Mapping High-Resolution Land Surface Radiative Fluxes from MODIS: Algorithms and Preliminary Validation Results

  • Shunlin Liang
  • Kaicun Wang
  • Wenhui Wang
  • Dongdong Wang
  • Sheng Gui
  • Xiaotong Zhang
  • Jeremy Mirmelstein
  • Xiufang Zhu
  • Hye-yun Kim
  • Juan Du
  • Steven Running
  • John Townshend
  • Si-Chee Tsay
  • Robert Wolf
  • Crystal Schaaf
  • Alan Strahler


Land surface radiative fluxes are needed to address a variety of scientific and application issues related to climate changes, hydrologic and biogeophysical modeling, solar energy applications, and agriculture. The Earth's surface radiation budget (SRB) is the key quantity that determines global climate and climate change from elevated greenhouse gases, air pollution (Wang K. et al. 2009), and land cover and land use changes (Wang et al. 2007b). The SRB is also important to life and to the use of clean renewable solar energy to improve the quality of the environment.

Altering surface radiation force will lead to a significant adjustment in surface temperature, moisture, and fluxes during the consequent complex land surface thermodynamic and hydrological processes. It affects the surface heat and moisture budget as well as biological productivity. The observed reduction in land surface radiation over the last several decades (1960–1990), the so-called “dimming effect,” and the more recent evidence of a reversal in “dimming” over some locations beyond 1990 suggest several consequences on climate, notably on the hydrological cycle (Liepert and Romanou 2005, Wild et al. 2005, 2007). Such a reduction in radiation should imply reduced surface temperature and precipitation. Overestimation of the incoming solar radiation over land has major impacts on the climate over land (Betts et al. 1996, Dickinson 1995, Garratt et al. 1993). Viterbo and Beljaars (1995) found that excessive net radiation at the surface forced excessive surface evaporation, and dried out the soil moisture during data assimilation in the ECMWF (European Centre for Medium-Range Weather Forecasts) global model.


Photosynthetically Active Radiation Land Surface Temperature Longwave Radiation Enhance Vegetation Index Downward Longwave Radiation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Annear, R. L., and S. A. Wells (2007), A comparison of five models for estimating clear-sky solar radiation, Water Resource Research, 43, W10415, doi:10.1029/2006WR005055.CrossRefGoogle Scholar
  2. ASTER. (1999),  [visited Nov. 30, 2005].
  3. Berg, A.A., J.S. Famiglietti, M. Rodell, R.H. Reichle, U. Jambor, S.L. Holl and P.R. Houser (2005), Development of a hydrometeorological forcing data set for global soil moisture estimation, International Journal of Climatology, 25(13): 1697-1714.CrossRefGoogle Scholar
  4. Berk, A., Bernstein, L. S.,  Anderson, G. P.,  Acharya, P. K., Robertson, D. C., Chetwynd, J. H.,  & Adler-Golden, S. M. (1998), MODTRAN cloud and multiple scattering upgrades with application to AVIRIS, Remote Sensing of Environment, 65, 367– 375.CrossRefGoogle Scholar
  5. Betts, A.K., Ball, J.H., Beljaars, A.C.M., Miller, M.J. and Viterbo, P.A., (1996). The land surface-atmosphere interaction: A review based on observational and global modeling perspectives. Journal of Geophysical Research, 101(D3): 7209-7225.CrossRefGoogle Scholar
  6. Bisht, G., V. Venturini, S. Islama, L. Jiang (2005), Estimation of the net radiation using MODIS (Moderate Resolution Imaging Spectroradiometer) data for clear sky days, Remote Sensing of Environment, 97, 52 – 67.CrossRefGoogle Scholar
