Author
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GAREN, DAVID - NRCS |
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Marks, Daniel |
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Submitted to: International Association of Hydrological Science
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 7/20/2001 Publication Date: 7/20/2001 Citation: Garen, D.C. and D. Marks, 2001. Spatial fields of meteorological input data including forest canopy corrections for an energy budget snow simulation model. In: Soil-Vegetation-Atmosphere Transfer Schemes and Large-Scale Hydrological Models, IAHS publication 270, 349-353. Interpretive Summary: Spatially distributed energy budget snow modelling requires input data on all major meteorological variables, including precipitation, air temperature, wind speed, and solar and thermal radiation. Each of these variables has its own characteristics and its own level of data availability, making it necessary to use a variety of procedures to develop spatial fields of each one. For an application of such a model to the Boise River in Idaho, USA, procedures have been developed to estimate 3h spatial field time series of these variables from the available ground measurements over a 2150 km2 area with a 250 m square grid cell size. Precipitation and temperature data are available at eight stations in and near the catchment. (Due to the rugged terrain, radar precipitation estimates are unavailable.) These spatial fields were computed using an interpolation procedure based on detrended kriging in which a linear trend with elevation represents the vertical variability, and the residuals from this trend are interpolated with ordinary kriging, representing the horizontal variability. Dew point temperature and wind speed are available at three stations. For these, a simpler interpolation procedure had to be used, combining a station average value with elevational trends derived from twice-a-day weather balloon upper air profiles at the nearby airport Technical Abstract: Spatially distributed energy budget snow modelling requires input data on all major meteorological variables, including precipitation, air temperature, wind speed, and solar and thermal radiation. Each of these variables has its own characteristics and its own level of data availability, making it necessary to use a variety of procedures to develop spatial fields of each one. For an application of such a model to the Boise River in Idaho, USA, procedures have been developed to estimate 3h spatial field time series of these variables from the available ground measurements over a 2150 km2 area with a 250 m square grid cell size. Precipitation and temperature data are available at eight stations in and near the catchment. (Due to the rugged terrain, radar precipitation estimates are unavailable.) These spatial fields were computed using an interpolation procedure based on detrended kriging in which a linear trend with elevation represents the vertical variability, and the residuals from this trend are interpolated with ordinary kriging, representing the horizontal variability. Dew point temperature and wind speed are available at three stations. For these, a simpler interpolation procedure had to be used, combining a station average value with elevational trends derived from twice-a-day weather balloon upper air profiles at the nearby airport |
