Snowmelt Energy Research Articles

Canopy Structure and Air Temperature Inversions Impact Simulation of Sub‐Canopy Longwave Radiation in Snow‐Covered Boreal Forests

AbstractLongwave radiation is often the dominant source of energy for snowmelt in forests. Measurements at forest sites of varying density in Sweden and Finland show that downwelling longwave radiation is enhanced under forest canopies, even for sparse canopies and particularly for clear skies. Canopy density must be estimated accurately to predict this enhancement. Linear regression with above‐canopy longwave radiation and air temperature as predictors of sub‐canopy radiation gives good predictions of sub‐canopy longwave radiation with weightings for transmission through canopy gaps that are close to measured sky view fractions. Air temperature serves here as a proxy for effective canopy radiative temperature. Adding above‐canopy shortwave radiation as a predictor gives little improvement in the predictions, suggesting that daytime heating of trunks above the air temperature (“hot trees”) has limited influence on longwave radiation under these continuous canopies. The influence of canopy temperatures falling below the above‐canopy air temperature (“cold trees”) on calm, clear nights, however, is apparent. Decoupling of canopy and above‐canopy air temperatures in an energy balance model of the type used in large‐scale land surface modeling allows this cooling.

The Role of Basin Geometry in Mountain Snowpack Responses to Climate Change

Snowmelt contributions to streamflow in mid-latitude mountain basins typically dominate other runoff sources on annual and seasonal timescales. Future increases in temperature and changes in precipitation will affect both snow accumulation and seasonal runoff timing and magnitude, but the underlying and fundamental roles of mountain basin geometry and hypsometry on snowmelt sensitivity have received little attention. To investigate the role of basin geometry in snowmelt sensitivity, a linear snow accumulation model and the Cold Regions Hydrological Modeling (CRHM) platform driven are used to estimate how hypsometry affects basin-wide snow volumes and snowmelt runoff. Area-elevation distributions for fifty basins in western Canada were extracted, normalized according to their elevation statistics, and classified into three clusters that represent top-heavy, middle, and bottom-heavy basins. Prescribed changes in air temperature alter both the snow accumulation gradient and the total snowmelt energy, leading to snowpack volume reductions (10–40%), earlier melt onsets (1–4 weeks) and end of melt season (3 weeks), increases in early spring melt rates and reductions in seasonal areal melt rates (up to 50%). Basin hypsometry controls the magnitude of the basin response. The most sensitive basins are bottom-heavy, and have a greater proportion of their area at low elevations. The least sensitive basins are top-heavy, and have a greater proportion of their area at high elevations. Basins with similar proportional areas at high and low elevations fall in between the others in terms of sensitivity and other metrics. This work provides context for anticipating the impacts of ongoing hydrological change due to climate change, and provides guidance for both monitoring networks and distributed modeling efforts.

Snowmelt modeling using two melt-rate models in the Urumqi River watershed, Xinjiang Uyghur Autonomous Region, China

In this paper, the performance of the classic snowmelt runoff model (SRM) is evaluated in a daily discharge simulation with two different melt models, the empirical temperature-index melt model and the energy-based radiation melt model, through a case study from the data-sparse mountainous watershed of the Urumqi River basin in Xinjiang Uyghur Autonomous Region of China. Theclassic SRM, which uses the empirical temperature-index method, and a radiation-based SRM, incorporating shortwave solar radiation and snow albedo, were developed to simulate daily runoff for the spring and summer snowmelt seasons from 2005 to 2012, respectively. Dailymeteorological and hydrological data were collected from three stations located in the watershed. Snowcover area (SCA) was extracted from satellite images. Solarradiation inputs were estimated based on a digital elevation model (DEM). Theresults showed that the overall accuracy of the classic SRM and radiation-based SRM for simulating snowmelt discharge was relatively high. Theclassic SRM outperformed the radiation-based SRM due to the robust performance of the temperature-index model in the watershed snowmelt computation. Nosignificant improvement was achieved by employing solar radiation and snow albedo in the snowmelt runoff simulation due to the inclusion of solar radiation as a temperature-dependent energy source and the local pattern of snowmelt behavior throughout the melting season. Ourresults suggest that the classic SRM simulates daily runoff with favorable accuracy and that the performance of the radiation-based SRM needs to be further improved by more ground-measured data for snowmelt energy input.

