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Article Type:
Research Article

Angular Effect of Undetected Clouds in Infrared Window Radiance Observations: Aircraft Experimental Analyses

Nicholas R. Nalli I.M. Systems Group, Inc., Rockville, Maryland

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William L. Smith Hampton University, Hampton, Virginia

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Quanhua Liu NOAA/NESDIS/Center for Satellite Applications and Research, College Park, Maryland

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Print Publication:
01 May 2016
Collections:
Aerosol-Cloud-Precipitation-Climate Interaction
DOI:
https://doi.org/10.1175/JAS-D-15-0262.1
Page(s):
1987–2010
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Abstract

This paper furthers previous investigations into the zenith angular effect of cloud contamination within infrared (IR) window radiance observations commonly used in the retrieval of environmental data records (EDRs). Here analyses were performed of clear-sky forward radiance calculations versus observations obtained under clear to partly cloudy conditions over ocean. The authors utilized high-resolution IR spectra observed by the aircraft-based National Polar-Orbiting Partnership (NPP) Aircraft Sounder Test Bed-Interferometer (NAST-I) during the Joint Airborne Infrared Atmospheric Sounding Interferometer (IASI) Validation Experiment (JAIVEx) and performed forward calculations using collocated dropsondes. An aerosol optical depth EDR product derived from Geostationary Operational Environmental Satellite (GOES) was then applied to detect clouds within NAST-I fields of view (FOVs). To calculate the angular variation of clouds, expressions were derived for estimating cloud aspect ratios from visible imagery where cloud shadow lengths can be estimated relative to cloud horizontal diameters. In agreement with sensitivity calculations, it was found that a small cloud fraction within window radiance observations can have a measurable impact on the angular agreement with clear-sky calculations on the order of 0.1–0.4 K in brightness temperature. It was also found that systematic sun-glint contamination can likewise have an impact on the order of 0.1 K. These results are germane to IR sensor data record (SDR) calibration/validation and EDR retrieval schemes depending upon clear-sky SDRs, as well as radiative transfer modeling involving randomly distributed broken cloud fields.

Corresponding author address: Nicholas R. Nalli, NOAA/NESDIS/ Center for Satellite Applications and Research (STAR), NCWCP E/RA2, 5830 University Research Court #2841, College Park, MD 20740-3818. E-mail: nick.nalli@noaa.gov

This article is included in the Aerosol-Cloud-Precipitation-Climate Interaction Special Collection.

Abstract

This paper furthers previous investigations into the zenith angular effect of cloud contamination within infrared (IR) window radiance observations commonly used in the retrieval of environmental data records (EDRs). Here analyses were performed of clear-sky forward radiance calculations versus observations obtained under clear to partly cloudy conditions over ocean. The authors utilized high-resolution IR spectra observed by the aircraft-based National Polar-Orbiting Partnership (NPP) Aircraft Sounder Test Bed-Interferometer (NAST-I) during the Joint Airborne Infrared Atmospheric Sounding Interferometer (IASI) Validation Experiment (JAIVEx) and performed forward calculations using collocated dropsondes. An aerosol optical depth EDR product derived from Geostationary Operational Environmental Satellite (GOES) was then applied to detect clouds within NAST-I fields of view (FOVs). To calculate the angular variation of clouds, expressions were derived for estimating cloud aspect ratios from visible imagery where cloud shadow lengths can be estimated relative to cloud horizontal diameters. In agreement with sensitivity calculations, it was found that a small cloud fraction within window radiance observations can have a measurable impact on the angular agreement with clear-sky calculations on the order of 0.1–0.4 K in brightness temperature. It was also found that systematic sun-glint contamination can likewise have an impact on the order of 0.1 K. These results are germane to IR sensor data record (SDR) calibration/validation and EDR retrieval schemes depending upon clear-sky SDRs, as well as radiative transfer modeling involving randomly distributed broken cloud fields.

Corresponding author address: Nicholas R. Nalli, NOAA/NESDIS/ Center for Satellite Applications and Research (STAR), NCWCP E/RA2, 5830 University Research Court #2841, College Park, MD 20740-3818. E-mail: nick.nalli@noaa.gov

This article is included in the Aerosol-Cloud-Precipitation-Climate Interaction Special Collection.

