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Using CERES SYN Surface Irradiance Data as Forcing for Snowmelt Simulation in Complex Terrain

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  • 1 Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, Washington
  • | 2 Department of Atmospheric Sciences, University of Washington, Seattle, Washington
  • | 3 Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington
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Abstract

The benefit of using solar and longwave surface irradiance data from NASA’s Clouds and the Earth’s Radiant Energy System (CERES) synoptic (SYN) satellite product in simulations of snowmelt has been examined. The accuracy of the SYN downwelling solar and longwave irradiances was first assessed by comparison to measurements at NOAA’s Surface Radiation Network (SURFRAD) reference stations and to remote mountain observations. Typical shortwave (longwave) biases had magnitudes less than 30 (10) W m−2, with most standard deviations below 140 (30) W m−2. The performance of a range of snow models of varying complexity when using SYN irradiances as forcing data was then evaluated. Simulated snow water equivalent and runoff from cases using SYN data fell in the range of those from simulations forced with irradiances from well-maintained surface observation sites as well as empirical methods that have been shown to perform well in mountainous terrain. The SYN irradiances are therefore judged to be suitable for use in snowmelt modeling. It is also noted that the SYN upwelling shortwave irradiances, and hence albedos derived from them, are frequently not representative of individual monitoring stations because of the high spatial variability of snow cover and other surface properties in mountainous regions. In addition, adjusting the SYN downwelling longwave irradiances to reflect the exact elevation of the point of interest relative to the mean altitude of the satellite grid box is recommended.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JHM-D-14-0179.s1.

Corresponding author address: Dr. Laura Hinkelman, JISAO, University of Washington, 3737 Brooklyn Ave. NE, Seattle, WA 98105. E-mail: laurahin@uw.edu

Abstract

The benefit of using solar and longwave surface irradiance data from NASA’s Clouds and the Earth’s Radiant Energy System (CERES) synoptic (SYN) satellite product in simulations of snowmelt has been examined. The accuracy of the SYN downwelling solar and longwave irradiances was first assessed by comparison to measurements at NOAA’s Surface Radiation Network (SURFRAD) reference stations and to remote mountain observations. Typical shortwave (longwave) biases had magnitudes less than 30 (10) W m−2, with most standard deviations below 140 (30) W m−2. The performance of a range of snow models of varying complexity when using SYN irradiances as forcing data was then evaluated. Simulated snow water equivalent and runoff from cases using SYN data fell in the range of those from simulations forced with irradiances from well-maintained surface observation sites as well as empirical methods that have been shown to perform well in mountainous terrain. The SYN irradiances are therefore judged to be suitable for use in snowmelt modeling. It is also noted that the SYN upwelling shortwave irradiances, and hence albedos derived from them, are frequently not representative of individual monitoring stations because of the high spatial variability of snow cover and other surface properties in mountainous regions. In addition, adjusting the SYN downwelling longwave irradiances to reflect the exact elevation of the point of interest relative to the mean altitude of the satellite grid box is recommended.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JHM-D-14-0179.s1.

Corresponding author address: Dr. Laura Hinkelman, JISAO, University of Washington, 3737 Brooklyn Ave. NE, Seattle, WA 98105. E-mail: laurahin@uw.edu

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