Difference in snowmelt processes between an opening and three Japanese cedar stands

AbstractSnowmelt was measured on a daily basis for 17 days at the open site and 18 days at three Japanese cedar sites with canopy closure of 17.8% (cedar stand A), 5.2% (B) and 2.4% (C) in April. Measured daily snowmelt at each site was reproduced by heat-balance calculation with an accuracy of <±1 mm w.e. From 1st April to the date of snow disappearance net radiation accounted for 88.4, 43.0, 32.7 and 34.2% of total snowmelt energy at the open site, the cedar stands A, B and C, respectively. The ratio of sensible and latent heat to total snowmelt was 33.1–37.9 and 25.9–29.4%, respectively, at three cedar stands. The ratios of sensible and latent heat increased over time in accordance with the rise in temperature at all cedar sites. They became large on a daily basis when air temperature and/or wind speed were high. Wind speed is dependent on morphology around each site that also dictated snowmelt.

On the exchange of sensible and latent heat between the atmosphere and melting snow

The snow energy balance is difficult to measure during the snowmelt period, yet critical for predictions of water yield in regions characterized by snow cover. Robust simplifications of the snowmelt energy balance can aid our understanding of water resources in a changing climate. Research to date has demonstrated that the net turbulent flux (FT) between a melting snowpack and the atmosphere is negligible if the sum of atmospheric vapor pressure (ea) and temperature (Ta) equals a constant, but it is unclear how frequently this situation holds across different sites. Here, we quantified the contribution of FT to the snowpack energy balance during 59 snowmelt periods across 11 sites in the FLUXNET2015 database with a detailed analysis of snowmelt in subarctic tundra near Abisko, Sweden. At the Abisko site we investigated the frequency of occurrences during which sensible heat flux (H) and latent heat flux (λE) are of (approximately) equal but opposite sign, and if the sum of these terms, FT, is therefore negligible during the snowmelt period. H approximately equaled -λE for less than 50% of the melt period and FT was infrequently a trivial term in the snowmelt energy balance at Abisko. The reason is that the relationship between observed ea and Ta is roughly orthogonal to the “line of equality” at which H equals -λE as warmer Ta during the melt period usually resulted in greater ea. This relationship holds both within melt periods at individual sites and across different sites in the FLUXNET2015 database, where FT comprised less than 20% of the energy available to melt snow, Qm, in 44% of the snowmelt periods studied here. FT/Qm was significantly related to the mean ea during the melt period, but not mean Ta, and FT tended to be near 0 W m−2 when ea averaged ca. 0.5 kPa. FT may become an increasingly important term in the snowmelt energy balance across many global regions as warmer temperatures are projected to cause snow to melt more slowly and earlier in the year under conditions of lower net radiation (Rn). Eddy covariance research networks such as Ameriflux must improve their ability to observe cold-season processes to enhance our understanding of water resources and surface-atmosphere exchange in a changing climate.

Local‐Scale Advection of Sensible and Latent Heat During Snowmelt

AbstractThe breakup of snow cover into patches during snowmelt leads to a dynamic, heterogeneous land surface composed of melting snow, and wet and dry soil and plant surfaces. Energy exchange with the atmosphere is therefore complicated by horizontal gradients in surface temperature and humidity as snow surface temperature and humidity are regulated by the phase change of melting snow unlike snow‐free areas. Airflow across these surface transitions results in local‐scale advection of energy that has been documented as sensible heat during snowmelt, while latent heat advection has received scant attention. Herein, results are presented from an experiment measuring near‐surface profiles of air temperature and humidity across snow‐free to snow‐covered transitions that demonstrates that latent heat advection can be the same order of magnitude as sensible heat advection and is therefore an important source of snowmelt energy. Latent heat advection is conditional on an upwind source of water vapor from a wetted snow‐free surface.

