1 / 45

REVIEW OF OBSERVED BIAS TRENDS OVER THE OCEAN AND POTENTIAL IMPACT OF PROCESSOR EVOLUTION

REVIEW OF OBSERVED BIAS TRENDS OVER THE OCEAN AND POTENTIAL IMPACT OF PROCESSOR EVOLUTION Joe & Nicolas IFREMER/CLS ESL Quality Working Group #5 May 30-31, 2011. Descending passes . Ascending passes. Simple Level 3 SSS products from SMOS L2 DPGS. July Aug Sep Oct Nov Dec.

ziva
Télécharger la présentation

REVIEW OF OBSERVED BIAS TRENDS OVER THE OCEAN AND POTENTIAL IMPACT OF PROCESSOR EVOLUTION

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. REVIEW OF OBSERVED BIAS TRENDS OVER THE OCEAN AND POTENTIAL IMPACT OF PROCESSOR EVOLUTION Joe & Nicolas IFREMER/CLS ESL Quality Working Group #5 May 30-31, 2011

  2. Descending passes Ascending passes. Simple Level 3 SSS products from SMOS L2 DPGS July Aug Sep Oct Nov Dec Latitudinal Drift Apparent in L3 SSS desc fromOct to Dec Differingbehaviourasc/desc VeryDifficult to merge both passes !

  3. Temporal evolution of the SMOS Level 2 GloballyaveragedError Processor Version changes Asc SSS saltier than Desc SSS by ~0.7 psu Since 4th Aug Stable temporal variance of the error Fluctuating temporal mean error: ~0.5-0.6 psu Figure 2:: 10-day running mean window average evolution of the global mean differences between SMOS level 2 and in situ SSS from July to January 2010. All Data (Black), Ascending passes (blue) and Descending passes (red)

  4. Temporal evolution of the SMOS Level 2 Meridionalaverage of ΔSSS –Correlationwithsun illumination Descending passes Ascending passes. Very Significant Latitudinal Bias In desc Passes after mid-oct: Sun ?

  5. SUN GEOMETRY REVIEW The following figures show sun angle from boresight as a function of time of year and latitude for descending and ascending passes.

  6. REVIEW OF BIAS TRENDS OVER THE OCEAN Long term bias trends for original DPGS Level 1B data, referenced to average of early June ascending and descending passes. For the dashed curves no correction for the June-July jump has been made, while for the solid curves offsets have been applied in early June and early August, where the offsets have been based on consecutive passes (of a given direction) over the Pacific.

  7. REVIEW OF BIAS TRENDS OVER THE OCEAN Long term bias trends for original DPGS Level 1B data including only the corrected curves.

  8. REVIEW OF BIAS TRENDS OVER THE OCEAN Long term bias trends for original DPGS Level 1B data including only the corrected curves. crossover of desc-asc discrepancy early May and early-mid August Direct sun correction + thermal loss variations: Tb(desc) < Tb(asc) Direct sun correction + thermal loss variations + scattered galactic noise modeling error: Tb(desc) > Tb(asc)

  9. REVIEW OF BIAS TRENDS OVER THE OCEAN Long term bias trends for Commissioning reprocessing Level 1B data, referenced to average of early June ascending and descending passes. The FTR and NIR calibration parameters remains fixed for the entire period. • FIXED NIR CAL • FIXED FTR • DIRECTSUN CORRECTION WITH V(0,0) and BHS BUGS • NO THERMAL LOSS MODEL

  10. REVIEW OF BIAS TRENDS OVER THE OCEAN Long term bias trends for Commissioning reprocessing Level 1A data reprocessed using JRECON image reconstruction with no direct sun correction. Aside from the area element discrepancy which has little impact over open ocean, main difference between DPGS and JRECON solutions is lack of direct sun correction in JRECON solutions. • FIXED NIR CAL • FIXED FTR • NO DIRECT SUN CORRECTION • NO THERMAL LOSS MODEL

  11. REVIEW OF BIAS TRENDS OVER THE OCEAN Long term bias trends for Commissioning reprocessing Level 1A data reprocessed using JRECON image reconstruction with no direct sun correction. Aside from the area element discrepancy which has little impact over open ocean, main difference between DPGS and JRECON solutions is lack of direct sun correction in JRECON solutions. • FIXED NIR CAL • FIXED FTR • NO DIRECT SUN CORRECTION • NO THERMAL LOSS MODEL Timing of crossovers of desc-asc discrepancy change only slightly Direct sun correction problem is gone leaving only the thermal loss variation impact : Tb(desc) < Tb(asc) Problem here is reduced to impact of thermal loss variations + scattered galactic noise modeling error: Tb(desc) > Tb(asc)