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  • Arndt, D. S., M. O. Baringer, and M. R. Johnson, 2010: State of the Climate in 2009. Bull. Amer. Meteor. Soc., 91, s1–s222, doi:10.1175/BAMS-91-7-StateoftheClimate.

    • Search Google Scholar
    • Export Citation

  • Benner, T. C., and J. A. Curry, 1998: Characteristics of small tropical cumulus clouds and their impact on the environment. J. Geophys. Res., 103, 28 753–28 767, doi:10.1029/98JD02579.

    • Search Google Scholar
    • Export Citation

  • Bréon, F. M., and N. Henriot, 2006: Spaceborne observations of ocean glint reflection and modeling of wave slope distributions. J. Geophys. Res., 111, C06005, doi:10.1029/2005JC003343.

    • Search Google Scholar
    • Export Citation

  • Cayla, F.-R., 1993: IASI infrared interferometer for operations and research. High Spectral Resolution Infrared Remote Sensing for Earth’s Weather and Climate Studies, A. Chedin, M. T. Chahine, and N. A. Scott, Eds., NATO ASI Series, Vol. 19, Springer-Verlag, 9–19.

  • Chahine, M. T., and Coauthors, 2006: AIRS: Improving weather forecasting and providing new data on greenhouse gases. Bull. Amer. Meteor. Soc., 87, 911–926, doi:10.1175/BAMS-87-7-911.

    • Search Google Scholar
    • Export Citation

  • Clough, S. A., M. W. Shephard, E. J. Mlawer, J. S. Delamere, M. J. Iacono, K. Cady-Pereira, S. Boukabara, and P. D. Brown, 2005: Atmospheric radiative transfer modeling: A summary of the AER codes. J. Quant. Spectrosc. Radiat. Transfer, 91, 233–244, doi:10.1016/j.jqsrt.2004.05.058.

    • Search Google Scholar
    • Export Citation

  • Cox, C., and W. Munk, 1955: Some problems in optical oceanography. J. Mar. Res., 14, 63–78.

  • Cox, C., 1974: Refraction and reflection of light at the sea surface. Optical Aspects of Oceanography, N. Jerlov and E. Nielsen, Eds., Academic Press, 51–75.

  • Goldberg, M. D., H. Kilcoyne, H. Cikanek, and A. Mehta, 2013: Joint Polar Satellite System: The United States next generation civilian polar-orbiting environmental satellite system. J. Geophys. Res. Atmos., 118, 13 463–13 475, doi:10.1002/2013JD020389.

    • Search Google Scholar
    • Export Citation

  • Goody, R. M., and Y. L. Yung, 1989: Atmospheric Radiation: Theoretical Basis. 2nd ed. Oxford University Press, 519 pp.

  • Hilton, F., and Coauthors, 2012: Hyperspectral Earth observation from IASI: Five years of accomplishments. Bull. Amer. Meteor. Soc., 93, 347–370, doi:10.1175/BAMS-D-11-00027.1.

    • Search Google Scholar
    • Export Citation

  • Inman, R. L., 1969: Computation of temperature at the lifted condensation level. J. Appl. Meteor., 8, 155–158, doi:10.1175/1520-0450(1969)008<0155:COTATL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Jackson, C. R., and W. Alpers, 2010: The role of the critical angle in brightness reversals on sunglint images of the sea surface. J. Geophys. Res., 115, C09019, doi:10.1029/2009JC006037.

    • Search Google Scholar
    • Export Citation

  • Kauth, R. J., and J. L. Penquite, 1967: The probability of clear lines of sight through a cloudy atmosphere. J. Appl. Meteor., 6, 1005–1017, doi:10.1175/1520-0450(1967)006<1005:TPOCLO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kay, S., J. D. Hedley, and S. Lavender, 2009: Sun glint correction of high and low spatial resolution images of aquatic scenes: A review of methods for visible and near-infrared wavelengths. Remote Sens., 1, 697–730, doi:10.3390/rs1040697.

    • Search Google Scholar
    • Export Citation

  • Knapp, K. R., T. H. Vonder Haar, and Y. J. Kaufman, 2002: Aerosol optical depth retrieval from GOES-8: Uncertainty study and retrieval validation over South America. J. Geophys. Res., 107, doi:10.1029/2001JD000505.

