1. UPDATE ON GALACTIC NOISE CORRECTION Joe Tenerelli SMOS Quality Working Group #9 ESA ESRIN 24 October 2012

2. PLAN 1.Briefly review the problem of scattered galactic radiation. Show impact on retrieved salinity. 2.Review the seasonal dependence of the signal. 3.Look at the impact of the simple specular reflection solution. Motivate development of more complicate scattering models. 4.Review the performance and problems with the pre-launch Kirchhoff scattering model, focusing on descending passes. 5.Introduce development of empirically fit geometrical optics models. Show differences between models derived from ascending and descending passes. 6.Compare distributions of SSS biases for the various models as a function of scattered galactic brightness.

3. Faraday rotation Cosmic+Galactic (up to 8 K after scattering) scattering by rough surface atm absorption (trans = 0.995) atm absorption (trans = 0.995) atm emission (2 K) atm emission (2 K) specular (100 K) +rough (10 K) surface emission Galactic radiation incident from all directions (Tx+Ty)/2

4. (Tx+Ty)/2 bias +1 K SSS bias -2 psu

5. SEASONAL AND PASS DIRECTION VARIATION

6. 5 m/s SCATTERING OF GALACTIC RADIATION

7. April 2 Sep 20 June 25 SEASONAL AND PASS DIRECTION VARIATION

8. April 2 Sep 20 June 25 SEASONAL AND PASS DIRECTION VARIATION

9. IMPACT OF CELESTIAL SKY BRIGHTNESS Averaging the scattered celestial sky brightness along alias-free portions of dwell lines: No correction for reflected celestial sky radiation leads to strong along-track bands of negative SSS anomalies:

10. IMPACT OF CELESTIAL SKY BRIGHTNESS No correction for reflected celestial sky radiation leads to strong along-track bands of negative SSS anomalies:

11. IMPACT OF CELESTIAL SKY BRIGHTNESS No correction for reflected celestial sky radiation leads to strong along-track bands of negative SSS anomalies:

12. IMPACT OF CELESTIAL SKY BRIGHTNESS No correction for reflected celestial sky radiation leads to strong along-track bands of negative SSS anomalies:

13. IMPACT OF CELESTIAL SKY BRIGHTNESS Correction assuming a specular surface:

14. IMPACT OF CELESTIAL SKY BRIGHTNESS Correction assuming a specular surface:

15. IMPACT OF CELESTIAL SKY BRIGHTNESS The preceding Kirchhoff formulation (using the Kudryavtsev wave spectral model) undercorrects for the celestial sky radiation, leaving a noticable along- track band of negative SSS bias (or high brightness temperature bias):

16. IMPACT OF CELESTIAL SKY BRIGHTNESS Initial fix for commissioning phase reprocessing was to use the ‘least rough’ Kirchhoff solution available, corresponding to a 10-m wind speed of 3 m/s. This significantly reduced the along-track bands of negative SSS bias, but some noticable banding remains:

17. Take high-frequency limit of the Kirchhoff approximation for scattering cross sections: Obtain expression in terms of slope probability distribution: Assume Gaussian slope probability distribution. Then fit the slope variance: GEOMETRICAL OPTICS GALACTIC MODEL

18. 1.Use reconstructed brightness temperatures over the alias-free field of view 2.Correct for running-averaged OTT. OTT based upon descending passes in first half of year and ascending passes in second half of year, to avoid large influence of galactic radiation upon OTTs. 3.Removal AF-FoV averaged bias as derived from time-latitude bias evolution. 4.Subtract model predicted brightness temperature, excluding contribution from celestial sky brightness. 5.Project resulting ‘residual’ brightness temperatures into a regular 1 o x1 o grid in celestial coordinates. 6.Use all data from June 2010-July 2012. Fit model on ascending and descending passes separately. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: APPROACH

19. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: ASCENDING PASSES SMOS residuals Example geometrical optics trial solutions

20. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: ASCENDING PASSES SMOS residuals Example geometrical optics trial solutions

21. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: ASCENDING PASSES

23. IMPACT OF CELESTIAL SKY BRIGHTNESS Reflected radiation for ascending passes in March not as strong as for descending passes in Sep/Oct:

24. IMPACT OF CELESTIAL SKY BRIGHTNESS Scattered radiation for ascending passes in March also not as strong as that for descending passes in Sep/Oct:

25. IMPACT OF CELESTIAL SKY BRIGHTNESS

27. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: DESCENDING PASSES SMOS residuals Example geometrical optics trial solutions

28. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: DESCENDING PASSES SMOS residuals Example geometrical optics trial solutions

29. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: DESCENDING PASSES

32. COMPARING THE ASC AND DESC MSS FITS At high incidence angles, optimal mean square slopes for descending passes are lower than those for ascending passes. Discrepancy is largest at 50 o incidence angle (where the GO fit is most problematic). At low incidence angles, the opposite is true. Change occurs somewhere between 20 o and 40 o incidence angle.

33. AN EXAMPLE OF THE FIT 40 o incidence angle Descending passes 6-8 m/s ECMWF surface wind speed first Stokes parameter: (Tx+Ty)/2

34. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: DESCENDING PASSES Descending SMOS

35. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: DESCENDING PASSES Descending geometrical optics model

36. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: DESCENDING PASSES Descending geometrical optics model

37. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: DESCENDING PASSES Kirchhoff model at 3 m/s

38. LOWER SURFACE WIND SPEED 40 o incidence angle Descending passes 3-6 m/s ECMWF surface wind speed first Stokes parameter: (Tx+Ty)/2

39. LOWER SURFACE WIND SPEED Descending geometrical optics model

40. Kirchhoff model at 3 m/s underpredicts scattered brightness along galactic plane and overpredicts it on either side. LOWER SURFACE WIND SPEED Kirchhoff model at 3 m/s

41. COMPARING ASCENDING AND DESCENDING GEOMETRICAL OPTICS MODEL FITS 40 o incidence angle Descending passes 3-6 m/s ECMWF surface wind speed first Stokes parameter: (Tx+Ty)/2

42. COMPARING ASC AND DESC GO MODELS Descending Empirical GO model – SMOS derived (Tx+Ty)/2:

43. Ascending empirical GO model underpredicts scattered celestial sky brightness along the galactic plane and overpredicts it on either side: Ascending Empirical GO model – SMOS derived (Tx+Ty)/2: COMPARING ASC AND DESC GO MODELS

44. Descending pass empirical GO model predicts A more sharply peaked distribution of scattered celestial sky noise: Descending - Ascending Empirical GO model COMPARING ASC AND DESC GO MODELS

45. ORIENTATION ANGLE DEPENDENCE surface scattering cross sections galactic brightness A possible explanation for descending-ascending differences in scattered galactic radiation for a given specular point…

46. ORIENTATION ANGLE DEPENDENCE The brightness incident at antenna for any given specular point depends upon orientation of the incidence plane. Models predict this and the data also suggest such a dependence.

47. IMPACT OF THE ORIENTATION ANGLE

48. SPECULAR REFLECTION OF THE GALAXY AT VERY LOW ECMWF 10 METER WIND SPEEDS

49. IMPACT OF CELESTIAL SKY BRIGHTNESS In some cases it appears that the galactic radiation is specularly reflected at ECMWF surface wind speeds below 2-3 m/s. But this is not always the case:

50. IMPACT OF CELESTIAL SKY BRIGHTNESS Green circles: evidence of specular reflection of galactic radiation

51. OVERALL MODEL PERFORMANCE Compile statistics on the SSS error obtained with each galactic model over a rectangular lat-lon domain from 50 o S to 20 o N latitude and from 180 o to 110 o W longitude. Desc: Sep/Oct 2010-2012 Asc: Mar/Apr 2011-2012

52. OVERALL MODEL PERFORMANCE Distribution of samples as function of scattered celestial sky brightness temperature for descending passes in September/October 2010-2012:

53. OVERALL MODEL PERFORMANCE Distribution of samples as function of scattered celestial sky brightness temperature for descending passes in September/October 2010-2012:

54. OVERALL MODEL PERFORMANCE Descending passes, very low ECMWF surface wind speeds:

55. OVERALL MODEL PERFORMANCE Descending passes, light-moderate ECMWF surface wind speeds:

56. OVERALL MODEL PERFORMANCE Descending passes, moderate ECMWF surface wind speeds (most likely case):

57. OVERALL MODEL PERFORMANCE Distribution of error for descending passes in September/October 2010-2012: Comparing the descending pass GO and the Kirchhoff model at 3 m/s.