Influence of snowpack and melt energy heterogeneity on snow cover depletion and snowmelt runoff simulation in a cold mountain environment

The spatial heterogeneity of mountain snow cover and ablation is important in controlling patterns of snow cover depletion (SCD), meltwater production, and runoff, yet is not well-represented in most large-scale hydrological models and land surface schemes. Analyses were conducted in this study to examine the influence of various representations of snow cover and melt energy heterogeneity on both simulated SCD and stream discharge from a small alpine basin in the Canadian Rocky Mountains. Simulations were performed using the Cold Regions Hydrological Model (CRHM), where point-scale snowmelt computations were made using a snowpack energy balance formulation and applied to spatial frequency distributions of snow water equivalent (SWE) on individual slope-, aspect-, and landcover-based hydrological response units (HRUs) in the basin. Hydrological routines were added to represent the vertical and lateral transfers of water through the basin and channel system. From previous studies it is understood that the heterogeneity of late winter SWE is a primary control on patterns of SCD. The analyses here showed that spatial variation in applied melt energy, mainly due to differences in net radiation, has an important influence on SCD at multiple scales and basin discharge, and cannot be neglected without serious error in the prediction of these variables. A single basin SWE distribution using the basin-wide mean SWE (SWE‾) and coefficient of variation (CV; standard deviation/mean) was found to represent the fine-scale spatial heterogeneity of SWE sufficiently well. Simulations that accounted for differences in (SWE‾) among HRUs but neglected the sub-HRU heterogeneity of SWE were found to yield similar discharge results as simulations that included this heterogeneity, while SCD was poorly represented, even at the basin level. Finally, applying point-scale snowmelt computations based on a single SWE depth for each HRU (thereby neglecting spatial differences in internal snowpack energetics over the distributions) was found to yield similar SCD and discharge results as simulations that resolved internal energy differences. Spatial/internal snowpack melt energy effects are more pronounced at times earlier in spring before the main period of snowmelt and SCD, as shown in previously published work. The paper discusses the importance of these findings as they apply to the warranted complexity of snowmelt process simulation in cold mountain environments, and shows how the end-of-winter SWE distribution represents an effective means of resolving snow cover heterogeneity at multiple scales for modelling, even in steep and complex terrain.

Diagnosis of the hydrology of a small Arctic basin at the tundra-taiga transition using a physically based hydrological model

A better understanding of cold regions hydrological processes and regimes in transitional environments is critical for predicting future Arctic freshwater fluxes under climate and vegetation change. A physically based hydrological model using the Cold Regions Hydrological Model platform was created for a small Arctic basin in the tundra-taiga transition region. The model represents snow redistribution and sublimation by wind and vegetation, snowmelt energy budget, evapotranspiration, subsurface flow through organic terrain, infiltration to frozen soils, freezing and thawing of soils, permafrost and streamflow routing. The model was used to reconstruct the basin water cycle over 28years to understand and quantify the mass fluxes controlling its hydrological regime. Model structure and parameters were set from the current understanding of Arctic hydrology, remote sensing, field research in the basin and region, and calibration against streamflow observations. Calibration was restricted to subsurface hydraulic and storage parameters. Multi-objective evaluation of the model using observed streamflow, snow accumulation and ground freeze/thaw state showed adequate simulation. Significant spatial variability in the winter mass fluxes was found between tundra, shrubs and forested sites, particularly due to the substantial blowing snow redistribution and sublimation from the wind-swept upper basin, as well as sublimation of canopy intercepted snow from the forest (about 17% of snowfall). At the basin scale, the model showed that evapotranspiration is the largest loss of water (47%), followed by streamflow (39%) and sublimation (14%). The models streamflow performance sensitivity to a set of parameter was analysed, as well as the mean annual mass balance uncertainty associated with these parameters.

Analysis and Predictability of the Hydrological Response of Mountain Catchments to Heavy Rain on Snow Events: A Case Study in the Spanish Pyrenees

From 18 to 19 June 2013, the Ésera river in the Pyrenees, Northern Spain, caused widespread damage due to flooding as a result of torrential rains and sustained snowmelt. We estimate the contribution of snow melt to total discharge applying a snow energy balance to the catchment. Precipitation is derived from sparse local measurements and the WRF-ARW model over three nested domains, down to a grid cell size of 2 km. Temperature profiles, precipitation and precipitation gradient are well simulated, although with a possible displacement regarding the observations. Snowpack melting was correctly reproduced and verified in three instrumented sites, and according to satellite images. We found that the hydrological simulations agree well with measured discharge. Snowmelt represented 33% of total runoff during the main flood event and 23% at peak flow. The snow energy balance model indicates that most of the energy for snow melt during the day of maximum precipitation came from turbulent fluxes. This approach forecast correctly peak flow and discharge during normal conditions at least 24 h in advance and could give an early warning of the extreme event 2.5 days before.

