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Microwave (AMSU) Calibration Update Bjorn Lambrigtsen Frank Sun Thomas Hearty

Microwave (AMSU) Calibration Update Bjorn Lambrigtsen Frank Sun Thomas Hearty. Topics. Radiometric calibration upgrade Moon in cold-cal FOV Pointing validation Radiometric validation. Radiometric Calibration Upgrade. The issue Cold-cal Tb c is assumed invariant

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Microwave (AMSU) Calibration Update Bjorn Lambrigtsen Frank Sun Thomas Hearty

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  1. Microwave (AMSU) Calibration UpdateBjorn LambrigtsenFrank SunThomas Hearty

  2. Topics • Radiometric calibration upgrade • Moon in cold-cal FOV • Pointing validation • Radiometric validation

  3. Radiometric Calibration Upgrade • The issue • Cold-cal Tbc is assumed invariant • Sum of cosmic background and Earth radiation into sidelobes • Baseline approach (from NOAA): use climatology to pre-compute Tbc(Earth) • In reality: Tbc (Earth) varies • Strong function of latitude; moderate func. of lon; weak func. of season • The effect: The computed cold-cal Tbc is erroneous • Prominent orbital cycle —> Varying calibration error • The solution • Take into account variability of Tbc(Earth) • Time/location-dependent climatology from prior observations • Tables are in place and can be populated for V4.0 • Will improve absolute radiometric accuracy by up to 1 K

  4. Cold-cal observations: Ch. 1-4 45 <—> ± 1.35 K Ch. 1 ± 1.35 K Ch. 3 ± 0.3 K Ch. 4 ± 0.6 K Ch. 2 ± 0.5 K

  5. Cold-cal observations: Ch. 5-8 Ch. 5 ± 0.8 K Ch. 7 ± 1.9 K Ch. 8 ± 0.3 K Ch. 6 ± 0.7 K

  6. Cold-cal observations: Ch. 9-12 Ch. 9 ± 0.4 K Ch. 11 ± 1.0 K Ch. 12 ± 0.8 K Ch. 10 ± 0.3 K

  7. Cold-cal observations: Ch. 13-15 • Will derive lat/lon “climatology” • Based on one 16-day cycle • Populate existing tables • Expect residual errors to be small • < 0.2 K • Should improve retrievals • May help ease sidelobe analysis Ch. 13 ± 0.9 K Ch. 15 ± 0.4 K Ch. 14 ± 0.8 K

  8. Moon in Cold-Cal FOV • The issue • Moon gets into cold-cal FOV several times a year • Can cause 3-4 K effect in AMSU (up to 20 K in HSB) • Baseline approach • Reject cold-cal if moon-in-FOV is predicted (computed moon angle < threshold) • Then: use last previously computed cal. coefficients • But not across granule boundaries • The result • If moon is in FOV, it may happen for several minutes • Because AMSU cold-cal view is snapshot in one single direction • Large gaps in calibration therefore occur periodically • This can span across granules - in that case, large data gaps can occur • The solution • Account for moon’s radiometric effect • Estimate ∆Tb from predicted moon angle - add to Tbc • Continue updating cal. coefficients => no calibration gaps => no data gaps • Can be implemented for V4.0

  9. Moon observations: Ch. 1-4 Ch. 1 3.5 K Ch. 3 2.6 K Ch. 4 2.5 K Ch. 2 2.9 K

  10. Moon observations: Ch. 5-8 Ch. 5 2.6 K Ch. 7 4.4 K Ch. 8 2.6 K Ch. 6 3.0 K

  11. Moon observations: Ch. 9-12 Ch. 9 3.1 K Ch. 11 3.5 K Ch. 12 3.5 K Ch. 10 2.9 K

  12. Moon observations: Ch. 13-15 • Results are close to expectations: • Tb ~ 200 + 25cos(-40°) @ 30 GHz • (Aqua) ~ 270° (1/2-waxing) + 8° (inclin) • Tb(moon/Aqua) ~ 185 K @ 30 GHz • (moon) ~ 0.52° ± 5% • Use simple functional approximation • Error < 1K • Use flag to alert data users • Can be improved with better pointing knowledge Ch. 13 3.6 K Ch. 15 2.9 K Ch. 14 3.7 K

  13. AMSU Pointing Analysis: Method • Method as described in 2002 • Instrument in nadir stare mode • Analyze coastal crossings • Perpendicular —> Pitch error • Oblique —> Roll error • Determine obs-calc time lag • Obs from Tb • Calc from ‘landfrac’ • ∆t = t(calc)-t(obs) • ∆pitch = ∆t*(6.65 km/sec)/(705 km) • Works well for window channels • Results shown here for pitch analysis • Several dozen crossings • 5 quasi window channels • Moon analysis will also be used • Results to be presented later Example HSB perpendicular crossing (sampled every 0.02 sec for 1.7 sec, followed by 1-sec gap)

  14. AMSU Pointing Analysis: Results Summary for 11 selected perpendicular crossings Example AMSU perpendicular crossing (sampled every 0.2 sec for 6 sec, followed by 2-sec gap)

  15. AMSU Pointing Analysis: Summary • Pitch errors are within requirements (±10% of FOV) • Can be largely corrected for in L1A geolocation processing • Relative tightly clustered • Small sample, large scatter: analysis statistics can be improved • Roll analysis to be reported on later • Yaw analysis: must use different method using full-scan data

  16. 0.35° AMSU Pointing Analysis Using Moon • Branches should be equal • Approach = Recede • At least near closest approach • Difference due to pointing error • “MoonAng” from assumed boresight centroid • Actual boresight differs • Complex geometry • Lunar “path” not symmetric • Varying mix of pitch/roll/yaw • Precise analysis needs work • Example shown • Offset = 0.35° • Implies pointing error of 0.175° • Combined pitch/roll/yaw Single lunar encounter - Ch. 1

  17. Lunar Pointing Analysis Example Ch. 4 Ch. 15 Small pointing error indicated for ch. 4 Large pointing error indicated for ch. 15

  18. AMSU Moon Analysis Extra Curious behavior of Ch. 14 • Should be identical • Shared front end • Ch. 9-13 look very similar Ch. 10 Ch. 14

  19. AMSU Radiometric Validation • Objectives • Absolute radiometric validation • Definitive sidelobe analysis • So far • Assess effect of clouds • Assess effect of wind • Comparison with ECMWF • Analysis is on-going • Comparison with radiosondes

  20. AMSU Obs-Calc vs. Wind speed Ch. 1 Ch. 2

  21. AMSU Obs-Calc vs. Wind speed Ch. 3 Ch. 15

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