Hydrology and Earth System Sciences
www.hydrol-earth-syst-sci.net
1027-5606
1607-7938
13
7
2009
10.5194/hess-13-969-2009
http://www.hydrol-earth-syst-sci.net/13/969/2009/
http://www.hydrol-earth-syst-sci.net/13/969/2009/hess-13-969-2009.html
http://www.hydrol-earth-syst-sci.net/13/969/2009/hess-13-969-2009.pdf
969
986
2009-07-07
High-resolution satellite-based cloud-coupled estimates of total downwelling surface radiation for hydrologic modelling applications
B. A. Forman
S. A. Margulis
margulis@seas.ucla.edu
Department of Civil and Environmental Engineering, University of California at Los Angeles, Los Angeles, California, 90095, USA
A relatively simple satellite-based radiation model yielding high-resolution
(in space and time) downwelling longwave and shortwave radiative fluxes at
the Earth's surface is presented. The primary aim of the approach is to
provide a basis for deriving physically consistent forcing fields for
distributed hydrologic models using satellite-based remote sensing data. The
physically-based downwelling radiation model utilises satellite inputs from
both geostationary and polar-orbiting platforms and requires only
satellite-based inputs except that of a climatological lookup table derived
from a regional climate model. Comparison against ground-based measurements
over a 14-month simulation period in the Southern Great Plains of the United
States demonstrates the ability to reproduce radiative fluxes at a spatial
resolution of 4 km and a temporal resolution of 1 h with good accuracy
during all-sky conditions. For hourly fluxes, a mean difference of −2 W m<sup>−2</sup>
with a root mean square difference of 21 W m<sup>−2</sup> was found for
the longwave fluxes whereas a mean difference of −7 W m<sup>−2</sup> with a root
mean square difference of 29 W m<sup>−2</sup> was found for the shortwave fluxes.
Additionally, comparison against advanced downwelling longwave and solar
insolation products during all-sky conditions showed comparable uncertainty
in the longwave estimates and reduced uncertainty in the shortwave
estimates. The relatively simple form of the model enables future usage in
ensemble-based applications including data assimilation frameworks in order
to explicitly account for input uncertainties while providing the potential
for conditioning estimates from other readily available products derived
from more sophisticated retrieval algorithms.
% vor jede Referenz Abbott, M. B., Bathurst, J. C., Cunge, J. A., O'Connell, P. E., and Rasmussen, J.: An Introduction to the European Hydrological System – Systeme Hydrologique Europeen, "SHE", 2: Structure of a Physically-based, Distributed Modelling System, J. Hydrol., 87, 61–77, 1986.
Beven, K. J.: Changing Ideas in Hydrology – The Case of Physically-based Models, J. Hydrol., 105, 157–172, 1989.
Bras, R. L.: Hydrology: An Introduction to Hydrologic Science, Addison-Wesley, Reading, MA, 643~pp., 1990.
Brock, F. V., Crawford, K. C., Elliott, R. L., Cuperus, G. W., Stadler, S. J., Johnson, H. L., and Eilts, M. D.: The Oklahoma Mesonet: A Technical Overview, J. Atmos. Ocean. Tech., 12, 5–19, 1995.
Coakley Jr., J. A., Cess, R. D., and Yurevich, F. B.: The Effect of Tropospheric Aerosols on the Earth's Radiation Budget: A Parameterization for Climate Models, J. Atmos. Sci., 40, 116–138, 1983.
Cosgrove, B. A., Lohmann, D., Mitchell, K. E., Houser, P. R., Wood, E. F., Schaake, J. C., Robock, A., Marshall, C., Sheffield, J., Duan, Q., Luo, L., Higgins, R. W., Pinker, R. T., and Tarpley, J. D.: Real-time and Retrospective Forcing in the North American Land Data Assimilation System (NLDAS) Project, J. Geophys. Res., 108(D22), 8842, doi:10.1029/2002JD003118, 2003.
Coulson, K. L.: Characteristics of the Radiation Emerging from the Top of a Rayleigh Atmosphere I: Intensity and Polarization, Planet. Space Sci., 1, 265–276, 1959.
Diak, G. R., Bland, W. L., Mecikalski, J. R., and Anderson, M. C.: Satellite-based Estimates of Longwave Radiation for Agricultural Applications, Agr. Forest Meteorol., 103, 349–355, 2000.
Dingman, S. L.: Physical Hydrology, 2nd ed., Prentice Hall, Upper Saddle River, NJ, USA, 646~pp., 2002.
Dutton, E. G., Michalsky, J. J., Stoffel, T., Forgan, B. W., Hickey, J., Nelson, D. W., Alberta, T. L., and Reda, I.: Measurement of Broadband Diffuse Solar Irradiance Using Current Commercial Instrumentation with a Correction for Thermal Offset Errors, J. Atmos. Ocean. Tech., 18, 297–314, 2001.
Gautier, C., Diak, G. R., and Masse, S.: A Simple Physical Model to Estimate Incident Solar Radiation at the Surface from GOES Satellite Data, J. Appl. Meteorol., 19, 1005–1012, 1980.