  7. Carder, K., Hawes, S. and Chen, R. (1999), Instantaneous photosynthetically available radiation and absorbed radiation by phytoplankton, Version 5. ATBD-MOD-20.Google Scholar
  8. Chandrasekhar, S. (1960), Radiative Transfer, Dover, Mineola, N. Y.Google Scholar
  9. Charlock, T., (2006), CAVE: Clouds & Radiative Swath (CRS) Footprint Validation, NOAA. Available:
  10. Charlson, R. J., F. P. J.Valero, J. H. Seinfeld (2005), In search of balance. Science, 308, 806-807.CrossRefGoogle Scholar
  11. Cleugh, H. A., Leuning, R., Mu, Q., & Running, S. W. (2007), Regional evaporation estimates from flux tower and MODIS satellite data. Remote Sensing of Environment, 106, 285−304.CrossRefGoogle Scholar
  12. Coll, C., E. Valor, R. Niclòs, J. M. Sánchez, R. Rivas, V. Caselles, and J. M. Galve (2005), Ground measurements for the validation of land surface temperatures derived from AATSR and MODIS data, Remote Sensing of Environment, 97, 288-300.CrossRefGoogle Scholar
  13. Dai, Y. et al., (2003), The Common Land Model (CLM), Bulletin of American Meteorological Society, 84(8), 1013.CrossRefGoogle Scholar
  14. Darnell, W.L., Gupta, S.K. and Staylor, W.F. (1986), Downward longwave surface radiation from sun-synchronous satellite data: Validation of methodology. Journal Climate and Applied Meteorology, 25, 1012-1021.CrossRefGoogle Scholar
  15. Diak, G.R. et al. (2004), Estimating land surface energy budgets from space - Review and current efforts at the University of Wisconsin-Madison and USDA-ARS. Bulletin of the American Meteorological Society, 85(1), 65-75.CrossRefGoogle Scholar
  16. Dickinson, R.E. (1995). Land atmosphere interaction. Reviews of Geophysics, Suppl.: 917-922.Google Scholar
  17. Duchon, C. E., and O. Malley (1999), Estimating Cloud Type from Pyranometer Observations. Journal of Applied Meteorology, 38, 132-141.CrossRefGoogle Scholar
  18. Dye, D. (2004), Spectral composition and quanta-to-energy ratio of diffuse photosynthetically active radiation under diverse cloud conditions. Journal of Geophysical Research, 109, D10203, doi:10.1029/2003JD004251.CrossRefGoogle Scholar
  19. Eck, T. F., and D. G. Dye (1991), Satellite estimation of incident photosynthetically active radiation using ultraviolet reflectance, Remote Sensing of Environment, 38, 135– 146.CrossRefGoogle Scholar
  20. Ellingson, R.G. (1995), Surface longwave fluxes from satellite observations: A critical review, Remote Sensing of Environment, 51, 89-97.CrossRefGoogle Scholar
  21. Forsythe, W. C., Rykiel, E. J., Stahl, R. S., Wu, H.-i. and Schoolfield, R. M. (1995), A model comparison for daylength as a function of latitude and day of year. Ecological Modelling, 80, 87-95.CrossRefGoogle Scholar
  22. Francis, J., and J. Secora. (2004), A 22-year dataset of surface longwave fluxes in the Arctic. Fourteenth ARM Science Team Meeting Proceedings, March 22-26, at Albuquerque, NM.Google Scholar
  23. Frouin, R. & Pinker, R. T. (1995), Estimating photosynthetically active radiation (PAR) at the earth's surface from satellite observations. Remote Sensing of Environment, 51, 98-107.CrossRefGoogle Scholar
  24. Frouin, R., Lingner, D. W., Gautier, C., Baker, K. S., & Smith, R. C. (1989). A simple analytical formula to compute clear sky total and photosynthetically available solar irradiance at the ocean surface. Journal of Geophysical Research, 94(C7), 9731– 9742.CrossRefGoogle Scholar
  25. Frouin, R., Franz, B. and Wang, M., (2000). Algorithm to estimate PAR from SeaWiFS data, Version 1.0 - Documentation.Google Scholar
