Geology topics
Publications and source records attributed to Caitlyn Florentine.
Glaciers lost 408 ± 132 Gt of mass during the hydrological year 2025, equivalent to 1.1 ± 0.4 mm sea-level rise. Since 1975, glacier mass loss has totalled 9,583 ± 1,211 Gt, equivalent to 26.4 ± 3.3 mm of sea-level rise, with six of the highest mass-loss years on record occurring in the past seven years.
This chapter summarizes the location, status, and projections of glaciers in Alaska and western North America. Recent events, including the 2021 surge of Muldrow Glacier in Denali National Park and Preserve, Alaska, are summarized. The implications of glacier loss for ecosystems, water resources, and mountain hazards are discussed.
Over the period 2021–2024, glaciers in Western Canada and the conterminous US (WCAN-US), and Switzerland respectively lost mass at rates of 22.2 ± 9.0 and 1.5 ± 0.3 Gt yr −1 representing a twofold increase in mass loss compared to the period 2010–2020. Since 2020, total ice volume was depleted by 12% (WCAN-US) and 13% (Switzerland). Meteorological conditions that favored high rates of mass loss included low winter snow accumulation, early-season heat waves, and prolonged warm, dry conditions. High transient snow lines, and impurity loading due to wildfires (WCAN-US) or Saharan dust (Switzerland) darkened glaciers and thereby increased mass loss via greater absorbed shortwave radiation available for melt. This ice-albedo feedback will lead to continued high rates of thinning unless recently exposed dark ice and firn at high elevations is buried by seasonal snowfall. Physical models that simulate impurity deposition and movement through firn and ice are needed to improve future projections of glacier mass change.
Tracking the extent of seasonal snow on glaciers over time is critical for assessing glacier vulnerability and the response of glacierized watersheds to climate change. Existing snow cover products do not reliably distinguish seasonal snow from glacier ice and firn, preventing their use for glacier snow cover detection. Despite previous efforts to classify glacier surface facies using machine learning on local scales, currently there is no published comparison of machine learning models for classifying glacier snow cover across different satellite image products. We present an automated snow detection workflow for mountain glaciers using supervised machine-learning-based image classifiers and Landsat 8 and 9, Sentinel-2, and PlanetScope satellite imagery. We develop the image classifiers by testing numerous machine learning algorithms with training and validation data from the U.S. Geological Survey Benchmark Glacier Project glaciers. The workflow produces daily to twice monthly time series of several glacier mass balance and snowmelt indicators (snow-covered area, accumulation area ratio, and seasonal snow line) from 2013 to present. Workflow performance is assessed by comparing automatically classified images and snow lines to manual interpretations at each glacier site. The image classifiers exhibit overall accuracies of 92%–98%, K scores of 84%–96%, and F scores of 93%–98% for all image products. The median difference between automatically and manually delineated median snow line altitudes is 31m (IQR of 73to0m)across all image products. The Sentinel-2 classifier (support vector machine) produces the most accurate glacier mass balance and snowmelt indicators and distinguishes snow from ice and f irn the most reliably. Although they are less accurate, the Landsat- and PlanetScope-derived estimates greatly enhance the temporal coverage of observations. The transient accumulation area ratio produces the least noisy time series, making it the most reliable indicator for characterizing seasonal snow trends. The temporally detailed accumulation area ratio time series reveal that the timing of minimum snow cover conditions varies by up to a month between Arctic (63°N) and midlatitude (48°N) sites, underscoring the potential for bias when estimating glacier minimum snow cover conditions from a single late-summer image. Widespread application of our automated snow detection workflow has the potential to improve regional assessments of glacier mass balance, land ice representations within Earth system models, water resources, and the impacts of climate change on snow cover across broad spatial scales.
The accumulation area ratio (AAR) of a glacier reflects its current state of equilibrium, or disequilibrium, with climate and its vulnerability to future climate change. Here, we present an inventory of glacier-specific annual accumulation areas and equilibrium line altitudes (ELAs) for over 3000 glaciers in Alaska and northwest Canada (88% of the regional glacier area) from 2018 to 2022 derived from Sentinel-2 imagery. We find that the 5 year average AAR of the entire study area is 0.41, with an inter-annual range of 0.25–0.49. More than 1000 glaciers, representing 8% of the investigated glacier area, were found to have effectively no accumulation area. Summer temperature and winter precipitation from ERA5-Land explained nearly 50% of the inter-annual ELA variability across the entire study region ( R 2 = 0.47 ). An analysis of future climate scenarios (SSP2-4.5) projects that ELAs will rise by ∼170 m on average by the end of the 21st century. Such changes would result in a loss of 25% of the modern accumulation area, leaving a total of 1900 glaciers (22% of the investigated area) with no accumulation area. These results highlight the current state of glacier disequilibrium with modern climate, as well as glacier vulnerability to projected future warming.
