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1. The sensitivity of satellite microwave observations to liquid water in the Antarctic snowpack

   https://doi.org/10.5194/tc-16-5061-2022  

   Picard, Ghislain; Leduc-Leballeur, Marion; Banwell, Alison F.; Brucker, Ludovic; Macelloni, Giovanni (January 2022, The Cryosphere)

   Abstract. Surface melting on the Antarctic Ice Sheet has been monitored by satellite microwave radiometry for over 40 years. Despite this long perspective, our understanding of the microwave emission from wet snow is still limited, preventing the full exploitation of these observations to study supraglacial hydrology. Using the Snow Microwave Radiative Transfer (SMRT) model, this study investigatesthe sensitivity of microwave brightness temperature to snow liquid water content at frequencies from 1.4 to 37 GHz. We first determine the snowpack properties for eight selected coastal sites byretrieving profiles of density, grain size and ice layers from microwave observations when the snowpack is dry during wintertime. Second, a series of brightness temperature simulations is run with added water. The results show that (i) a small quantity of liquid water (≈0.5 kg m−2) can be detected, but the actual quantity cannot be retrieved out of the full range of possible water quantities; (ii) the detection of a buried wet layer is possible up to a maximum depth of 1 to 6 m depending on the frequency (6–37 GHz) and on the snow properties (grain size, density) at each site; (iii) surface ponds and water-saturated areas may prevent melt detection, but the current coverage of these waterbodies in the large satellite field of view is presently too small in Antarctica to have noticeable effects; and (iv) at 1.4 GHz, while the simulations are less reliable, we found a weaker sensitivity to liquid water and the maximal depth of detection is relatively shallow (<10 m) compared to the typical radiation penetration depth in dry firn (≈1000 m) at this low frequency. These numerical results pave the way for the development of improved multi-frequency algorithms to detect melt intensity and the depth of liquid water below the surface in the Antarctic snowpack. 

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2. Monitoring a snowpack’s ability to store liquid water at the small catchment scale

   https://doi.org/10.1190/gpr2020-027.1  

   Webb, Ryan; Musselman, Keith; Hale, Katherine; Molotch, Noah (November 2020, 18th International Conference on Ground Penetrating Radar)

   null (Ed.)

   An important consideration for water resources planning is runoff timing, which can be strongly influenced by the physical process of water storage within and release from seasonal snowpacks. The aim of this presentation is to introduce a novel method that combines light detection and ranging (LiDAR) with ground-penetrating radar (GPR) to nondestructively estimate the spatial distribution of bulk liquid water content in a seasonal snowpack during spring melt. This method was developed at multiple plots in Colorado in 2017 and applied at the small catchment scale in 2019. We developed this method in a manner to observe rapid changes that occur at subdaily timescales. Observed volumetric liquid water contents ranged from near zero to 19%vol within the scale of meters during method development. We also show rapid changes in bulk liquid water content of up to 5%vol that occur over subdaily timescales. The presented methods have an average uncertainty in bulk liquid water content of 1.5%vol, making them applicable for studies to estimate the complex spatio-temporal dynamics of liquid water in snow. During the spring snowmelt season of 2019, we applied this method to a small headwater catchment in the Colorado Front Range. A total of 9 GPR surveys of approximately 3 km in length were conducted over a six-week period. Additionally, five LiDAR scans occurred over the same area. Using this technique, we identify locations that melting snow accumulates and is stored as liquid water within the snowpack. This work shows that the vadose zone may be conceptualized, during snowmelt, as extending above the soil-snow interface to include variably saturated flow processes within the snowpack. 

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3. Long-term measurements of seasonal snowpacks indicate increases in mid-winter snowmelt and earlier snowpack disappearance in the northeastern U.S.

   https://doi.org/10.1371/journal.pclm.0000529  

   Wilson, Geoff; Green, Mark; Campbell, John; Contosta, Alix; Lany, Nina; Bailey, Amey (December 2024, PLOS Climate)

   Ai, Zhipin (Ed.)

   Snowpacks are changing in northeastern North America as the regional climate warms, yet the relative influence of changes in precipitation compared to changes in ablation on snowpacks is poorly understood. We use 56 years of weekly snow water equivalent (SWE) measurements from three locations within a study site which vary in elevation and aspect, paired with adjacent daily climate measurements, to investigate relationships between climate and snowpack onset, maximum, and disappearance. Maximum snowpack size and snowpack duration are shrinking at all sites, at rates ranging from 4.3 days/decade at the coldest site to 9.6 days/decade at the warmest site. The shorter snowpack duration at all sites results from an earlier snowpack disappearance, stemming largely from reduced winter maximum snowpack sizes. Trends in snowpack establishment dates vary, with the south-facing site showing a trend toward later establishment but the two north-facing sites showing no change. The date of the maximum snowpack size varies by aspect and elevation but is not changing at any site. Using a 0° C threshold for frozen vs. liquid precipitation, we only observed a decrease in the proportion of precipitation falling in frozen form at the warmer, south-facing site in the winter period. In contrast, the total weekly snowpack ablation in the winter period has been increasing at least marginally at each site, even at sites which do not show increases in thawing conditions. Ablation increases range from 0.4 cm/decade at the warmest site, to 1.4 and 1.2 cm/decade at the north-facing sites. The south-facing site shows only marginally significant trends in total winter ablation, which we interpret as being limited by the smaller snowpack at this site. Overall, we conclude that rising air temperatures are leading to warmer, more sensitive snowpacks and this change becomes evident before those temperatures lead to changes in precipitation form. 

