1.2. Hydrometeorological and Societal Impacts of Snow and Ice Changes in Arctic and Alpine Regions

28 March 2025 | 10:30 - 12:00 (MDT)

Open Session - HYBRID

Room:  UMC Third Floor - 386

Organisers:  Kabir Rasouli (Desert Research Institute, USA); Greta Wells (University of Iceland, Iceland); Philip Marsh (Wilfred Laurier University, Canada)

Session Description:

Snow and ice cover play an important role in controlling land-atmosphere interaction, influencing climate variability at regional and global scales, sustaining water resources and impacting ecological integrity. Hydrologic and geomorphic processes are rapidly changing in Arctic and alpine regions, and the frequency of geohazards such as rain on snow floods, sudden melt and thaw events, catastrophic drainage of thermokarst lakes, and glacial lake outburst floods increase in response to climate and terrestrial changes. We cordially invite researchers, scientists and practitioners to contribute to this session to investigate the links between cryospheric, hydrologic, terrestrial, and societal systems. We are particularly interested in, but not limited to, studies that can:

• Improve our understanding of cryospheric and hydrogeomorphic processes in Arctic and alpine environments
• Advance knowledge of hydrologic, geomorphic, and societal impacts of climate change in cryospheric regions
• Provide sustainable and adaptive strategies to mitigate the societal impacts of snow and ice-related geohazards

This session covers a broad scope of topics and methods, including remote sensing, numerical or statistical modeling, and experimental or theoretical approaches for diagnosing or predicting changes, understanding extreme events, and providing sustainable adaptation strategies for hydrologic and geomorphic systems. We will have a group discussion at the end of the session to discuss contributions to ICARP research priorities and implementation. Though most closely aligned with ICARP RPT 1, this session can contribute to multiple other RPTs, especially 2, 3, and 7, as well as the sub-theme of the role of Arctic terrestrial systems in global change at the 2025 ASSW meeting.

Instructions for Speakers:  Oral presentations in this session should be at most 12-minutes in length, with an additional 3 minutes for questions (unless more detailed instructions are provided by session conveners). See more detailed presenter instructions here.

Oral Presentations: 

• unfold_moreUnderstanding ice, snow, and permafrost conditions in McGarth, Alaska and Bayanzurkh, Mongolia using remote sensing and machine learning  —  Paulina Mnev

  Paulina Mnev ¹;  Kelsey Nyland ¹;  Vera Kuklina ¹;  Ryan Engstrom ^{1
  1} The George Washington University

  Format: Oral in-person

  Abstract:

  Changes in snow, ice, and permafrost conditions pose risks for local ecosystems and traditional livelihoods, underscoring the need for adaptive strategies. Remote sensing helps us understand and assess these conditions when other data are unavailable. This work focuses on remote Arctic and subarctic regions: McGrath, Alaska, and Bayanzürkh, Mongolia. Both communities have experienced climate warming since the mid-20th century and rely on snow and ice for transportation and traditional subsistence practices including hunting and herding. Half of McGrath’s population identifies as Alaska Natives and belong to the Tanana Chiefs Conference (TCC) tribal consortium, while most residents of Bayanzürkh are Indigenous Darkhad and Dukha herders in the Khövsgöl Aimag. Our methodology integrates remote sensing, statistical modeling, and meteorological data to assess the duration of snow cover and river ice. For understanding snow and ice conditions, we utilized the MODIS Snow Map product from 2001-2023 covering the TCC Upper Kuskokwim region and the Khövsgöl Aimag. Future work will use machine learning techniques to analyze SPOT imagery from McGrath and Bayanzürkh, captured during the summer months of 2021 and 2022, to classify permafrost conditions in these settlement regions. Both imagery analyses can be replicated in other regions where there is limited access to data on snow and ice cover duration or permafrost conditions. Results can inform stakeholders on how and where they can plan future infrastructure projects and adaptation strategies under a changing climate. With community guidance, future work can examine other characteristics of snow, ice, and permafrost conditions relevant for local use. 

