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At least 685 records · Page 38Linked to original sources

USGS2015

End-of-winter snow depth variability on glaciers in Alaska

A quantitative understanding of snow thickness and snow water equivalent (SWE) on glaciers is essential to a wide range of scientific and resource management topics. However, robust SWE estimates are observationally challenging, in part because SWE can vary abruptly over short distances in complex terrain due to interactions between topography and meteorological processes. In spring 2013, we measured snow accumulation on several glaciers around the Gulf of Alaska using both ground- and helicopter-based ground-penetrating radar surveys, complemented by extensive ground truth observations. We found that SWE can be highly variable (40% difference) over short spatial scales (tens to hundreds of meters), especially in the ablation zone where the underlying ice surfaces are typically rough. Elevation provides the dominant basin-scale influence on SWE, with gradients ranging from 115 to 400 mm/100 m. Regionally, total accumulation and the accumulation gradient are strongly controlled by a glacier's distance from the coastal moisture source. Multiple linear regressions, used to calculate distributed SWE fields, show that robust results require adequate sampling of the true distribution of multiple terrain parameters. Final SWE estimates (comparable to winter balances) show reasonable agreement with both the Parameter-elevation Relationships on Independent Slopes Model climate data set (9–36% difference) and the U.S. Geological Survey Alaska Benchmark Glaciers (6–36% difference). All the glaciers in our study exhibit substantial sensitivity to changing snow-rain fractions, regardless of their location in a coastal or continental climate. While process-based SWE projections remain elusive, the collection of ground-penetrating radar (GPR)-derived data sets provides a greatly enhanced perspective on the spatial distribution of SWE and will pave the way for future work that may eventually allow such projections.

Alaska↗

USGS2006

Erosion rates at the Mars Exploration Rover landing sites and long-term climate change on Mars

Erosion rates derived from the Gusev cratered plains and the erosion of weak sulfates by saltating sand at Meridiani Planum are so slow that they argue that the present dry and desiccating environment has persisted since the Early Hesperian. In contrast, sedimentary rocks at Meridiani formed in the presence of groundwater and occasional surface water, and many Columbia Hills rocks at Gusev underwent aqueous alteration during the Late Noachian, approximately coeval with a wide variety of geomorphic indicators that indicate a wetter and likely warmer environment. Two-toned rocks, elevated ventifacts, and perched and undercut rocks indicate localized deflation of the Gusev plains and deposition of an equivalent amount of sediment into craters to form hollows, suggesting average erosion rates of ???0.03 nm/yr. Erosion of Hesperian craters, modification of Late Amazonian craters, and the concentration of hematite concretions in the soils of Meridiani yield slightly higher average erosion rates of 1-10 nm/yr in the Amazonian. These erosion rates are 2-5 orders of magnitude lower than the slowest continental denudation rates on Earth, indicating that liquid water was not an active erosional agent. Erosion rates for Meridiani just before deposition of the sulfate-rich sediments and other eroded Noachian areas are comparable with slow denudation rates on Earth that are dominated by liquid water. Available data suggest the climate change at the landing sites from wet and likely warm to dry and desiccating occurred sometime between the Late Noachian and the beginning of the Late Hesperian (3.7-3.5 Ga). Copyright 2006 by the American Geophysical Union.

Journal of Geophysical Research E: Planets↗

USGS2014

Improving groundwater predictions utilizing seasonal precipitation forecasts from general circulation models forced with sea surface temperature forecasts

Recent studies have found a significant association between climatic variability and basin hydroclimatology, particularly groundwater levels, over the southeast United States. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater-level forecasts based on the precipitation forecasts from ECHAM 4.5 General Circulation Model Forced with Sea Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater Climate Response Network and Hydro-Climatic Data Network were selected to represent groundwater and surface water flows, respectively, having minimal anthropogenic influences within the Flint River Basin in Georgia, United States. The writers employ two low-dimensional models [principle component regression (PCR) and canonical correlation analysis (CCA)] for predicting groundwater and streamflow at both seasonal and monthly timescales. Three modeling schemes are considered at the beginning of January to predict winter (January, February, and March) and spring (April, May, and June) streamflow and groundwater for the selected sites within the Flint River Basin. The first scheme (model 1) is a null model and is developed using PCR for every streamflow and groundwater site using previous 3-month observations (October, November, and December) available at that particular site as predictors. Modeling schemes 2 and 3 are developed using PCR and CCA, respectively, to evaluate the role of precipitation forecasts in improving monthly and seasonal groundwater predictions. Modeling scheme 3, which employs a CCA approach, is developed for each site by considering observed groundwater levels from nearby sites as predictands. The performance of these three schemes is evaluated using two metrics (correlation coefficient and relative RMS error) by developing groundwater-level forecasts based on leave-five-out cross-validation. Results from the research reported in this paper show that using precipitation forecasts in climate models improves the ability to predict the interannual variability of winter and spring streamflow and groundwater levels over the basin. However, significant conditional bias exists in all the three modeling schemes, which indicates the need to consider improved modeling schemes as well as the availability of longer time-series of observed hydroclimatic information over the basin.

