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AN UPDATE ON BIAS TRENDS Joe Tenerelli 13 April 2011

AN UPDATE ON BIAS TRENDS Joe Tenerelli 13 April 2011. SUMMARY. In the following slides we take a brief look at SMOS AF and EAF FOV bias trends over 2010 for six possible solution strategies:

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AN UPDATE ON BIAS TRENDS Joe Tenerelli 13 April 2011

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  1. AN UPDATE ON BIAS TRENDS Joe Tenerelli 13 April 2011

  2. SUMMARY In the following slides we take a brief look at SMOS AF and EAF FOV bias trends over 2010 for six possible solution strategies: Commissioning reprocessing fixed NIR calibration solutions with fixed FTR and with direct sun correction; Commissioning reprocessing fixed NIR calibration solutions with no FTT and without direct sun correction; Reprocessing with optimal NIR calibration and FTT with variable FTR; Reprocessing with optimal NIR calibration, no FTT (similar to fixed FTR) and no direct sun correction; Reprocessing with the new loss model, optimal NIR calibration, no direct sun correction and FTT with variable FTR; Reprocessing with the new loss model, optimal NIR calibration, no direct sun correction and no FTT.

  3. SUMMARY The initial results indicate that: Although the (fixed NIR cal and fixed FTR) commissioning reprocessing (with or without direct sun correction) AF biases seem rather stable, the EAF biases increase markedly in April 2010 (and more for asc than desc passes). Introducing the optimal NIR cal parameters stabilizes the EAF biases if no FTT is used, but the AF biases become less stable, dropping significantly. If FTT is introduced with variable FTR, both AF and EAF biases increase markedly from March to May as the FTR is changed. With the new loss model consistency between asc and desc biases seems to increase but a jump in both AF and EAF biases is introduced in early June. For all types of solutions the bias spatial pattern evolves significantly over time, but use of variable FTR does not resolve this problem; instead, abruptly changing the FTR introduces jumps in both AF and EAF bias trends.

  4. COMMISSIONING REPROCESSING BIAS TRENDS As a basis for looking at the impact of calibration changes let us begin by looking at the AF and EAF bias evolutions for Tx and Ty for the commissioning reprocessing data. Ascending pass AF bias is quite stable while EAF bias jumps up by 2 K in Tx and 1.5 K in Ty in April 2010. All curves referenced to bias in early March ascending pass

  5. COMMISSIONING REPROCESSING BIAS TRENDS For descending passes the EAF jump is equal in Tx and Ty and smaller, about 1K, but the bias continues to rise slowly over the following months, equally in Tx and Ty for EAF until early September, when Ty levels off while Tx continues to rise (probably galactic noise modeling error). All curves referenced to bias in early March ascending pass

  6. COMMISSIONING REPROCESSING BIAS TRENDS Here is show AF and EAF reprocessing bias trends in (Tx+Ty)/2 for the 38 passes used for testing the new loss model. Again, EAF bias jumps up while AF bias remains more stable over time. These curves are based on L1B produced by L1 with constant FTR and direct sun removal on. All curves referenced to average of asc and desc bias in mid-January.

  7. FIXED NIR CALIBRATION, NO FTT Here are similar curves but for JRECON. Even without the new loss model there appears to be more consistency between asc and desc biases than with the L1 solutions. This may be related to the direct sun correction which is not implemented in JRECON. Rise in EAF bias here All curves referenced to average of asc and desc bias in mid-January.

  8. OPTIMAL NIR CALIBRATION, NO FTT If we now keep the old loss model and but introduce optimal NIR calibration then we obtain the following bias trends with JRECON. Here there is no FTR so these curves should be close to what we would obtain with L1 with constant FTR and no sun correction. We now have a drop of AF bias from March to June, while the EAF bias is more stable than with fixed NIR calibration during this same time period. Opposite bias drift without FTT All curves referenced to average of asc and desc bias in mid-January.

  9. OPTIMAL NIR CALIBRATION, VARYING FTR If we now switch to the L1 results with varying FTR we obtain the following bias trends. The trends differ from those obtained with JRECON mainly when the FTR in L1 changes. Here the new loss model is not used and there is some notable inconsistency between ascending and descending pass biases. All curves referenced to average of asc and desc bias in mid-January.