• unfold_moreGroundwater Monitoring in Cold Regions; Sentinels of Climate Change — Jeffrey McKenzie

  Jeffrey McKenzie ¹;  Brendan Mulligan ^{2
  1} McGill University; ² Government of Yukon – Water Resources Branch

  Format: Oral in-person

  Abstract:

  In Arctic, Subarctic, and Alpine regions, groundwater and surface water form a single water resource that is vulnerable to climate change, including snow and permafrost changes. Across Alaska, the Yukon, Northwest Territories, and Nunavut, almost 50% of the population rely on groundwater for their drinking water supply, including 97% of Yukoners. There are concerns for Northern groundwater due to climate change, including changing quantities and potential anthropogenic and geogenic contamination. We present results from the Yukon Observation Well Network (YOWN), a unique observatory for monitoring climate change impacts on northern groundwater. The YOWN was adapted from a small Yukon-wide observation program that started with one observation well in 2001. The network is rapidly growing, now with more than 60 wells between 60.04º and 67.57º North, with continuous water level observations and periodic water quality measurements. Results from YOWN show that groundwater levels follow seasonal and local climate trends, particularly with snow melt. Broadly, the YOWN wells show different responses to climatic trends: many wells show large recharge events during snowmelt or driven by storm event precipitation in the late summer and fall seasons. However, some observations well show that the snowpack from an antecedent winter is the primary control on a subsequent year’s groundwater levels. This ‘groundwater staircase’ leads to multi-year changes in groundwater levels and demonstrate that change cryosphere and snow conditions affects groundwater systems. The results establish that groundwater observations not only reflect climate change impacts but are sentinels of ongoing environmental change.

• unfold_moreEnhancing Snow Cover Representation in CLM5 with High-Resolution Datasets — Johanna Malle

  Johanna Malle ¹;  Giulia Mazzotti ^2,3,4;  Dirk Karger ⁵;  Gabriela Schaepman-Strub ⁶;  Tobias Jonas ^{2
  1} Department of Evolutionary Biology and Environmental Studies, University of Zurich, Switzerland; ² WSL Institute for Snow and Avalanche Research, Switzerland; ³ Univ. Grenoble Alpes, Université de Toulouse, France; ⁴ Centre d’Études de la Neige, France; ⁵ Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), Switzerland; ⁶ Department of Evolutionary Biology and Environmental Studies, University of Zurich, Switzerland

  Format: Oral in-person

  Abstract:

  Cryospheric processes vary considerably at small spatial and temporal scales, in particular in mountainous terrain and complex topography. This variability remains challenging to represent in land surface models intended for global applications. To examine the impact of spatial resolution and representativeness of input data on modeled cryospheric as well as interrelated ecophysiological processes, we conducted simulations using the Community Land Model 5 (CLM5) at different resolutions and based on a range of input datasets over the spatial extent of Switzerland as well as at selected Arctic sites. Using high-resolution meteorological forcing data specifically optimized for snow simulations in alpine terrain as well as high-resolution land use data, we found that increased resolution substantially improved the representation of snow cover in CLM5 (up to 52 % enhancement), allowing CLM5 to closely match the performance of a dedicated snow model. However, a simple lapse-rate-based temperature downscaling provided large positive effects on model performance, even if simulations were based on coarse-resolution forcing datasets only. Results demonstrate the need for resolutions higher than 0.25° for accurate snow simulations in topographically complex terrain. These findings carry significant implications for climate impact assessments in alpine and arctic regions, particularly regarding hydrometeorological responses to snow changes.

• unfold_moreMonitoring high latitude snow depths using small, cheap, and easy-to-deploy ground surface temperature sensors — Claire Bachand

  Claire Bachand ¹;  Chen Wang ²;  Baptiste Dafflon ²;  Lauren Thomas ^3,4;  Ian Shirley ²;  Sarah Maebius ^4,5;  Colleen Iversen ⁶;  Katrina Bennett ^{4
  1} University of Alaska, Fairbanks; ² Lawrence Berkeley National Lab; ³ University of Colorado, Boulder; ⁴ Los Alamos National Lab; ⁵ Princeton University; ⁶ Oak Ridge National Lab

  Format: Oral in-person

  Abstract:

