Estimation of Continental-Basin-Scale Sublimation in the Lena River Basin, Siberia

The Lena River basin in Siberia produces one of the largest river inflows into the Arctic Ocean. One of the most important sources of runoff to the river is spring snowmelt and therefore snow ablation processes have great importance for this basin. In this study, we simulated these processes with fine resolution at basin scale using MicroMet/SnowModel and SnowAssim. To assimilate snow water equivalent (SWE) data in SnowAssim, we used routine daily snow depth data and Sturm’s method. Following the verification of this method for SWE estimation in the basin, we evaluated the impact of snow data assimilation on basin-scale snow ablation. Through validation against MODIS snow coverage data and in situ snow survey observations, we found that SnowAssim could not improve on the original simulation by MicroMet/SnowModel because of estimation errors within the SWE data. Vegetation and accumulated snowfall control the spatial distribution of sublimation and we established that sublimation has an important effect on snow ablation. We found that the ratio of sublimation to snowfall in forests was around 26% and that interannual variation of sublimation modulated spring river runoff

Modeling Snow Depth for Improved Simulation of Snow–Vegetation–Atmosphere Interactions

The presence of snow and its relationship to surrounding vegetation significantly impacts the surface energy balance. For accurate atmospheric model simulations, the degree to which a snowpack can cover vegetation must be realistically represented. Both vegetation height and snow depth must be reasonably known to determine the amount of masking. The Regional Atmospheric Modeling System/Land Ecosystem–Atmosphere Feedback, version two (RAMS/ LEAF-2) snow model was modified to simulate snow depth in addition to snow water equivalent and was driven offline with observed atmospheric forcing data. The model was run for five of the Boreal Ecosystem–Atmosphere Study (BOREAS) surface mesonet stations over the 1995/96 winter. The time evolution of simulated snow depth was compared with the observed snow depth. Averaged over the winter, the modeled snow depth at the four low-wind stations was within 0.09 m of the observations, and the average percent error was 27%, while the one wind-blown station was considerably worse. The average depth error at all five stations was 60.08 m. This is shown to be sufficient to reasonably account for the surface energy balance effects of vegetation protruding through the snow. 1

Distributed Modeling of Ablation (1996–2011) and Climate Sensitivity on the Glaciers of Taylor Valley, Antarctica

The McMurdo Dry Valleys of Antarctica host the coldest and driest ecosystem on Earth, which is acutely sensitive to the availability of water coming from glacial runoff. We modeled the spatial variability in ablation and assessed climate sensitivity of the glacier ablation zones using 16 years of meteorological and surface mass-balance observations collected in Taylor Valley. Sublimation was the primary form of mass loss over much of the ablation zones, except for near the termini where melt, primarily below the surface, dominated. Microclimates in ~10 m scale topographic basins generated melt rates up to ten times higher than over smooth glacier surfaces. In contrast, the vertical terminal cliffs on the glaciers can have higher or lower melt rates than the horizontal surfaces due to differences in incoming solar radiation. The model systematically underpredicted ablation for the final 5 years studied, possibly due to an increase of windblown sediment. Surface mass-balance sensitivity to temperature was ~−0.02 m w.e. K−1, which is among the smallest magnitudes observed globally. We also identified a high sensitivity to ice albedo, with a decrease of 0.02 having similar effects as a 1 K increase in temperature, and a complex sensitivity to wind speed

Simulations of snow distribution and hydrology in a mountain basin

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

Assimilating MODIS and AMSR-E Snow Observations in a Snow Evolution Model

In this paper four simple computationally inexpensive, direct insertion data assimilation schemes are presented, and evaluated, to assimilate Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover, which is a binary observation, and Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E) snow water equivalent (SWE) observations, which are at a coarser resolution than MODIS, into a numerical snow evolution model. The four schemes are 1) assimilate MODIS snow cover on its own with an arbitrary 0.01 m added to the model cells if there is a difference in snow cover; 2) iteratively change the model SWE values to match the AMSR-E equivalent value; 3) AMSR-E scheme with MODIS observations constraining which cells can be changed, when both sets of observations are available; and 4) MODIS-only scheme when the AMSR-E observations are not available, otherwise scheme 3. These schemes are used in the winter of 2006/07 over the southeast corner of Colorado and the tri-state area: Wyoming, Colorado, and Nebraska. It is shown that the inclusion of MODIS data enables the model in the north domain to have a 15% improvement in number of days with a less than 10% disagreement with the MODIS observation 24 h later and approximately 5% for the south domain. It is shown that the AMSR-E scheme has more of an impact in the south domain than the north domain. The assimilation results are also compared to station snow-depth data in both domains, where there is up-to-a-factor-of-5 underestimation of snow depth by the assimilation schemes compared with the station data but the snow evolution is fairly consistent

Near-Surface Internal Melting: a Substantial Mass Loss on Antarctic Dry Valley Glaciers

