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)

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 • Conclusions

OutlineOutline 2

The Far-Infrared Frontier

3

• Current EOS A-Train measure 3.4 to 15 μm, don’t measure 15-100 μm

• IRIS-D measured to 25 μm in 1970

• 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

• 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 (50 – 2000 cm-1)

spectral range• NeDT goal ~0.2 K (10-60 μm),

~0.5 K (60-100 μm)• 10 km IFOV, 10 multiplexed

detectors• Cooling

• Spectrometer LN2 cooled• Detectors liquid He cooled

• Scan time: 1.4-8.5 sec• 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)

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 • Heating rate error for scenes with clouds generally higher due to lack of

vertical cloud information7 Heating RatesHeating Rates

Tropical Conditions Sub-Artic Winter Conditions

Extrapolating Far-IR with Clouds• Retrieval of T(z), H2O(z), CWC(z),

CER(z) difficult with AIRS spectra• Use AIRS channels to

extrapolate far-IR channels?– Depends on cloud conditions, T(Z),

H2O(z)

– 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

8 CloudsClouds

Test Flight on September 18, 2006:Ft, Sumner NM

AQUA MODIS L1B RGB Image

Test flightTest flight 9

AIRS FootprintsFIRST Balloon

CloudSat/CALIPSO Track

CloudSat/CALIPSO signals

10 Test flightTest flight

• CloudSat and CALIPSO near collocation• No signal from CloudSat • CALIPSO signal consistent with FIRST residual

• Instrument collocation• FIRST balloon-borne spectra• AIRS• MODIS

• Residuals are consistent with clouds ~ 5 km, De ~ 60 μm

Test flightTest flight 11

FIRST and AIRS Cloud Signatures

CloudDetected !

Climate Model Considerations

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• Climate models produce fields that specify mid- & far-IR spectra.

• Multi-moment statistical comparisons of measured spectra and spectra produced by models avoid subtle biases from data processing algorithms– Spectral and atmospheric state spaces should be considered jointly.

• Far-IR climate model analysis requires more far-IR data– Extrapolation of far-IR should retain some physical basis and be verified with

hyperspectral measurements.

– Agreement with CERES data is only partial verification and presents a non-unique checksum

• Future work is required to assess how spectra impart information towards climate model processes.

Model evaluationModel evaluation

Conclusions• AIRS measures mid-IR, but far-IR is not covered A-Train spectrometers.• FIRST provides thorough description of 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 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

Cloud Radiative Effect (CRE)

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• CRE = TOA clear broadband flux – TOA broadband flux

• CERES provides collocated measurements of CRE from broadband radiometers– Most CERES products contain

multiple data-streams

• AIRS L3 CRE lower than CERES CRE– Other A-Train sets

(CloudSat/CALIPSO) can arbitrate difference

CloudsClouds

Towards CLARREO

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• NRC Decadal Survey recommended CLARREO for– Radiance calibration

– Climate monitoring

• CLARREO specified to cover 200 – 2000 cm-1 with < 2 cm-1 resolution– NIST traceability requirement

• Prototyped far-IR instruments provide a science and engineering test-bed for next generation of satellite instruments

• Further orbital simulations required to test how mid-IR state space uncertainties appear as far-IR spectral residuals

• More integrated A-train analyses w.r.t. Far-IR warranted

• Larger Far-IR dataset analysis needed to demonstrate utility of long wavelength measurements for climate monitoring

• Don’t forget about 50-200 cm-1 (200-50 μm).

Future directionsFuture directions