• Augustine, J. A., J. J. DeLuisi, and C. N. Long, 2000: SURFRAD – A national surface radiation budget network for atmospheric research. Bull. Amer. Meteor. Soc., 81 , 23412357.

    • Search Google Scholar
    • Export Citation
  • Barkstrom, B. R., E. F. Harrison, G. L. Smith, R. N. Green, J. F. Kibler, and R. D. Cess, and ERBE Science Team, 1989: Earth Radiation Budget Experiment archival and April 1985 results. Bull. Amer. Meteor. Soc., 70 , 12541262.

    • Search Google Scholar
    • Export Citation
  • Bloom, S., A. da Silva, and D. Dee, 2005: Documentation and validation of the Goddard Earth Observing System (GEOS) Data Assimilation System — version 4. NASA Tech. Rep. Series on Global Modeling and Data Assimilation, NASA/TM-2005-104606, 26 pp.

    • Search Google Scholar
    • Export Citation
  • Cess, R. D., and S. N. Tiwari, 1972: Infrared radiative energy transfer in gases. Advances in Heat Transfer, Vol. 8, J. P. Hartnett and T. F. Irvine Jr., Eds., Academic Press, 229–282.

    • Search Google Scholar
    • Export Citation
  • Charlock, T. P., and Coauthors, 1997: Compute surface and atmospheric fluxes (System 5.0). CERES Algorithm Theoretical Basis Doc. (ATBD Release 2.2), NASA/RP-1376, 84 pp.

    • Search Google Scholar
    • Export Citation
  • Charlock, T. P., F. G. Rose, D. A. Rutan, Z. Jin, and S. Kato, 2006: The global surface and atmospheric radiation budget: An assessment of accuracy with 5 years of calculations and observations. Proc. 12th Conf. on Atmospheric Radiation, Madison, WI, Amer. Meteor. Soc., 10.5. [Available online at http://ams.confex.com/ams/pdfpapers/112984.pdf].

    • Search Google Scholar
    • Export Citation
  • Collins, W. D., P. J. Rasch, B. E. Eaton, B. V. Khattatov, J-F. Lamarque, and C. S. Zender, 2001: Simulating aerosols using a chemical transport model with assimilation of satellite aerosol retrievals: Methodology for INDOEX. J. Geophys. Res., 106 , 73137336.

    • Search Google Scholar
    • Export Citation
  • Darnell, W. L., W. F. Staylor, S. K. Gupta, and F. M. Denn, 1988: Estimation of surface insolation using Sun-synchronous satellite data. J. Climate, 1 , 820835.

    • Search Google Scholar
    • Export Citation
  • Darnell, W. L., W. F. Staylor, S. K. Gupta, N. A. Ritchey, and A. C. Wilber, 1992: Seasonal variation of surface radiation budget derived from ISCCP-C1 data. J. Geophys. Res., 97 , 1574115760.

    • Search Google Scholar
    • Export Citation
  • Ellingson, R. G., J. S. Ellis, and S. B. Fels, 1991: The intercomparison of radiation codes used in climate models: Longwave results. J. Geophys. Res., 96 , 89298953.

    • Search Google Scholar
    • Export Citation
  • Gautier, C., and M. Landsfeld, 1997: Surface solar radiation flux and cloud radiative forcing for the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP): A satellite, surface observations, and radiative transfer model study. J. Atmos. Sci., 54 , 12891307.

    • Search Google Scholar
    • Export Citation
  • Gupta, S. K., 1989: A parameterization for longwave surface radiation from Sun-synchronous satellite data. J. Climate, 2 , 305320.

  • Gupta, S. K., W. L. Darnell, and A. C. Wilber, 1992: A parameterization for longwave surface radiation from satellite data: Recent improvements. J. Appl. Meteor., 31 , 13611367.

    • Search Google Scholar
    • Export Citation
  • Gupta, S. K., A. C. Wilber, N. A. Ritchey, F. G. Rose, T. L. Alberta, T. P. Charlock, and L. H. Coleman, 1997: Regrid humidity and temperature fields (System 12.0). CERES Algorithm Theoretical Basis Doc. (ATBD Release 2.2), NASA/RP-1376, 20 pp.