58. OVERALL MODEL PERFORMANCE Distribution of error for descending passes in September/October 2010-2012: Comparing the descending and ascending pass empirical GO models.

59. OVERALL MODEL PERFORMANCE Distribution of error for descending passes in September/October 2010-2012: Comparing the descending pass GO and the Kirchhoff-3 model for high scattered celestial sky brightness.

60. CONCLUSIONS: GALACTIC MODEL 1.Model for scattering of celestial sky brightness has been under continual refinement. 2.Originally proposed Kirchhoff scattering model using the Kudryavtsev wave spectrum strongly underpredicts the scattered brightness near the galactic plane and overpredicts the brightness away from the galactic plane under most surface wind speeds. 3.Kirchhoff scattering model evaluated at surface wind speed of 3 m/s better predicts the scattered brightness under most wind conditions, but still underpredicts brightness near galactic plane at low wind speeds, and overpredicts brightness at high wind speeds. Lack of wind speed dependence is unrealistic. 4.Semi-empirical models based upon geometrical optics produce improved predictions relative to those based on Kirchhoff and retain wind speed dependence. 5.Geometrical optics fits to the data are different for ascending and descending passes, possibly due to inaccurate representation of scattering cross sections away from specular direction. Possible solution is to introduce ascending and descending lookup tables for scattered celestial sky brightness.

61. OVERALL MODEL PERFORMANCE Distribution of error for ascending passes in March/April 2011-2012: Comparing the ascending pass GO and the Kirchhoff model at 3 m/s for high scattered celestial sky brightness.

62. OVERALL MODEL PERFORMANCE Distribution of error for ascending passes in March/April 2011-2012: Comparing the descending and ascending pass empirical GO models for high scattered celestial sky brightness.

63. Appears clearly in global maps of monthly mean AF- FoV first Stokes parameter bias (descending- ascending). Latitudinal drift apparent towards the end of every year. Seasonal drift in latitudinally averaged bias. BRIGHTNESS TEMPERATURE DRIFT

64. Impact upon global maps of salinity bias (descending- ascending) is clearly evident. Latitudinal drift apparent towards the end of every year. Seasonal drift in latitudinally averaged bias. BRIGHTNESS TEMPERATURE DRIFT

65. Time-latitude structure of the AF-FoV bias over the mission lifetime:

66. BRIGHTNESS TEMPERATURE DRIFT Evaluating the long-term drift of first Stokes parameter (averaged over large latitude range in southern hemisphere). Descending passes: 1-Slope, Calibrated L1, JRECON (1-slope) Over 1 K drop in (Tx+Ty)/2 towards the end of the year for both 1- slope model and the new ‘calibrated L1’ approach!

67. BRIGHTNESS TEMPERATURE DRIFT Evaluating the long-term drift of first Stokes parameter (averaged over large latitude range in southern hemisphere). Ascending passes: 1-Slope, Calibrated L1, JRECON (1-slope) Over 1 K drop in (Tx+Ty)/2 towards the end of the year for both 1- slope model and the new ‘calibrated L1’ approach!

68. BIAS TRENDS: NIR ANTENNA TEMPERATURE Compare drift in latitudinally averaged NIR antenna temperatures to corresponding AF-FoV averaged drift. Modify latitude range for averaging to avoid impact from land and ice at high latitudes. Account for sun impact on antenna temperatures. Especially important for descending passes late in the year.

