Abstract. The objectives of this study were to measure and evaluate the energy balance of a continental, midlatitude alpine snowpack during spring snowmelt conditions, to relate variations in the energy budget and snowmelt to synoptic weather patterns, and to evaluate the performance of a point energy and mass balance model of a snow cover (SNTHERM) in alpine conditions. The investigation was conducted during the 1994 snowmelt season at Niwot Ridge (3517 rn above sea level (asl); 40ø03'N, 105ø35'W) in the Colorado Front Range. Net radiative fluxes and net turbulent fluxes respectively provided 75% and 25% of the total energy available for snowmelt during the season. Sublimation losses were limited to only 4% of the initial snow water equivalence at the site. The largest energy available for snowmelt was associated with a ridge in the upper airflow over the central and southern Rocky Mountains that permitted warmer air into the region. Using measured data from the study site, the SNTHERM model estimated the disappearance of the snowpack just 3 days earlier than the observed 42-day ablation period. IntroductionUnderstanding and predicting the response of hydrologic and biogeochemical transfers within snowmelt-dominated alpine basins to climate variability and change requires a thorough understanding of the energy transfers between the snowpack and the atmosphere that lead to changes in the internal energy of the snowpack and eventually cause snowmelt. The majority of snow energy exchange studies have been concerned with seasonal snowpacks at low elevations, in forested areas, on glaciers, or on sea ice [Kuusisto, 1986], and the substantial differences between conditions in these environments and conditions found in the alpine make comparisons complicated. Since relatively few studies have examined snowpack energy exchanges for entire snowmelt seasons or at high-altitude locations, our basic understanding of snowpack energy transfers in alpine areas is quite limited. Addressing this problem is the basic objective of this paper.In general, radiative and turbulent transfer are the two most important processes affecting snow surface energy exchange. Additional Incident and reflected shortwave radiative fluxes were measured using a Kipp and Zonen CM14 albedometer, which has two pyranometers (upward and downward looking) housed in a single instrument. Incident and upwelling longwave radiative fluxes were measured using a Kipp and Zonen CG2, again, a single housing containing upward and a downward looking pyrgeometers. Each pyrgeometer in the CG2 contains a thermistor adjacent to the sensor to permit temperature compensation of the longwave measurements. Net radiation fluxes reported in this paper were determined as shown by (2), using QH = b(Cp) d)H[ln(z2/zl)] d)•t[ln(z2/zl)] (3) and the latent heat flux is expressed as ( k(q2-qO ( k(u2-uO ) QE = b(Lv) •-r•(•2•-•-)] (b•t[ln(z•/zO] (4) where b is the density of air, Cp is the specific heat of air at a constant pressure, L•, is the latent heat of vaporization of water,...
Abstract. We present a modeling approach that couples information about snow cover duration from remote sensing with a distributed energy balance model to calculate the spatial distribution of snow water equivalence (SWE) in a 1.2 km 2 mountain basin at the peak of the accumulation season. In situ measurements of incident solar radiation, incident longwave radiation, air temperature, relative humidity, and wind speed were distributed around the basin on the basis of topography. Snow surface albedo was assumed to be spatially constant and to decrease with time. Distributed snow surface temperature was estimated as a function of modeled air temperature. We computed the energy balance for each pixel at hourly intervals using the estimated radiative fluxes and bulk-aerodynamic turbulent-energy flux algorithms from a snowpack energy and mass balance model. Fractional snow cover within each pixel was estimated from three multispectral images (Landsat thematic mapper), one at peak accumulation and two during snowmelt, using decision trees and a spectral mixture model; from these we computed snow cover duration at subpixel resolution. The total cumulative energy for snowmelt at each remote sensing date was weighted by the fraction of each pixel's area that lost its snow cover by that date to determine an initial SWE for each pixel. We tested the modeling approach in the well-studied Emerald Lake basin in the southern Sierra Nevada. With no parameter fitting the modeled spatial pattern of SWE and the mean basin SWE agreed with intensive field survey data. As the modeling approach requires only a remote sensing time series and an ability to estimate the energy balance over the model domain, it should prove useful for computing SWE distributions at peak accumulation over larger areas, where extensive field measurements of SWE are not practical.
Abstract-Snow is a critical component of the global water cycle and climate system, and a major source of water supply in many parts of the world. There is a lack of spatially distributed information on the accumulation of snow on land surfaces, glaciers, lake ice and sea ice. Satellite missions for systematic and global snow observations will be essential to improve the representation of the cryosphere in climate models and to advance the knowledge and prediction of the water cycle variability and changes that depend on snow and ice resources. This article describes the scientific drivers and technical approach of the proposed Cold Regions Hydrology Highresolution Observatory (CoReH 2 O) satellite mission for snow and cold land processes. The sensor is a synthetic aperture radar (SAR), operating at 17.2 GHz and 9.6 GHz, VV and VH polarizations. The dual-frequency and dual-polarization design enables the decomposition of the scattering signal for retrieving snow mass and other physical properties of snow and ice.
Abstract. We applied a version of the Regional Hydro-Ecologic Simulation System (RHESSys) that implements snow redistribution, elevation partitioning, and wind-driven sublimation to Loch Vale Watershed (LVWS), an alpine-subalpine Rocky Mountain catchment where snow accumulation and ablation dominate the hydrologic cycle. We compared simulated discharge to measured discharge and the simulated snow distribution to photogrammetrically rectified aerial (remotely sensed) images. Snow redistribution was governed by a topographic similarity index. We subdivided each hillslope into elevation bands that had homogeneous climate extrapolated from observed climate. We created a distributed wind speed field that was used in conjunction with daily measured wind speeds to estimate sublimation. Modeling snow redistribution was critical to estimating the timing and magnitude of discharge. Incorporating elevation partitioning improved estimated timing of discharge but did not improve patterns of snow cover since wind was the dominant controller of areal snow patterns. Simulating wind-driven sublimation was necessary to predict moisture losses.
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