  26. Garratt, J.R., Krummel, P. and Kowalczyk, E.A. (1993), The surface energy balance at local and regional scales - A comparison of general circulation model results with observations. Journal of Climate, 6, 1090-1109.CrossRefGoogle Scholar
  27. Gu, L. et al., (2002). Advantages of diffuse radiation for terrestrial ecosystem productivity. Journal of Geophysical Research, 107(D6), 4050, doi:10.1029/2001JD001242.CrossRefGoogle Scholar
  28. Gu, L.H. et al. (2003), Response of a deciduous forest to the Mount Pinatubo eruption: Enhanced photosynthesis. Science, 299: 2035-2038.CrossRefGoogle Scholar
  29. Gu, J., Smith, E. A., Cooper, H. J.,  Grose, A.,  Liu, G.,  Merritt, J. D., Waterloo, M. J.,  de Araújo, A. C.,  Nobre, A. D.,  Manzi, A. O., Marengo, J., de Oliveira, P. J.,  von Randow, C.,  Norman, J., & Silva Dias, P. (2004), Modeling Carbon Sequestration over the Large-Scale Amazon Basin, Aided by Satellite Observations. Part I: Wet- and Dry-Season Surface Radiation Budget Flux and Precipitation Variability Based on GOES Retrievals. Journal of Applied Meteorology, 43(6), 870–886.CrossRefGoogle Scholar
  30. Gupta, S.K., Darnell, W.L. and Wilber, A.C. (1992), A parameterization for longwave surface radiation from satellite data: Recent improvements. Journal of Applied Meteorology, 31, 1361-1367.CrossRefGoogle Scholar
  31. Hicke, J.A. (2005), NCEP and GISS solar radiation data sets available for ecosystem modeling: Description, differences, and impacts on net primary production, Global Biogeochemical Cycles, 19, GB2006, doi:10.1029/2004GB002391.CrossRefGoogle Scholar
  32. Inamdar, A.K., and V. Ramanathan, Clouds and the Earth’s Radiant Energy System (CERES) algorithm theoretical basis document: estimation of longwave surface radiation budget from CERES (subsystem 4.6.2), 1997.Google Scholar
  33. Jin, M., S. Liang (2006), Improved emissivity parametrization for land surface modeling using global remote sensing observations, Journal of Climate,  19(12), 2867-2881.CrossRefGoogle Scholar
  34. Kaufman, Y. J., D. Tanre, L. Remer, E. F. Vermote, A. Chu, and B. N. Holben (1997a), Operational remote sensing of tropospheric aerosol over the land from EOS-MODIS., Journal of Geophysical Research, 102(D14), 17,051 –17,068.Google Scholar
  35. Kaufman, Y. J., A. Wald, L. A. Lorraine, B. C. Gao, R. R. Li, and L. Flynn (1997b), Remote sensing of aerosol over the continents with the aid of a 2.2 um channel, IEEE Transactions on Geoscience and Remote Sensing, 35, 1286– 1298.CrossRefGoogle Scholar
  36. Kim, H. Y., (2008), Estimation of Land Surface Shortwave Radiation Budget from MODIS Data, Ph.D dissertation, Department of Geography, University of MarylandGoogle Scholar
  37. Kjaersgaard, J. H., R. H. Cuenca, F. L. Plauborg, S. Hansen (2007), Long-term comparisons of net radiation calculation schemes. Boundary-Layer Meteorology, 123, 417–431.CrossRefGoogle Scholar
  38. Lee, H.T. and Ellingson, R.G. (2000), Development of a nonlinear statistical method for estimating the downward longwave radiation at the surface from satellite observations, Journal of Atmospheric and Oceanic Technology, 19(10), 1500- 1515.CrossRefGoogle Scholar
  39. Liang, S. (2004), Quantitative Remote Sensing of Land Surfaces, 534 pp., John Wiley, Hoboken, N. J.Google Scholar
  40. Liang, S., T. Zheng, R. Liu, H. Fang, S. C. Tsay, S. Running, (2006), Estimation of incident Photosynthetically Active Radiation from MODIS Data, Journal of Geophysical Research, 111, D15208,doi:10.1029/2005JD006730.CrossRefGoogle Scholar