The McMurdo Dry Valleys, southern Victoria Land, East Antarctica, are a polar desert, and melt from glacial ice is the primary source of water to streams, lakes and associated ecosystems. Previous work found that to adequately model glacier ablation and subsurface ice temperatures with a surface energy-balance model required including the transmission of solar radiation into the ice. Here we investigate the contribution of subsurface melt to the mass balance of (and runoff from) Dry Valley glaciers by including a drainage process in the model and applying the model to three glacier sites using 13years of hourly meteorological data. Model results for the smooth glacier surfaces common to many glaciers in the Dry Valleys showed that sublimation was typically the largest component of surface lowering, with rare episodes of surface melting, consistent with anecdotal field observations. Results also showed extensive internal melting 5-15 cm below the ice surface, the drainage of which accounted for 50% of summer ablation. This is consistent with field observations of subsurface streams and formation of a weathering crust. We identify an annual cycle of weathering crust formation in summer and its removal during the 10 months of winter sublimation

Interpreting Sentinel-1 SAR Backscatter Signals of Snowpack Surface Melt/Freeze, Warming, and Ripening, Through Field Measurements and Physically-Based SnowModel

The transition of a cold winter snowpack to one that is ripe and contributing to runoff is crucial to gauge for water resource management, but is highly variable in space and time. Snow surface melt/freeze cycles, associated with diurnal fluctuations in radiative inputs, are hallmarks of this transition. C-band synthetic aperture radar (SAR) reliably detects meltwater in the snowpack. Sentinel-1 (S1) C-band SAR offers consistent acquisition patterns that allow for diurnal investigations of melting snow. We used over 50 snow pit observations from 2020 in Grand Mesa, Colorado, USA, to track temperature and wetness in the snowpack as a function of depth and time during snowpack phases of warming, ripening, and runoff. We also ran the physically-based SnowModel, which provided a spatially and temporally continuous independent indication of snowpack conditions. Snowpack phases were identified and corroborated by comparing field measurements with SnowModel outputs. Knowledge of snowpack warming, ripening, and runoff phases was used to interpret diurnal changes in S1 backscatter values. Both field measurements and SnowModel simulations suggested that S1 SAR was not sensitive to the initial snowpack warming phase on Grand Mesa. In the ripening and runoff phases, the diurnal cycle in S1 SAR co-polarized backscatter was affected by both surface melt/freeze as well as the conditions of the snowpack underneath (ripening or ripe). The ripening phase was associated with significant increases in morning backscatter values, likely due to volume scattering from surface melt/freeze crusts, as well as significant decreases in evening backscatter values associated with snowmelt. During the runoff phase, both morning and evening backscatter decreased compared to reference values. These unique S1 diurnal signatures, and their interpretations using field measurements and SnowModel outputs, highlight the capacities and limitations of S1 SAR to understand snow surface states and bulk phases, which may offer runoff forecasting or energy balance model validation or parameterization, especially useful in remote or sparsely-gauged alpine basins

A Changing Hydrological Regime: Trends in Magnitude and Timing of Glacier Ice Melt and Glacier Runoff in a High Latitude Coastal Watershed

With a unique biogeophysical signature relative to other freshwater sources, meltwater from glaciers plays a crucial role in the hydrological and ecological regime of high latitude coastal areas. Today, as glaciers worldwide exhibit persistent negative mass balance, glacier runoff is changing in both magnitude and timing, with potential downstream impacts on infrastructure, ecosystems, and ecosystem resources. However, runoff trends may be difficult to detect in coastal systems with large precipitation variability. Here, we use the coupled energy balance and water routing model SnowModel-HydroFlow to examine changes in timing and magnitude of runoff from the western Juneau Icefield in Southeast Alaska between 1980 and 2016. We find that under sustained glacier mass loss (−0.57 ± 0.12 m w. e. a−1), several hydrological variables related to runoff show increasing trends. This includes annual and spring glacier ice melt volumes (+10% and +16% decade−1) which, because of higher proportions of precipitation, translate to smaller increases in glacier runoff (+3% and +7% decade−1) and total watershed runoff (+1.4% and +3% decade−1). These results suggest that the western Juneau Icefield watersheds are still in an increasing glacier runoff period prior to reaching “peak water.” In terms of timing, we find that maximum glacier ice melt is occurring earlier (2.5 days decade−1), indicating a change in the source and quality of freshwater being delivered downstream in the early summer. Our findings highlight that even in maritime climates with large precipitation variability, high latitude coastal watersheds are experiencing hydrological regime change driven by ongoing glacier mass loss.The authors would like to thank W. P. Dryer, C. McNeil, S. Candela, and J. Pierce for help in the field. R. Crumley and C. Cosgrove assisted with SnowModel initialization. The Juneau Icefield Research Program (JIRP) provided field data and logistical support. E. Berthier provided geodetic data, F. Ziemen contributed model results, and C. McNeil provided assistance with datasets on behalf of both USGS and JIRP. The authors thank three anonymous reviewers for suggestions that have greatly improved the manuscript. This work was supported by a Department of Interior Alaska Climate Adaptation Science Center graduate fellowship awarded under Cooperative Agreement G17AC00213, by NASA under award NASANNX16AQ88G, by the National Science Foundation under award OIA-1208927 and by the State of Alaska (Experimental Program for Stimulating Competitive Research–Alaska Adapting to Changing Environments award), and by the University of Alaska Fairbanks Resilience and Adaptation Program. The authors acknowledge that field work was conducted on the traditional and unceded lands of the Lingit Aani (Tlingit), Michif Piyii (Métis), and Dënéndeh nations.Ye