1. 1 © ACRI-ST, all rights reserved – 2012 TEC estimation Jean-Luc Vergely (ACRI-ST) Jacqueline Boutin (LOCEAN)

2. 2 © ACRI-ST, all rights reserved – 2012 Issue : how to improve TEC estimation ? Aim of this study : To list different possibilities of TEC retrieval To propose an algorithm in order to improve the TEC estimation.

3. 3 © ACRI-ST, all rights reserved – 2012 About TEC… In L1c products : TEC is considered as constant on a snapshot. Magnetic field orientation is considered as constant on a snapshot. In L2 processing : TEC is considered as constant along a dwell SSS estimator is robust even if TEC is not well estimated (SSS depends principally on Stokes 1) TEC estimation is very sensitive to calibration (OTT). TB sensitivity to TEC : SMOS TBs are sensitive to TEC according to the latitude (depending on orbit type). In descending orbits, around 30° south, TEC gradient is very large. At this position, SMOS TBs are sensitive to TEC variations. In ascending orbits, low TEC values and no strong gradients. So, TEC variation impact should be relatively marginal on SSS estimation in most of the cases. TEC estimation impact on WS estimation ? But, possibility to extract TEC using SMOS data (from TX, TY and/or A3).

4. 4 © ACRI-ST, all rights reserved – 2012 TEC retrieval TEC estimation could use Bayesian approach because : - TEC is a priori well known in most of the cases - outlier could give wrong Faraday rotation. Bayesian approach allows to put a weight on the TEC a priori knowledge. - possibility to manage a spatial (xi,eta) or (lat,lon) correlation length for TEC estimation Use only measured TBs sensitive to TEC : TB filtering In order to remove outliers : computation should be done after TB filtering (RFI, coast, ice, other outliers…). Require OTT correction.

5. 5 © ACRI-ST, all rights reserved – 2012 TEC estimation : first approach (1) Using collocated TBs (TX,TY,A3) : -TEC estimation from a set of (TX,TY,A3) without forward model -assuming St3 emission at ground level ≈ 0 -Tg(2.(Faraday+geomrot))=A3/(TX-TY) Require: -TBs interpolation -OTT correction -magnetic field Could be done offline or in the L2OS processor. Disadvantages : -Very noised estimation of TEC -problem over land where TX is close to TY (forest). Coast problems ? TEC smoothing in the (xi, eta) plan or (lat, lon) coordinates in order to introduce spatial coherence.

6. 6 © ACRI-ST, all rights reserved – 2012 Faraday rotation from SMOS data using 42.5 browse products (descending orbits, 11/2011) Large Faraday rotation with strong TEC gradient Low Faraday rotation Lon Lat Faraday=atan(A3/(TX-TY))/2 at xi=0 BUT, if TX-TY vanishes (low incidence angle, forest …), A3/(TX-TY) has a very bad statistics behavior (non gaussian). -> we should use modeled TX-TY and not measured TX-TY in order to estimate Faraday rotation or TEC if using A3/(TX-TY) TEC estimation : first approach (2) Forest : TX-TY vanishes

7. 7 © ACRI-ST, all rights reserved – 2012 TEC variations along the dwell line using ocean forward model. Using TBs organized in dwell line : -Depends on the modeled TBs -> only on ocean target. -Faraday retrieval along the dwell line with a large correlation length according to the incidence angle or the eta position. Require: -OTT correction (for instance reference ocean TB in the latitude where the TBs are not sensitive to Faraday rotation). -a priori Faraday rotation -> L1c products Could be done in the L2OS processor : associated to the retrieval scheme Disadvantages : -TEC spatial coherence is not used -No TEC retrieval on land surface -add parameters in the L2OS retrieval scheme. Instead of one TEC value, n TEC values shall be estimated. TEC estimation : second approach.

8. 8 © ACRI-ST, all rights reserved – 2012 TEC estimation : third approach (1) TEC(lat,lon) at the altitude 400 km along the orbit using ocean forward model. Using A3 at high incidence angles in the afFOV. Selected A3 close to xi=0 (across track TEC variations are negligible ?). TEC estimation according to the (lat, lon) position using only A3 at high incidence angles. SMOS TEC surface (lat,lon) V sat TEC altitude Smoothing of TEC estimation according to the latitude (at the altitude 400 km) in order to decrease the noise. TEC interpolation for any SMOS measurement according to the intersection of the los with the TEC area. Extrapolation close to the coast ? Intersection los/TEC area los

9. 9 © ACRI-ST, all rights reserved – 2012 Details on TEC(lat,lon) retrieval using A3 : Select measured A3 for a FOV (xi, eta) position along the whole half orbit. Compute modeled A3mod and dA3/dTEC using a priori TEC 0 from L1c and ECMWF data Correct TBs from OTT (from external OTT or from OTT estimated at adequate latitude) Convert (xi, eta) -> (lat, lon) using knowledge of TEC altitude for each measured A3 Compute Smooth TEC estimation according to the latitude. Possibility to use TX and TY but less sensitive to TEC than A3 (in the afFOV at high incidence angles). TEC/Faraday estimation : third approach (2)

10. 10 © ACRI-ST, all rights reserved – 2012 TEC retrieved from A3 L1c TEC Lat TEC TEC/Faraday estimation : third approach (3)

11. 11 © ACRI-ST, all rights reserved – 2012 TEC/Faraday conclusions Possibility to extract TEC/Faraday from SMOS data. Some targets are not adapted for TEC retrieval (Forest, coast, area contaminated by RFI/outliers, insensitive regions …etc). Important to consider the spatial coherence of the TEC estimation. Possibility to extract the TEC using A3, TX or TY because St3 ground is likely negligible. OTT correction is required. Possibility to consider, for each measurement, a TEC estimation which is associated to the latitude position of the intersection between los and TEC area -> better than the current solution which affects a mean TEC value for the whole dwell line. -> third approach seems the best one.