    • Search Google Scholar
    • Export Citation

  • Larar, A. M., W. L. Smith, D. K. Zhou, X. Liu, H. Revercomb, J. P. Taylor, S. M. Newman, and P. Schlüssel, 2010: IASI spectral radiance validation inter-comparisons: Case study assessment from the JAIVEx field campaign. Atmos. Chem. Phys., 10, 411–430, doi:10.5194/acp-10-411-2010.

    • Search Google Scholar
    • Export Citation

  • Lawrence, M. G., 2005: The relationship between relative humidity and the dewpoint temperature in moist air: A simple conversion and applications. Bull. Amer. Meteor. Soc., 86, 225–233, doi:10.1175/BAMS-86-2-225.

    • Search Google Scholar
    • Export Citation

  • Liu, Q., and S. Boukabara, 2014: Community Radiative Transfer Model (CRTM) applications in supporting the Suomi National Polar-orbiting Partnership (SNPP) mission validation and verification. Remote Sens. Environ., 140, 744–754, doi:10.1016/j.rse.2013.10.011.

    • Search Google Scholar
    • Export Citation

  • Lund, I. A., and M. D. Shanklin, 1972: Photogrammetrically determined cloud-free lines-of-sight through the atmosphere. J. Appl. Meteor., 11, 773–782, doi:10.1175/1520-0450(1972)011<0773:PDCFLO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Lund, I. A., and M. D. Shanklin, 1973: Universal methods for estimating probabilities of cloud-free lines-of-sight through the atmosphere. J. Appl. Meteor., 12, 28–35, doi:10.1175/1520-0450(1973)012<0028:UMFEPO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Maddy, E. S., and Coauthors, 2011: Using MetOp-A AVHRR clear-sky measurements to cloud-clear MetOp-A IASI column radiances. J. Atmos. Oceanic Technol., 28, 1104–1116, doi:10.1175/JTECH-D-10-05045.1.

    • Search Google Scholar
    • Export Citation

  • Mandel, J., 1984: The Statistical Analysis of Experimental Data. Dover Books on Mathematics, Dover Publications, 432 pp.

  • Martin, S., 2004: An Introduction to Ocean Remote Sensing. 1st ed. Cambridge University Press, 426 pp.

  • Masuda, K., 2006: Infrared sea surface emissivity including multiple reflection effect for isotropic Gaussian slope distribution model. Remote Sens. Environ., 103, 488–496, doi:10.1016/j.rse.2006.04.011.

    • Search Google Scholar
    • Export Citation

  • Merchant, C. J., A. R. Harris, E. Maturi, O. Embury, S. N. MacCallum, J. Mittaz, and C. P. Old, 2009: Sea surface temperature estimation from the Geostationary Operational Environmental Satellite-12 (GOES-12). J. Atmos. Oceanic Technol., 26, 570–581, doi:10.1175/2008JTECHO596.1.

    • Search Google Scholar
    • Export Citation

  • Nalli, N. R., and L. L. Stowe, 2002: Aerosol correction for remotely sensed sea surface temperatures from the National Oceanic and Atmospheric Administration advanced very high resolution radiometer. J. Geophys. Res., 107, 3172, doi:10.1029/2001JC001162.

    • Search Google Scholar
    • Export Citation

  • Nalli, N. R., and W. L. Smith, 2003: Retrieval of ocean and lake surface temperatures from hyperspectral radiance observations. J. Atmos. Oceanic Technol., 20, 1810–1825, doi:10.1175/1520-0426(2003)020<1810:ROOALS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Nalli, N. R., W. L. Smith, and B. Huang, 2001: Quasi-specular model for calculating the reflection of atmospheric emitted infrared radiation from a rough water surface. Appl. Opt., 40, 1343–1353, doi:10.1364/AO.40.001343.

    • Search Google Scholar
    • Export Citation

  • Nalli, N. R., and Coauthors, 2006: Ship-based measurements for infrared sensor validation during Aerosol and Ocean Science Expedition 2004. J. Geophys. Res., 111, D09S04, doi:10.1029/2005JD006385.

