We present a new version of the PROMICE | GC-NET automatic weather station (AWS) data product, combining observations from two Greenland AWS networks; PROMICE and GC-NET. As of late 2025, the dataset integrates records from 52 active and historical AWS sites across the Greenland Ice Sheet, peripheral glaciers and land areas. This new version includes improvements in station design, sensor configuration, and data processing. Two primary station types are used: dual-boom masts in the accumulation area, and free-standing tripods with a single instrument boom in the ablation area. Data are processed with pypromice, an open-source Python package designed for standardized, transparent, and reproducible workflows, including calibration, filtering, variable derivation, and correction. The resulting products are distributed in CF-compliant NetCDF and CSV formats and include both measured and derived variables for applications in polar meteorology, climatology, and glaciology. Access is open under license CC-BY 4.0. A GitHub-based issue tracker (https://github.com/GEUS-Glaciology-and-Climate/PROMICE-AWS-data-issues, last access: 12 November 2025) supports community-driven quality control within a living data framework. The datasets are openly available at 10.22008/FK2/IW73UU .

Abstract. We present an updated version of the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) ice velocity product (https://doi.org/10.22008/FK2/K70OPK; Solgaard and Kusk (2026)), providing a continuous time series of Greenland Ice Sheet velocity mosaics from January 2016 to the present. The product is derived from Sentinel-1 synthetic aperture radar (SAR) data, gridded at 200 m spatial resolution and updated every 12 days using data spanning two consecutive Sentinel-1 repeat cycles (24 days). Data are typically released within 10 days of the final acquisition and include all valid 6- and 12-day image pairs within the 24-day window. This update includes several important improvements to the processing chain. The spatial resolution has been refined from 500 m to 200 m, justified by the implementation of an adaptive correlation template size approach for offset tracking, improving velocity retrievals and enhancing delineation of narrow outlet glaciers. We further implement a new mosaicking strategy, which reduces noise associated with ionospheric disturbances. Additional improvements include enhanced error handling and outlier rejection. The full processing workflow is described, including data selection, mosaicking, uncertainty estimation, and filtering procedures. Validation against in-situ GNSS measurements over the full time series shows that the standard deviation of the differences between satellite- and GNSS-derived velocities (with corresponding bias) is 22 m/yr (-0.3 m/yr) and 38 m/yr (-0.4 m/yr) for the easting and northing components, respectively. These values fall within expected ranges, although a substantial fraction of the discrepancy likely reflects uncertainty in the GNSS measurements. This interpretation is supported by validation over stable terrain, where substantially lower values are obtained: 9 m/yr (0.1 m/yr) and 15 m/yr (-0.1 m/yr) for the easting and northing components, respectively. Compared to the previous product version, uncertainties are higher due to a prolonged period when only one Sentinel-1 satellite was operational, resulting in increased noise and reduced temporal sampling. We quantify the impact of these conditions on spatial coverage. Overall, coverage is highest during winter, when radar coherence is strong and acquisitions are most comprehensive, whereas summer coverage is reduced due to surface melt. Despite these seasonal and mission-related constraints, the PROMICE ice velocity product provides consistent temporal sampling and broad spatial coverage, supporting investigations of ice-sheet-wide and glacier-specific dynamics and ice discharge on seasonal to multi-year timescales.

The Greenland Ice Sheet is a key component of the Earth's climate system and assessing its mass balance is crucial for predicting sea-level rise. Solid ice discharge is a critical parameter that can be determined by calculating the mass flux through gates spanning all outlet glaciers. However, this calculation relies on accurate ice-thickness measurements. Here, we present an open-source Python package (PRODEM-Xtract) to extract high-resolution annual ice surface elevation and associated ice-thickness profiles along user-defined flux gates overthe marginal zone of the Greenland Ice Sheet. PRODEM-Xtract builds on PRODEM, an annual series (2019-2024) of Digital Elevation Models covering the margin of the Greenland Ice Sheet, while further refining the product to deliver a higher spatial resolution of 32 metres. Bed topography is derived from BedMachine v6. Using PRODEM-Xtract, we analyse changes in surface elevation and corresponding ice thickness along flux gates across the three largest outlet glaciers of the Greenland Ice Sheet, for which we observe complex spatial and temporal variability overthe period from 2019 to 2024 (inclusive). The evolving annual ice thickness will be incorporated into future assessments of the dynamic ice discharge from the Greenland Ice Sheet.