  12. REVIEW OF BIAS TRENDS OVER THE OCEAN Long term bias trends for Commissioning reprocessing Level 1B data, referenced to average of early June ascending and descending passes. The FTR and NIR calibration parameters remains fixed for the entire period. • FIXED NIR CAL • FIXED FTR • DIRECTSUN CORRECTION WITH V(0,0 and BHS BUGS • NO THERMAL LOSS MODEL Timing of crossovers of desc-asc discrepancy change only slightly Direct sun correction problem is gone leaving only the thermal loss variation impact : Tb(desc) < Tb(asc) Problem here is reduced to impact of thermal loss variations + scattered galactic noise modeling error: Tb(desc) > Tb(asc)

  13. REVIEW OF BIAS TRENDS OVER THE OCEAN Long term bias trends for Commissioning reprocessing Level 1A data reprocessed using JRECON image reconstruction with no direct sun correction. Aside from the area element discrepancy which has little impact over open ocean, main difference between DPGS and JRECON solutions is lack of direct sun correction in JRECON solutions. • FIXED NIR CAL • NO FTT • NO DIRECT SUN CORRECTION • NO THERMAL LOSS MODEL Timing of crossovers of desc-asc discrepancy change only slightly Direct sun correction problem is gone leaving only the thermal loss variation impact : Tb(desc) < Tb(asc) Problem here is reduced to impact of thermal loss variations + scattered galactic noise modeling error: Tb(desc) > Tb(asc)

  14. REVIEW OF BIAS TRENDS OVER THE OCEAN Next we considered a reprocessing in which NIR parameters are updated in an optimal way using the periodic cold sky calibrations. Here we have not used the FTT and so the solutions should be very close to those obtained with fixed FTR. • OPTIMAL NIR CAL • NO FTT • NO DIRECT SUN CORRECTION • NO THERMAL LOSS MODEL Timing of crossovers of desc-asc discrepancy change only slightly Direct sun correction problem is gone leaving only the thermal loss variation impact : Tb(desc) < Tb(asc) Problem here is reduced to impact of thermal loss variations + scattered galactic noise modeling error: Tb(desc) > Tb(asc)

  15. REVIEW OF BIAS TRENDS OVER THE OCEAN Next we considered a reprocessing in which NIR parameters are updated in an optimal way using the periodic cold sky calibrations. Here we have not used the FTT and so the solutions should be very close to those obtained with fixed FTR. • OPTIMAL NIR CAL • NO FTT • NO DIRECT SUN CORRECTION • COMPLETE NEW THERMAL LOSS MODEL Timing of crossovers of desc-asc discrepancy change only slightly No direct sun correction and new loss model resolve discrepany almost completely in May-August Dsc-asc discrepancies in Sep-Oct are much reduced and the remaining discrepancy is likely related to scattered galactic noise modeling error: Tb(desc) > Tb(asc)

  16. REVIEW OF BIAS TRENDS OVER THE OCEAN Next we considered a reprocessing in which NIR parameters are updated in an optimal way using the periodic cold sky calibrations. • OPTIMAL NIR CAL • NO FTT • NO DIRECT SUN CORRECTION • COMPLETE NEW THERMAL LOSS MODEL Updating the FTR changes significantly the bias trends up through early May. FTR updates are marked by black vertical bars.

  17. REVIEW OF BIAS TRENDS OVER THE OCEAN Next we considered a reprocessing in which NIR parameters are updated in an optimal way using the periodic cold sky calibrations. Here we have not used the FTT and so the solutions should be very close to those obtained with fixed FTR. • OPTIMAL NIR CAL • FTT/UPDATED FTR • NO DIRECT SUN CORRECTION • COMPLETE NEW THERMAL LOSS MODEL Updating the FTR changes significantly the bias trends up through early May. FTR updates are marked by black vertical bars.

  18. REVIEW OF BIAS TRENDS OVER THE OCEAN Here we replot the bias curves for the solutions without the new loss model but without offsetting the curves in any way in order to provide a feel for absolute biases and EAF-AF bias discrepancies. • OPTIMAL NIR CAL • FTT/UPDATED FTR • NO DIRECT SUN CORRECTION • COMPLETE NEW THERMAL LOSS MODEL

  19. REVIEW OF BIAS TRENDS OVER THE OCEAN Here we replot the bias curves for the solutions with the new loss model and without offsetting the curves in any way in order to provide a feel for absolute biases and EAF-AF bias discrepancies. • OPTIMAL NIR CAL • FTT/UPDATED FTR • NO DIRECT SUN CORRECTION • COMPLETE NEW THERMAL LOSS MODEL

  20. REVIEW OF BIAS TRENDS OVER THE OCEAN Descending minus ascending L1-JRECON reveals a complex pattern of biases and bias trends associated with the buggy direct sun correction.