Georgia↗

USGS2022

Predicting near-term effects of climate change on nitrogen transport to Chesapeake Bay

Understanding effects of climate change on nitrogen fate and transport in the environment is critical to nutrient management. We used climate projections within a previously calibrated spatially referenced regression (SPARROW) model to predict effects of expected climate change over 1995 through 2025 on total nitrogen fluxes to Chesapeake Bay and in watershed streams. Assuming nitrogen inputs and other watershed conditions remain at 2012 levels, effects of increasing temperature, runoff, streamflow, and stream velocity expected between 1995 and 2025 will include an estimated net 6.5% decline in annual nitrogen delivery to the bay from its watershed. This predicted decline is attributable to declines in the delivery of nitrogen from upland nonpoint sources to streams due to predicted warmer temperatures. Such temperature-driven declines in the delivery of nitrogen to streams more than offset predicted increased delivery to and within streams due to increased runoff and streamflow and may be attributable to increasing rates of denitrification or ammonia volatilization or to changes in plant phenology. Predicted climate-driven declines in nitrogen flux are generally similar across the watershed but vary slightly among major nonpoint source sectors and tributary watersheds. Nitrogen contributions to the bay from point sources are not affected by temperature-driven changes in delivery from uplands and are therefore predicted to increase slightly between 1995 and 2025.

Chesapeake Bay watershed↗

USGS2010

Simulation and analysis of conjunctive use with MODFLOW's farm process

The extension of MODFLOW onto the landscape with the Farm Process (MF-FMP) facilitates fully coupled simulation of the use and movement of water from precipitation, streamflow and runoff, groundwater flow, and consumption by natural and agricultural vegetation throughout the hydrologic system at all times. This allows for more complete analysis of conjunctive use water-resource systems than previously possible with MODFLOW by combining relevant aspects of the landscape with the groundwater and surface water components. This analysis is accomplished using distributed cell-by-cell supply-constrained and demand-driven components across the landscape within " water-balance subregions" comprised of one or more model cells that can represent a single farm, a group of farms, or other hydrologic or geopolitical entities. Simulation of micro-agriculture in the Pajaro Valley and macro-agriculture in the Central Valley are used to demonstrate the utility of MF-FMP. For Pajaro Valley, the simulation of an aquifer storage and recovery system and related coastal water distribution system to supplant coastal pumpage was analyzed subject to climate variations and additional supplemental sources such as local runoff. For the Central Valley, analysis of conjunctive use from different hydrologic settings of northern and southern subregions shows how and when precipitation, surface water, and groundwater are important to conjunctive use. The examples show that through MF-FMP's ability to simulate natural and anthropogenic components of the hydrologic cycle, the distribution and dynamics of supply and demand can be analyzed, understood, and managed. This analysis of conjunctive use would be difficult without embedding them in the simulation and are difficult to estimate a priori. Journal compilation ?? 2010 National Ground Water Association. No claim to original US government works.

Ground Water↗

USGS2021

Assessment and significance of the frequency domain for trends in annual peak streamflow

Risk management of nonstationary floods depends on an understanding of trends over a range of flood frequencies representing small (frequent) to large (infrequent) floods. Quantile regression is applied to the annual peak streamflow distributions at 2683 sites in the contiguous United States to test for trends in the 10th quantile (floods with a 0.9 annual exceedance probability), the 50th quantile (median annual flood), and 90th quantile (floods with a 0.1 annual exceedance probability). Trends are most common (36% of sites) for the median annual flood (50th quantile) and often coherent with trends in both frequent small floods (10th quantile) and infrequent large floods (90th quantile). Changes in the at-site variance of annual peak streamflow, indicated by convergence (decreasing variance) or divergence (increasing variance) of the 10th and 90th quantiles over time, are primarily in response to reservoir operation or urban development rather than climate. An analysis of synthetic series generated from nonstationary distributions demonstrates that quantile regression and standard trend tests used in flood frequency analysis have limited power and high rates of false negatives (>70%) when a test has a significance of p = 0.05. Quantile regression and tests with lower significance complement standard trend testing to inform flood risk management.

