1. Outlier detection in L2OSPP - usefulness in RFI detection- SMOS L2OS Progress Meeting – 21/22 February -BEC

2. Outlier detection in L2OSPP - On L1c measurements- Applied during pre-processing on L1c measurements Done for each gridpoint and separately for each polarisation Successive steps: 1°) Apply OTT to valid measurements 2°) Separate by polarisation all measurements associated to one gridpoint 3°) For each polarisation: - Computation of the median over all measured Tbs : M meas - Computation of the median over all associated modelled Tbs : M model - Computation of the difference DA = M meas – M model 4°) For each measured Tbs - Correction of the modelled Tbs : M model_corr = M model + DA - Test : abs(M meas - M model_corr ) > N √(radiometric error² + modelled error²) Yes  this measurement is flagged as outlier and discarded from the retrieval 5°) Counting the outlier measurements - If % outliers > Tg_many_outliers  gridpoint flagged In any case, gridpoint is processed Inconstency with ATBD: Median of the differences vs difference of the medians

4. Diff(median) vs median(diff) Not a big issue when there are only a few outlier measurements or when there are few very high measurements

5. Real issue for some cases : No longer outlier Detected as Outlier

6. Usefulness for RFI detection RFI  Too high Tbs measurements (> 500 K) L2OSPP Outlier detection  only gridpoints close too RFI are flagged SSS retrieval near Greenland: - Color scale from 30 to 40 pss - White spots = GP flagged as « many_outlier » - close to RFI: SSS > 80 or SSS <0

7. Try to detect some characteristic behaviour of the TBs close to on RFI  focuse on gridpoints contained in an affected snapshot: Blue = Tbs close to 0 Red = Tb close to 1000 K Only a small area seems to be not affected by the RFI (i.e. realistic values of SSS)

8. Question : Are Out of range Tbs values sufficient to detect RFI effect ? 60 -40 90 -10 -Ok for gridpoints close to the RFI spot - Not relevant for further gridpoints  Improvement of outlier detection ?? For each gridpoint, the maximum and minimum associated Tbs are observed

9. 4 specific gridpoints : 2 with retrieved SSS > 40 pss 2 with retrieved SSS close to 0 Each of them not flagged as « many_outlier » RFI spot = gridpoint with the maximal Tb over the whole snapshot

10. close to RFI gp, SSS = 104.15 pss In VV pol, Alternation between Tb meas >> Tb model and Tb meas << Tb model = characteristic behaviour??

11. No difference between the two « methods » for HH pol Difference for VV pol for incidence <50

12. Far from RFI gp, SSS = 50.62 Several outlier measurements close to modelled Tbs

13. Most of the outliers are no longer flagged with the « ATBD » method  Which influence on the SSS retrieval values ??

14. close to RFI gp, SSS = 2.44 pss For incidence >45°, same alternation in VV pol

15. No significant change for HH or VV pol

16. Far from RFI gp, SSS = 7.3088

17. For VV pol : - all measurements with incidence > 54° and incidence <38 are no longer flagged as outlier - several measurements with incidence  [38, 54]° are now flagged as outlier

18. CONCLUSION : Change of outlier detection in L2OSPP : -method «median of the differences » closest to modelled TBs - influence on SSS retrieval? Outliers are mostly observed on VV polarisation Alternation between higher and smaller measurements than modelled TBs = carcateristical behaviour of affected gridpoints ?