The surface elevation of the Greenland Ice Sheet is constantly changing due to the interplay between surface mass balance processes and ice dynamics, each exhibiting distinct spatiotemporal patterns. Here, we employ satellite and airborne altimetry data with fine spatial (1 km) and temporal (monthly) resolutions to document this spatiotemporal evolution from January 2003 to August 2023. To estimate elevation changes of the Greenland Ice Sheet (GIS), we utilize radar altimetry data from CryoSat-2 and EnviSat, laser altimetry data from the ICESat and ICESat-2, and laser altimetry data from NASA's Operation IceBridge Airborne Topographic Mapper. We produce continuous monthly ice surface elevation changes from January 2003 to August 2023 on a 1 km grid covering the entire GIS. We estimate cumulative ice loss of 4352 Gt +/- 315 Gt (12.1 +/- 0.9 mm sea level equivalent) during this period, excluding peripheral glaciers. Between 2003 and 2023, the ice sheet land-terminating margin underwent a significant cumulative thinning of several meters. Ocean-terminating glaciers exhibited thinning between 20-40 m, with Jakobshavn Isbr ae experiencing an exceptional thinning of nearly 70 m. This dataset of fine-resolution altimetry data in both space and time will support studies of ice mass loss and will be useful for GIS modeling. To validate our monthly mass changes of the Greenland ice sheet, we use mass change from satellite gravimetry and mass change from the input-output method. On multiannual timescales, there is a strong correlation between the time series, with R values ranging from 0.88 to 0.92 (10.5061/dryad.s4mw6m9dh, Khan et al., 2025)

Ice-marginal lakes form at the edge of the Greenland Ice Sheet and its surrounding peripheral glaciers and ice caps (PGIC), where outflowing glacial meltwater is trapped by a moraine, or by the ice itself, and create a reservoir that is in contact with the adjacent ice. While glacial meltwater is typically assumed to flow directly into the ocean, ice-marginal lakes temporarily store a portion of this runoff, influencing glacier dynamics and ablation, ecosystems, and downstream hydrology. Their presence, and change in abundance and size, remain under-represented in projections of sea level change and glacier mass loss. Here, we present an eight-year (2016–2023) inventory of 2918 automatically classified ice-marginal lakes (≧0.05 km2) across Greenland, tracking changes in lake abundance, surface extent, and summer surface temperature over time. Fluctuations in lake abundance were most pronounced at the north (22 %) and northeast (14 %) PGIC margins and the southwest Ice Sheet margin (8 %). Over the study period, an increase in surface lake area was evident at 283 lakes, a decreasing trend was evident at 240 lakes, and 1373 remained stable (±0.05 km2). The northeast region contained the largest lakes, with a median size of 0.40 km2 at the ice sheet margin and 0.24 km2 at PGIC margins. Average summer surface temperatures fluctuated between 3.8 °C (2018) and 5.3 °C (2023), with spatial and temporal trends identified with possible links to lake setting and size. Validation against manually identified lakes showed 64 % agreement, yielding an error estimate of −809 lakes (36 %), while lake area uncertainty was ±5 %. Surface temperature estimates showed strong agreement with in situ measurements (r2=0.87, RMSE =1.68 °C, error ±1.2 °C). This dataset provides a crucial foundation for quantifying meltwater storage at ice margins and refining sea level contribution projections while supporting research on glacier-lake interactions, Arctic ecology, and environmental management. The inventory series is openly accessible on the GEUS Dataverse (https://doi.org/10.22008/FK2/MBKW9N, How et al., 2025) with full metadata and documentation, and a reproducible processing workflow.

Surface topography within the marginal zone of the Greenland Ice Sheet continually evolves in response to varying weather, season, climate and ice dynamics. However, existing ice sheet Digital Elevation Models (DEMs) usually rely on multi-year data, obscuring these changes over time. We have here developed an annual series (2019-2023) of summer DEMs in 500m resolution for the Greenland ice sheet marginal zone, referred to as PRODEMs. Encompassing all outlet glaciers from the Greenland ice sheet, these PRODEMs result from fusing CryoSat-2 radar altimetry and ICESat-2 laser altimetry using a regionally-varying Kriging method. Validated through leave-one-out cross-validation, they demonstrate accurate representation of surface elevations within the spatially varying prediction uncertainties with a median value of 1.4m. The PRODEMs capture the recent annual evolution in summer surface topography of all outlet glaciers from the Greenland ice sheet. We observe a general lowering of surface elevations compared to ArcticDEM, but the spatial pattern of change is highly complex and with annual changes superimposed. The PRODEMs offer detailed insights into marginal ice sheet elevation changes, temporally as well as spatially, making them valuable for researchers and users studying ice sheet dynamics under changing environmental conditions.