Journal of Flood Risk Management↗

USGS2026

Assessing future hydrologic extremes using an integrated hydrology and river operations model in the Russian River watershed

Study region The Russian River watershed, situated in coastal, northern California, experiences hydrologic extremes, including periodic droughts and flooding. Water managers are working to maintain sustainable water supplies and environmental flows, while mitigating flood risks. Study focus This paper introduces an integrated hydrology and river operations model for the Russian River watershed. This model is distinct from models in previous studies because it represents surface-groundwater interactions and uses climate forcings to estimate dynamic water use demands that are superimposed onto both reservoir operations and water supply constraints. The model was used to examine three historical (1990–2015) and eight future (2016–2099) water use and climate change scenarios. New hydrological insights for the region The direct connection between streams and aquifers facilitated both annual aquifer replenishment by high winter streamflows and streamflow depletion by groundwater wells (19 % of pumped groundwater in alluvial aquifers from stream leakage) during critical low flow periods. Simulated streamflow changes included 59 % longer and 54 % more severe streamflow droughts, 26 % lower seasonal low streamflows, and up to 125 % higher peak streamflows, averaged over future climate and water use scenarios, suggesting increased future flood and water availability risks. Results showed the importance of reservoir operations for mitigating the impacts of increased hydroclimatic volatility, despite a decrease in reservoir reliability at Lake Mendocino, suggesting that reservoir management may be used to decrease future risks.

California↗

USGS2012

Constancy of local spread rates for buffelgrass (Pennisetum ciliare L.) in the Arizona Upland of the Sonoran Desert

In North American deserts, grass invasions threaten native vegetation via competition and altered fire regimes. Accurate prediction and successful mitigation of these invasions hinge on estimation of spread rates and their degree of constancy in time and space. We used high-resolution aerial photographs from 11 sites in the Santa Catalina Mountains, southern Arizona to reconstruct the spread of buffelgrass ( Pennisetum ciliare ), a C4 perennial bunchgrass, since 1980. The total area infested was fit to a logistic model and residuals of the model were compared to climatic factors of the corresponding and lagged time periods. Infestations grew from small colonizing patches in the 1980s to 66 ha in 2008, doubling every 2.26–7.04 years since 1988. Although buffelgrass germination, establishment and distribution are favored by wet summers and warm winters, climate variables did not predict spread rates. Buffelgrass has grown at a constant rate, at least since 1988, when much of its expansion took place. In the study area, minimum requirements are met almost every year for germination and reproduction, establishing a consistent baseline for spread that manifests as a constant spread rate.

Sonoran Desert;Arizona Upland↗

USGS2015

Modeling climate change, urbanization, and fire effects on Pinus palustris ecosystems of the southeastern U.S.

Managing ecosystems for resilience and sustainability requires understanding how they will respond to future anthropogenic drivers such as climate change and urbanization. In fire-dependent ecosystems, predicting this response requires a focus on how these drivers will impact fire regimes. Here, we use scenarios of climate change, urbanization and management to simulate the future dynamics of the critically endangered and fire-dependent longleaf pine ( Pinus palustris ) ecosystem. We investigated how climate change and urbanization will affect the ecosystem, and whether the two conservation goals of a 135% increase in total longleaf area and a doubling of fire-maintained open-canopy habitat can be achieved in the face of these drivers. Our results show that while climatic warming had little effect on the wildfire regime, and thus on longleaf pine dynamics, urban growth led to an 8% reduction in annual wildfire area. The management scenarios we tested increase the ecosystem's total extent by up to 62% and result in expansion of open-canopy longleaf by as much as 216%, meeting one of the two conservation goals for the ecosystem. We find that both conservation goals for this ecosystem, which is climate-resilient but vulnerable to urbanization, are only attainable if a greater focus is placed on restoration of non-longleaf areas as opposed to maintaining existing longleaf stands. Our approach demonstrates the importance of accounting for multiple relevant anthropogenic threats in an ecosystem-specific context in order to facilitate more effective management actions.

