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Jean Emmanuel Sicart, Richard L. H. Essery, John W. Pomeroy, Janet Hardy, Timothy Link, and Danny Marks

Abstract

This study investigates the dependence of net radiation at snow surfaces under forest canopies on the overlying canopy density. The daily sum of positive values of net radiation is used as an index of the snowmelt rate. Canopy cover is represented in terms of shortwave transmissivity and sky-view factor. The cases studied are a spruce forest in the Wolf Creek basin, Yukon Territory, Canada, and a pine forest near Fraser, Colorado. Of particular interest are the atmospheric conditions that favor an offset between shortwave energy attenuation and longwave irradiance enhancement by the canopy, such that net radiation does not decrease with increasing forest density. Such an offset is favored in dry climates and at high altitudes, where atmospheric emissivities are low, and in early spring when snow albedos are high and solar elevations are low. For low snow albedos, a steady decrease in snowmelt energy with increasing canopy cover is found, up to a forest density close to the actual densities of mature spruce forests. Snowmelt rates for high albedos are either insensitive or increase with increasing canopy cover. At both sites, foliage area indices close to 2 are associated with a minimum in net radiation, independent of snow albedo or cloud cover. However, these results are more uncertain for open forests because solar heating of trees may invalidate the longwave assumptions, increasing the longwave irradiance.

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Richard Essery, Peter Bunting, Aled Rowlands, Nick Rutter, Janet Hardy, Rae Melloh, Tim Link, Danny Marks, and John Pomeroy

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.

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John Pomeroy, Chad Ellis, Aled Rowlands, Richard Essery, Janet Hardy, Tim Link, Danny Marks, and Jean Emmanuel Sicart

Abstract

The spatial variation of melt energy can influence snow cover depletion rates and in turn be influenced by the spatial variability of shortwave irradiance to snow. The spatial variability of shortwave irradiance during melt under uniform and discontinuous evergreen canopies at a U.S. Rocky Mountains site was measured, analyzed, and then compared to observations from mountain and boreal forests in Canada. All observations used arrays of pyranometers randomly spaced under evergreen canopies of varying structure and latitude. The spatial variability of irradiance for both overcast and clear conditions declined dramatically, as the sample averaging interval increased from minutes to 1 day. At daily averaging intervals, there was little influence of cloudiness on the variability of subcanopy irradiance; instead, it was dominated by stand structure. The spatial variability of irradiance on daily intervals was higher for the discontinuous canopies, but it did not scale reliably with canopy sky view. The spatial variation in irradiance resulted in a coefficient of variation of melt energy of 0.23 for the set of U.S. and Canadian stands. This variability in melt energy smoothed the snow-covered area depletion curve in a distributed melt simulation, thereby lengthening the duration of melt by 20%. This is consistent with observed natural snow cover depletion curves and shows that variations in melt energy and snow accumulation can influence snow-covered area depletion under forest canopies.

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Janet Hardy, Robert Davis, Yeohoon Koh, Don Cline, Kelly Elder, Richard Armstrong, Hans-Peter Marshall, Thomas Painter, Gilles Castres Saint-Martin, Roger DeRoo, Kamal Sarabandi, Tobias Graf, Toshio Koike, and Kyle McDonald

Abstract

The local scale observation site (LSOS) is the smallest study site (0.8 ha) of the 2002/03 Cold Land Processes Experiment (CLPX) and is located within the Fraser mesocell study area. It was the most intensively measured site of the CLPX, and measurements here had the greatest temporal component of all CLPX sites. Measurements made at the LSOS were designed to produce a comprehensive assessment of the snow, soil, and vegetation characteristics viewed by the ground-based remote sensing instruments. The objective of the ground-based microwave remote sensing was to collect time series of active and passive microwave spectral signatures over snow, soil, and forest, which is coincident with the intensive physical characterization of these features. Ground-based remote sensing instruments included frequency modulated continuous wave (FMCW) radars operating over multiple microwave bandwidths; the Ground-Based Microwave Radiometer (GBMR-7) operating at channels 18.7, 23.8, 36.5, and 89 GHz; and in 2003, an L-, C-, X- and Ku-band scatterometer radar system. Snow and soil measurements included standard snow physical properties, snow wetness, snow depth transects, and soil moisture. The stem and canopy temperature and xylem sap flux of several trees were monitored continuously. Five micrometeorological towers monitored ambient conditions and provided forcing datasets for 1D snow and soil models. Arrays of pyranometers (0.3–3 μm) and a scanning thermal radiometer (8–12 μm) characterized the variability of radiative receipt in the forests. A field spectroradiometer measured the hyperspectral hemispherical-directional reflectance of the snow surface. These measurements, together with the ground-based remote sensing, provide the framework for evaluating and improving microwave radiative transfer models and coupling them to land surface models. The dataset is archived at the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado.

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