    • Search Google Scholar
    • Export Citation

  • Nalli, N. R., P. J. Minnett, E. Maddy, W. W. McMillan, and M. D. Goldberg, 2008a: Emissivity and reflection model for calculating unpolarized isotropic water surface leaving radiance in the infrared. 2: Validation using Fourier transform spectrometers. Appl. Opt., 47, 4649–4671, doi:10.1364/AO.47.004649.

    • Search Google Scholar
    • Export Citation

  • Nalli, N. R., P. J. Minnett, and P. van Delst, 2008b: Emissivity and reflection model for calculating unpolarized isotropic water surface leaving radiance in the infrared. 1: Theoretical development and calculations. Appl. Opt., 47, 3701–3721, doi:10.1364/AO.47.003701.

    • Search Google Scholar
    • Export Citation

  • Nalli, N. R., C. D. Barnet, E. S. Maddy, and A. Gambacorta, 2012: On the angular effect of residual clouds and aerosols in clear-sky infrared window radiance observations: Sensitivity analyses. J. Geophys. Res., 117, D12208, doi:10.1029/2012JD017667.

    • Search Google Scholar
    • Export Citation

  • Nalli, N. R., C. D. Barnet, A. Gambacorta, E. S. Maddy, H. Xie, T. S. King, E. Joseph, and V. R. Morris, 2013a: On the angular effect of residual clouds and aerosols in clear-sky infrared window radiance observations 2. Satellite experimental analyses. J. Geophys. Res. Atmos., 118, 1420–1435, doi:10.1029/2012JD018260.

    • Search Google Scholar
    • Export Citation

  • Nalli, N. R., and Coauthors, 2013b: Validation of satellite sounder environmental data records: Application to the Cross-track Infrared Microwave Sounder Suite. J. Geophys. Res. Atmos., 118, 13 628–13 643, doi:10.1002/2013JD020436.

    • Search Google Scholar
    • Export Citation

  • Newman, S. M., and Coauthors, 2012: The Joint Airborne IASI Validation Experiment: An evaluation of instrument and algorithms. J. Quant. Spectrosc. Radiat. Transfer, 113, 1372–1390, doi:10.1016/j.jqsrt.2012.02.030.

    • Search Google Scholar
    • Export Citation

  • NOAA/NESDIS, 2003: GOES level 3 6km near real time SST 1 hour. PO.DAAC, accessed 3 December 2010, doi:10.5067/GOES3-1HOUR.

  • Prados, A. I., S. Kondragunta, P. Ciren, and K. R. Knapp, 2007: GOES Aerosol/Smoke Product (GASP) over North America: Comparisons to AERONET and MODIS observations. J. Geophys. Res., 112, D15201, doi:10.1029/2006JD007968.

    • Search Google Scholar
    • Export Citation

  • Remote Sensing Systems, 2008: GHRSST level 4 mw_ir_OI global foundation sea surface temperature analysis. PO.DAAC, accessed 13 April 2011, doi:10.5067/GHMWI-4FR01.

  • Smith, W. L., Sr., D. K. Zhou, A. M. Larar, S. A. Mango, H. B. Howell, R. O. Knuteson, H. E. Revercomb, and W. L. Smith Jr., 2005: The NPOESS Airborne Sounding Testbed Interferometer—Remotely sensed surface and atmospheric conditions during CLAMS. J. Atmos. Sci., 62, 1118–1134, doi:10.1175/JAS3384.1.

    • Search Google Scholar
    • Export Citation

  • Smith, W. L., Sr., and Coauthors, 2009: Technical note: Evolution, current capabilities, and future advance in satellite nadir viewing ultra-spectral IR sounding of the lower atmosphere. Atmos. Chem. Phys., 9, 5563–5574, doi:10.5194/acp-9-5563-2009.

    • Search Google Scholar
    • Export Citation

  • Sokolik, I. N., 2002: The spectral radiative signature of wind-blown mineral dust: Implications for remote sensing in the thermal IR region. Geophys. Res. Lett., 29, 2154, doi:10.1029/2002GL015910.

    • Search Google Scholar
    • Export Citation

  • Stephens, G. L., 1994: Remote Sensing of the Lower Atmosphere: An Introduction. Oxford University Press, 523 pp.

  • Stull, R. B., 1985: A fair-weather cumulus cloud classification scheme for mixed-layer studies. J. Climate Appl. Meteor., 24, 49–56, doi:10.1175/1520-0450(1985)024<0049:AFWCCC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. Kluwer Academic Publishers, 666 pp.