Glaciers are indicators of ongoing anthropogenic climate change 1 . Their melting leads to increased local geohazards 2 , and impacts marine 3 and terrestrial 4 , 5 ecosystems, regional freshwater resources 6 , and both global water and energy cycles 7 , 8 . Together with the Greenland and Antarctic ice sheets, glaciers are essential drivers of present 9 , 10 and future 11 , 12 , 13 sea-level rise. Previous assessments of global glacier mass changes have been hampered by spatial and temporal limitations and the heterogeneity of existing data series 14 , 15 , 16 . Here we show in an intercomparison exercise that glaciers worldwide lost 273 ± 16 gigatonnes in mass annually from 2000 to 2023, with an increase of 36 ± 10% from the first (2000–2011) to the second (2012–2023) half of the period. Since 2000, glaciers have lost between 2% and 39% of their ice regionally and about 5% globally. Glacier mass loss is about 18% larger than the loss from the Greenland Ice Sheet and more than twice that from the Antarctic Ice Sheet 17 . Our results arise from a scientific community effort to collect, homogenize, combine and analyse glacier mass changes from in situ and remote-sensing observations. Although our estimates are in agreement with findings from previous assessments 14 , 15 , 16 at a global scale, we found some large regional deviations owing to systematic differences among observation methods. Our results provide a refined baseline for better understanding observational differences and for calibrating model ensembles 12 , 16 , 18 , which will help to narrow projection uncertainty for the twenty-first century 11 , 12 , 18 .
Introduction The cryosphere is the collective parts of the Earth where water is in its frozen state and includes snow, glaciers, ice sheets, ice shelves, freshwater ice, sea ice, and permafrost. The cryosphere is a climate indicator and climate regulator. Surface cryosphere features, such as glaciers, snow, and sea ice, store freshwater and make the surface of the Earth bright white, which affects how much energy from the sun is absorbed or reflected by the planet. The subsurface cryosphere, such as permafrost and ground ice, stores water and other materials, including carbon, nutrients, heavy metals, and viruses. Carbon storage in permafrost is one way the cryosphere regulates the Earth's climate. Changes to the cryosphere indicate the state of the Earth's climate. The cryosphere spans many regions of the Earth, from subtropical regions of the Himalayas to polar regions of the Arctic and Antarctica, and intersects many of the Earth's spheres, including the lithosphere, biosphere, atmosphere, and hydrosphere.
Recent advances in remote sensing have produced global glacier surface elevation change data. Parsing these elevation change signals into contributions from the climate (i.e. climatic mass balance) and glacier dynamics (i.e. flux divergence) is critical to enhance our process-based understanding of glacier change. In this study, we evaluate three approaches for direct, continuous measurements of the climatic mass balance, flux divergence, and elevation change at a site on Gulkana Glacier in Alaska using low-cost GNSS sensors, GNSS interferometric reflectometry (GNSS-IR), banded ablation stakes with time-lapse cameras, and combinations thereof. Cumulative climatic mass balance over the season was 4.85 m and the three approaches were within 0.08 m through early July before the snowpack melted, and within 0.28 m through mid-August. The flux divergence increased from 0.52 ± 0.03 cm d -1 before June 3 to roughly 0.73 cm d -1 after June 27. We demonstrate a single GNSS system fixed atop an ablation stake can measure contemporaneous climatic mass balance, flux divergence, and elevation change based on the antenna’s position and GNSS-IR techniques. The ability of these systems to measure glacier mass balance and flux divergence offers unique opportunities for year-round observations on mountain glaciers in the future.
Knowledge of snow and firn-density change is needed to use elevation-change measurements to estimate glacier mass change. Additionally, firn-density evolution on glaciers is closely connected to meltwater percolation, refreezing and runoff, which are key processes for glacier mass balance and hydrology. Since 2016, the U.S. Geological Survey Benchmark Glacier Project has recovered firn cores from a site on Wolverine Glacier in Alaska's Kenai Mountains. We use annual horizons in repeat cores to track firn densification and meltwater retention over seasonal and interannual timescales, and we use density measurements to quantify how the firn air content (FAC) changes through time. The results suggest the firn is densifying due primarily to compaction rather than refreezing. Liquid-water retention in the firn is transient, likely due to gravity-fed drainage and irreducible-water-content decreases that accompany decreasing porosity. We show that the uncertainty (±60 kg m −3 ) in the commonly used volume-to-mass conversion factor of 850 kg m −3 is an underestimation when glacier-wide FAC variability exceeds 12% of the glacier-averaged height change. Our results demonstrate how direct measurements of firn properties on mountain glaciers can be used to better quantify the uncertainty in geodetic volume-to-mass conversions.