  41. Liang, S. T. Zheng,  D. Wang, K. Wang, R. Liu,  S. C. Tsay, S. Running, J. Townshend, (2007),  Mapping High-Resolution Incident Photosynthetically Active Radiation over Land from Polar-Orbiting and Geostationary Satellite Data, Photogrammetric Engineering and Remote Sensing, 73(10), 1085-1089.Google Scholar
  42. Liepert, B.G. and Romanou, A. (2005), Global dimming and brightening and the water cycle. Bulletin of the American Meteorological Society, 86(5), 622-623.Google Scholar
  43. Liu, R., S. Liang, H. He, J. Liu, and T. Zheng (2008), Mapping Photosynthetically Active Radiation from MODIS Data in China. Remote Sensing of Environment, 112, 998-1009.CrossRefGoogle Scholar
  44. Meerkoetter, H. and H. Grassl (1984),Longwave net flux at the ground from radiance at the top, presented at IRS '84 current problems in atmospheric radiation; proceedings of the International Radiation Symposium, Perugia, Italy, 1984.Google Scholar
  45. Morcrette, J. J., and P. Y. Deschamps. (1986). Downward longwave radiation at the surface in clear sky atmospheres: comparison of measured, satellite-derived and calculated fluxes. Proc. ISLSCP Conf, at Rome, ESA SO-248M Darmstadt, Germany.Google Scholar
  46. Mu, Q., F. A. Heinsch, M. Zhao, S. W. Running (2007), Development of a global evapotranspiration algorithm based on MODIS and global meteorology data.  Remote Sensing of Environment, 111, 519-536.  CrossRefGoogle Scholar
  47. Pinker, R.T. and Laszlo, I. (1992), Modeling surface solar irradiance for satellite applications on a global scale, Journal of Applied Meteorology, 31: 194-211.CrossRefGoogle Scholar
  48. Pinker, R. T., et al. (2003), Surface radiation budgets in support of the GEWEX Continental-Scale International Project (GCIP) and the GEWEX Americas Prediction Project (GAPP), including the North American Land Data Assimilation System (NLDAS) project, Journal of Geophysical Research, 108(D22), 8844, doi:10.1029/2002JD003301.CrossRefGoogle Scholar
  49. Prince, S.D. and S.N. Goward (1995), Global primary production: a remote sensing approach, Journal of Biogeography, 22(4-5), 815-835.CrossRefGoogle Scholar
  50. Raschke, E., Bakan, S. and Kinne, S., 2006. An assessment of radiation budget data provided by the ISCCP and GEWEX-SRB. Geophysical Research Letters, 33, L07812, doi:10.1029/2005GL025503.CrossRefGoogle Scholar
  51. Remer, L.A. et al. (2005) The MODIS aerosol algorithm, products, and validation. Journal of the Atmospheric Sciences, 62(4), 947-973.CrossRefGoogle Scholar
  52. Remer, L. A., et al. (2008), Global aerosol climatology from the MODIS satellite sensors, Journal of Geophysical Research, 113, D14S07, doi:10.1029/2007JD009661.CrossRefGoogle Scholar
  53. Running, S.W., Nemani, R., Glassy, J.M. and Thornton, P. (1999), MODIS PSN (net photosynthesis) and NPP (net primary productivity) products, Version 3.0. MOD17 PSN/NPP Algorithm Technical Basis Document.Google Scholar
  54. Running, S., Nemani, R.R., Heinsch, F.A., Zhao, M., Reeves, M., & Hashimoto, H. (2004), A continuous satellite-derived measure of Global terrestrial primary production. Bioscience, 54, 547−560.CrossRefGoogle Scholar
  55. Salomonson, V., W. Barnes, P. Maymon, H. Montgomery, and H. Ostrow (1989), MODIS: advanced facility instrument for studies of the Earth as a system. IEEE Transactions on Geoscience and Remote Sensing, 27, 145–153.CrossRefGoogle Scholar