Estimation of Needleleaf Canopy and Trunk Temperatures and Longwave Contribution to Melting Snow

AbstractA measurement and modeling campaign evaluated variations in tree temperatures with solar exposure at the edge of a forest clearing and how the resulting longwave radiation contributed to spatial patterns of snowmelt energy surrounding an individual tree. Compared to measurements, both a one-dimensional (1D) energy-balance model and a two-dimensional (2D) radial trunk heat transfer model that simulated trunk surface temperatures and thermal inertia performed well (RMSE and biases better than 1.7° and ±0.4°C). The 2D model that resolved a thin bark layer better simulated daytime temperature spikes. Measurements and models agreed that trunk surfaces returned to ambient air temperature values near sunset. Canopy needle temperatures modeled with a 1D energy-balance approach were within the range of measurements. The radiative transfer model simulated substantial tree-contributed snow surface longwave irradiance to a distance of approximately one-half the tree height, with higher values on the sun-exposed sides of the tree. Trunks had very localized and substantially lower longwave energy influence on snowmelt compared to that of the canopy. The temperature and radiative transfer models provide the spatially detailed information needed to develop scaling relationships for estimating net radiation for snowmelt in sparse and discontinuous forest canopies.

Characterization of snowmelt flux and groundwater storage in an alpine headwater basin

Snowmelt recharge of groundwater and its delayed release is considered an important mechanism for sustaining the baseflow of alpine streams, but relatively little is known about groundwater storage capacity in alpine regions. The goal of this study is to quantify the storage capacity and the timing of recharge and discharge in a partially glaciated, first-order watershed in the Canadian Rockies using detailed measurements of hydrological input and output fluxes. We computed daily input fluxes from direct measurements of snow accumulation at 1300 points within the watershed near the peak accumulation date, time-lapse photography during the melt season, and high-resolution (25 m) snowmelt simulation using a field-validated snowmelt energy balance model; and estimated the amount and timing of water storage within the watershed from the water balance. The peak storage amount was on the order of 60–100 mm averaged over the watershed, which was relatively small compared to the pre-melt snow water equivalent in the watershed (500–640 mm), but significant in comparison to the fall and winter baseflow (<0.5 mm d−1) sustaining the aquatic ecosystem. This is an important finding demonstrating the critical role of groundwater storage and delayed release in alpine environments, which generally have little soil water storage.

Evaluation of a Two-Source Snow–Vegetation Energy Balance Model for Estimating Surface Energy Fluxes in a Rangeland Ecosystem

Abstract The utility of a snow–vegetation energy balance model for estimating surface energy fluxes is evaluated with field measurements at two sites in a rangeland ecosystem in southwestern Idaho during the winter of 2007: one site dominated by aspen vegetation and the other by sagebrush. Model parameterizations are adopted from the two-source energy balance (TSEB) modeling scheme, which estimates fluxes from the vegetation and surface substrate separately using remotely sensed measurements of land surface temperature. Modifications include development of routines to account for surface snowmelt energy flux and snow masking of vegetation. Comparisons between modeled and measured surface energy fluxes of net radiation and turbulent heat showed reasonable agreement when considering measurement uncertainties in snow environments and the simplified algorithm used for the snow surface heat flux, particularly on a daily basis. There was generally better performance over the aspen field site, likely due to more reliable input data of snow depth/snow cover. The model was robust in capturing the evolution of surface energy fluxes during melt periods. The model behavior was also consistent with previous studies that indicate the occurrence of upward sensible heat fluxes during daytime owing to solar heating of vegetation limbs and branches, which often exceeds the downward sensible heat flux driving the snowmelt. However, model simulations over aspen trees showed that the upward sensible heat flux could be reversed for a lower canopy fraction owing to the dominance of downward sensible heat flux over snow. This indicates that reliable vegetation or snow cover fraction inputs to the model are needed for estimating fluxes over snow-covered landscapes.

