1. CORRECTION OF SPATIAL ERRORS IN SMOS BRIGHTNESS TEMPERATURE IMAGES L.Wu, I. Corbella, F. Torres, N. Duffo, M. Martn-Neira

2. SMOS Image Reconstruction Errors

All visibility samples show residual systematic errors due to non-perfect instrument calibration.

• PMS gain (residual Tph dependence)

• PMS offset (heater)

• Gkj phase (LO rate)

The Flat Target response, as a set of Visibilities, isprone to the same errors.

Uncertainties in antenna patterns are directly inherited by the G-matrix elements.

As a result: The reconstructed Brightness temperature shows spatial distortion in the , plane

This error is systematic and cannot be reduced by time averaging.

3. Spatial errors model

At each snapshot MIRAS delivers a Brightness Temperature imageT B ( , ) .

Spatial artifacts can be modeled as having

• Different gains at each grid point

• Different offsets at each grid point

The first option is considered here as offset is highly cancelled by the Flat Target Transformation

4. Estimating the spatial error

Spatial error is estimated by carefully analyzing a large number of measurements over a constant target (i.e. the ocean).

To minimize temporal and geophysical variations, a large number of orbits at different dates are used.

Ascending and descending orbits are considered.

The final estimation is an image independentmaskto be applied to all measurements.

5. Basics on mask estimation over the ocean Geometry (faraday) rotation Polynomial regression Geometry (faraday) rotation The final mask is computed on antenna frame. 6. Polynomial regression

Measured brightness temperature at different ( - ) is converted to ground plane and arranged for equal incidence angle.

Geophysical variability within the FOV of a single snapshot is neglected.

Spatial errors are computed as the difference between the measured brightness temperature and its estimation by polynomial regression.

7. Mask estimation

Brightness temperature absolute errors at ground frame are estimated by the regression

Errors are transformed to instrument frame and converted to relative

The mask is computed from the estimated relative errors as:

Once the mask is available, the corrected TB is:

8. Faraday rotation angle

Faraday rotation is stronger when the TEC (Total Electron Content) of the atmosphere is larger

• Descending orbits

• Spring and Fall

9. Faraday rotation correction

Faraday rotation correction must be applied.

Difference between ascending and descending orbits, before (left) and after (right) faraday rotation correction. 10. Final Mask on antenna frame Mask is computed using several orbits over the pacific ocean from 20 th ,Feb to 20 th ,Sep, 2010. 11. Cuts of the mask X pol Y pol The spatial error is constrained to 2% in SMOS AF-FoV 12. Mask average along track Mask average along track is not zero mean producing artifacts along this direction. 13. Images over the Indian ocean (01/12) applying the mask 14. Residual Spatial errors Radiometric spatial errors (pixel bias) over ocean The mask clearly reduces the residual error and randomizes its spatial distribution. case Error budget v7.0 2.13 2.13 Before mask correction 1.34 1.57 After mask correction 0.38 0.47 15. Corrected brightness temperature H/V brightness temperature arranged for equal incidence angle for a SMOS image over the Atlantic Ocean and the Indian Ocean, before (top) and after (bottom) applying the mask correction. 16. Effect on Level 1C brightness temperature Horizontal polarization Vertical polarization (35 to 55 incidence) 17. Image cut at -25 latitude 18. Mask stability check (i) single mask deviation from mean mask computed in March, May and July 2010 to show temporal stability. 19. Mask stability check (ii) the masks computed using ascending orbits' data are more stable than using descending orbits'. 20. Conclusions

Systematic image reconstruction spatial errors have been estimated from a large number of observations over the ocean.

A method to correct for these errors has been developed, with special application to improve salinity retrievals.

Correction is as simple as multiplying the raw measurements at level 1B by a constant, direction dependent mask.

The mask computation is affected by Faraday rotation correction.

Results both in L1B and L1C data show that there is a reduction of the artifacts.