  • Sun, B., A. Reale, D. J. Seidel, and D. C. Hunt, 2010: Comparing radiosonde and cosmic atmospheric profile data to quantify differences among radiosonde types and the effects of imperfect collocation on comparison statistics. J. Geophys. Res., 115, D23104, doi:10.1029/2010JD014457.

    • Search Google Scholar
    • Export Citation

  • Susskind, J., C. D. Barnet, and J. M. Blaisdell, 2003: Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB data in the presence of clouds. IEEE Trans. Geosci. Remote Sens., 41, 390–409, doi:10.1109/TGRS.2002.808236.

    • Search Google Scholar
    • Export Citation

  • Taylor, P. C., and R. G. Ellingson, 2008: A study of the probability of clear line of sight through single-layer cumulus cloud fields in the tropical western Pacific. J. Atmos. Sci., 65, 3497–3512, doi:10.1175/2008JAS2620.1.

    • Search Google Scholar
    • Export Citation

  • Thomas, G. E., and K. Stamnes, 1999: Radiative Transfer in the Atmosphere and Ocean. Cambridge Atmospheric and Space Science, Cambridge University Press, 517 pp.

  • Thomas, S. M., A. K. Heidinger, and M. J. Pavolonis, 2004: Comparison of NOAA’s operational AVHRR-derived cloud amount to other satellite-derived cloud climatologies. J. Climate, 17, 4805–4822, doi:10.1175/JCLI-3242.1.

    • Search Google Scholar
    • Export Citation

  • Weng, F., X. Zou, X. Wang, S. Yang, and M. D. Goldberg, 2012: Introduction to Suomi national polar-orbiting partnership advanced technology microwave sounder for numerical weather prediction and tropical cyclone applications. J. Geophys. Res., 117, D19112, doi:10.1029/2012JD018144.

    • Search Google Scholar
    • Export Citation

  • WMO, 1956: International cloud Atlas: Abridged Atlas. World Meteorological Organization, 62 pp.

  • WMO, 1987: International Cloud Atlas. Vol. II. World Meteorological Organization WMO-407, 212 pp. [Available online at http://library.wmo.int/pmb_ged/wmo_407_en-v2.pdf.]

  • Wong, S., E. J. Fetzer, M. Schreier, G. Manipon, E. F. Fishbein, B. H. Kahn, Q. Yue, and F. W. Irion, 2015: Cloud-induced uncertainties in AIRS and ECMWF temperature and specific humidity. J. Geophys. Res. Atmos., 120, 1880–1901, doi:10.1002/2014JD022440.

    • Search Google Scholar
    • Export Citation

  • Wu, X., and W. L. Smith, 1997: Emissivity of rough sea surface for 8–13μm: Modeling and validation. Appl. Opt., 36, 2609–2619, doi:10.1364/AO.36.002609.

    • Search Google Scholar
    • Export Citation

  • Yao, Z., J. Li, and J. Li, 2012: Sunglint impact on atmospheric soundings from hyperspectral resolution infrared radiances. Adv. Atmos. Sci., 29, 455–463, doi:10.1007/s00376-011-1013-8.

    • Search Google Scholar
    • Export Citation

  • Závody, A. M., and A. R. Birks, 2004: Sun glint contamination in ATSR-2 data: Comparison of observations and values calculated from the measured 1.6-μm reflectivities. J. Atmos. Oceanic Technol., 21, 787–798, doi:10.1175/1520-0426(2004)021<0787:SGCIAD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Zhang, H., and M. Wang, 2010: Evaluation of sun glint models using MODIS measurements. J. Quant. Spectrosc. Radiat. Transfer, 111, 492–506, doi:10.1016/j.jqsrt.2009.10.001.

    • Search Google Scholar
    • Export Citation

  • Zhao, T. X.-P., P. K. Chan, and A. K. Heidinger, 2013: A global survey of the effect of cloud contamination on the aerosol optical thickness and its long-term trend derived from operational AVHRR satellite observations. J. Geophys. Res. Atmos., 118, 2849–2857, doi:10.1002/jgrd.50278.

    • Search Google Scholar
    • Export Citation
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