Spectral Profiler Probe for In Situ Snow Grain Size and Composition Stratigraphy

An ultimate goal of the climate change, snow science, and hydrology communities is to measure snow water equivalent (SWE) from satellite measurements. Seasonal SWE is highly sensitive to climate change and provides fresh water for much of the world population. Snowmelt from mountainous regions represents the dominant water source for 60 million people in the United States and over one billion people globally. Determination of snow grain sizes comprising mountain snowpack is critical for predicting snow meltwater runoff, understanding physical properties and radiation balance, and providing necessary input for interpreting satellite measurements. Both microwave emission and radar backscatter from the snow are dominated by the snow grain size stratigraphy. As a result, retrieval algorithms for measuring snow water equivalents from orbiting satellites is largely hindered by inadequate knowledge of grain size

Snowpack regimes of the Western United States

Snow accumulation and melt patterns play a significant role in the water, energy, carbon, and nutrient cycles in the montane environments of the Western United States. Recent studies have illustrated that changes in the snow/rainfall apportionments and snow accumulation and melt patterns may occur as a consequence of changes in climate in the region. In order to understand how these changes may affect the snow regimes of the region, the current characteristics of the snow accumulation and melt patterns must be identified. Here we characterize the snow water equivalent (SWE) curve formed by the daily SWE values at 766 snow pillow stations in the Western United States, focusing on several metrics of the yearly SWE curves and the relationships between the different metrics. The metrics are the initial snow accumulation and snow disappearance dates, the peak snow accumulation and date of peak, the length of the snow accumulation season, the length of the snowmelt season, and the snow accumulation and snowmelt slopes. Three snow regimes emerge from these results: a maritime, an intermountain, and a continental regime. The maritime regime is characterized by higher maximum snow accumulations reaching 300 cm and shorter accumulation periods of less than 220 days. Conversely, the continental regime is characterized by lower maximum accumulations below 200 cm and longer accumulation periods reaching over 260 days. The intermountain regime lies in between. The regions that show the characteristics of the maritime regime include the Cascade Mountains, the Klamath Mountains, and the Sierra Nevada Mountains. The intermountain regime includes the Eastern Cascades slopes and foothills, the Blue Mountains, Northern and Central basins and ranges, the Columbia Mountains/Northern Rockies, the Idaho Batholith, and the Canadian Rockies. Lastly, the continental regime includes the Middle and Southern Rockies, and the Wasatch and Uinta Mountains. The implications of snow regime classification are discussed in the context of possible changes in accumulation and melt patterns associated with regional warming

Record-setting forest stress in the Rocky Mountains caused by low snowfall and high potential evapotranspiration, consistent with expected future conditions

Projections of future climate for the Southwestern U.S. and other semi-arid regions globally include reductions in mountain snow accumulation and increased summer potential evapotranspiration. These changes may significantly alter runoff production, evapotranspiration, and gross primary productivity in mountain forests. Analysis of remotely sensed vegetation greenness data indicate strong forest and understory growth dependencies associated with snow accumulation and snowmelt with peak snow water equivalent explaining 40-50% of inter-annual variability in forest greenness in the Sierra Nevada and Rocky Mountains. Examples of these dependencies will be presented based on the 2012 drought in the Southwestern US whereby near record low snow accumulation and record high potential evapotranspiration have resulted in record low forest greening as evident in the 30+ year satellite record. Forest response to aridity in 2012 was exacerbated by forest disturbance with greenness anomalies 90% greater in magnitude in Bark Beetle and Spruce Budworm affected areas versus undisturbed areas and 182% greater in magnitude in areas impacted by fire. Given potential future changes in the hydroclimatology of mountainous regions, the results of these measurements may identify tipping points regarding ecosystem responses to water availability across gradients in physiography

Topoclimate effects on growing season length and montane conifer growth in complex terrain

Spatial variability in the topoclimate-driven linkage between forest phenology and tree growth in complex terrain is poorly understood, limiting our understanding of how ecosystems function as a whole. To characterize the influence of topoclimate on phenology and growth, we determined the start, end, and length of the growing season (GS(start), GS(end), and GSL, respectively) using the correlation between transpiration and evaporative demand, measured with sapflow. We then compared these metrics with stem relative basal area increment (relative BAI) at seven sites among elevation and aspects in a Colorado montane forest. As elevation increased, we found shorter GSL (-50 d km(-1)) due to later GS(start) (40 d km(-1)) and earlier GS(end) (-10 d km(-1)). North-facing sites had a 21 d shorter GSL than south-facing sites at similar elevations (i.e. equal to 200 m elevation difference on a given aspect). Growing season length was positively correlated with relative BAI, explaining 83% of the variance. This study shows that topography exerts strong environmental controls on GSL and thus forest growth. Given the climate-related dependencies of these controls, the results presented here have important implications for ecosystem responses to changes in climate and highlight the need for improved phenology representation in complex terrain

