ABOUT 150-200 KM FROM THE COAST. CORRECTION IS LESS EFFECTIVE WITHIN 150 KM OF THE COAST.

39. EVALUATION OF THE CORRECTION 1.Global perspective for May 2011 2.Impact in areas with stable SSS: Australia and South America in May 2011 using ISAS as the reference 3.Comparison with ARGO data around Australia and South America over the period 2010-2013 4.Impact in areas with strongly varying SSS: Panama and the Amazon plume regions

40. ARGO COLLOCATIONS: AUSTRALIA

41. TIME PERIOD: 2010-2013 ARGO-SMOS collocations are binned into 50 km wide bands (as a function of distance to coast). Biases are then computed in these bands.

42. ARGO COLLOCATIONS: AUSTRALIA UNCORRECTED SMOS SSS

43. ARGO COLLOCATIONS: AUSTRALIA CORRECTED SMOS SSS

44. ARGO COLLOCATIONS: AUSTRALIA

45. bias reduction of about 0.5 pss

46. ARGO COLLOCATIONS: AUSTRALIA Impact of the LSC correction drops rapidly within about 200 km of the coast

47. ARGO COLLOCATIONS: AUSTRALIA bias reduction of about 0.8 pss

48. A COMPARISON WITH SHIP TSG DATA WITHOUT LSC CORRECTION

49. A COMPARISON WITH SHIP TSG DATA WITH LSC CORRECTION

50. ARGO COLLOCATIONS: SOUTH AMERICA

54. bias reduction of about 1 pss

55. ARGO COLLOCATIONS: SOUTH AMERICA bias reduction of about 2 pss

56. EVALUATION OF THE CORRECTION 1.Global perspective for May 2011 2.Impact in areas with stable SSS: Australia and South America in May 2011 using ISAS as the reference 3.Comparison with ARGO data around Australia and South America over the period 2010-2013 4.Impact in areas with strongly varying SSS: Panama and the Amazon plume regions

57. DYNAMIC ZONE: PANAMA Comparing Matisse transect with SMOS SSS

58. DYNAMIC ZONE: PANAMA Comparing Matisse transect with SMOS SSS

59. DYNAMIC ZONE: PANAMA bias reduction of nearly 2 pss

60. DYNAMIC ZONE: PANAMA Comparing Matisse transect with SMOS SSS

61. DYNAMIC ZONE: PANAMA Comparing Matisse transect with SMOS SSS

62. DYNAMIC ZONE: PANAMA bias reduction of about 1 pss

63. AMAZON PLUME: ANACONDA TSG Comparing Anaconda transects with 10-day SMOS SSS

64. AMAZON PLUME: ANACONDA TSG Comparing Anaconda transects with 10-day SMOS SSS

65. AMAZON PLUME: ANACONDA TSG Comparing Anaconda transects with 10-day SMOS SSS

66. AMAZON PLUME: ANACONDA TSG Comparing Anaconda transects with 10-day SMOS SSS Corrected SMOS SSS differs from the reference used to derive the LSC correction.

67. AMAZON PLUME: ANACONDA TSG

75. LSC correction seems to overcorrect the bias (when compared to the ship TSG) in two zones along the ship track. In fact, the corrected SSS exceeds the reference used to derive the LSC correction (black curve)! To be investigated further…

76. CONCLUSIONS Introduced the new land sea contamination lookup table, now defined over the extended alias-free field of view. Comparison with ISAS monthly SSS map for May 2011 around Australia and South America shows reduction in LSC. Comparisons with ARGO from 2010- 2013 also show reduction in the LSC. Reductions in LSC may also be seen in regions of strongly time varying SSS such as near Panama and in the Amazon plume region. However, results are mixed in these areas and cases have been found in which application of the correction seems to increase the biases relative to in-situ measurements. This must be investigated further.

77. REMAINING ISSUES Difficult to derive the correction in RFI-contaminated areas such as the west Pacific, north Atlantic and Pacific, and some areas around Africa and South America. Impossible to derive the correction where the ice distribution varies with time in the field of view. Correction lookup table remains contaminated in some areas, possible due to residual RFI that is not detected by the snapshot filter. Latitudinal drift is not corrected when deriving the correction, and this drift may impact the correction. Method of handling RFI requires testing and refinement. A forward model is required to derive the correction, and errors in this model will impact the correction. Reference for salinity for the forward model is WOA-2009. Need to examine use of better reference such as Aquarius SSS maps or ISAS maps. Analysis based upon v500 data. Analysis needs to be redone using the data from the latest reprocessing campaign. Analysis based upon v500 data. Analysis needs to be redone using the data from the latest reprocessing campaign.

78. AMAZON PLUME