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The Far-Infrared Frontier of Terrestrial Remote Sensing. GPS Planetary Science Seminar October 16, 2007 Daniel Feldman, Yuk Yung (Caltech) Kuo -Nan Liou (UCLA) Marty Mlynczak , Dave Johnson ( LaRC ). Presentation Outline. Motivation for studying the far-infrared
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The Far-Infrared Frontier of Terrestrial Remote Sensing GPS Planetary Science Seminar October 16, 2007 Daniel Feldman, Yuk Yung (Caltech) Kuo-Nan Liou (UCLA) Marty Mlynczak, Dave Johnson (LaRC)
Presentation Outline • Motivation for studying the far-infrared • FIRST instrument description • Mid-IR vs Far-IR capabilities • Clear-sky • Cloudy-sky • Lessons learned from collocated test flights • Multi-instrument analysis of clouds • Outline
Atmospheric Energy Balance • Motivation Earth Radiation Budget Cartoon From Liou, 2002
The far infrared frontier Current spectrometers don’t measure 15-100 μm (650 – 100 cm-1) FIR, through H2O rotational band, contributes substantially to OLR, tropospheric cooling rates Far-IR processes inferred from other spectral regions Mid-IR passive spectroscopy Microwave active and passive sounding Vis/NIR lidar No spectral measurements beyond line • Motivation Figure from Mlynczak et al, SPIE, 2002
Clouds and the far-infrared In tropics, cirrus causes increased tropospheric radiative heating in mid-IR & increased cooling in far-IR In sub-arctic winter, cirrus leads to less mid-IR heating, enhanced IR cooling Interaction between UT H2O and cirrus clouds requires knowledge of both Currently inferred from measurements in other spectral regions • Motivation Figure adapted from Stackhouse & Stephens, 1991
CLARREO Mission 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 • Motivation Figure adapted from Anderson presentation, 2007
Remote sensing of far-infrared: a frontier in spectroscopy • FIRST = Far Infrared Spectroscopy of the Troposphere • Developed at NASA LaRC, Marty Mlynczak PI, NASA IIP project • FTS w/ 0.6 cm-1 unapodized resolution, ±0.8 cm scan length • Multilayer beamsplitter • Germanium • Polypropylene • Optically inactive over broad spectral ranges in far-infrared • 5-200 μm (50 – 2000 cm-1) spectral range • NeDT ~ 0.2 K • 10 km IFOV, 10 multiplexed detectors • LN2 or liquid helium cooled • Scan time: 1.4-8.5 sec • FIRST instrument
Prototype Configuration and Test Flights • FIRST instrument Pictures from http://stratocat.com.ar/fichas-e/2005/FSU-20050607.htm
AIRS and FIRST T, H2O, O3 clear-sky retrievals Standard retrievals using a linear Bayesian update for clear-sky cases Mid- and Far-IR profile retrievals T profiles comparable FIRST has superior H2O profile performance in upper troposphere Normalized averaging kernels quickly reveal relative retrieval power • Mid-IR vs. Far-IR: clear
Spectra and residuals Much of the initial residual structure removed during retrieval Tsurf not retrieved here Retrieval using FIRST vs AIRS shows structure at low wavenumbers and larger residuals in H2O v3 band Upper troposphere H2O retrieval power difference revealed • Mid-IR vs. Far-IR: clear
Cooling Rate Information Information from the spectrometers can impart understanding of cooling rate profiles (Feldman et al, 2007). Far-IR measurements provide marginal improvement of upper-troposphere clear-sky cooling rates Comparable performance for tropical, sub-arctic winter atmospheres • Mid-IR vs. Far-IR: clear
Cloud & H2O signatures Ice cloud absorption, extinction, asymmetry factors can be reasonably parameterized with: Cloud-water content profiles Cloud effective radius profiles AIRS spectra utilize 8-12 µm window band and 6.3 µm H2O band for cloud and H2O profile retrieval Degree to which cirrus cloud properties can be retrieved with H2O profiles is active area of research • Mid-IR vs. Far-IR: cloud
Suite of A-Train measurements Polar-orbiting sun-synchronous constellation of satellites with diverse instrumentation Aqua AIRS (mid-IR passive spectrometer for sounding) AMSU (Passive microwave sounder) MODIS (vis/near-IR imaging spectroradiometer) CloudSat (94 GHz cloud pulse radar) CALIPSO (2-channel vis/near-IR lidar) • Multi-instrument analysis
Test Flight 2 AQUA MODIS L1B RGB Image • Test flights Ft. Sumner, NM; stratiform clouds; Aqua, Cloudsat/CALIPSO overpass
FIRST and AIRS Cloud Signatures • Instrument collocation • FIRST balloon-borne spectra • AIRS • MODIS • Residuals are consistent with clouds ~ 5 km, De ~ 60 μm • Test flights
Active sounders • CloudSat and CALIPSO near collocation • No signal from CloudSat • CALIPSO signal consistent with FIRST residual • Multi-instrument analysis
Conclusions • FIRST provides a comprehensive description of the far-infrared which is relevant to CLARREO development • FIRST clear-sky retrievals vs. AIRS • Improved H2O retrieval relative to AIRS • Relies on low instrument FIR NeDT • Implied cooling rate information difference is negligible. • FIR instrumentation can impart significant info on cloud radiative effect • Multi-instrument analysis is powerful for understanding FIRST test flight spectra • In the future: • Orbital simulation environment testing is necessary to compare the relative abilities of mid- and far-IR under different, realistic conditions • FIRST radiance calibration is required to gain quantitative information out of test flights about H2O lines and cloud cover.
Acknowledgements • NASA ESSF Program • Jack Margolis and the YLY IR Radiation Team at Caltech • Tom Pagano, Duane Waliser, Eric Fetzer and Alex Ruzmaikan of JPL • Tony Clough and the RT Team at AER, Inc. • The CloudSat and CALIPSO product support teams