Gautier, C. and Landsfeld, M.: 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, 1289–1307, 1997.
Geiger, B., Meurey, C., Lajas, D., Franchistéguy, L., Carrer, D., and Roujean, J.-L.: Near Real-time Provision of Downwelling Satellite Shortwave Radiation Estimates Derived from Satellite Observations, Meteorol. Appl., 15, 411–420, 2008.
Gillies, R. R., Carlson, T. N., Cui, J., Kustas, W. P., and Humes, K. S.: A Verification of the "Triangle" Method for Obtaining Surface Soil Water Content and Energy Fluxes from Remote Measurements of the Normalized Difference Vegetation Index (NDVI) and Surface Radiant Temperature, Int. J. Remote Sens., 18, 3145–3166, 1997.
Giorgi, F. and Mearns, L. O.: Introduction to Special Section: Regional Climate Modeling Revisited, J. Geophys. Res., 104, 6335–6352, 1999.
Grayson, R. and Blöschl, G.: Spatial Patterns in Catchment Hydrology: Observations and Modelling, Cambridge University Press, New York, 404~pp., 2001.
Gupta, S. K., Darnell, W. L., and Wilber, A. C.: A Parameterization for Longwave Surface Radiation from Satellite Data: Recent Improvements, J. Appl. Meteorol., 31, 1361–1367, 1992.
Hall, D. K., Riggs, G. A., and Salomonson, V. V.: MODIS/Terra Snow Cover Daily L3 Global 500 m Grid V004, Boulder, CO, USA: National Snow and Ice Data Center,updated daily, 2000.
Hansen, J. E., Johnson, D., Lacis, A. A., Lebedeff, S., Lee, P., Rind, D., and Russell, G.: Climate Impact of Increasing Atmospheric Carbon Dioxide, Science, 213, 957–266, 1981.
Hunt, L. A., Kuchar, L., and Swanton, C. J.: Estimation of Solar Radiation for Use in Crop Modelling, Agr. Forest Meteorol., 91, 293–300, 1998.
Idso, S. B.: A Set of Equations for Full Spectrum and 8- to 14-μm and 10.2- to 12.5-μm Thermal Radiation from Cloudless Skies, Water Resour. Res., 17, 295–304, 1981.
Ivanov, V. Y., Vivoni, E. R., Bras, R. L., and Entekhabi, D.: Catchment Hydrologic Response with a Fully Distributed Triangulated Network Model, Water Resour. Res., 40, 102–124, 2004.
Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S.-K., Hnilo, J. J., Fiorino, M., and Potter, G. L.: NCEP-DOE AMIP-II Reanalysis (R-2), B. Am. Meteorol. Soc., 83, 1631–1643, 2002.
Kokhanovsky, A. A., Rozanov, V. V., Burrows, J. P., Eichmann, K.-U., Lotz, W., and Vountas, M.: The SCIAMACHY Cloud Products: Algorithms and Examples from ENVISAT, Adv. Space Res., 36, 789–799, 2005.
Koren, I., Oreopoulos, L., Feingold, G., Remer, L. A., and Altaratz, O.: How small is a small cloud?, Atmos. Chem. Phys., 8, 3855–3864, 2008.
Lee, S. and Margulis, S. A.: High-resolution Ensemble Surface Insolation Estimates through Assimilation of Coarse-scale Retrievals into a Simple Physical Model, Part I: Physical Model Development and Accuracy Tests, J. Geophys. Res., 112, D08212, doi:10.1029/2006JD007872, 2007a.
Lee, S. and Margulis, S. A.: High-resolution Ensemble Surface Insolation Estimates through Assimilation of Coarse-scale Retrievals into a Simple Physical Model, Part II: Ensemble Implementation and SRB Data Assimilation, J. Geophys. Res., 112, D10219, doi:10.1029/2006JD007873, 2007b.
Li, Z., Cribb, M. C., Chang, F.-L., Trishchenko, A., and Luo, Y.: Natural Variability and Sampling Errors in Solar Radiation Measurements for Model Validation over the Atmospheric Radiation Measurement Southern Great Plains Region, J. Geophys. Res., 110, D15S19, doi:10.1029/2004JD005028, 2005.
Liou, K. N.: Radiation and Cloud Processes in the Atmosphere, Oxford University Press, New York, 487~pp., 1992.
Meetschen, D., van den Hurk, B. J. J. M., Ament, F., and Drusch, M.: Optimized Surface Radiation Fields Derived from Meteosat Imagery and a Regional Atmospheric Model, J. Hydrometeorol., 5, 1091–1101, 2004.
Minnis, P., Kratz, D. P., Coakley Jr., J. A., King, M. D., Garber, D., Heck, P., Mayor, S., Smith Jr., W. L., Young, D. F., and Ardaini, R.: Clouds and the Earth's Radiant Energy System (CERES) Algorithm Theoretical Basis Document, 135–175, 1995.
