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Comparison of AIRS and IASI observed radiances using SNOs: Approach and Preliminary Results Dave Tobin, Fred Nagle, Steve Dutcher 29 March 2008 crank://Users/davet/Documents/sno2mes/airs_iasi_snos_11jan2008.ppt MoHvaHon AIRS and IASI


  1. Comparison of AIRS and IASI observed radiances using SNOs: Approach and Preliminary Results Dave Tobin, Fred Nagle, Steve Dutcher 29 March 2008 crank://Users/davet/Documents/sno2mes/airs_iasi_snos_11jan2008.ppt 

  2. MoHvaHon • AIRS and IASI are high spectral resoluHon infrared sounders, designed primarily for weather applicaHons and also currently serving as references for in‐orbit infrared calibraHon. • Previous studies performed for both AIRS and IASI suggest that the sensors are, in general, accurate to the 0.2 to 0.5 K (3‐sigma) level. • Direct comparisons of AIRS and IASI via Simultaneous Nadir Overpasses (SNOs) provide another way to assess the accuracies of the sensors. page 2

  3. Analysis Approach The locaHons and Hmes of the Simultaneous Nadir Overpasses (SNOs) for IASI and • AIRS are computed, spanning 14 May 2007 to 10 Jan 2008, for SNOs for which the AIRS and IASI observaHon Hmes are within 2 minutes of each other (N=284 cases). For each SNO, the AIRS FOVs within 30 km of the SNO locaHon are idenHfied • (typically 6 to 8 FOVs per SNO) and the mean (MN) and standard deviaHon (SD) radiance spectra are computed. The same is done for IASI (typically 3 to 4 FOVs per SNO). For each SNO, the spectra are processed to have common spectral resoluHon and • sampling (i.e. de‐apodize the IASI L1C spectra and then convolve with the AIRS L1B SRFs, and convolve the AIRS L1B spectra with the de‐apodized IASI L1C SRFs) and the difference between AIRS and IASI is computed (i.e. δ i = MN ’ AIRS,i ‐ MN ’ IASI,i ). The resulHng primary source of comparison error for each SNO case is due to the • difference in the sparse sampling of the scene radiance provided by AIRS (nearly conHguous 3x3 FOVs) and IASI (non‐conHguous 2x2 FOVs). The 1‐sigma uncertainty for each SNO case is therefore computed as σ i = [SD ’ 2 + SD ’ 2 ] ½ . IASI,i AIRS,i For ensembles of SNOs, the spaHal sampling differences are assumed to be • random from case to case. The mean differences between AIRS and IASI and their uncertainHes are computed using weighted mean differences using the spaHal standard deviaHons to compute the weights for each case (i.e. ω i = 1/ σ i 2 , Δ = σ Δ 2 [ Σ i=1:N ω i δ i ], and σ Δ = [ Σ i=1:N ω i ] ‐½ ) page 3

  4. SNO locaHons and Hmes 73.8° N 73.8° S page 4

  5. Sample Hme series plot: mean differences and uncertainHes for channels within AIRS module M‐04a (1541‐1623 cm ‐1 ) Northern laHtude SNOs AIRS – IASI (K) Southern laHtude SNOs AIRS – IASI (K) page 5

  6. 900.31 cm ‐1 channel differences as a funcHon of IASI and AIRS spaHal standard deviaHons IASI spaHal STDDEV (K) |AIRS – IASI|(K) AIRS spaHal STDDEV (K) page 6

  7. Differences for AIRS array M‐07 (911.2‐974.3 cm ‐1 ) as a funcHon of IASI and AIRS spaHal standard deviaHons IASI spaHal STDDEV (K) |AIRS – IASI|(K) AIRS spaHal STDDEV (K) page 7

  8. Northern SNOs BT (K) mean AIRS spectrum mean IASI spectrum wavenumber (cm ‐1 ) Difference � A and B side A side only AIRS – IASI (K) B side only Uncertainty wavenumber (cm ‐1 ) page 8

  9. Southern SNOs BT (K) mean AIRS spectrum mean IASI spectrum wavenumber (cm ‐1 ) Difference � A and B side A side only AIRS – IASI (K) B side only Uncertainty wavenumber (cm ‐1 ) page 9

  10. Northern SNOs BT (K) mean AIRS spectrum mean IASI spectrum wavenumber (cm ‐1 ) Difference Uncertainty AIRS – IASI (K) wavenumber (cm ‐1 ) page 10

  11. Southern SNOs BT (K) mean AIRS spectrum mean IASI spectrum wavenumber (cm ‐1 ) Difference Uncertainty AIRS – IASI (K) Note small jumps at module boundaries wavenumber (cm ‐1 ) Spectral Shift A-B State Differences page 11

  12. Northern SNOs mean AIRS spectrum mean IASI spectrum BT (K) wavenumber (cm ‐1 ) Difference Uncertainty AIRS – IASI (K) Modules offset ~0.15 K wavenumber (cm ‐1 ) page 12

  13. Southern SNOs mean AIRS spectrum mean IASI spectrum BT (K) wavenumber (cm ‐1 ) Difference Uncertainty AIRS – IASI (K) wavenumber (cm ‐1 ) page 13

  14. Northern SNOs mean AIRS spectrum mean IASI spectrum BT (K) wavenumber (cm ‐1 ) Difference Uncertainty AIRS – IASI (K) wavenumber (cm ‐1 ) page 14

  15. Southern SNOs mean AIRS spectrum mean IASI spectrum BT (K) wavenumber (cm ‐1 ) Difference Uncertainty AIRS – IASI (K) wavenumber (cm ‐1 ) page 15

  16. Summary, Conclusions, QuesHons Although the agreement between AIRS and IASI observed radiances is very good on one level, the • SNO comparisons reported here reveal some fundamental measurement differences which can potenHally impact both weather and climate applicaHons. Specific findings include: • The comparisons show no significant long term (8 months) trends versus Hme. – Significant differences, on the order of 500 mK, are observed between the longwave differences from the – northern to southern laHtude SNOs, parHcularly for AIRS detector array M‐12 (649‐681 cm ‐1 ). Further analyses and comparisons with L. Strow’s spectral shik analyses suggests that these differences are due primarily to orbital variaHons of the AIRS spectral centroids, which is not included in producHon of the AIRS L1B product. SNO comparisons with IASI should be performed again aker producHon of the AIRS L1C climate products, which are expected to include knowledge of these spectral shik variaHons. AIRS A‐B state related differences are observed within some detector arrays, most notably within array M‐08 – (851‐903 cm ‐1 ) with differences of approximately 400 mK between A‐side only and B‐side only channels. For upper level water vapor channels, mean differences on the order of 200 mK are observed for AIRS – detector arrays M‐04a (1541‐1623 cm ‐1 ) and M‐04b (1460‐1527 cm ‐1 ), while the mean differences for neighboring arrays are approximately zero, suggesHng that these differences are due, at least parHally, to AIRS. IASI shortwave channels are very noisy for the very cold southern laHtude SNOs. OpHmal random noise – filtering and/or wavenumber averaging should be used to improve the comparisons for these cases. ResulHng quesHons: • Are the differences reported here for relaHvely cold scenes representaHve of differences for warmer scenes ? – To what degree have the observed differences been absorbed , correctly or not, into forward model – parameterizaHons and/or retrieval bias funcHons and/or derived climate products ? What calibraHon refinements can be implemented to account for the observed differences ? – page 16

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