    • Search Google Scholar
    • Export Citation
  • Gupta, S. K., D. P. Kratz, P. W. Stackhouse Jr., and A. C. Wilber, 2001: The Langley Parameterized Shortwave Algorithm (LPSA) for surface radiation budget studies (version 1.0). NASA/TP-2001-211272, 31 pp.

    • Search Google Scholar
    • Export Citation
  • Gupta, S. K., D. P. Kratz, A. C. Wilber, and L. C. Nguyen, 2004: Validation of parameterized algorithms used to derive TRMM-CERES surface radiative fluxes. J. Atmos. Oceanic Technol., 21 , 742752.

    • Search Google Scholar
    • Export Citation
  • Haywood, J. M., V. Ramaswamy, and B. J. Soden, 1999: Tropospheric aerosol climate forcing in clear-sky satellite observations over the oceans. Science, 283 , 12991303.

    • Search Google Scholar
    • Export Citation
  • Inamdar, A. K., and V. Ramanathan, 1997: On monitoring the atmospheric greenhouse effect from space. Tellus, 49B , 216230.

  • Jin, Z., T. P. Charlock, and C. K. Rutledge, 2002: Analysis of the broadband solar radiation and albedo over the ocean surface at COVE. J. Atmos. Oceanic Technol., 19 , 15851601.

    • Search Google Scholar
    • Export Citation
  • Li, Z., and L. Garand, 1994: Estimation of surface albedo from space: A parameterization for global application. J. Geophys. Res., 99 , 83358350.

    • Search Google Scholar
    • Export Citation
  • Li, Z., H. G. Leighton, and R. D. Cess, 1993a: Surface net solar radiation estimated from satellite measurements: Comparisons with tower observations. J. Climate, 6 , 17641772.

    • Search Google Scholar
    • Export Citation
  • Li, Z., H. G. Leighton, K. Masuda, and T. Takashima, 1993b: Estimation of SW flux absorbed at the surface from TOA reflected flux. J. Climate, 6 , 317330.

    • Search Google Scholar
    • Export Citation
  • Loeb, N. G., S. Kato, K. Loukachine, and N. Manalo-Smith, 2005: Angular distribution models for top-of-atmosphere radiative flux estimation from the Clouds and the Earth’s Radiant Energy System instrument on the Terra satellite. Part I: Methodology. J. Atmos. Oceanic Technol., 22 , 338351.

    • Search Google Scholar
    • Export Citation
  • Loeb, N. G., S. Kato, K. Loukachine, N. Manalo-Smith, and D. R. Doelling, 2007: Angular distribution models for top-of-atmosphere radiative flux estimation from the Clouds and the Earth’s Radiant Energy System instrument on the Terra satellite. Part II: Validation. J. Atmos. Oceanic Technol., 24 , 564584.

    • Search Google Scholar
    • Export Citation
  • Masuda, K., H. G. Leighton, and Z. Li, 1995: A new parameterization for the determination of solar flux absorbed at the surface from satellite measurements. J. Climate, 8 , 16151629.

    • Search Google Scholar
    • Export Citation
  • Michalsky, J., E. Dutton, M. Rubes, D. Nelson, T. Stoffel, M. Wesley, M. Splitt, and J. DeLuisi, 1999: Optimal measurement of surface shortwave irradiance using current instrumentation. J. Atmos. Oceanic Technol., 16 , 5569.

    • Search Google Scholar
    • Export Citation
  • Minnis, P., and Coauthors, 1997: Cloud optical property retrieval (System 4.3). CERES Algorithm Theoretical Basis Doc. (ATBD Release 2.2), NASA/RP-1376, 60 pp.

    • Search Google Scholar
    • Export Citation
  • Minnis, P., and Coauthors, 2008: Cloud detection in nonpolar regions for CERES using TRMM VIRS and Terra and Aqua MODIS data. IEEE Trans. Geosci. Remote Sens., 46 , 38573884.

    • Search Google Scholar
    • Export Citation
  • Moser, W., and E. Raschke, 1984: Incident solar radiation over Europe estimated from METEOSAT data. J. Climate Appl. Meteor., 23 , 166170.