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4. Isolating forest process effects on modelled snowpack density and snow water equivalent

   https://doi.org/10.1002/hyp.14475  

   Bonner, Hannah M.; Raleigh, Mark S.; Small, Eric E. (January 2022, Hydrological Processes)

   Abstract Understanding how the presence of a forest canopy influences the underlying snowpack is critical to making accurate model predictions of bulk snow density and snow water equivalent (SWE). To investigate the relative importance of forest processes on snow density and SWE, we applied the SUMMA model at three sites representing diverse snow climates in Colorado (USA), Oregon (USA), and Alberta (Canada) for 5 years. First, control simulations were run for open and forest sites. Comparisons to observations showed the uncalibrated model with NLDAS‐2 forcing performed reasonably. Then, experiments were completed to isolate how forest processes affected modelled snowpack density and SWE, including: (1) mass reduction due to interception loss, (2) changes in the phase and amount of water delivered from the canopy to the underlying snow, (3) varying new snow density from reduced wind speed, and (4) modification of incoming longwave and shortwave radiation. Delivery effects (2) increased forest snowpack density relative to open areas, often more than 30%. Mass effects (1) and wind effects (3) decreased forest snowpack density, but generally by less than 6%. The radiation experiment (4) yielded negligible to positive effects (i.e., 0%–10%) on snowpack density. Delivery effects on density were greatest at the warmest times in the season and at the warmest site (Oregon): higher temperatures increased interception and melted intercepted snow, which then dripped to the underlying snowpack. In contrast, mass effects and radiation effects were shown to have the greatest impact on forest‐to‐open SWE differences, yielding differences greater than 30%. The study highlights the importance of delivery effects in models and the need for new types of observations to characterize how canopies influence the flux of water to the snow surface. 

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5. Antecedent Snowpack Cold Content Alters the Hydrologic Response to Extreme Rain-on-Snow Events

   https://doi.org/10.1175/JHM-D-22-0090.1  

   Katz, Lisa; Lewis, Gabriel; Krogh, Sebastian; Drake, Stephen; Hanan, Erin; Hatchett, Benjamin; Harpold, Adrian (October 2023, Journal of Hydrometeorology)

   Abstract Predicting winter flooding is critical to protecting people and securing water resources in California’s Sierra Nevada. Rain-on-snow (ROS) events are a common cause of widespread flooding and are expected to increase in both frequency and magnitude with anthropogenic climate change in this region. ROS flood severity depends on terrestrial water input (TWI), the sum of rain and snowmelt that reaches the land surface. However, an incomplete understanding of the processes that control the flow and refreezing of liquid water in the snowpack limits flood prediction by operational and research models. We examine how antecedent snowpack conditions alter TWI during 71 ROS events between water years 1981 and 2019. Observations across a 500-m elevation gradient from the Independence Creek catchment were input into SNOWPACK, a one-dimensional, physically based snow model, initiated with the Richards equation and calibrated with collocated snow pillow observations. We compare observed “historical” and “scenario” ROS events, where we hold meteorologic conditions constant but vary snowpack conditions. Snowpack variables include cold content, snow density, liquid water content, and snow water equivalent. Results indicate that historical events with TWI > rain are associated with the largest observed streamflows. A multiple linear regression analysis of scenario events suggests that TWI is sensitive to interactions between snow density and cold content, with denser (>0.30 g cm⁻³) and colder (<−0.3 MJ of cold content) snowpacks retaining >50 mm of TWI. These results highlight the importance of hydraulic limitations in dense snowpacks and energy limitations in warm snowpacks for retaining liquid water that would otherwise be available as TWI for flooding. Significance StatementThe purpose of this study is to understand how the snowpack modulates quantities of water that reach the land surface during rain-on-snow (ROS) events. While the amount of near-term storm rainfall is reasonably predicted by meteorologists, major floods associated with ROS are more difficult to predict and are expected to increase in frequency. Our key findings are that liquid water inputs to the land surface vary with snowpack characteristics, and although many hydrologic models incorporate snowpack cold content and density to some degree, the complexity of ROS events justifies the need for additional observations to improve operational forecasting model results. Our findings suggest additional comparisons between existing forecasting models and those that physically represent the snowpack, as well as field-based observations of cold content and density and liquid water content, would be useful follow-up investigations. 

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