Minnis, P., Trepte, Q. Z., Sun-Mack, S., Chen, Y., Doelling, D. R., Young, D. F., Spangenberg, D. A., Miller, W. F., Wielicki, B. A., Brown, R. R., Gibson, S. C., and Geier, E. B.: Cloud Detection in Non-polar Regions for CERES Using TRMM VIRS and Terra and Aqua MODIS Data, IEEE T. Geosci. Remote, 46, 3857–3884, 2008.
Mitchell, K. E., Lohmann, D., Houser, P. R., Wood, E. F., Schaake, J. C., Robock, A., Cosgrove, B. A., Sheffield, J., Duan, Q., Luo, L., Higgins, R. W., Pinker, R. T., Tarpley, J. D., Lettenmaier, D. P., Marshall, C. H., Entin, J. K., Pan, M., Shi, W., Koren, V., Meng, J., Ramsay, B. H., and Bailey, A. A.: The Multi-institution North American Land Data Assimilation System (NLDAS): Utilizing Multiple GCIP Products and Partners in a Continental Distributed Hydrological Modeling Systems, J. Geophys. Res., 109, D07S90, doi:10.1029/2003JD003823, 2004.
Myers, D. R.: Solar Radiation Modeling and Measurements for Renewable Energy Applications: Data and Model Quality, Energy, 30, 1517–1531, 2005.
Pan, M., Wood, E. F., Wojcik, R., and McCabe, M. F.: Estimation of Regional Terrestrial Water Cycle Using Multi-sensor Remote Sensing Observations and Data Assimilation, Remote Sens. Environ., 112, 1282–1294, 2008.
Pinker, R. T. and Ewing, J. A.: Modeling Surface Solar Radiation: Model Formulation and Validation, J. Clim. Appl. Meteorol., 24, 389–401, 1985.
Pinker, R. T., Frouin, R., and Li, Z.: A Review of Satellite Methods to Derive Surface Shortwave Irradiance, Remote Sens. Environ., 51, 108–124, 1995.
Pinker, R. T., Tarpley, J. D., Laszlo, I., Mitchell, K. E., Houser, P. R., Wood, E. F., Schaake, J. C., Robock, A., Lohmann, D., Cosgrove, B. A., Sheffield, J., Duan, Q., Luo, L., and Higgins, R. W.: 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, J. Geophys. Res., 108(D22), 8844, doi:10.1029/2002JD003301, 2003.
Prata, A. J.: A New Longwave Formula for Estimating Downward Clear-Sky Radiation at the Surface, Q. J. Roy. Meteorol. Soc., 122, 1127–1151, 1996.
Privette, J. L., Mukelabai, M., Zhang, H., and Schaaf, C. B.: Characterization of MODIS Land Albedo (MOD43) Accuracy with Atmospheric Conditions in Africa, Geoscience and Remote Sensing Symposium, Anchorage, AK, 2004.
Reynolds, R. W., Rayner, N. A., Smith, T. M., Stokes, D. C., and Wang, W.: An Improved In Situ and Satellite SST Analysis for Climate, J. Climate, 15, 1609–1625, 2002.
Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K. E., Meng, C.-J., Arsenault, K., Cosgrove, B. A., Radakovich, J., Bosilovich, M. G., Entin, J. K., Walker, J. P., Lohmann, D., and Toll, D.: The Global Land Data Assimilation System, B. Am. Meteorol. Soc., 85, 381–394, 2004.
Satterlund, D. R.: An Improved Equation for Estimating Long-wave Radiation from the Atmosphere, Water Resour. Res., 15, 1649–1650, 1979.
Sharif, H. O., Crow, W. T., Miller, N. L., and Wood, E. F.: Multidecadal High-resolution Hydrologic Modeling of the Arkansas-Red River Basin, J. Hydrometeorol., 8, 1111–1127, 2007.
Slingo, A.: A GCM Parameterization for the Shortwave Radiation Properties of Water Clouds, J. Atmos. Sci., 46, 1419–1427, 1989.
Stephens, G. L.: Remote Sensing of the Lower Atmosphere, Oxford University Press, New York, NY, 523~pp., 1994.
Trigo, I. F., Barroso, C., Freitas, S. C., and Viterbo, P.: Assessment of Algorithms for Land Surface Analysis Downwelling Longwave Radiation at the Surface, Proceedings of the 2007 EUMETSAT Meteorological Satellite Conference, Amsterdam, Netherlands, 2007.
US Naval Observatory (Ed.): The Astronomical Almanac, US Naval Observatory, Washington, DC, 2007.
Wielicki, B. A., Barkstrom, B. R., Baum, B. A., Charlock, T. P., Green, R. N., Kratz, D. P., Lee, R. B., Minnis, P., Smith, G. L., Wong, T., Young, D. F., Cess, R. D., Coakley Jr., J. A., Crommelynck, D. A. H., Donner, L., Kandel, R., King, M. D., Miller, A. J., Ramanathan, V., Randall, D. A., Stowe, L. L., and Welch, R. M.: Clouds and the Earth's Radiant Energy System (CERES): Algorithm Overview, IEEE T. Geosci. Remote, 36, 1127–1141, 1998.