Journal of Environmental Management↗

USGS2015

Past and future warming of a deep European lake (Lake Lugano): What are the climatic drivers?

We used four decades (1972–2013) of temperature data from Lake Lugano, Switzerland and Italy, to address the hypotheses that: [i] the lake has been warming; [ii] part of the warming reflects global trends and is independent from climatic oscillations and [iii] the lake will continue to warm until the end of the 21st century. During the time spanned by our data, the surface waters of the lake (0–5 m) warmed at rates of 0.2–0.9 °C per decade, depending on season. The temperature of the deep waters (50-m bottom) displayed a rising trend in a meromictic basin of the lake and a sawtooth pattern in the other basin, which is holomictic. Long-term variation in surfacewater temperature correlated to global warming and multidecadal variation in two climatic oscillations, the Atlantic Multidecadal Oscillation (AMO) and the East Atlantic Pattern (EA).However, we did not detect an influence of the EA on the lake's temperature (as separate from the effect of global warming). Moreover, the effect of the AMO, estimated to a maximum of +1 °C, was not sufficient to explain the observed temperature increase (+2–3 °C in summer). Based on regional climate projections, we predicted that the lake will continue to warm at least until the end of the 21st century. Our results strongly suggest that the warming of Lake Lugano is tied to globalclimate change. To sustain current ecosystem conditions in Lake Lugano, we suggest that manage- ment plans that curtail eutrophication and (or) mitigation of global warming be pursued.

Lake Lugano↗

USGS2001

Biomes of western North America at 18,000, 6000 and 0 14C yr BP reconstructed from pollen and packrat midden data

A new compilation of pollen and packrat midden data from western North America provides a refined reconstruction of the composition and distribution of biomes in western North America for today and for 6000 and 18,000 radiocarbon years before present (14C yr BP). Modern biomes in western North America are adequately portrayed by pollen assemblages from lakes and bogs. Forest biomes in western North America share many taxa in their pollen spectra and it can be difficult to discriminate among these biomes. Plant macrofossils from packrat middens provide reliable identification of modern biomes from arid and semiarid regions, and this may also be true in similar environments in other parts of the world. However, a weighting factor for trees and shrubs must be used to reliably reconstruct modern biomes from plant macrofossils. A new biome, open conifer woodland, which includes eurythermic conifers and steppe plants, was defined to categorize much of the current and past vegetation of the semiarid interior of western North America. At 6000 14C yr BP, the forest biomes of the coastal Pacific North-west and the desert biomes of the South-west were in near-modern positions. Biomes in the interior Pacific North-west differed from those of today in that taiga prevailed in modern cool/cold mixed forests. Steppe was present in areas occupied today by open conifer woodland in the northern Great Basin, while in the central and southern Rocky Mountains forests grew where steppe grows today. During the mid-Holocene, cool conifer forests were expanded in the Rocky Mountains (relative to today) but contracted in the Sierra Nevada. These differences from the forests of today imply different climatic histories in these two regions between 6000 14C yr BP and today. At 18,000 14C yr BP, deserts were absent from the South-west and the coverage of open conifer woodland was greatly expanded relative to today. Steppe and tundra were present in much of the region now covered by forests in the Pacific North-west.

Journal of Biogeography↗

USGS2018

Corresponding long-term shifts in stream temperature and invasive fish migration

By investigating historic trapping records of invasive sea lamprey ( Petromyzon mari nus) throughout tributaries to the Laurentian Great Lakes, we found that upstream spawning migration timing was highly correlated with stream temperatures over large spatial and temporal scales. Furthermore, several streams in our study exceeded a critical spring thermal threshold (i.e., 15°C) and experienced peak spawning migration up to 30 days earlier since the 1980s, whereas others were relatively unchanged. Streams exhibiting warming trends and earlier migration were spatially clustered and generally found on the leeward side of the Great Lakes where the lakes most affect local climate. These findings highlight that all streams are not equally impacted by climate change and represent, to our knowledge, the first observation linking long-term changes in stream temperatures to shifts in migration timing of an invasive fish. Earlier sea lamprey migration in Great Lakes tributaries may improve young of the year growth and survival, but not limit their spatial distribution, making sea lamprey control more challenging.

