Comparison of AIRS and IASI observed radiances using SNOs: Approach - - PowerPoint PPT Presentation

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Comparison of AIRS and IASI observed radiances using SNOs: Approach - - PowerPoint PPT Presentation

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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

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Comparison of AIRS and IASI

  • bserved 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

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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.

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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. δi = 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 σi = [SD’

IASI,i 2 + SD’ AIRS,i 2]½.

  • 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. ωi = 1/σi

2, Δ = σΔ 2

[Σi=1:N ωi δi], and σΔ = [Σi=1:N ωi]‐½)

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SLIDE 4

SNO locaHons and Hmes

73.8° N 73.8° S page 4

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Sample Hme series plot: mean differences and uncertainHes for channels within AIRS module M‐04a (1541‐1623 cm‐1)

AIRS – IASI (K) AIRS – IASI (K) Northern laHtude SNOs Southern laHtude SNOs

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900.31 cm‐1 channel differences as a funcHon of IASI and AIRS spaHal standard deviaHons

AIRS spaHal STDDEV (K) IASI spaHal STDDEV (K) |AIRS – IASI|(K)

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Differences for AIRS array M‐07 (911.2‐974.3 cm‐1) as a funcHon of IASI and AIRS spaHal standard deviaHons

AIRS spaHal STDDEV (K) IASI spaHal STDDEV (K) |AIRS – IASI|(K)

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Northern SNOs

BT (K) AIRS – IASI (K)

wavenumber (cm‐1) wavenumber (cm‐1) mean AIRS spectrum mean IASI spectrum

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Difference

A and B side A side only B side only

Uncertainty

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SLIDE 9

Southern SNOs

BT (K) AIRS – IASI (K)

wavenumber (cm‐1) wavenumber (cm‐1) mean AIRS spectrum mean IASI spectrum

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Difference

A and B side A side only B side only

Uncertainty

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SLIDE 10

Northern SNOs

BT (K) AIRS – IASI (K)

wavenumber (cm‐1) wavenumber (cm‐1) Difference Uncertainty mean AIRS spectrum mean IASI spectrum

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Southern SNOs

BT (K) AIRS – IASI (K)

wavenumber (cm‐1) wavenumber (cm‐1) mean AIRS spectrum mean IASI spectrum Difference Uncertainty

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Spectral Shift A-B State Differences Note small jumps at module boundaries

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Northern SNOs

BT (K) AIRS – IASI (K)

wavenumber (cm‐1) wavenumber (cm‐1) mean AIRS spectrum mean IASI spectrum Difference Uncertainty

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Modules offset ~0.15 K

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SLIDE 13

Southern SNOs

BT (K) AIRS – IASI (K)

wavenumber (cm‐1) wavenumber (cm‐1) mean AIRS spectrum mean IASI spectrum Difference Uncertainty

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SLIDE 14

Northern SNOs

BT (K) AIRS – IASI (K)

wavenumber (cm‐1) wavenumber (cm‐1) mean AIRS spectrum mean IASI spectrum Difference Uncertainty

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SLIDE 15

Southern SNOs

BT (K) AIRS – IASI (K)

wavenumber (cm‐1) wavenumber (cm‐1) mean AIRS spectrum mean IASI spectrum Difference Uncertainty

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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 ?

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