    • Search Google Scholar
    • Export Citation
  • Ohmura, A., and Coauthors, 1998: Baseline Surface Radiation Network (BSRN/WCRP): New precision radiometry for climate change research. Bull. Amer. Meteor. Soc., 79 , 21152136.

    • Search Google Scholar
    • Export Citation
  • Peixoto, J. P., and A. H. Oort, 1993: Physics of Climate. American Institute of Physics, 520 pp.

  • Philipona, R., 2002: Underestimation of solar global and diffuse radiation measured at Earth’s surface. J. Geophys. Res., 107 , 4654. doi:10.1029/2002JD002396.

    • Search Google Scholar
    • Export Citation
  • Rossow, W. B., and Y-C. Zhang, 1995: Calculation of surface and top of atmosphere radiative fluxes from physical quantities based on ISCCP data sets 2. Validation and first results. J. Geophys. Res., 100 , 11671197.

    • Search Google Scholar
    • Export Citation
  • Rossow, W. B., and R. A. Schiffer, 1999: Advances in understanding clouds from ISCCP. Bull. Amer. Meteor. Soc., 80 , 22612287.

  • Rutan, D. A., F. G. Rose, N. M. Smith, and T. P. Charlock, 2001: Validation data set for CERES surface and atmospheric radiation budget (SARB). WCRP/GEWEX News, No. 1, International GEWEX Project Office, Silver Spring, MD, 11–12.

    • Search Google Scholar
    • Export Citation
  • Salomonson, V. V., W. L. Barnes, P. W. Maymon, H. E. Montgomery, and H. Ostrow, 1989: MODIS – Advanced facility instrument for studies of the Earth as a system. IEEE Trans. Geosci. Remote Sens., 27 , 145153.

    • Search Google Scholar
    • Export Citation
  • Stokes, G. M., and S. E. Schwartz, 1994: The Atmospheric Radiation Measurement (ARM) program: Programmatic background and design of the cloud and radiation testbed. Bull. Amer. Meteor. Soc., 75 , 12011221.

    • Search Google Scholar
    • Export Citation
  • Suttles, J. T., and G. Ohring, 1986: Surface radiation budget for climate applications. NASA Reference Publication 1169, Washington, DC, 132 pp.

    • Search Google Scholar
    • Export Citation
  • Wielicki, B. A., B. R. Barkstrom, E. F. Harrison, R. B. Lee III, G. L. Smith, and J. E. Cooper, 1996: Clouds and the Earth’s Radiant Energy System (CERES): An Earth Observing System experiment. Bull. Amer. Meteor. Soc., 77 , 853868.

    • Search Google Scholar
    • Export Citation
  • Wilber, A. C., D. P. Kratz, and S. K. Gupta, 1999: Surface emissivity maps for use in satellite retrievals of longwave radiation. NASA/TP-1999-209362, 35 pp.

    • Search Google Scholar
    • Export Citation
  • Yang, S. K., S. Zhou, and A. J. Miller, 1997: SMOBA: A 3-dimensional daily ozone analysis using SBUV/2 and TOVS measurements. NOAA rep. [Available online at http://www.cpc.noaa.gov/products/stratosphere/SMOBA/smoba_doc.shtml].

    • Search Google Scholar
    • Export Citation
  • Young, D. F., P. Minnis, D. R. Doelling, G. G. Gibson, and T. Wong, 1998: Temporal interpolation methods for the Clouds and the Earth’s Radiant Energy System (CERES) experiment. J. Appl. Meteor., 37 , 572590.

    • Search Google Scholar
    • Export Citation
  • Zelenka, A., R. Perez, R. Seals, and D. Renne, 1999: Effective accuracy of satellite-derived hourly irradiances. Theor. Appl. Climatol., 62 , 199207.

