Search Results
the LSOS consisted of a high sampling density within relatively uniform areas of the LSOS to facilitate a comparison of microwave remote sensing data, radiative transfer models, detailed physical models of the snow and the underlying soil, and ground observations. A network of footpaths was established throughout the LSOS to prevent the disruption of the specific measurement sites. 2. Summary of collected data parameters a. Canopy characterization In the fall of 2001, Cold Regions Research and
the LSOS consisted of a high sampling density within relatively uniform areas of the LSOS to facilitate a comparison of microwave remote sensing data, radiative transfer models, detailed physical models of the snow and the underlying soil, and ground observations. A network of footpaths was established throughout the LSOS to prevent the disruption of the specific measurement sites. 2. Summary of collected data parameters a. Canopy characterization In the fall of 2001, Cold Regions Research and
; Pomeroy et al. 1998 ). In general, the energy balance of a snow cover is expressed as where Δ Q is change in snow cover energy, and R n , H , L υ E , G and M are net radiative, sensible, latent, conductive, and advective energy fluxes (all terms are in W m −2 ), respectively; L υ is the latent heat of vaporization or sublimation (J kg −1 ) and E is the mass flux by sublimation from or condensation to the snow surface (kg m −2 s −1 ). In this context, advected energy M is heat lost
; Pomeroy et al. 1998 ). In general, the energy balance of a snow cover is expressed as where Δ Q is change in snow cover energy, and R n , H , L υ E , G and M are net radiative, sensible, latent, conductive, and advective energy fluxes (all terms are in W m −2 ), respectively; L υ is the latent heat of vaporization or sublimation (J kg −1 ) and E is the mass flux by sublimation from or condensation to the snow surface (kg m −2 s −1 ). In this context, advected energy M is heat lost
fluxes to the snowpack than SNTHERM, which created less meltwater. The specific reasons for the different behaviors between energy fluxes and meltwater production in the two models are unknown. Although both were forced with the same hydrometeorological data over a wide range of physical settings influencing radiative and turbulent energy exchange, small differences between the model representations of liquid water, and perhaps differences in layer structure, were sufficient to cause divergence
fluxes to the snowpack than SNTHERM, which created less meltwater. The specific reasons for the different behaviors between energy fluxes and meltwater production in the two models are unknown. Although both were forced with the same hydrometeorological data over a wide range of physical settings influencing radiative and turbulent energy exchange, small differences between the model representations of liquid water, and perhaps differences in layer structure, were sufficient to cause divergence
1. Introduction Forest canopies strongly modify radiative fluxes reaching the underlying surface. This has important implications for hydrological and ecological processes, such as snowmelt and succession, in forested environments ( Pomeroy and Dion 1996 ; Battaglia et al. 2002 ; Hardy et al. 2004 ). Conversely, radiation reflected and emitted from trees complicates the retrieval of forest snow properties by remote sensing ( Chang et al. 1996 ; Klein et al. 1998 ). Land surface models and
1. Introduction Forest canopies strongly modify radiative fluxes reaching the underlying surface. This has important implications for hydrological and ecological processes, such as snowmelt and succession, in forested environments ( Pomeroy and Dion 1996 ; Battaglia et al. 2002 ; Hardy et al. 2004 ). Conversely, radiation reflected and emitted from trees complicates the retrieval of forest snow properties by remote sensing ( Chang et al. 1996 ; Klein et al. 1998 ). Land surface models and
temperature. The layer interfaces are assumed to be planar. The sandwich model, based on multiple scattering radiative transfer, is used ( Wiesmann et al. 1998 ) to combine internal scattering and reflections at the interfaces. Internal volume scattering is accounted for by a two-flux model (up- and downwelling streams) derived from a six-flux approach (fluxes in all spatial directions). The absorption and scattering coefficients are functions of the six-flux parameters. The absorption coefficient can be
temperature. The layer interfaces are assumed to be planar. The sandwich model, based on multiple scattering radiative transfer, is used ( Wiesmann et al. 1998 ) to combine internal scattering and reflections at the interfaces. Internal volume scattering is accounted for by a two-flux model (up- and downwelling streams) derived from a six-flux approach (fluxes in all spatial directions). The absorption and scattering coefficients are functions of the six-flux parameters. The absorption coefficient can be
using up- and down-looking pyranometers and pyrgeometers for shortwave and longwave, respectively. Pyrgeometers were also deployed at 4 and 25 m above the ground surface to evaluate longwave radiative flux divergence. Soil measurements include three levels of temperature (0.025, 0.05, and 0.10 m), two levels of moisture (0.05 and 0.10 m), and a heat flux measurement at 0.10 m. A probe capable of measuring thermal properties of the soil was installed to determine heat capacity and thermal
using up- and down-looking pyranometers and pyrgeometers for shortwave and longwave, respectively. Pyrgeometers were also deployed at 4 and 25 m above the ground surface to evaluate longwave radiative flux divergence. Soil measurements include three levels of temperature (0.025, 0.05, and 0.10 m), two levels of moisture (0.05 and 0.10 m), and a heat flux measurement at 0.10 m. A probe capable of measuring thermal properties of the soil was installed to determine heat capacity and thermal
(0.1 m). Observations were made in the ISAs, the local scale observation site (LSOS), and at a site adjacent to the National Center for Atmospheric Research (NCAR) flux tower (close to the southeast corner of the Potter Creek ISA; Fig. 1 ; Table 2 ). Data were collected on 8–9 April (snow-covered sites) and 18–19 September 2003 (snow-free sites). Data are available for all sites except for snow depth contours at the site adjacent to the NCAR flux tower. Elevation data were acquired from
(0.1 m). Observations were made in the ISAs, the local scale observation site (LSOS), and at a site adjacent to the National Center for Atmospheric Research (NCAR) flux tower (close to the southeast corner of the Potter Creek ISA; Fig. 1 ; Table 2 ). Data were collected on 8–9 April (snow-covered sites) and 18–19 September 2003 (snow-free sites). Data are available for all sites except for snow depth contours at the site adjacent to the NCAR flux tower. Elevation data were acquired from
) results from the Moderate Resolution Imaging Spectroradiometer (MODIS) snow-covered area and grain size (MODSCAG) model for the Cold Land Processes Field Experiment (CLPX) in the St. Louis Creek intensive study area (ISA) of the Fraser Experimental Forest. MODSCAG combines a radiative transfer model for snow spectral endmembers with a multiple endmember spectral mixture analysis approach in which the number of endmembers as well as the endmembers themselves may vary on a pixel by pixel basis. When
) results from the Moderate Resolution Imaging Spectroradiometer (MODIS) snow-covered area and grain size (MODSCAG) model for the Cold Land Processes Field Experiment (CLPX) in the St. Louis Creek intensive study area (ISA) of the Fraser Experimental Forest. MODSCAG combines a radiative transfer model for snow spectral endmembers with a multiple endmember spectral mixture analysis approach in which the number of endmembers as well as the endmembers themselves may vary on a pixel by pixel basis. When
