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Development of New SSES for AATSR L2P

Development of New SSES for AATSR L2P. Gary Corlett AATSR Validation Scientist. Content. Reminder of current SSES scheme SSTs from AATSR What affects the quality of AATSR SSTs? An alternate scheme using view differences Examples Analysis of GHRSST-PP MDB Future work

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Development of New SSES for AATSR L2P

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  1. Development of New SSES for AATSR L2P Gary Corlett AATSR Validation Scientist

  2. Content • Reminder of current SSES scheme • SSTs from AATSR • What affects the quality of AATSR SSTs? • An alternate scheme using view differences • Examples • Analysis of GHRSST-PP MDB • Future work • Summary & Conclusions

  3. Revised (Realistic) Content • Reminder of current SSES scheme • SSTs from AATSR • What affects the quality of AATSR SSTs? • An alternate scheme using view differences • Examples • Analysis of GHRSST-PP MDB • Future work • Summary & Conclusions

  4. What Affects AATSR Data Quality?

  5. What Affects the Quality of AATSR SSTs? • For December 2005 coefficients • D2-D3 bias (the latitude dependent correction) owing to limited number of channels • Small residual bias (~ 0.15 K at T < 280 K) most likely due to temperature dependent emissivity • These issues are being addressed in (A)RC project • Suspected 12 μm calibration error • In process of analysing flight-spare FPA • Clouds and aerosols (claerosols) • AATSR cloud screening is over-zealous • AATSR is designed for climate SSTs • Much better during day owing to 1.6 µm channel • Observable edge effects at night • Dual-view corrects for tropospheric aerosol • But not quite! • Being addressed in (A)RC project • Relative alignment of nadir and forward views • New results suggest systematic offset • Currently being investigated by AATSR QWG

  6. Suspected 12 μm Error: Implication for SSTs Calibration offset seen between AATSR and ATSR-2 12 μm clear-sky SEA BTs ATS_MET_2P and AT2_MET_2P products analysed Validation results suggest AATSR is incorrect Results in increase in latitude dependent D2-D3 bias Effect on current D3 SSTs is ~ + 0.05 K Effect on current D2 SSTs is ~ - 0.04 K

  7. Distribution of M-AERI Matchups LEGEND All +ve D-N -ve D-N • Bi-modal distribution of differences • 1 distribution due to -ve dual-nadir SST differences • 1 distribution due to +ve dual-nadir SST differences • Matchups • Day; Overpass ± 60 min; 1x1 Block

  8. The Affect of Saharan Dust on AATSR SSTs (30’) Nov 2003 July 2003

  9. Caribbean SST differences for ‘clean months’ – November to MarchData is derived from 30’ product Day D2-N2 Threshold = -0.03 K Night D3-N3 Threshold = +0.26 K

  10. Caribbean SST differences for ‘clean months’ – November to MarchData is derived from 1-km product Day D2-N2 Threshold = +0.25 K Night D3-N3 Threshold = +0.26 K

  11. Pacific Ocean – ‘clean’ months

  12. BT

  13. Schematic of BT Effects

  14. Relative alignment of forward and nadir views (1) Forward View 3.7 micron Nadir View 3.7 micron

  15. Relative alignment of forward and nadir views (2) Forward minus Nadir View 3.7 micron Forward minus Nadir View 3.7 micron with shift

  16. Basis of New SSES Scheme

  17. Requirements for AATSR SSES • Need, per pixel: • Bias • Retrieval bias, or • Bias to a common standard – GHRSST match-up database • Standard deviation • What exactly is a single pixel standard deviation? • Quality flag • Scale of 1-5 agreed in Melbourne • 1: Cloudy • 2: Bad • 3: Acceptable (defined by provider) • 4: Good • 5: Excellent

  18. Updated QF Scheme – Theoretical Thresholds

  19. Updated QF Scheme – Experimental Thresholds T2U = + 0.04 ± 0.09 °C T2L = - 1.53 ± 0.09 °C T3U = +0.51 ± 0.07 °C T3L = -0.51 ± 0.07 °C

  20. Updated PCF Scheme - Stratification

  21. Potential SSES Scheme: Summary • Effect of clouds and aerosols can be accounted for using D-N SST differences • Should get well-defined normal distribution • Can set thresholds to remove data not in normal distribution • Suspected alignment error between forward and nadir views will contribute to D-N differences • Significant positive edge structures still seen after view-difference shift • D-N test is designed for current AATSR data • Will need revising if and when relative alignment is corrected • 12 μm calibration error will contribute to D-N differences • D-N test is designed for current AATSR data • Will need revising if and when 12 μm calibration error is corrected

  22. Examples

  23. Example 1 • AATSR Orbit: ATS_NR__2PNPDE20060516_012117_000049912047_00403_22000_0504.N1 • Area of interest: 102 ºE to 118 ºE by 12 ºS to 4 ºS • Day time descending node • The day time example demonstrates the over-zealous cloud-screening, as the updated PCF mask is mainly indicating good data, while the larger-scale bad data is most likely affected by aerosol rather than cloud. The data are for 16th May 2006 over Indonesia, and it is noted that the volcano Mount Merapi, in central Java, was fairly active during May 2006.

