A new scheme of wind speed convergence with multi-angular SMOS TB

1. A new scheme of wind speed convergence with multi-angular SMOS TB  Xiaobin Yin1, Jacqueline Boutin1 and Jean-Luc Vergely2 1. LOCEAN 2. ACRI

2. Why do we need a better estimation of wind speed? Retrieved WS1 v38r2 – v37r2 ECMWF WS v38r2 – v37r2 1m/s 1m/s -1m/s -1m/s The differences between two versions of ECMWF are partially but not totally reduced by the L2OS retrievals.

3. Why do we need a better estimation of wind speed? rWS1 v38r2 – v37r2 rSSS1 v38r2 – v37r2 1m/s 0.2psu -1m/s -0.2psu The difference between two versions of retrieved WS and that of SSS are well collocated, and the correlation coefficient between the two is 0.859. Errors in ECMWF WS can lead to errors in SSS, since retrieved WS can not reduce the errors in WS a priori totally with the L2OS retrieval scheme.

4. Introduction The retrievals are based on the Levenberg and Marquardt iterative convergence method. The first guessed geophysical inputs (SSS, SST, WS and TEC) are adjusted so as to minimize a so called “cost function” χ2 expressed by • Can we reduce the biases in retrieved wind speed, if • Relax the weight factor (σWS) of WS a priori, i.e. 2m/s -> 5m/s. • Update WS a priori (WSprior) by the WS retrievals during the first few iterations (Jean-Luc’s idea). • Two step scheme.

5. Introduction • Two step scheme: to reduce the biases in the retrieved SSS and WS, and not to increase noises in the retrievals. • 1st step: ECWMF WS a priori with increasing weight factor of WS a priori (σWS) to 5m/s -> retrieved WS -> 2D spatial median filtering (50 km radius) -> smoothed WS • 2st step: smoothed WS from 1st step (instead of ECMWF) a priori with (σWS) to be 2 m/s -> retrieved SSS and WS • Note: • for both steps, weight factors of first guess SSS, SST and TEC are the same as the operational L2OS processor, i.e. 100psu, 1°C and 10 tecu.

6. Data 1. One orbit in April 2013, with two versions of ECMWF WS(v38r2 and v37r2). Can the retrieved WS and SSS converge, with two different versions of WS a priori? 2. One month of ascending orbits in Aug, 2010 in the eastern equatorial pacific ocean, where we found large WS biases between ECWMF and SSMI. Comparisons among SMOS retrieved WS, ECWMF WS and SSMI WS, and comparisons of SSS? Radiometer wind speeds lower than ECMWF WS in the eastern equatorial pacific ocean because of strong surface currents, but still higher than SSMI WS -> positive anomalies in retrieved SSS compared with ARGO/ISAS SSS SMOS operational retrieved WS ECMWF WS SSMI WS rSSS - ISAS

7. Results Can the retrieved WS converge to the same value with the two step scheme, using two different versions of ECMWF WS a priori? YES with some exceptions! Two step, rWS1 v38r2 – v37r2 Operational, rWS1 v38r2 – v37r2 1m/s 1m/s -1m/s -1m/s Exceptions: 1) too large differences between two WS a priori (5 m/s weight is used for the test shown here); or 2) RFI

8. Results Can the retrieved SSS converge to the same value with the two step scheme, using two different versions of ECMWF WS a priori? YES with some exceptions! Operational, rSSS1 v38r2 – v37r2 Two step, rSSS1 v38r2 – v37r2 0.2psu 0.2psu -0.2psu -0.2psu Exceptions: 1) too large differences between two WS a priori (5 m/s weight is used for the test shown here); 2) RFI

9. Results Comparisons among SMOS retrieved WS, ECWMF WS and SSMI WS in the eastern equatorial pacific ocean (EEP) rWS(operational) – SSMI WS Mean=0.9m/s ECMWF-SSMI WS Mean=1.4m/s ECMWF WS are higher than SSMI WS in EEP. The retrieved WS from L2OS operation processor decrease the differences between ECMWF WS and SSMI WS in EEP

10. Results Comparisons among SMOS retrieved WS, ECWMF WS and SSMI WS in the eastern equatorial pacific ocean (EEP) rWS(operational) – SSMI WS Mean=0.9m/s rWS(twostep) – SSMI WS Mean=0.55m/s The retrieved WS from the two step scheme further decrease the differences between ECMWF WS and SSMI WS in EEP.

11. Results Comparisons among SMOS retrieved SSS and ISAS SSS in EEP rSSS1(operational) – ISAS SSS Mean=0.36 psu rSSS1(twostep) – ISAS SSS Mean=0.27psu The retrieved SSS with the two step scheme are closer to ISAS SSS than the L2 OP SSS in EEP (reduce the positive SSS anomalies in EEP)

12. Results Comparisons among SMOS retrieved SSS and ISAS SSS in EEP rSSS(twostep) – rSSS(operational) Mean=0.09 psu The retrieved SSS with the two step are lower than the L2 OP SSS in EEP and the maximum difference can reach up to 0.5 psu in magnitude.

13. TESTs: comparisons of different methods • Tests (one orbit in 2010/08/06,13h-14h): • L2OS, σWS = 2 m/s • Two step: 1) σWS = 5 m/s + WS smoothing; 2) σWS = 2 m/s • Two step: 1) σWS = 5m/s + no WS smoothing; 2) σWS = 2 m/s • L2 OS, σWS = 5 m/s • Update WS a priori (WSprior) by the WS retrievals during the first few iterations (Jean-Luc’s idea). 3S-2N

14. Conclusions and discussions • The retrieved SSS and WS converge with the two step scheme, using two different versions of ECMWF WS a priori. • The retrieved WS with the two step scheme are closer to SSMI WS in EEP than the L2OS OP WS. • The retrieved SSS with the two step scheme are closer to ISAS SSS in EEP than the L2OS OP SSS, but still higher than ISAS (problem of roughness model at low WS below 3 m/s)? • Compared with L2OS OP retrievals, the two step scheme does not increase the noises in retrieved SSS and WS. Perspectives • Choose a best weight factor of WS first guess for the 1st step. Choose a best WS smoothing method for the WS derived in the 1st step. • Test JV’s idea for the WS in the first step. • Roughness model at low WS below 3 m/s.

15. rWS1(twostep) – SSMI WS Mean(median)=0.40(-0.03)m/s rWS1(up) – SSMI WS Mean(median)=0.08(-0.35)m/s

16. rSSS1(twostep) – ISAS SSS Mean=0.27 psu rSSS3(twostep) – ISAS SSS Mean=0.17 psu

17. rWS1(twostep) – SSMI WS Mean=0.55m/s rWS1(twostep) – SSMI WS Mean=0.53m/s

18. rWS1(twostep) – ECMWF WS V37r2 rWS1(twostep) – ECMWF WS V38r2