Abstract

The National Operational Hydrologic Remote Sensing Center (NOHRSC) Snow Model (NSM) is an energy- and mass-balance model used by the National Oceanic and Atmospheric Administration’s National Weather Service for moderate-resolution spatially distributed snow analysis and data assimilation over the United States. The NSM was evaluated in a one-dimensional mode using meteorological and snowpit observations from five sites in Colorado collected during 2002–03. Four parameters estimated by the NSM [snow water equivalent (SWE), snow depth, average snowpack temperature, and snow surface temperature] were compared with snowpit observations and with estimates from another snow energy and mass-balance model, SNTHERM. Root-mean-squared differences (RMSDs) between snowpit SWE observations (January–June) at all sites and estimates from the NSM were about 11% (RMSD = 0.073 m) of the average maximum observed SWE from all sites of 0.694 m. SNTHERM exhibited only a slightly better agreement (RMSD = 0.066 m). During the winter and early spring period before snowpacks became isothermal at 273.15 K, both NSM and SNTHERM simulated significantly cooler average snowpack temperatures than observed (RMSD = 3 and 2 K, respectively). During this snow accumulation period estimates of SWE by both models were very similar. Differences in modeled SWE were traced to short periods (5–21 days) during isothermal conditions in early spring when the two models diverged. These events caused SWE differences that persisted throughout the ablation period and resulted in a range in melt-out times of 0.2–7.2 days between depth observations and modeled estimates. The divergence in SWE resulted from differences in snowmelt fluxes estimated by the two models, which are suggested to result from 1) liquid water fractions within a snowpack being estimated by the NSM using an internal energy method and by SNTHERM using a semiempirical temperature-based approach, and 2) SNTHERM, but not the NSM, accounting for the small liquid water fraction that coexists in equilibrium with snow when the snowpack surface is dry (<273.15 K).

Abstract

Ground-based, subcanopy measurements of incoming shortwave and longwave radiation are frequently used to drive and validate energy balance and snowmelt models. These subcanopy measurements are frequently obtained using different configurations (linear or distributed; stationary or moving) of radiometer arrays that are installed to capture the spatial and temporal variability of longwave and shortwave radiation. Three different radiometer configurations (stationary distributed, stationary linear, and moving linear) were deployed in a spruce forest in the eastern Swiss Alps during a 9-month period, capturing the annual range of sun angles and sky conditions. Results showed a strong seasonal variation in differences between measurements of shortwave transmissivity between the three configurations, whereas differences in longwave enhancement appeared to be seasonally independent. Shortwave transmissivity showed a larger spatial variation in the subcanopy than longwave enhancement at this field site. The two linear configurations showed the greatest similarity in shortwave transmissivity measurements, and the measurements of longwave enhancement were largely similar between all three configurations. A reduction in the number of radiometers in each array reduced the similarities between each stationary configuration. The differences presented here are taken to reflect the natural threshold of spatial noise in subcanopy measurements that can be expected between the three configurations.

Abstract

A short-term meteorological database has been developed for the Cold Land Processes Experiment (CLPX). This database includes meteorological observations from stations designed and deployed exclusively for CLPX as well as observations available from other sources located in the small regional study area (SRSA) in north-central Colorado. The measured weather parameters include air temperature, relative humidity, wind speed and direction, barometric pressure, short- and longwave radiation, leaf wetness, snow depth, snow water content, snow and surface temperatures, volumetric soil moisture content, soil temperature, precipitation, water vapor flux, carbon dioxide flux, and soil heat flux. The CLPX weather stations include 10 main meteorological towers, 1 tower within each of the nine intensive study areas (ISA) and one near the local scale observation site (LSOS); and 36 simplified towers, with one tower at each of the four corners of each of the nine ISAs, which measured a reduced set of parameters. An eddy covariance system within the North Park mesocell study area (MSA) collected a variety of additional parameters beyond the 10 standard CLPX tower components. Additional meteorological observations come from a variety of existing networks maintained by the U.S. Forest Service, U.S. Geological Survey, Natural Resource Conservation Service, and the Institute of Arctic and Alpine Research. Temporal coverage varies from station to station, but it is most concentrated during the 2002/03 winter season. These data are useful in local meteorological energy balance research and for model development and testing. These data can be accessed through the National Snow and Ice Data Center Web site.

Abstract

Solar radiation beneath a forest canopy can have large spatial variations, but this is frequently neglected in radiative transfer models for large-scale applications. To explicitly model spatial variations in subcanopy radiation, maps of canopy structure are required. Aerial photography and airborne laser scanning are used to map tree locations, heights, and crown diameters for a lodgepole pine forest in Colorado as inputs to a spatially explicit radiative transfer model. Statistics of subcanopy radiation simulated by the model are compared with measurements from radiometer arrays, and scaling of spatial statistics with temporal averaging and array size is discussed. Efficient parameterizations for spatial averages and standard deviations of subcanopy radiation are developed using parameters that can be obtained from the model or hemispherical photography.

The Northern Hemisphere has large areas that are forested and seasonally snow covered. Compared with open areas, forest canopies strongly influence interactions between the atmosphere and snow on the ground by sheltering the snow from wind and solar radiation and by intercepting falling snow; these influences have important consequences for the meteorology, hydrology, and ecology of forests. Many of the land surface models used in meteorological and hydrological forecasting now include representations of canopy snow processes, but these have not been widely tested in comparison with observations. Phase 2 of the Snow Model Intercomparison Project (SnowMIP2) was therefore designed as an intercomparison of surface mass and energy balance simulations for snow in forested areas. Model forcing and calibration data for sites with paired forested and open plots were supplied to modeling groups. Participants in 11 countries contributed output from 33 models, and the results are published here for sites in Canada, the United States, and Switzerland. On average, the models perform fairly well in simulating snow accumulation and ablation, although there is a wide intermodal spread and a tendency to underestimate differences in snow mass between open and forested areas. Most models capture the large differences in surface albedos and temperatures between forest canopies and open snow well. There is, however, a strong tendency for models to underestimate soil temperature under snow, particularly for forest sites, and this would have large consequences for simulations of runoff and biological processes in the soil.