  10. NEW LOSS MODEL, VARYING FTR If we now introduce the new loss model the discrepancy between asc and desc pass biases tends to (but not for all passes) decrease. But now a large jump is introduced in early June that was not present in the optimal cal old loss model solutions. Note the FTR does not change in early June so this should not be the origin of this jump. Jump in bias in early June with new loss model, not related to FTR change… All curves referenced to average of asc and desc bias in mid-January.

  11. NEW LOSS MODEL, NO FTT Indeed even JRECON solutions exhibit this bias jump… Jump even in JRECON with no FTT… All curves referenced to average of asc and desc bias in mid-January.

  12. OLD LOSS MODEL, NO FTT But the old loss model solutions do not exhibit this jump… No jump with old loss model. All curves referenced to average of asc and desc bias in mid-January.

  13. DIFFERENT TYPES OF PROCESSING Impact of varying FTR Old loss model, optimal NIR cal, varying FTR Old loss model, optimal NIR cal, no FTT Impact of new loss model Impact of optimal NIR cal Old loss model, fixed NIR cal (repro) New loss model, no FTT

  14. DIFFERENT TYPES OF PROCESSING Impact of varying FTR Old loss model, optimal NIR cal, varying FTR Old loss model, optimal NIR cal, no FTT Which is best??? Impact of new loss model New loss model, with varying FTR New loss model, no FTT

  15. OTT EVOLUTION WITH VARYING FTR If we look at bias in (Tx+Ty)/2 over the field of view relative to the bias in January we get a feel for the evolution of the spatial pattern of the bias. Here we see this evolution for the L1 solutions with optimal NIR cal, the new loss model and FTT with variable FTR. Clearly the bias pattern is evolving significantly over time and part of this is coming from the variable FTR (see the next slide). Note also the strange bias patterns in the April 8 plot. These seem to come and go and do not appear in the March 20 and June 3 plots. March 20 ascending pass June 3 ascending pass April 8 ascending pass

  16. OTT EVOLUTION WITH NO FTT Here we have the same plots but for the no FTT solutions. The strange patterns on April 8 remain, but now the bias pattern evolution is very different, and the main difference between these solutions and those on the previous slide is the use of the FTT with variable FTR. March 20 ascending pass June 3 ascending pass April 8 ascending pass

  17. THE JUMP IN JUNE WITH THE NEW LOSS MODEL The jump is June appears to be an overall level drop over the FOV.

  18. BIAS TRENDS WITH LATITUDE: IMPACT OF LOSS MODEL Here we compare the variation with latitude of the AF-FOV bias between SMOS and the forward model for pairs of nearby ascending and descending half-orbits. All biases are relative to the latitudinal average (between 50 degS and the equator) of the average of the AF biases for one ascending and one descending pass on March 20, 2010. Ascending pass biases are blue while descending pass biases are red. Here we show bias for two passes on Nov 9 2010. In this case the old loss model (left) shows slightly higher discrepancy between asc and desc passes, especially far from the equator, than the new loss model (right). You can also see the substantial drift in the overall biases since March 20 (the reference), with and without FTT (the curves have drifted away from 0 over time).

  19. BIAS TRENDS WITH LATITUDE: IMPACT OF LOSS MODEL A similar result on November 10…

  20. BIAS TRENDS WITH LATITUDE: IMPACT OF LOSS MODEL For the pair of passes in mid September we see reduced asc-desc discrepancy with the new loss model but descending passes still have higher biases than ascending passes. This is likely associated with error in the scattered galactic noise modeling.

  21. BIAS TRENDS WITH LATITUDE: IMPACT OF LOSS MODEL In June both old and new loss models produce little asc-desc discrepancy…

  22. BIAS TRENDS WITH LATITUDE: IMPACT OF LOSS MODEL Little difference between results in April as well…

  23. BIAS TRENDS WITH LATITUDE: IMPACT OF LOSS MODEL Little difference between results in March. In fact if anything the old loss model produces slightly more consistency between asc and desc than the new loss model.

  24. BIAS TRENDS WITH LATITUDE: IMPACT OF LOSS MODEL For the pair of passes in January the new loss model yields larger asc-desc discrepancy than the old model. So the improvement with the new loss model is not always observed. We may need to test the new model on larger set of orbits than just the 38 used so far.

  25. DESC-ASC Tp7 OVER THE YEAR [degC]

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