  56. Schaaf, C., Gao, F., Strahler, A., Lucht, W., Li, X., Tsung, T., Strugll, N., Zhang, X., Jin, Y., Muller, P., Lewis, P., Barnsley, M., Hobson, P., Disney, M., Roberts, G., Dunderdale, M., Doll, C., d'Entremont, R., Hu, B., Liang, S., Privette, J., & Roy, D. (2002). First operational BRDF, albedo nadir reflectance products from MODIS. Remote Sensing of Environment, 83, 135-148.CrossRefGoogle Scholar
  57. Schmetz, J., (1989), Towards a surface radiation climatology: retrieval of downward irradiances from satellites, Atmospheric Research, 23, 287-321.CrossRefGoogle Scholar
  58. Seemann, Suzanne W., Jun Li, W. Paul Menzel, and Liam E. Gumley (2003), Operational retrieval of atmospheric temperature, moisture, and ozone from MODIS infrared radiances, Journal of Applied Meteorology, 42(8), 1072-1091.CrossRefGoogle Scholar
  59. Sellers, P.J. et al. (1996), A revised land surface parameterization (SiB2) for Atmospheric GCMs. Part II: The generation of global fields of terrestrial biophysical parameters from satellite data. Journal of Climate, 9, 706-737.CrossRefGoogle Scholar
  60. Smith, W. L., and H. M. Wolfe (1983), Geostationary satellite sounder (VAS) observations of longwave radiation flux. The Satellite Systems to Measure Radiation Budget Parameters and Climate Change Signal, 29 Aug - 2 Sep, at Igls, Austria.Google Scholar
  61. Van Laake, P. E., & Sanchez-Azofeifa, G. A. (2004). Simplified atmospheric radiative transfer modelling for estimating incident PAR using MODIS atmosphere products. Remote Sensing Environment, 91, 98–113.CrossRefGoogle Scholar
  62. Van Laake, P. E., & Sanchez-Azofeifa, G. A. (2005). Mapping PAR using MODIS atmosphere products. Remote Sensing of Environment, 94(4), 554– 563.CrossRefGoogle Scholar
  63. Viterbo, P. and Beljaars, C. (1995), An improved land surface parametrization scheme in the ECMWF model and its validation, Journal of Climate, 8, 2716-2748.CrossRefGoogle Scholar
  64. Vermote, E. F., Tanré, N. Z., Deuzé, J. L., Herman, M., & Morcette, J. J. (1997), Second simulation of the satellite signal in the solar spectrum: An overview. IEEE Transactions on Geoscience and Remote Sensing, 35, 675-686.CrossRefGoogle Scholar
  65. Wan, Z. and J. Dozier. (1996), A generalized split-window algorithm for retrieving land-surface temperature from space. IEEE Transactions on Geoscience and Remote Sensing, 34(4), 892-905.CrossRefGoogle Scholar
  66. Wan, Z. (1999), MODIS land-surface temperature algorithm theoretical basis document (LST ATBD): version 3.3, University of California, Santa Barbara, Santa Barbara, CA, 1999.Google Scholar
  67. Wan, Z., Y.-L. Zhang, Q.-C. Zhang, and Z.-L. Li (2002), Validation of the land surface temperature products retrieved from terra moderate resolution imaging spectroradiometer data, Remote Sensing of Environment, 83, 163–180.CrossRefGoogle Scholar
  68. Wan, Z., Y. Zhang, Q. Zhang, and Z. L. Li, (2004), Quality assessment and validation of the MODIS global land surface temperature International Journal Remote Sensing, 25, 261-274.CrossRefGoogle Scholar
  69. Wan, Z. (2008), New refinements and validation of the MODIS land-surface temperature/emissivity products, Remote Sensing of Environment, 112, 59-74.CrossRefGoogle Scholar
  70. Wang, D., S. Liang and T. Zheng, (2009), Estimation of daily-integrated PAR from sparse satellite observations: comparison of temporal scaling methods, International Journal of Remote Sensing, in press.Google Scholar
  71. Wang, K., Z. Wan, P. Wang, M. Sparrow, J. Liu, X. Zhou, and S. Haginoya (2005), Estimation of surface long wave radiation and broadband emissivity using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature/emissivity products, Journal of Geophysical Research, 110, D11109, doi:10.1029/2004JD005566.CrossRefGoogle Scholar