  21. UPDATE ON DIRECT SUN CORRECTION The impact of the V(0,0) and back half space solid angle bugs appears clearly in the latitude-time bias plots. Here we show for the Commissioning Reprocessing Pacific descending passes a hovmoller plot of the difference between AF-FOV bias for solutions obtained using JRECON with no direct sun correction and those obtained from L1OP L1B files, which include the direct sun correction with BOTH the V(0,0) and back half space bugs. The sun passes between the front and back of the array along the solid black curves. Clearly evident is the latitudinal bias introduced by the V(0,0) bug (when the sun is in the front half space) between October and March and the negative bias (with strange jumps) introduced by the solid angle bug when the sun is in the back half space. This plot shows how these two problems with the direct sun correction have introduced significant biases on both short and long time scales, obscuring the true impact of the thermal loss model. Sun in front: V(0,0) bug Sun in back: Solid angle bug Sun in front: V(0,0) bug Sun in back: Solid angle bug Sun in back: Solid angle bug

  22. UPDATE ON DIRECT SUN CORRECTION The impact of the V(0,0) and back half space solid angle bugs appears clearly in the latitude-time bias plots. Here we show for the Commissioning Reprocessing Pacific descending passes a hovmoller plot of the difference between AF-FOV bias for solutions obtained using JRECON with no direct sun correction and those obtained from L1OP L1B files, which include the direct sun correction with BOTH the V(0,0) and back half space bugs. The sun passes between the front and back of the array along the solid black curves. Clearly evident is the latitudinal bias introduced by the V(0,0) bug (when the sun is in the front half space) between October and March and the negative bias (with strange jumps) introduced by the solid angle bug when the sun is in the back half space. This plot shows how these two problems with the direct sun correction have introduced significant biases on both short and long time scales, obscuring the true impact of the thermal loss model. Sun in front: V(0,0) bug Sun in back: Solid angle bug Sun in front: V(0,0) bug Sun in back: Solid angle bug

  23. UPDATE ON DIRECT SUN CORRECTION Descending minus ascending L1-JRECON reveals a complex pattern of biases and bias trends associated with the buggy direct sun correction.

  24. UPDATE ON DIRECT SUN CORRECTION In the figure below we show the difference in AF-FOV (Tx+Ty)/2 bias between five possible solutions and a reference solution for the Nov 9 descending pass. The reference solution is Roger’s latest run using the new loss model with no direct sun correction. The blue curve shows the solution difference obtained using the direct sun correction with the V(0,0) fix but with the solid angle bug when the sun is in the back half-space. Bias differences are close to zero north of about 50 degS, but note the jump in bias when the sun passes into the BHS around 50 degS. The red curve shows the difference obtained using L1PP with the latest corrected direct sun correction (with both the V(0,0) and back half-space bugs fixed). The bias jump is not present in the corrected solution. For reference I also include difference curves for the Original (No) Loss Model solution with no direct sun correction (magenta curve), the Commissioning reprocessing solutions obtained from L1OP with the bad (bug in back half-space and missing V(0,0) correction) direct sun correction (green curve) and from JRECON with no direct sun correction (cyan curve).

  25. UPDATE ON DIRECT SUN CORRECTION Here we show the same set of curves but for the Dec 20, 2010 descending Pacific pass. From these two figures we see that the back half-space problem appearing in the blue curves disappears in the latest solutions shown by the red curves. The latest corrected direct sun correction, including the V(0,0) correction, has little impact on the differences (relative to no sun correction) when the sun is in the front half-space (north of 40 degS in the figure below and north of around 50 degS in the previous slide). Also note the progressive reduction of differences as we move from Reprocessing L1OP L1B to Reprocessing JRECON (with no dir sun correction) and finally to the latest solution with the new thermal loss model.

  26. UPDATE ON DIRECT SUN CORRECTION The direct sun correction does slightly improve solutions in the AF and EAF FOV in terms of standard deviation of bias between SMOS and the model. Below we show one example of this reduction for the Dec 20 descending pass. Here we evaluate the median and standard deviation of the difference between SMOS and model brightness temperatures (actually we show only Txx for the standard deviation) for both the solutions with no sun correction (left panels) and solutions with the latest sun correction (right panels), using snapshots from 10 degN to 30 degN. The standard deviations in the lower panels do show some reduction with the sun correction in the AF and EAF FOV and this is consistent along the orbit. Improvement in bias is less evident.

  27. UPDATE ON DIRECT SUN CORRECTION The direct sun correction does slightly improve solutions in the AF and EAF FOV in terms of standard deviation of bias between SMOS and the model. Below we show one example of this reduction for the Dec 20 descending pass. Here we evaluate the median and standard deviation of the difference between SMOS and model brightness temperatures (actually we show only Txx for the standard deviation) for both the solutions with no sun correction (left panels) and solutions with the latest sun correction (right panels), using snapshots from 10 degN to 30 degN. The standard deviations in the lower panels do show some reduction with the sun correction in the AF and EAF FOV and this is consistent along the orbit. Improvement in bias is less evident.