  Changing snow patterns in the Arctic disrupt transportation networks, permafrost stability, wildlife migrations, fishing, hunting, and more. However, Arctic snow depths vary at fine spatial scales due to snow drifting, so adequately characterizing changing snow depths requires a network of observations across space and time. Instruments commonly used for monitoring snow depth (e.g. snow sonic sensors) are expensive and time consuming to deploy, limiting such networks. To address this challenge, we assessed whether snow depth can be estimated from ground surface temperatures alone. Snow is an insulator and decreases ground surface temperature variability. Snow properties (including depth) modulate this dampening effect, which led us to hypothesize that ground surface temperatures can provide a predictive understanding of snow depth. We trained a machine learning model to predict snow depth from ground surface temperature data. The model performed well (RMSE

• unfold_moreImproved snow distribution for the Arctic — Katrina Bennett

  Katrina Bennett ¹;  Claire Bachand ²;  Rich Fiorella ¹;  Cade Trotter ¹;  Ryan Crumley ¹;  Chen Wang ³;  Baptiste Dafflon ³;  Ben Sulman ⁴;  Peter Thornton ⁴;  Colleen Iversen ^{4
  1} Los Alamos National Lab; ² University of Alaska Fairbanks; ³ Lawrence Berkeley National Lab; ⁴ Oak Ridge National Lab

  Format: Oral in-person

  Abstract:

  Snow is a fundamental control on Arctic and subarctic processes, including surface and subsurface energy, water, and carbon balances. The distribution of Arctic snow is an important driver of subsurface thermal regimes, including permafrost temperatures, as deeper snow acts to insulate the subsurface like a blanket. Snow distribution also interacts with vegetation dynamics, leading to the entrainment of snow within shrub patches, increasing soil moisture and leading to feedbacks that can enhance shrub growth. As the climate shifts, an acceleration of the Arctic hydrologic cycle has led to increased snow and shrubification—expansion and enlargement of shrubs within Arctic ecosystems. However, Arctic processes related to subgrid-scale snow distribution are not well represented within Earth system models, leading to potential errors in both permafrost thaw and associated carbon dynamics. Here, we introduce a version of the land model component of the Energy Exascale Earth System Model (E3SM), ELM, with improved snow representation for Arctic ecosystems. Through intercomparisons with intensive in-situ observations, we evaluate ELM’s configurations using snow data collected at study sites on the Seward Peninsula, Alaska. Our ELM improvements include the use of local parameterizations using site-specific data sets, subgrid topographic model frameworks, and model structure enhancements for shrub allometry. Our work is important for the development of improved Earth system models that can capture snow-vegetation-permafrost interactions and better characterize the Arctic carbon balance as a whole.

 

Poster Presentations (during Poster Exhibit and Session on Wednesday 26 March): 

• unfold_moreThe long-term changes in the mass balance of glaciers at Kaffiøyra area, Svalbard, Arctic — Ireneusz Sobota

  Ireneusz Sobota ¹;  Kamil Czarnecki ¹;  Marcin Nowak ^{1
  1} Nicolaus Copernicus University in Toruń, Polar Research Center

  Format: Poster in-person

  Poster number: #145

  Abstract:

  The main objective of the present work was to assess the nature of the temporal variability and the spatial distribution of the mass balance of glaciers. Most of the research consisted of direct field measurements carried out in 1996–2024, and the investigated changes were mainly related to the mass balance on the Waldemarbreen and the Irenebreen, valley glaciers located in Kaffiøyra, a coastal lowland in northwestern Spitsbergen. To identify the changes in the glaciated area of the studied region, a detailed analysis of the degree of changes in the glaciers' surface area and recession was carried out, starting with the period of their maximum extent in the late 19th and early 20th centuries. Individual components of the mass balance were measured using standard glaciological methods, supplemented by geodetic and remote sensing methods and satellite imagery.

  The recession of the glaciers in the Kaffiøyra area during the analysis period results from a negative trend in the mass balance and dynamics of the Svalbard glaciers. The rapid and substantial changes in the mass balance of glaciers occurring in recent years are also reflected in a growing rate of surface area shrinkage. From the maximum advance to 2024, the glaciers in this area decreased by about 50% on average. The decreasing glacial mass is a phenomenon which began decades ago, but it has become most evident in recent years. The investigations of the glacier's mass balance in the Kaffiøyra region are especially important, being some of longest mass balance records available regarding Svalbard.