Laurentian Great Lakes↗

USGS2004

Sequestration of carbon in soil organic matter in Senegal: an overview

Sequestration of Carbon in Soil Organic Matter ( SOCSOM ) in Senegal is a multi-disciplinary development project planned and refined through two international workshops. The project was implemented by integrating a core of international experts in remote sensing, biogeochemical modeling, community socio-economic assessments, and carbon measurements in a fully collaborative manner with Senegal organizations, national scientists, and local knowledge and expertise. The study addresses the potential role developing countries in semi-arid areas can play in climate mitigation activities. Multiple benefits to smallholders could accrue as a result of management practices to re-establish soil carbon content lost because of land use changes or management practices that are not sustainable. The specific importance for the Sahel is because of the high vulnerability to climate change in already impoverished rural societies. The project focuses on four objectives in specific locations across the agroecological zones of Senegal. These objectives are: use of soil sampling and biogeochemical modeling to quantify the biophysical potential for carbon sequestration and to determine the sensitivity of the carbon stocks to various management and climate scenarios, to evaluate the socio-economic and cultural requirements necessary for successful project implementation directed toward an aggregation of smallholders to sequester around 100,000 t carbon (C), to support capacity building to develop a Carbon Specialist Team, and to initiate extrapolation from site-specific project areas to the Sahel region and the national level.

Journal of Arid Environments↗

USGS2020

Identifying sustainable winter habitat for whooping cranes

The only self-sustaining population of endangered whooping cranes ( Grus americana ) requires a network of conservation lands for wintering along the Texas Gulf Coast (USA), so that this increasing population can reach downlisting under the Endangered Species Act (1,000 birds). We identify locations providing the highest quality and most sustainable wintering habitat for these whooping cranes through 2100 by predicting future habitats under three projections of sea level rise (0.6, 1.0 and 2.0 m by 2100), while incorporating two scenarios of future urban development. Our method combines predictions of future habitat quality with current whooping crane density estimates to calculate the potential carrying capacity of whooping cranes for each 10 m pixel within this 17,725 km 2 area. We found whooping cranes used locations with salt marsh at twice the rate of places lacking marsh. Areas > 15 km from development or < 2 km from estuarine water had increased crane use. Predicted area of salt marsh habitat oscillated across time given different rates of sea level rise. One urbanization scenario predicted 3% and the other 1% of the area converting to development by 2100. We estimated the study area can support 4414 (95% CI: 4096-4789) whooping cranes currently, 4795 (95% CI: 4402-5269) with 0.6 m sea level rise, 3559 (95% CI: 3352-3791) with 1 m sea level rise, and 2480 (95% CI: 2375-2592) with 2 m sea level rise by 2100, under the more aggressive urban development scenario. By anticipating climate-induced habitat loss with species population expansion we provide the requisite spatial information for conservation planners to build a sustainable conservation estate for downlisting whooping cranes. By coupling wildlife biology with conservation planning and on-the-ground implementation, our work exemplifies a proactive approach to recover endangered species.

Texas↗

USGS2016

Groundwater level trends and drivers in two northern New England glacial aquifers

We evaluated long-term trends and predictors of groundwater levels by month from two well-studied northern New England forested headwater glacial aquifers: Sleepers River, Vermont, 44 wells, 1992-2013; and Hubbard Brook, New Hampshire, 15 wells, 1979-2004. Based on Kendall Tau tests with Sen slope determination, a surprising number of well-month combinations had negative trends (decreasing water levels) over the respective periods. Sleepers River had slightly more positive than negative trends overall, but among the significant trends ( p < 0.1), negative trends dominated 67 to 40. At Hubbard Brook, negative trends outnumbered positive trends by a nearly 2:1 margin and all seven of the significant trends were negative. The negative trends occurred despite generally increasing trends in monthly and annual precipitation. This counterintuitive pattern may be a result of increased precipitation intensity causing higher runoff at the expense of recharge, such that evapotranspiration demand draws down groundwater storage. We evaluated predictors of month-end water levels by multiple regression of 18 variables related to climate, streamflow, snowpack, and prior month water level. Monthly flow and prior month water level were the two strongest predictors for most months at both sites. The predictive power and ready availability of streamflow data can be exploited as a proxy to extend limited groundwater level records over longer time periods.