  28. UPDATE ON DIRECT SUN CORRECTION The direct sun correction does slightly improve solutions in the AF and EAF FOV in terms of standard deviation of bias between SMOS and the model. Below we show one example of this reduction for the Dec 20 descending pass. Here we evaluate the median and standard deviation of the difference between SMOS and model brightness temperatures (actually we show only Txx for the standard deviation) for both the solutions with no sun correction (left panels) and solutions with the latest sun correction (right panels), using snapshots from 10 degN to 30 degN. The standard deviations in the lower panels do show some reduction with the sun correction in the AF and EAF FOV and this is consistent along the orbit. Improvement in bias is less evident.

  29. UPDATE ON DIRECT SUN CORRECTION The direct sun correction does slightly improve solutions in the AF and EAF FOV in terms of standard deviation of bias between SMOS and the model. Below we show one example of this reduction for the Dec 20 descending pass. Here we evaluate the median and standard deviation of the difference between SMOS and model brightness temperatures (actually we show only Txx for the standard deviation) for both the solutions with no sun correction (left panels) and solutions with the latest sun correction (right panels), using snapshots from 10 degN to 30 degN. The standard deviations in the lower panels do show some reduction with the sun correction in the AF and EAF FOV and this is consistent along the orbit. Improvement in bias is less evident.

  30. UPDATE ON DIRECT SUN CORRECTION The direct sun correction does slightly improve solutions in the AF and EAF FOV in terms of standard deviation of bias between SMOS and the model. Below we show one example of this reduction for the Dec 20 descending pass. Here we evaluate the median and standard deviation of the difference between SMOS and model brightness temperatures (actually we show only Txx for the standard deviation) for both the solutions with no sun correction (left panels) and solutions with the latest sun correction (right panels), using snapshots from 10 degN to 30 degN. The standard deviations in the lower panels do show some reduction with the sun correction in the AF and EAF FOV and this is consistent along the orbit. Improvement in bias is less evident.

  31. UPDATE ON DIRECT SUN CORRECTION The direct sun correction does slightly improve solutions in the AF and EAF FOV in terms of standard deviation of bias between SMOS and the model. Below we show one example of this reduction for the Dec 20 descending pass. Here we evaluate the median and standard deviation of the difference between SMOS and model brightness temperatures (actually we show only Txx for the standard deviation) for both the solutions with no sun correction (left panels) and solutions with the latest sun correction (right panels), using snapshots from 10 degN to 30 degN. The standard deviations in the lower panels do show some reduction with the sun correction in the AF and EAF FOV and this is consistent along the orbit. Improvement in bias is less evident.

  32. UPDATE ON DIRECT SUN CORRECTION The direct sun correction does slightly improve solutions in the AF and EAF FOV in terms of standard deviation of bias between SMOS and the model. Below we show one example of this reduction for the Dec 20 descending pass. Here we evaluate the median and standard deviation of the difference between SMOS and model brightness temperatures (actually we show only Txx for the standard deviation) for both the solutions with no sun correction (left panels) and solutions with the latest sun correction (right panels), using snapshots from 10 degN to 30 degN. The standard deviations in the lower panels do show some reduction with the sun correction in the AF and EAF FOV and this is consistent along the orbit. Improvement in bias is less evident.

  33. UPDATE ON DIRECT SUN CORRECTION The direct sun correction does slightly improve solutions in the AF and EAF FOV in terms of standard deviation of bias between SMOS and the model. Below we show one example of this reduction for the Dec 20 descending pass. Here we evaluate the median and standard deviation of the difference between SMOS and model brightness temperatures (actually we show only Txx for the standard deviation) for both the solutions with no sun correction (left panels) and solutions with the latest sun correction (right panels), using snapshots from 10 degN to 30 degN. The standard deviations in the lower panels do show some reduction with the sun correction in the AF and EAF FOV and this is consistent along the orbit. Improvement in bias is less evident.

  34. UPDATE ON DIRECT SUN CORRECTION Finally, we have just recently discovered that the back half space direct sun correction may influence the long term drift bias curves noticeably. To see this consider first the bias curves for the latest processing of Roger using the new loss model and direct sun correction with the back half-space bug. Some residual asc-desc discrepancies remain even with the new loss model especially in mid-July through September.

  35. UPDATE ON DIRECT SUN CORRECTION But after switching to the latest direct sun correction the residual asc-desc discrepancy is reduced further in mid-July through September:

  36. About the Land contamination SSS invertedfromreprocessed L1A with L1B from JRECON Withscale factor corrected on V(0,0)

  37. Land Contamination in SMOS SSS Before & after bug correction Before After ClearlyReduced contamination but there are stillsign-changedresidual signatures

More Related