• unfold_moreShifts in iron and carbon cycling in West Greenlandic lake systems following a compound extreme heat and precipitation event — Thomas Grindle

  Thomas Grindle ¹;  Jasmine Saros ^{1
  1} Systems Approaches to Understanding and Navigating the New Arctic NRT, University of Maine

  Format: Poster in-person

  Poster number: #447

  Abstract:

  The area around Kangerlussuaq, West Greenland is pockmarked by thousands of lakes, many of which are considered closed-basin. In September 2022, the typically arid region experienced a compound event of heat and precipitation extremes, which saturated the permafrost and resulted in significant shifts in the hydromorphology of the region. Extreme climate events in the Arctic are becoming increasingly common and understanding their effects on interrelated natural and human systems is crucial. The sudden inflow of decades of organic matter and thawed iron-rich permafrost caused rapid, cohesive browning across a geographically broad and conditionally varied landscape. The community of Kangerlussuaq, home to hundreds of year-round residents, relies on the region’s lakes for clean water; dissolved organic matter (DOM) can influence the efficacy of water treatment, and sediment-bound heavy metals can pose a threat to the water supply. This lays the foundation for a unique opportunity for insight into rapid change in a diverse cross-section of lake systems in the arid Arctic.

  The sudden expansion of lake-watershed connectivity resulted in a shift across many lake systems in the primary source of DOM from principally internal production to principally external production and raised questions about the ultimate fate of iron in the water column and the extent to which these factors drive browning in Arctic lake systems. We will present preliminary data on the status of iron within the water column across various lake environments, and the potential impact of long-term ultraviolet radiation exposure on a regionally novel DOM regime.

• unfold_moreModelling the winter snow pack evolution in Greenland — Kirsty Langley

  Kirsty Langley ¹;  Ward van Pelt ²;  Arno Hammann ¹;  Ida Jacobsen ³;  Alexandra Messerli ¹;  Karoline Nilsson ^{1
  1} Asiaq - Greenland Survey; ² University of Uppsala; ³ Greenland Institute of Natural Resources

  Format: Poster in-person

  Poster number: #326

  Abstract:

  The purpose of this study is to understand the dynamics of the snowpack in the Kangerluarsunnguaq (Kobbefjord) area of Greenland and its implications for vegetation, wildlife, and human activities. The snowpack plays a crucial role in insulating and protecting the underlying ground, affecting winter transport, recreation, and water resources upon melting. The research aims to model the evolution of the snowpack over recent and historic periods, with a focus on identifying the occurrence and thickness of ice layers.

  Using a snow model developed by van Pelt et al (2019), we aim to answer the following questions : What happens in the winter snowpack over the course of a winter? When and where do ice layers form and how thick do they get? Is this occurring more frequently in recent years? How does this link to vegetation cover and type?

  This is the first time this model has been applied for Greenland. The model will be tested and tuned for Greenland conditions at a well-known and data rich G-E-M site in West Greenland, Kangerluarsunnguaq (Kobbefjord), thus paving the way for its broader use. Here we present the preliminary results.

  W. van Pelt et al., “A long-term dataset of climatic mass balance, snow conditions, and runoff in Svalbard (1957–2018),” Cryosph., vol. 13, no. 9, pp. 2259–2280, Sep. 2019, doi: 10.5194/tc-13-2259-2019.

• unfold_moreImproved Alaska snow water equivalent assessments under a changing climate — Svetlana Stuefer

  Kate Hale ¹;  Svetlana Stuefer ¹;  Glen Liston ^{2
  1} Institute of Northern Engineering, University of Alaska Fairbanks, Fairbanks, Alaska, USA; ² Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado, USA

  Format: Poster in-person

  Poster number: #421

  Abstract:

