Outlier detection in L2OSPP - usefulness in RFI detection-

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

2. Inconstency with ATBD: Median of the differences vs difference of the medians 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 : Mmeas - Computation of the median over all associated modelled Tbs : Mmodel - Computation of the difference DA = Mmeas – Mmodel 4°) For each measured Tbs - Correction of the modelled Tbs : Mmodel_corr = Mmodel + DA - Test : abs(Mmeas - Mmodel_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

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

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. Only a small area seems to be not affected by the RFI (i.e. realistic values of SSS) • 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 0Red = Tb close to 1000 K

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

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 Tbmeas >> Tbmodel and Tbmeas<< 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 ?