Observations of glacier mass changes are key to understanding the response of glaciers to climate change and related impacts, such as regional runoff, ecosystem changes, and global sea level rise. Spaceborne optical and radar sensors make it possible to quantify glacier elevation changes, and thus multi-annual mass changes, on a regional and global scale. However, estimates from a growing number of studies show a wide range of results with differences often beyond uncertainty bounds. Here, we present the outcome of a community-based inter-comparison experiment using spaceborne optical stereo (ASTER) and synthetic aperture radar interferometry (TanDEM-X) data to estimate elevation changes for defined glaciers and target periods that pose different assessment challenges. Using provided or self-processed digital elevation models (DEMs) for five test sites, 12 research groups provided a total of 97 spaceborne elevation-change datasets using various processing approaches. Validation with airborne data showed that using an ensemble estimate is promising to reduce random errors from different instruments and processing methods but still requires a more comprehensive investigation and correction of systematic errors. We found that scene selection, DEM processing, and co-registration have the biggest impact on the results. Other processing steps, such as treating spatial data voids, differences in survey periods, or radar penetration, can still be important for individual cases. Future research should focus on testing different implementations of individual processing steps (e.g. co-registration) and addressing issues related to temporal corrections, radar penetration, glacier area changes, and density conversion. Finally, there is a clear need for our community to develop best practices, use open, reproducible software, and assess overall uncertainty to enhance inter-comparison and empower physical process insights across glacier elevation-change studies.
Glaciers in western North American outside of Alaska are often overlooked in global studies because their potential to contribute to changes in sea level is small. Nonetheless, these glaciers represent important sources of freshwater, especially during times of drought. Differencing recent ICESat-2 data from a digital elevation model derived from a combination of synthetic aperture radar data (TerraSAR-X/TanDEM-X), we find that over the period 2013–2020, glaciers in western North America lost mass at a rate of -12.3 ± 3.5 Gt yr −1 . This rate is comparable to the rate of mass loss (-11.7 ± 1.0 Gt yr −1 ) for the period 2018–2022 calculated through trend analysis using ICESat-2 and Global Ecosystems Dynamics Investigation (GEDI) data.
Innovations in geodesy enable widespread analysis of glacier surface elevation change and geodetic mass balance. However, coincident glacier area data are less widely available, causing inconsistent handling of glacier area change. Here we quantify the bias introduced into meters water equivalent (m w.e.) specific geodetic mass balance results when using a fixed, maximum glacier area, and illustrate the bias for five North American glaciers. Sites span latitudes from the northern U.S. Rocky Mountains (48°N) to the Central Alaska Range (63°N) between 1948 and 2021. Results show that fixed (maximum) area treatment subdues the m w.e. mass change signal, underestimating mass balance by up to 19% in our test cases. This bias scales with relative glacier area change and the mass balance magnitude. Thus, the bias for specific geodetic mass balances will be most pronounced across rapidly deglaciating regions. Our analysis underscores the need for temporally resolved glacier area in geodetic mass balance studies.
Precisely measuring the Earth’s changing surface on decadal to centennial time scales is critical for many science and engineering applications, yet long-term records of quantitative landscape change are often temporally and geographically sparse. Archives of scanned historical aerial photographs provide an opportunity to augment these records with accurate elevation measurements that capture the historical state of the Earth surface. Structure from Motion (SfM) photogrammetry workflows produce high-quality digital elevation models (DEMs) and orthoimage mosaics from these historical images, but time-intensive tasks like manual image preprocessing (e.g., fiducial marker identification) and ground control point (GCP) selection impede processing at scale. We developed an automated method to process historical images and generate self-consistent time series of high-resolution (0.5–2 m) DEMs and orthomosaics, without manual GCP selection. The method relies on SfM to correct camera interior and exterior orientation and a robust multi-stage co-registration approach using modern reference terrain datasets for geolocation refinement. We demonstrate the method using scanned images from the North American Glacier Aerial Photography (NAGAP) archive collected between 1967 and 1997. We present results for two sites with variable photo acquisition geometry and overlap — Mount Baker and South Cascade Glacier in Washington State, USA. The automated method corrects initial camera position errors of several kilometers and produces accurately georeferenced, high-resolution DEMs and orthoimages, regardless of camera configuration, acquisition geometry, terrain characteristics, and reference DEM properties. The average RMS reprojection error following bundle adjustment optimization was 0.67 px (0.15 m) for the 261 images contributing to 10 final DEM mosaics between 1970 and 1992 at Mount Baker, and 0.65 px (0.13 m) for the 243 images contributing to 18 individual DEMs between 1967 and 1997 at South Cascade Glacier. The relative accuracy of elevation values in the historical time series stacks was 0.68 m at Mount Baker and 0.37 m at South Cascade Glacier. Our products have reduced systematic error and improved accuracy compared to DEM products generated using SfM with manual GCP selection. Final elevation change measurement precision was ∼ "> ∼ 0.7–1.0 m over a 30-year period, enabling the study of processes with rates as low as ∼ "> ∼ 1-3 cm/yr. Our results demonstrate the potential of this scalable method to rapidly process archives of historical imagery and deliver new quantitative insights on long-term geodetic change and Earth surface processes.