  Measuring and modeling snow water equivalent (SWE) is imperative for improved assessment of seasonal snowpack evolution, which acts to regulate the climate, supplies water to societies, and affects ecological and biological cycles, including growing seasons. The availability of SWE measurements is dependent on relevant observation networks, which are particularly sparse in Boreal and Arctic regions of Alaska due to extreme topographic gradients and the state’s vast spatial extent. Across most of Alaska, snowfall and the subsequent snowpack and snowmelt serve as the primary water resource. Yet warming-induced seasonal snowpack changes, including the seasonality and magnitude, impact snowmelt runoff timing and amount, creating cascading effects and vulnerability for surrounding users. To evaluate long-term snowpack trends in Alaska, SnowModel has been employed to capture spatially distributed SWE in northern Boreal forest and Arctic tundra regions of Alaska. Within SnowModel simulations, we leverage existing atmospheric forcing datasets from NASA’s MERRA-2 reanalysis, and the University of Alaska Fairbanks (UAF); and SWE measurements collected by UAF, Cold Regions Research and Engineering Laboratory, USDA SNOTEL, UAF LTER networks, and by the recently completed NASA SnowEx Alaska 2022-2023 field campaigns. We present simulated Boreal forest SWE and snowpack trends and demonstrate an advancement of snow modeling capabilities with data assimilation and with a novel high-density and high-quality validation dataset. This work contributes to larger SWE uncertainty analyses in Boreal and Arctic environments and informs local to regional water resource management as we continue to navigate a changing climate.

• unfold_moreHigh-Resolution Monitoring of Supraglacial Lakes on Kahiltna Glacier, Alaska: Implications on Glacier Dynamics (2017–2024) — Vandana L

  Vandana L ¹;  Gulab Singh ^{1
  1} Indian Institute of Technology Bombay, Powai, Mumbai, Maharashtra, India

  Format: Poster in-person

  Poster number: #532

  Abstract:

  Glacier-lake interactions in the Alaskan Arctic are gaining increasing attention due to their implications for ice loss and climate change. This study investigates the Kahiltna Glacier in Denali National Park, focusing on the development of supraglacial lakes between 2017 and 2024. Using high-resolution imagery from PlanetScope satellites, the Normalized Difference Water Index (NDWI) was applied to monitor the formation and evolution of these lakes. To improve mapping accuracy, a Random Forest classifier was employed, capturing seasonal variations in lake distribution and size. Our findings show a distinct relationship between increasing summer temperatures and the expansion of supraglacial lakes on Kahiltna Glacier. These lakes act as catalysts for ice melting, absorbing more solar radiation than the surrounding ice and contributing to surface melt and fracturing. This accelerates mass loss and glacier thinning. Spatial analysis reveals that lakes predominantly form in lower elevation regions, where ice is thinner and more susceptible to warming-induced deformation.

  The study underscores the importance of continuous monitoring of glacier-lake systems in the Alaskan Arctic, as these lakes play a crucial role in glacier dynamics and feedback mechanisms influencing regional climate patterns. By integrating advanced satellite data with machine learning approaches, this research provides new insights into how supraglacial lakes contribute to glacier mass loss in Alaska’s rapidly changing environment. These findings will support improved glacier models and help predict the future behavior of glaciers under projected climate scenarios.

• unfold_moreGlacier Retreat and Morphological Changes in the Suru Sub Basin of Ladakh, Western Himalayas — Sakshi Mankotia

  Sakshi Mankotia ^{1
  1} Jamia Millia Islamia

  Format: Poster in-person

  Poster number: #566

  Abstract:

  Glaciers are an important part of earth cryosphere are under consistent threat of melting due to global warming and climate change . Himalayan Glaciers are rapidly receding due to climate change, posing significant challenges for communities dependent on their meltwater .The present study aims to develop glacier inventories for the years 1992 and 2023 in Suru Sub Basin and classify them based on Global Land Ice Measurement from Space. The retreat analysis is carried out for 29 glaciers based on their snout positions.

  Landsat TM/OLI sensor data was used along with ASTER DEM to identify and map the glacier boundary, which was further validated by Google Earth imagery. The retreat was calculated by using the centreline method for demarcating the retreating snout based on elevation change. The field measurement was further used to validate the snout change in Parkachik Glacier.

  In 2023, 214 glaciers were identified, with 52.8 percent north-facing glaciers. There has been a significant decline of 24.9 percent in the area in 31 years. The average glacier retreat was 23.6% in all glaciers between 1992 and 2023. The snout retreat of Glacier-18 shows the highest retreat of 45.8m/yr.

  This study used long-term data to calculate glacier retreat patterns with a combination of satellite data and field measurements which adds ground truth and validate the study, further, the data can be used by policymakers and stakeholders to understand climate adaptation strategies in the region.