Approximating snow surface temperature from standard temperature and humidity data: New possibilities for snow model and remote sensing evaluation

[1] Snow surface temperature (Ts) is important to the snowmelt energy balance and land-atmosphere interactions, but in situ measurements are rare, thus limiting evaluation of remote sensing data sets and distributed models. Here we test simple Ts approximations with standard height (2–4 m) air temperature (Ta), wet-bulb temperature (Tw), and dew point temperature (Td), which are more readily available than Ts. We used hourly measurements from seven sites to understand which Ts approximation is most robust and how Ts representation varies with climate, time of day, and atmospheric conditions (stability and radiation). Td approximated Ts with the lowest overall bias, ranging from −2.3 to +2.6°C across sites and from −2.8 to 1.5°C across the diurnal cycle. Prior studies have approximated Ts with Ta, which was the least robust predictor of Ts at all sites. Approximation of Ts with Td was most reliable at night, at sites with infrequent clear sky conditions, and at windier sites (i.e., more frequent turbulent instability). We illustrate how mean daily Td can help detect surface energy balance bias in a physically based snowmelt model. The results imply that spatial Td data sets may be useful for evaluating snow models and remote sensing products in data sparse regions, such as alpine, cold prairie, or Arctic regions. To realize this potential, more routine observations of humidity are needed. Improved understanding of Td variations will advance understanding of Ts in space and time, providing a simple yet robust measure of snow surface feedback to the atmosphere.

Implications of mountain shading on calculating energy for snowmelt using unstructured triangular meshes

AbstractIn many parts of the world, snowmelt energetics is dominated by solar irradiance. This is particularly the case in the Canadian Rocky Mountains, where clear skies dominate the winter and spring. In mountainous regions, solar irradiance at the snow surface is not only affected by solar angles, atmospheric transmittance, the slope and aspect of immediate topography but also by shadows from surrounding terrain. Accumulation of errors in estimating solar irradiation can lead to significant errors in calculating the timing and rate of snowmelt owing to the seasonal storage of internal energy in the snowpack. Gridded methods, which are often used to estimate solar irradiance in complex terrain, work best with high‐resolution digital elevation models (DEMs), such as those produced using Light Detection and Ranging. However, such methods also introduce errors caused by the rigid nature of the mesh as well as limiting the ability to represent basin characteristics. Unstructured triangular meshes are more efficient in their use of DEM data than fixed grids when producing solar irradiance information for spatially distributed snowmelt calculations, and they do not suffer from the artefact problems of a gridded DEM. This paper demonstrates the increased accuracy of using a horizon‐shading algorithm model with an unstructured mesh versus standard self‐shading algorithms. A systematic over‐prediction in irradiance is observed when only self‐shadows are considered. The modelled results are diagnosed by comparison to measurements of mountain shadows by time‐lapse digital cameras and solar irradiance by a network of radiometers in Marmot Creek Research Basin, Alberta, Canada. Results show that, depending on the depth and aspect of the snowpack of the Mount Allan cirque, 6.0 to 66.4% of the pre‐melt snowpack could be prematurely melted. On average at a basin scale, there was a 14.4‐mm SWE difference in equivalent melt energy between the two shading algorithms with maximum differences over 100% of the total annual snowfall. Copyright © 2012 John Wiley &amp; Sons, Ltd.

The effect of peatland harvesting on snow accumulation, ablation and snow surface energy balance

AbstractSnow distribution, ablation and snowmelt energy balance components were characterized in a vacuum harvested and an adjacent undisturbed forested section of a peatland during the 2009 snowmelt period to determine snow distribution and melt dynamics on a previously harvested peatland, since abandoned and partly revegetated. The forested peatland had the deepest snowpack at 121 cm, particularly along the edge of the forested section adjacent to the more windblown previously harvested peatland. The snowpack density was greatest in the harvested peatland, which was subject to greater wind compaction and mid‐winter melt‐refreeze episodes; however, snow water equivalence was higher in the forested peatland. Radiative fluxes dominated the snowmelt energy balance. Increased canopy cover within the forested peatland restricted incident radiation and delayed melt, whereas melt rates were rapid across the harvested peatland, driven by higher radiant and turbulent fluxes. Ablation calculated using a simple, one‐dimensional model showed good temporal agreement with the observed ablation trends except when standing melt water pooled on the surface of the harvested section, causing more rapid modelled melt rates than observed. The shallower snowpack and more rapid melt across the harvested peatland limited the amount of melt water that was available for spring recharge. Copyright © 2012 John Wiley &amp; Sons, Ltd.