  72. Wang, K., Z. Li, and M. Cribb (2006), Estimation of evaporative fraction from a combination of day and night land surface temperature and NDVI: A new method to determine the Priestley–Taylor parameter, Remote Sensing of Environment, 102, 293-305.CrossRefGoogle Scholar
  73. Wang, K., Z. Wan, P. Wang, M. Sparrow, J. Liu, and S. Haginoya (2007a), Evaluation and improvement of the MODIS land surface temperature/emissivity products using ground-based measurements at a semi-desert site on the western Tibetan Plateau. International Journal Remote Sensing, 28, 2549 - 2565.CrossRefGoogle Scholar
  74. Wang, K., J. Wang, P. Wang, M. Sparrow, J. Yang, and H. Chen, (2007b), Influences of urbanization on surface characteristics as derived from the Moderate-Resolution Imaging Spectroradiometer: A case study for the Beijing metropolitan area. Journal of Geophysical Research, 112, D22S06, doi:10.1029/2006JD007997.CrossRefGoogle Scholar
  75. Wang, K., P. Wang, Z. Li, M. Cribb, and M. Sparrow (2007c) A simple method to estimate actual evapotranspiration from a combination of net radiation, vegetation index, and temperature, Journal of Geophysical Research, 112, D15107, doi:10.1029/2006JD008351.CrossRefGoogle Scholar
  76. Wang, K., and S. Liang (2008), An improved method for estimating global evapotranspiration based on satellite determination of surface net radiation, vegetation index, temperature, and soil moisture, Journal of Hydrometeorology, 9, 712-727.CrossRefGoogle Scholar
  77. Wang, K., R. E. Dickinson, and S. Liang (2008), Observational evidence on the effects of clouds and aerosols on net ecosystem exchange and evapotranspiration,  Geophysical Research Letter, 35, L10401, doi:10.1029/2008GL034167.CrossRefGoogle Scholar
  78. Wang, K., R. E. Dickinson, S. Liang, (2009), Clear Sky Visibility Has Decreased over Land Globally from 1973 to 2007, Science, 323, 1468-1470.CrossRefGoogle Scholar
  79. Wang, K., S. Liang (2009a), Estimation of daytime net radiation from shortwave radiation measurements and meteorological observations, Journal of Applied Meteorology and Climatology, 48:634-643.CrossRefGoogle Scholar
  80. Wang, K. and S. Liang, (2009b), Evaluation of ASTER and MODIS land surface temperature and emissivity products using surface longwave radiation observations at SURFRAD sites, Remote Sensing of Environment, 113:1156-1165.Google Scholar
  81. Wang, K., S. Liang, T. Zheng and D. Wang (2009). Simultaneous estimation of surface photosynthetically active radiation and albedo from GOES, Remote Sensing of Environment, revised.Google Scholar
  82. Wang, W., S. Liang, and T. Meyer, (2008), Validating MODIS land surface temperature products, Remote Sensing of Environment, 112, 623-635CrossRefGoogle Scholar
  83. Wang, W., S. Liang, J. A. Augustine, (2009), Estimating clear-sky land surface upward longwave radiation from MODIS data, IEEE Transactions on Geoscience and Remote Sensing, 47(5):1555-1570, DOI: 10.1109/TGRS.2008.2005206.Google Scholar
  84. Wang, W. & S. Liang, (2009), Estimating High-Spatial Resolution Clear-Sky Land Surface Downwelling Longwave Radiation from MODIS Data, Remote Sensing of Environment, 113:745-754.CrossRefGoogle Scholar
  85. Wielicki, B.A. et al. (1998), Clouds and the Earth's Radiant Energy System (CERES): Algorithm overview. IEEE Transactions on Geosciences and Remote Sensing, 36, 1127-1141.CrossRefGoogle Scholar
