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Determination of atmospheric temperature



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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 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 The Far Infrared Frontier Current EOS A Train measure 3 4 to 15 m don t measure 15 100 m 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 IRIS D measured to 25 m in 1970 Currently inferred from measurements in other spectral regions Motivation No spectral measurements to the right of line Figures derived from Mlynczak et al SPIE 2002 3 FIRST Far Infrared Spectroscopy of the Troposphere FTS w 0 6 cm 1 unapodized resolution 0 8 cm scan length Multilayer beamsplitter AIRS FIRST AIRS Germanium on polypropylene Good performance over broad spectral ranges in the far infrared 5 200 m 50 2000 cm 1 spectral range NeDT goal 0 2 K 10 60 m 0 5 K 60 100 m 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 instrument 4 Retrieval Sensitivity Test Flow Chart T z H2O z O3 z CWC z CER z Random Perturbations Model Atmosphere RTM Noise A priori Atmospheric State A priori uncertainty RTM A priori spectrum Synthetic Measurement Retrieval algorithm Analyze retrieved state spectra and associated statistics Sensitivity tests 5 Clear Sky Retrieval Test 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 Sensitivity tests 6 Clear Sky Heating Rates Tropical Conditions Sub Artic Winter Conditions 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 Heating Rates 7 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 m band low BT channels in far IR High BT channels scale from midto far IR For tropics channels with BT 250270 K emitting 5 8 km are complicated Clouds 8 Test Flight on September 18 2006 Ft Sumner NM AQUA MODIS L1B RGB Image FIRST Balloon Test flight AIRS Footprints CloudSat CALIPSO Track 9 CloudSat CALIPSO signals CloudSat and CALIPSO near collocation No signal from CloudSat CALIPSO signal consistent with FIRST residual Test flight 10 FIRST and AIRS Cloud Signatures Instrument collocation FIRST balloon borne spectra AIRS MODIS Residuals are consistent with clouds 5 km De 60 m Test flight Cloud Detected 11 Climate Model Considerations 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 12 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 Conclusions 13 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 Thank you for your time 14 Cloud Radiative Effect CRE 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 15 Towards CLARREO 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 m Future directions 16


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