Equations to predict daily snowmelt energy in a deciduous fruit orchard

Equations to predict daily snowmelt energy in a deciduous fruit orchard

Snowmelt energy balance in a burned forest plot, Crowsnest Pass, Alberta, Canada

AbstractForested headwater basins in western North America are subject to major change from natural and anthropogenic disturbance, including wildfire, insect infestation, disease, and forest harvesting. These changes have subsequent impacts on sub‐canopy snow processes, particularly snow accumulation and melt, with cascading effects on downstream systems. We apply a simple, process‐based point energy balance model to quantify differences in energy balance characteristics between a burned and a control plot. In the burned plot, more snow accumulated on the ground surface, there was more energy available for snowmelt, the snow melted more rapidly, and complete snowpack removal occurred sooner than in the control plot. Although results are comparable to cleared forest stands, standing dead trees in burned forest stands attenuate incoming short‐wave radiation, wind speed, temperature, and snow accumulation on the surface to a greater degree than is observed in cleared stands. Copyright © 2011 John Wiley &amp; Sons, Ltd.

Effects of needleleaf forest cover on radiation and snowmelt dynamics in the Canadian Rocky Mountains

Radiation is the main energy source for snowpack warming and melt in mountain needleleaf forests, and runoff from these forests is the main contributor to spring river flows in western North America. Utilizing extensive field observations, the effect of needleleaf forest cover on radiation and snowmelt timing was quantified at pine and spruce forest sites and nearby clearings of varying slope and aspect in an eastern Canadian Rocky Mountain headwater basin. Compared with open clearing sites, shortwave radiation was much reduced under forest cover, resulting in smaller differences in melt timing between forested slopes relative to open slopes with different aspects. In contrast, longwave radiation to snow was substantially enhanced under forest cover, especially at the dense spruce forest sites where longwave radiation dominated total energy for snowmelt. In both pine and spruce environments, forest cover acted to substantially reduce total radiation to snow and delay snowmelt timing on south-facing slopes while increasing total radiation and advancing snowmelt timing on north-facing slopes. Results strongly suggest that impacts on radiation to snow and snowmelt timing from changes in mountain forest cover will depend much on the slope and aspect at which changes occur.

Role of Snow in Runoff Processes in a Subalpine Hillslope: Field Study in the Ward Creek Watershed, Lake Tahoe, California, during 2000 and 2001 Water Years

Field study is an essential component of hydrologic science because all hydrological studies must be conducted by such observation-based knowledge of real watersheds. Hillslope runoff processes have been intensively investigated, but the flow process at the boundary between the snowpack and ground surface has not been well documented. A field site at the northwest sector of the Ward Creek watershed, Lake Tahoe Basin, was built for observations of overland flow, subsurface stormflow, and channel flow, simultaneously with atmospheric measurements to examine the hydrology at a snow-covered hillslope. Also, the groundwater table under the snowpack was monitored by shallow wells at the hillslope. All field-measured atmospheric data were synthesized with an energy-balance snow model, and the snowmelt rate and energy balance were computed. The results of the analyses indicate that most of the snowmelt water infiltrated into the topsoil layers and that saturated subsurface flow was the largest contributor to the ...

Improvement of distributed snowmelt energy balance modeling with MODIS‐based NDSI‐derived fractional snow‐covered area data

AbstractDescribing the spatial variability of heterogeneous snowpacks at a watershed or mountain‐front scale is important for improvements in large‐scale snowmelt modelling. Snowmelt depletion curves, which relate fractional decreases in snow‐covered area (SCA) against normalized decreases in snow water equivalent (SWE), are a common approach to scale‐up snowmelt models. Unfortunately, the kinds of ground‐based observations that are used to develop depletion curves are expensive to gather and impractical for large areas. We describe an approach incorporating remotely sensed fractional SCA (FSCA) data with coinciding daily snowmelt SWE outputs during ablation to quantify the shape of a depletion curve. We joined melt estimates from the Utah Energy Balance Snow Accumulation and Melt Model (UEB) with FSCA data calculated from a normalized difference snow index snow algorithm using NASA's moderate resolution imaging spectroradiometer (MODIS) visible (0·545–0·565 µm) and shortwave infrared (1·628–1·652 µm) reflectance data. We tested the approach at three 500 m2 study sites, one in central Idaho and the other two on the North Slope in the Alaskan arctic. The UEB‐MODIS‐derived depletion curves were evaluated against depletion curves derived from ground‐based snow surveys. Comparisons showed strong agreement between the independent estimates. Copyright © 2010 John Wiley &amp; Sons, Ltd.