Determination of atmospheric temperature, water vapor, and heating rates from mid- and
far- infrared hyperspectral measurements
AGU Fall Meeting, Wednesday, December 12, 2007GC34A-02
D.R. Feldman (Caltech); K.N. Liou (UCLA); Y.L. Yung (Caltech);
D. G. Johnson (LaRC); M. L. Mlynczak (LaRC)
http://www.gps.caltech.edu/~drf/misc/agu2007
Presentation Outline
• Motivation for studying the far-infrared• FIRST instrument description• Sensitivity tests of mid-IR vs far-IR capabilities
– Clear-sky– Cloudy-sky
• Multi-instrument data comparison• Climate model considerations• Conclusions
OutlineOutline 2
The Far-Infrared Frontier
3
• Current EOS A-Train spectrometers measure 3.4 to 15 μm, don’t measure 15-100 μm
• Far-IR, through H2O rotational band, affects OLR, tropospheric cooling rates
• Far-IR processes inferred from other spectral regions
• Mid-IR, Microwave, Vis/NIR
• Interaction between UT H2O and cirrus clouds requires knowledge of both
• Currently inferred from measurements in other spectral regions
Figures derived from Mlynczak et al, SPIE, 2002 MotivationMotivation
No spectral measurementsto the right of line
FIRST: Far Infrared Spectroscopy of the Troposphere
• NASA IIP FTS w/ 0.6 cm-1 unapodized resolution, ±0.8 cm scan length
• Multilayer beamsplitter– Germanium on polypropylene– Good performance over broad
spectral ranges in the far-infrared
• 5-200 μm (2000 – 50 cm-1) spectral range
• NeDT goal ~0.2 K (10-60 μm), ~0.5 K (60-100 μm)
• 10 km IFOV, 10 multiplexed detectors
• Balloon-borne & ground-based observations
FIRST instrumentFIRST instrument 4
FIRSTAIRS AIRS
Retrieval Sensitivity TestFlow Chart
5
Model Atmosphere A priori Atmospheric State)
Random Perturbations
Synthetic Measurement
RTM + Noise
A priori spectrum
RTM
Retrieval algorithm
A prioriuncertainty
Analyze retrieved state, spectra, and associated statistics
Sensitivity testsSensitivity tests
T(z)H2O(z)O3(z)CWC(z)CER(z)
From Rodgers, 2000
Clear-Sky Retrieval Test
6 Sensitivity testsSensitivity tests
• AIRS and FIRST T(z) retrievals comparable.• FIRST better than AIRS in H2O(z) retrievals 200-300 mbar.• Residual signal in far IR seen 100-200 cm-1 → low NeDT critical
Clear-Sky Heating Rates
• Spectra provide information about fluxes/heating rates• Error propagation (Taylor et al, 1994; Feldman et al, In Review) can
be used to determine heating rate uncertainty. • Heating rate error for scenes with clouds is generally higher.
7 Heating RatesHeating Rates
A prioriσ(T(z)) = 3 Kσ(H2O(z)) = 20%σ(O3(z)) = 20%
A posterioriσ(T(z)) ≈ 1 Kσ(H2O(z)) ≈ 10%σ(O3(z)) ≈ 10%
Extrapolating Far-IR with Clouds• Retrieval of T(z), H2O(z), CWC(z),
CER(z) difficult with AIRS spectra• AIRS H2O channels correlate with
far-IR channels– Low BT channels from 6.3 μm band
≈ low BT channels in far-IR– High BT channels scale from mid- to
far-IR– For tropics, channels with BT 250-
270 K (emitting ~ 5-8 km) are complicated
• Broadband IR radiance can be computed from mid-IR channels
8 CloudsClouds
Test Flight on September 18, 2006:Ft, Sumner NM
AQUA MODIS L1B RGB Image
9
AIRS FootprintsFIRST Balloon
CloudSat/CALIPSO Footprint Track Test flightTest flight
• Instrument collocation• FIRST balloon-borne spectra• AIRS• MODIS
• FIRST residuals are consistent with clouds ~ 5 km, CER ~ 6 μm
10
FIRST and AIRS Cloud Signatures
CloudDetected !
Test flightTest flight
CloudSat/CALIPSO signals
11 Test flightTest flight
• CloudSat and CALIPSO near collocation• No signal from CloudSat • CALIPSO signal consistent with FIRST residual
Climate Model Considerations
12
• Climate models produce fields that specify mid- & far-IR spectra.– RT in Far-IR requires state and spectral space treatment.
• Far-IR climate model analysis requires more far-IR data– Far-IR extrapolation should retain physical basis and be verified with
measurements.
– Agreement with CERES is a partial verification and presents a non-unique checksum
• Future work required to assess how mid- and far-IR spectra impart information towards far-IR climate model processes.
Model evaluationModel evaluation
Conclusions• AIRS measures mid-IR, but far-IR is not covered by A-Train
spectrometers.– FIRST describes far-IR but limited spectra are available.
• FIRST clear-sky T retrievals comparable, improved UT H2O retrieval relative to AIRS– Implied cooling rate information difference is small.
• Extrapolating far-IR channels with cirrus cloud good for Tb ~ 220 K, ok for Tb ~ 300 K, difficult for Tb ~250-270 K.
• Multi-instrument analysis with A-Train facilitates comprehensive understanding of FIRST test flight spectra.
• AIRS mid-IR spectra can validate climate models, but far-IR should not be neglected.
13 ConclusionsConclusions
Acknowledgements
• NASA Earth Systems Science Fellowship, grant number NNG05GP90H.
• Yuk Yung Radiation Group: Jack Margolis, Vijay Natraj, King-Fai Li, & Kuai Le
• George Aumann and Duane Waliser from JPL• Xianglei Huang from U. Michigan and Yi Huang from Princeton• AIRS, CloudSat, and CALIPSO Data Processing Teams
14 Thank you for your timeThank you for your time