    • Search Google Scholar
    • Export Citation
  • Zhou, Y., D. P. Kratz, A. C. Wilber, S. K. Gupta, and R. D. Cess, 2007: An improved algorithm for retrieving surface downwelling longwave radiation from satellite measurements. J. Geophys. Res., 112 , D15102. doi:10.1029/2006JD008159.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 794 614 0
PDF Downloads 193 65 0

Validation of the CERES Edition 2B Surface-Only Flux Algorithms

View More View Less
  • 1 Science Directorate, NASA Langley Research Center, Hampton, Virginia
  • | 2 Science Systems Applications, Inc., Hampton, Virginia
Restricted access

Abstract

The Clouds and the Earth’s Radiant Energy System (CERES) project uses two shortwave (SW) and two longwave (LW) algorithms to derive surface radiative fluxes on an instantaneous footprint basis from a combination of top-of-atmosphere fluxes, ancillary meteorological data, and retrieved cloud properties. Since the CERES project examines the radiative forcings and feedbacks for Earth’s entire climate system, validation of these models for a wide variety of surface conditions is paramount. The present validation effort focuses upon the ability of these surface-only flux algorithms to produce accurate CERES Edition 2B single scanner footprint data from the Terra and Aqua spacecraft measurements. To facilitate the validation process, high-quality radiometric surface observations have been acquired that were coincident with the CERES-derived surface fluxes. For both SW models, systematic errors range from −20 to −12 W m−2 (from −2.8% to −1.6%) for global clear-sky cases, while for the all-sky SW model, the systematic errors range from 14 to 21 W m−2 (3.2%–4.8%) for global cloudy-sky cases. Larger systematic errors were seen for the individual surface types, and significant random errors where observed, especially for cloudy-sky cases. While the SW models nearly achieved the 20 W m−2 accuracy requirements established for climate research, further improvements are warranted. For the clear-sky LW model, systematic errors were observed to fall within ±5.4 W m−2 (±1.9%) except for the polar case in which systematic errors on the order from −15 to −11 W m−2 (from −13% to −7.2%) occurred. For the all-sky LW model, systematic errors were less than ±9.2 W m−2 (±7.6%) for both the clear-sky and cloudy-sky cases. The random errors were less than 17 W m−2 (6.2%) for clear-sky cases and 28 W m−2 (13%) for cloudy-sky cases, except for the desert cases in which very high surface skin temperatures caused an overestimation in the model-calculated surface fluxes. Overall, however, the LW models met the accuracy requirements for climate research.

Corresponding author address: Dr. David P. Kratz, NASA Langley Research Center, Mail Stop 420, Hampton, VA 23681-2199. Email: david.p.kratz@nasa.gov

Abstract

The Clouds and the Earth’s Radiant Energy System (CERES) project uses two shortwave (SW) and two longwave (LW) algorithms to derive surface radiative fluxes on an instantaneous footprint basis from a combination of top-of-atmosphere fluxes, ancillary meteorological data, and retrieved cloud properties. Since the CERES project examines the radiative forcings and feedbacks for Earth’s entire climate system, validation of these models for a wide variety of surface conditions is paramount. The present validation effort focuses upon the ability of these surface-only flux algorithms to produce accurate CERES Edition 2B single scanner footprint data from the Terra and Aqua spacecraft measurements. To facilitate the validation process, high-quality radiometric surface observations have been acquired that were coincident with the CERES-derived surface fluxes. For both SW models, systematic errors range from −20 to −12 W m−2 (from −2.8% to −1.6%) for global clear-sky cases, while for the all-sky SW model, the systematic errors range from 14 to 21 W m−2 (3.2%–4.8%) for global cloudy-sky cases. Larger systematic errors were seen for the individual surface types, and significant random errors where observed, especially for cloudy-sky cases. While the SW models nearly achieved the 20 W m−2 accuracy requirements established for climate research, further improvements are warranted. For the clear-sky LW model, systematic errors were observed to fall within ±5.4 W m−2 (±1.9%) except for the polar case in which systematic errors on the order from −15 to −11 W m−2 (from −13% to −7.2%) occurred. For the all-sky LW model, systematic errors were less than ±9.2 W m−2 (±7.6%) for both the clear-sky and cloudy-sky cases. The random errors were less than 17 W m−2 (6.2%) for clear-sky cases and 28 W m−2 (13%) for cloudy-sky cases, except for the desert cases in which very high surface skin temperatures caused an overestimation in the model-calculated surface fluxes. Overall, however, the LW models met the accuracy requirements for climate research.

Corresponding author address: Dr. David P. Kratz, NASA Langley Research Center, Mail Stop 420, Hampton, VA 23681-2199. Email: david.p.kratz@nasa.gov

Save