  24. Comparison of N1 and L2P SSTs

  25. L2P Quality Control

  26. N1 D-N & New QF

  27. Change in QF

  28. Summary of Main Changes Due to New Scheme • Large number of pixels classified as QF 2 and QF 3 data are now classed as QF 5 • Little change for QF 4 and QF 5 (except night time) • A lot of pixels identified as bad (QF 2) by new scheme was previously classed as QF 3

  29. Analysis of GHRSST-PP MDB

  30. Definitions of SST SSTskin – SST10m (K) -0.3 -0.2 -0.1 0.0 SSTskin – SST10m (K) 0 0.5 1.0 1.5 2.0 2.5 3.0 10mm 10mm 1 mm 1 mm Infrared sensors (dT ~10s) 1 m 1 m Depth Depth Contact thermometers Ships/Buoys (dT ~minutes) 10 m 10 m • Night time situation, light wind • AATSR 3 channel (b) Day time situation, strong solar radiation and light winds AATSR 2-channel

  31. Location of GHRSST-PP Match-ups (1)

  32. Location of GHRSST-PP Match-ups (2) Others Drifting Buoys

  33. Example: Day time “Good” data low wind speed

  34. Example: Night time “high” data low wind speed

  35. Statistics from GHRSST-PP MDB Analysis A: Data below lower threshold B: Data within upper and lower thresholds C: Data above upper threshold

  36. New Confidence Values and Statistics Biases have been converted to skin biases by adding 0.17 K

  37. Summary & Conclusions (1) • Current PCF scheme used in L2P applied to AATSR data is appropriate for nadir-only IR with poor cloud screening • Does not account for over-zealous operational AATSR cloud screening • Does not account for impact of claerosols on forward view • Have developed improved quality flag for AATSR • Use D-N SST difference to identify retrievals affected by claerosols • Threshold = mode + 3 * sigma • Also stratification according to wind speed • Future scheme could take into account spatial and temporal variation in SST retrievals

  38. Summary & Conclusions (2) • Issues • Data classed as “others” • No day time wind speed dependence • May imply no significant diurnal warming has started or diurnal warming cancels out cool-skin effect • Night-time sub-skin correction • No current agreement on how to correct (consistently) • Would only recommend QF 5 data if using AATSR as reference • Requires changes to L2P product • Addition of nadir-only SST for each dual-view SST • Addition of flag to identify 3-channel retrievals

  39. Acknowledgements Defra, the UK Department of Environment, Food and Rural Affairs, who funded AATSR to support their programme of climate prediction and research, which in turn provides inputs to their policy-making processes Funding agencies in Australia who made significant contributions The European Space Agency This work was funded by ESA (ESA-NOCS Contract: AO/1-4362/03/I-LG) and Defra (Space ConneXions Contract: 2004-03-001/CPEG10)

  40. Current SSES Scheme

  41. Current SSES scheme for AATSR L2P

  42. AATSR SSTs

  43. Imaging infrared and visible radiometer on ENVISAT Similar channels to AVHRR & MODIS. Dual view (nadir and 55° to nadir) Along-track scanning, two views of same scene at different angles, for better atmospheric correction On-board calibration 2 on-board black bodies for IR calibration VISCAL unit for visible channel calibration 500 km swath 1 km IFOV at nadir Stirling Cycle Coolers, cooling low noise detectors to 80K, for optimum signal-to-noise ratios What is AATSR?

  44. AATSR SST Retrievals • Retrievals by radiative transfer modelling • Usually of the form: where n is the number of channels • For AATSR we have 2 channels during day and 3 during night • 3.7 µm not used during day owing to solar contamination • We have two views, so we have four SST retrievals in total • We also have two product formats • 1-km gridded (swath) • Spatially –averaged (gridded) Four Possible Retrievals: Nadir 2-channel N2 Nadir 3-channel N3 Dual 2-channel D2 Dual 3-channel D3

  45. Retrieval Coefficients: 1-km

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