69. BIAS TRENDS: NIR ANTENNA TEMPERATURE Compare drift in latitudinally averaged NIR antenna temperatures to corresponding AF-FoV averaged drift. Modify latitude range for averaging to avoid impact from land and ice at high latitudes. Account for sun impact on antenna temperatures. Especially important for descending passes late in the year.

70. Big jump in sun L-band Tb from end of 2010 to end of 2011!

71. BIAS TRENDS: NIR ANTENNA TEMPERATURE Bias trends in NIR antenna temperatures similar to AF-FoV trends except for descending passes at the end of 2011:

72. BIAS TRENDS: NIR ANTENNA TEMPERATURE Bias trends in NIR antenna temperatures similar to AF-FoV trends except for descending passes at the end of 2011:

73. OTT EVOLUTION reference

74. OTT EVOLUTION reference

75. OTT EVOLUTION reference

76. OTT EVOLUTION reference

77. OTT EVOLUTION reference

78. CONCLUSIONS: DRIFT 1.Reconstructed brightness temperatures obtained from the first ESA reprocessing using the 1-Slope loss model, exhibit a strong drop of over 1 K in (Tx+Ty)/2 in

79. EXTRA SLIDES

80. BIAS TRENDS

86. The Kirchhoff integral in the previous equation is an integral over the surface Kirchhoff kernel which is a function only of incident and scattered wave directions and polarization Surface correlation function PRE-LAUNCH KIRCHHOFF MODEL The correlation function is computed from Kudryavtsev wave spectrum evamuated using ECMWF 10-m wind speed.

87. Scattering up to 40 o away from specular direction can contribute to total scattered brightness. Geometrical optics model rapidly becomes inaccurate beyond about 15 o from the specular direction. GEOMETRICAL OPTICS GALACTIC MODEL

88. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: ASCENDING PASSES SMOS residuals Example geometrical optics trial solutions

89. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: ASCENDING PASSES SMOS residuals Example geometrical optics trial solutions

90. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: DESCENDING PASSES SMOS residuals Example geometrical optics trial solutions

91. FITTING A GEOMETRICAL OPTICS MODEL TO THE DATA: DESCENDING PASSES SMOS residuals Example geometrical optics trial solutions

92. A MORE DIFFICULT EXAMPLE OF THE FIT 50 o incidence angle Descending passes 3-6 m/s ECMWF surface wind speed first Stokes parameter: (Tx+Ty)/2

93. A MORE DIFFICULT EXAMPLE OF THE FIT As derived from the SMOS brightness temperatures:

94. As modeled using the descending empirical GO model: A MORE DIFFICULT EXAMPLE OF THE FIT

95. Empirical GO model – SMOS derived (Tx+Ty)/2: Model prediction of scattered brightness is too low either side of galactic plane A MORE DIFFICULT EXAMPLE OF THE FIT

96. Original Kirchhoff at 3 m/s – SMOS derived (Tx+Ty)/2: But the original Kirchhoff model, even using the solution at the lowest wind speed of 3 m/s, strongly underpredicts the maximum scattered brightness: A MORE DIFFICULT EXAMPLE OF THE FIT

97. 9 m/s SCATTERING OF GALACTIC RADIATION

98. IMPACT OF CELESTIAL SKY BRIGHTNESS Correction assuming a specular surface:

99. HIGHER SURFACE WIND SPEED 40 o incidence angle Descending passes 8-12 m/s ECMWF surface wind speed first Stokes parameter: (Tx+Ty)/2

100. HIGHER SURFACE WIND SPEED Empirical GO model – SMOS derived (Tx+Ty)/2:

101. Original Kirchhoff at 3 m/s – SMOS derived (Tx+Ty)/2: Kirchhoff model at 3 m/s overpredicts scattered brightness along galactic plane and underpredicts it on either side. HIGHER SURFACE WIND SPEED

102. IMPACT OF CELESTIAL SKY BRIGHTNESS No correction for reflected celestial sky radiation leads to strong along-track bands of negative SSS anomalies:

103. IMPACT OF CELESTIAL SKY BRIGHTNESS Ascending GO model does not completely eliminate low SSS trough