Objective Characterization of Snow Microstructure for Microwave Emission Modeling

Passive microwave (PM) measurements are sensitive to the presence and quantity of snow, a fact that has long been used to monitor snowcover from space. In order to estimate total snow water equivalent (SWE) within PM footprints (on the order of approx 100 sq km), it is prerequisite to understand snow microwave emission at the point scale and how microwave radiation integrates spatially; the former is the topic of this paper. Snow microstructure is one of the fundamental controls on the propagation of microwave radiation through snow. Our goal in this study is to evaluate the prospects for driving the Microwave Emission Model of Layered Snowpacks with objective measurements of snow specific surface area to reproduce measured brightness temperatures when forced with objective measurements of snow specific surface area (S). This eliminates the need to treat the grain size as a free-fit parameter

Impacts of increasing aridity and wildfires on aerosol loading in the intermountain Western US

Feedbacks between climate warming, land surface aridity, and wildfire-derived aerosols represent a large source of uncertainty in future climate predictions. Here, long-term observations of aerosol optical depth, surface level aerosol loading, fire-area burned, and hydrologic simulations are used to show that regional-scale increases in aridity and resulting wildfires have significantly increased summertime aerosol loading in remote high elevation regions of the Intermountain West of the United States. Surface summertime organic aerosol loading and total aerosol optical depth were both strongly correlated (p < 0.05) with aridity and fire area burned at high elevation sites across major western US mountain ranges. These results demonstrate that surface-level organic aerosol loading is dominated by summertime wildfires at many high elevation sites. This analysis provides new constraints for climate projections on the influence of drought and resulting wildfires on aerosol loading. These empirical observations will help better constrain projected increases in organic aerosol loading with increased fire activity under climate change

Algae drive enhanced darkening of bare ice on the Greenland ice sheet

Surface ablation of the Greenland ice sheet is amplified by surface darkening caused by light-absorbing impurities such as mineral dust, black carbon, and pigmented microbial cells. We present the first quantitative assessment of the microbial contribution to the ice sheet surface darkening, based on field measurements of surface reflectance and concentrations of light-absorbing impurities, including pigmented algae, during the 2014 melt season in the southwestern part of the ice sheet. The impact of algae on bare ice darkening in the study area was greater than that of non-algal impurities and yielded a net albedo reduction of 0.038 ± 0.0035 for each algal population doubling. We argue that algal growth is a crucial control of bare ice darkening, and incorporating the algal darkening effect will improve mass balance and sea level projections of the Greenland ice sheet and ice masses elsewhere

Testing Above- and Below-Canopy Representations of Turbulent Fluxes in an Energy Balance Snowmelt Model

Turbulent fluxes of sensible and latent heat are important processes in the surface energy balance that drives snowmelt. Modeling these fluxes in a forested environment is complicated because of the canopy effects on the wind field. This paper presents and tests a turbulent flux model developed to represent these processes in an energy balance snowmelt model. The goal is to model these processes using the readily available inputs of canopy height and leaf area index in a way that minimizes the number of parameters, state variables, and assumptions about hard to quantify processes. Selected periods from 9 years of eddy-covariance (EC) measurements at Niwot Ridge, Colorado, were used to evaluate the effectiveness of this modeling approach. The model was able to reproduce the above-canopy sensible and latent heat fluxes reasonably with the correlation higher for sensible heat than latent heat. The modeled values of the below-canopy latent heat fluxes also matched the EC-measured values. The model captured the nighttime below-canopy sensible heat flux quite well, but there were discrepancies in daytime sensible heat flux possibly due to mountain slope circulation not quantifiable in this kind of model. Despite the uncertainties in the below-canopy sensible heat fluxes, the results are encouraging and suggest that reasonable predictions of turbulent flux energy exchanges and subsequent vapor losses from snow in forested environments can be obtained with a parsimonious single-layer representation of the canopy. The model contributes an improved physically based capability for predicting the snow accumulation and melt in a forested environment