The U.S. Geological Survey Benchmark Glacier Project combines decades of direct glaciological data with remote sensing data to advance the quantitative understanding of glacier-climate interactions. The global loss of glaciers, and consequent implications for water resources, sea level rise, and ecosystem function underscores the importance of U.S. Geological Survey glaciology research to facilitate adaptive strategies.
Seasonal snow melt dominates the hydrologic budget across a large portion of the globe. Snow accumulation and melt vary over a broad range of spatial scales, preventing accurate extrapolation of sparse in situ observations to watershed scales. The lidar onboard the Ice, Cloud, and land Elevation, Satellite (ICESat-2) was designed for precise mapping of ice sheets and sea ice, and here we assess the feasibility of snow depth-mapping using ICESat-2 data in more complex and rugged mountain landscapes. We explore the utility of ATL08 Land and Vegetation Height and ATL06 Land Ice Height differencing from reference elevation datasets in two end member study sites. We analyze ∼3 years of data for Reynolds Creek Experimental Watershed in Idaho's Owyhee Mountains and Wolverine Glacier in southcentral Alaska's Kenai Mountains. Our analysis reveals decimeter-scale uncertainties in derived snow depth and glacier mass balance at the watershed scale. Both accuracy and precision decrease as slope increases: the magnitudes of the median and median of the absolute deviation of elevation errors (MAD) vary from ∼0.2 m for slopes <5° to >1 m for slopes >20°. For glacierized regions, failure to account for intra- and inter-annual evolution of glacier surface elevations can strongly bias ATL06 elevations, resulting in under-estimation of the mass balance gradient with elevation. Based on these results, we conclude that ATL08 and ATL06 observations are best suited for characterization of watershed-scale snow depth and mass balance gradients over relatively shallow slopes with thick snowpacks . In these regions, ICESat-2 elevation residual-derived snow depth and mass balance transects can provide valuable watershed scale constraints on terrain parameter- and model-derived estimates of snow accumulation and melt.
Glaciers are important drivers of environmental heterogeneity and biological diversity across mountain landscapes. Worldwide, glaciers are receding rapidly due to climate change, with important consequences for biodiversity in mountain ecosystems. However, the effects of glacier loss on biodiversity have never been quantified across a mountainous region, primarily due to a lack of adequate data at large spatial and temporal scales. Here, we combine high-resolution biological and glacier change (ca. 1850–2015) datasets for Glacier National Park, USA, to test the prediction that glacier retreat reduces biodiversity in mountain ecosystems through the loss of uniquely adapted meltwater stream species. We identified a specialized cold-water invertebrate community restricted to the highest elevation streams primarily below glaciers, but also snowfields and groundwater springs. We show that this community and endemic species have unexpectedly persisted in cold, high-elevation sites, even in catchments that have not been glaciated in ∼170 y. Future projections suggest substantial declines in suitable habitat, but not necessarily loss of this community with the complete disappearance of glaciers. Our findings demonstrate that high-elevation streams fed by snow and other cold-water sources continue to serve as critical climate refugia for mountain biodiversity even after glaciers disappear.
Currently, the volume of land ice on Earth is decreasing, driving consequential changes to global sea level and local stream habitat. Glacier retreat in Glacier National Park, Montana, U.S.A., is one example of land ice loss and glacier change. The U.S. Geological Survey Benchmark Glacier Project conducts glaciological research and collects field measurements across select North American glaciers, including Sperry Glacier located in Glacier National Park. These records provide direct evidence of glacier change. The amount and timing of Earth’s land ice that will be lost in the future depends on the future trajectory of greenhouse gas emissions. Ongoing glaciological research will enhance physical understanding and forecasting capabilities; however, the continued retreat and ice mass loss of small glaciers in Glacier National Park is certain.