1. Determination of atmospheric temperature, water vapor, and heating rates from mid- and far- infrared hyperspectral measurements AGU Fall Meeting, Wednesday, December 12, 2007 GC34A-02 D.R. Feldman (Caltech); K.N. Liou (UCLA); Y.L. Yung (Caltech); D. G. Johnson (LaRC); M. L. Mlynczak (LaRC)

2. 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  Outline 2

3. 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 H 2 O rotational band, affects OLR, tropospheric cooling rates Far-IR processes inferred from other spectral regions Mid-IR, Microwave, Vis/NIR Interaction between UT H 2 O and cirrus clouds requires knowledge of both Currently inferred from measurements in other spectral regions Figures derived from Mlynczak et al, SPIE, 2002  Motivation No spectral measurements to the right of line

4. 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 LN 2 cooled Detectors liquid He cooled Scan time: 1.4-8.5 sec Balloon-borne & ground-based observations  FIRST instrument 4 FIRST AIRS

5. Retrieval Sensitivity Test Flow Chart 5 Model AtmosphereA priori Atmospheric State) Random Perturbations Synthetic Measurement RTM + Noise A priori spectrum RTM Retrieval algorithm A priori uncertainty Analyze retrieved state, spectra, and associated statistics  Sensitivity tests T(z) H 2 O(z) O 3 (z) CWC(z) CER(z)

6. Clear-Sky Retrieval Test 6  Sensitivity tests AIRS and FIRST T(z) retrievals comparable. FIRST better than AIRS in H 2 O(z) retrievals 200-300 mbar. Residual signal in far IR seen 100-200 cm -1 → low NeDT critical

7. 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 information 7  Heating Rates Tropical ConditionsSub-Artic Winter Conditions

8. Extrapolating Far-IR with Clouds Retrieval of T(z), H 2 O(z), CWC(z), CER(z) difficult with AIRS spectra Use AIRS channels to extrapolate far-IR channels? – Depends on cloud conditions, T(Z), H 2 O(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  Clouds

9. Test Flight on September 18, 2006: Ft, Sumner NM AQUA MODIS L1B RGB Image 9 AIRS FootprintsFIRST Balloon CloudSat/CALIPSO Track  Test flight

10. CloudSat/CALIPSO signals 10  Test flight CloudSat and CALIPSO near collocation No signal from CloudSat CALIPSO signal consistent with FIRST residual

11. Instrument collocation FIRST balloon-borne spectra AIRS MODIS Residuals are consistent with clouds ~ 5 km, D e ~ 60 μm 11 FIRST and AIRS Cloud Signatures Cloud Detected !  Test flight

12. Climate Model Considerations 12 Climate models produce fields that specify mid- & far-IR spectra. Multi-moment statistical comparisons of measured spectra and modeled spectra avoid subtle biases from data processing. – Spectral and atmospheric state spaces should be considered jointly. 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 only partial verification and presents a non-unique checksum Future work to assess how spectra impart information towards climate model processes.  Model evaluation

13. 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 H 2 O retrieval relative to AIRS – Implied cooling rate information difference is small. Extrapolating far-IR channels good for T b ~ 220 K, ok for T b ~ 300 K, difficult for T b ~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  Conclusions

14. 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 time

15. Cloud Radiative Effect (CRE) 15 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  Clouds

16. Towards CLARREO 16 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 directions