New Hampshire, Vermont↗

USGS2002

Environmental variation, vegetation distribution, carbon dynamics and water/energy exchange at high latitudes

The responses of high latitude ecosystems to global change involve complex interactions among environmental variables, vegetation distribution, carbon dynamics, and water and energy exchange. These responses may have important consequences for the earth system. In this study, we evaluated how vegetation distribution, carbon stocks and turnover, and water and energy exchange are related to environmental variation spanned by the network of the IGBP high latitude transects. While the most notable feature of the high latitude transects is that they generally span temperature gradients from southern to northern latitudes, there are substantial differences in temperature among the transects. Also, along each transect temperature co-varies with precipitation and photosynthetically active radiation, which are also variable among the transects. Both climate and disturbance interact to influence latitudinal patterns of vegetation and soil carbon storage among the transects, and vegetation distribution appears to interact with climate to determine exchanges of heat and moisture in high latitudes. Despite limitations imposed by the data we assembled, the analyses in this study have taken an important step toward clarifying the complexity of interactions among environmental variables, vegetation distribution, carbon stocks and turnover, and water and energy exchange in high latitude regions. This study reveals the need to conduct coordinated global change studies in high latitudes to further elucidate how interactions among climate, disturbance, and vegetation distribution influence carbon dynamics and water and energy exchange in high latitudes.

Journal of Vegetation Science↗

USGS2022

Predictions and drivers of sub-reach-scale annual streamflow permanence for the upper Missouri River basin: 1989-2018

The presence of year-round surface water in streams (i.e., streamflow permanence) is an important factor for identifying aquatic habitat availability, determining the regulatory status of streams, managing land use change, allocating water resources, and designing scientific studies. However, accurate, high resolution, and dynamic prediction of streamflow permanence that accounts for year-to-year variability at a regional extent is a major gap in modeling capability. Herein, we expand and adapt the U.S. Geological Survey (USGS) PRObability of Streamflow PERmanence (PROSPER) model from its original implementation in the Pacific Northwest (PROSPER PNW ) to the upper Missouri River basin (PROSPER UM ), a geographical region that includes mountain and prairie ecosystems of the northern United States. PROSPER UM is an empirical model used to estimate the probability that a stream channel has year-round flow in response to climatic conditions (monthly and annual) and static physiographic predictor variables of the upstream basin. The structure and approach of PROSPER UM are generally consistent with the PROSPER PNW model but include improved spatial resolution (10 m) and a longer modeling period. Average model accuracy was 81 %. Drainage area, upstream proportion as wetlands, and upstream proportion as developed land cover were the most important predictor variables. The PROSPER UM model identifies decreases in streamflow permanence during climatically drier years, although there is variability in the magnitude across basins highlighting geographically varying sensitivity to drought. Variability in the response of perennial streams to drought conditions among basins in the study area was also observed.

Montana, North Dakota, South Dakota, Wyoming↗

USGS2026

The Python Energy Balance model for Snow and Ice (PEBSI): Application and tradeoff analysis on Gulkana Glacier, Alaska

Glacier energy-balance models offer mechanistic insights into glacier mass balance under a changing climate, yet their considerable data requirements hinder large-scale applications. Here we present the open-source Python Energy Balance model for Snow and Ice (PEBSI), which includes physically based albedo evolution using the Snow, Ice and Aerosol Radiative (SNICAR) model. PEBSI is calibrated and validated using robust in situ data from Gulkana Glacier, Alaska from 2000 to 2024. Simulations forced with original and bias-corrected climate reanalysis data show that statistically downscaling reanalysis data with in situ observations is necessary to reproduce summer mass balance (mean absolute error [MAE] = 0.75 m w.e. vs 0.22 m w.e., respectively). A grid search across two parameters, a precipitation factor and a densification parameter, reveals tradeoffs in performance compared to seasonal mass balance and end-of-winter snow density and depth. No single combination of parameters minimizes all errors, underscoring the inherent overparameterization of energy-balance models and challenges with translating coarse climate data to the glacier scale. The calibrated model successfully simulates the 2024 melt season, agreeing with surface-height change (MAE = 0.48 m) and albedo (MAE = 0.066) observations. Moving forward, PEBSI provides unique opportunities to quantify albedo feedbacks and their impact on present and future glacier mass loss.

Alaska↗