  86. Wild, M. et al. (2005), From dimming to brightening: Decadal changes in solar radiation at Earth's surface. Science, 308, 847-850.CrossRefGoogle Scholar
  87. Wild, M., A. Ohmura, and K. Makowski, (2007), Impact of global dimming and brightening on global warming, Geophysical Research Letters, 34, L04702, doi:10.1029/2006GL028031CrossRefGoogle Scholar
  88. Winslow, J.C., Hunt, E.R.J. and Piper, S.C. (2001), A globally applicable model of daily solar irradiance estimated from air temperature and precipitation data. Ecological Modelling, 143, 227-243.CrossRefGoogle Scholar
  89. Yang, K., Koike, T., Stackhouse, P., Mikovitz, C., & Cox, S. J. (2006). An assessment of satellite surface radiation products for highlands with Tibet Instrumental data. Geophysical Research Letter, 33, L22403, doi: 10.1029/2006GL027640.CrossRefGoogle Scholar
  90. Yang, K., R. T. Pinker, Y. Ma, T. Koike, M. M. Wonsick, S. J. Cox, Y. Zhang, and P. Stackhouse (2008), Evaluation of satellite estimates of downward shortwave radiation over the Tibetan Plateau, Journal of Geophysical Research, 113, D17204, doi:10.1029/2007JD009736.CrossRefGoogle Scholar
  91. Zhang, Y.C., Rossow, W.B., Lacis, A.A., Oinas, V. and Mishchenko, M.I., (2004), Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: Refinements of the radiative transfer model and the input data. Journal of Geophysical Research, 109, D19105, doi:10.1029/2003JD004457.CrossRefGoogle Scholar
  92. Zhang, Y., W. B. Rossow, and P. W. Stackhouse Jr., (2007), Comparison of different global information sources used in surface radiative flux calculation: Radiative properties of the surface. Journal of Geophysical Research, 112, D01102, doi:10.1029/2005JD007008.CrossRefGoogle Scholar
  93. Zhao, M., S. Running and R. Nemani, (2006), Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses, Journal of Geophysical Research, 111: G01002, doi:10.1029/2004JG000004.CrossRefGoogle Scholar
  94. Zheng, T., Liang, S. andWang, K., (2008), Estimation of incident PAR from GOES imagery. Journal of Applied Meteorology and Climatology, 47, 853-868.CrossRefGoogle Scholar
  95. Zhong, B., S. Liang, and B. Holben, (2007), Validating a New Algorithm for Estimating Aerosol Optical Depths over Land from MODIS Imagery, International Journal of Remote Sensing, 28(18), 4207-4214.CrossRefGoogle Scholar
  96. Zhou, Y.P. and Cess, R.D. (2001), Algorithm development strategies for retrieving the downwelling longwave flux at the Earth's surface. Journal of Geophysical Research, 106(D12): 12477-12488.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Shunlin Liang
    • 1
  • Kaicun Wang
    • 1
  • Wenhui Wang
    • 2
  • Dongdong Wang
    • 1
  • Sheng Gui
    • 1
    • 3
  • Xiaotong Zhang
    • 1
    • 3
  • Jeremy Mirmelstein
    • 1
  • Xiufang Zhu
    • 1
  • Hye-yun Kim
    • 2
  • Juan Du
    • 4
  • Steven Running
    • 5
  • John Townshend
    • 1
  • Si-Chee Tsay
    • 6
  • Robert Wolf
    • 7
  • Crystal Schaaf
    • 8
  • Alan Strahler
    • 8
  1. 1.Department of GeographyUniversity of MarylandMarylandUSA
  2. 2.NOAA/NESDIS/STAR and I. M. System Groups, Inc.,MarylandUSA
  3. 3.School of Resource and Environmental ScienceWuhan UniversityWuhanChina
  4. 4.College of Resources Science and TechnologyBeijing Normal UniversityBeijingP.R. China
  5. 5.School of ForestryUniversity of MontanaMissoulaUSA
  6. 6.NASA Goddard Space Flight CenterGreenbeltUSA
  7. 7.Code 614.5, NASA Goddard Space Flight CenterGreenbeltUSA
  8. 8.Department of GeographyBoston UniversityBostonUSA

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