The rapid demise of ice sheets and glaciers worldwide has increased the need for mass balance observations at a temporal and spatial resolution, where they can both help us understand the physical processes and also serve as validation or calibration for remote sensing data products or regional climate model output. Here we present the latest developments in measuring crucial components of the surface mass balance at automatic weather stations, including snow water equivalent, snow height in the vicinity of the station, sufficiently accurate transmitted position and elevation of the station, snow compaction and non-stake ice sheet ablation. Immediate access to the observations is key to certain applications, such as numerical weather forecasts. Hence, we also present the complications of providing near real-time data transmission and quality-checking as well as obstacles to a wider distribution on the WMO Global Telecommunication System (GTS).

Ice sheet mass loss is typically provided for grounded ice, because changes in floating ice are more difficult to measure and contribute minimally to sea level rise. However, gross freshwater mass flow rate across ice sheet boundaries, including floating ice, is a better metric of ice sheet health. Here, we present total mass flows across ice sheet boundaries for both the Greenlandic and Antarctic ice sheets and their peripheral glaciers from 2010 through 2019. In addition to total mass flow, we provide constituent terms and gross rather than net values, including components that combine to provide surface mass balance. Ice mass loss in Greenland is 330 $\pm$50 Gt yr-1 which is $\sim$30% larger than the 255 $\pm$40 Gt yr-1 grounded ice mass loss estimates that neglect floating ice changes. Ice mass loss in Antarctica is 450 $\pm$270 Gt yr-1 which is $\sim$2.4x the 190 $\pm$115 Gt yr-1 grounded ice mass loss estimates. Freshwater mass flow rate from Greenland is $\sim$1065 $\pm$120 Gt yr-1 or $\sim$3x mass loss ( $\sim$4x grounded mass loss), and from Antarctica is $\sim$3110 $\pm$1515 Gt yr-1, or $\sim$7x mass loss ( $\sim$16x grounded mass loss).

We examine the feasibility of an overland motorised traverse from Pituffik to Greenland’s oldest ice outcrop in Warming Land, North Greenland. We assess a 778 km overland traverse that departs Pituffik via the Nunatarssuaq Take-Off Ramp, which is an alternative to the more frequently used, but more heavily crevassed, Thule Take-Off Ramp. The traverse route includes brief sea ice and primitive road conditions, each c. 4% of the route length, and a lengthy ice sheet segment (c. 92% of the route length). This study outlines challenges for each of these traverse segments, including primitive road conditions and snow cover, seasonality of extreme cold conditions (air temperatures below –30°C), seasonality of surface melting and softening (air temperatures above 0°C), sea-ice thickness and potential ridging hazards and ice dynamics and potential crevasse hazards. Ongoing work is required for annual vetting of the traverse route to ensure operational safety. The optimal operational window for such a traverse is departing Pituffik in mid-April and returning in mid-May. In comparison to aircraft-supported ice-sheet fieldwork, scientific traverses offer the opportunity for more intensive ground-based science, while significantly reducing carbon emissions. Based on previously reported traverse fuel consumptions, a ground traverse from Pituffik to Warming Land would use 90% less fuel than aircraft-supported fieldwork. This assessment underscores the potential for sustainable ground-based access to Greenland’s oldest ice outcrop and other science sites within the region.

Accurately quantifying all the components of the surface energy balance (SEB) is a prerequisite for the reliable estimation of surface melt and the surface mass balance over ice and snow. This study quantifies the SEB closure by comparing the energy available for surface melt, determined from continuous measurements of radiative fluxes and turbulent heat fluxes, to the surface ablation measured on the Greenland ice sheet between 2003 and 2023. We find that the measured daily energy available for surface melt exceeds the observed surface melt by on average 18 +/- 30 W m-2 for snow and 12 +/- 54 W m-2 for ice conditions (mean +/- SD), which corresponds to 46 and 10% of the average energy available for surface melt, respectively. When the surface is not melting, the daily SEB is on average closed within 5 W m-2. Based on the inter-comparison of different ablation sensors and radiometers installed on different stations, and on the evaluation of modelled turbulent heat fluxes, we conclude that measurement uncertainties prevent a better daily to sub-daily SEB closure. These results highlight the need and challenges in obtaining accurate long-term in situ SEB observations for the proper evaluation of climate models and for the validation of remote sensing products.

Surface topography across the marginal zone of the Greenland Ice Sheet is constantly evolving in response to changing weather, season, climate, and ice dynamics. However, current digital elevation models (DEMs) for the ice sheet are usually based on data from a multi-year period, thus obscuring these changes over time. Here we present four 500 m resolution summer DEMs (PRODEMs) of the Greenland Ice Sheet marginal zone for 2019 through 2022. The PRODEMs cover the marginal zone from the ice edge to 50 km inland, hence capturing all Greenland outlet glaciers. Each PRODEM is based on data fusion of CryoSat-2 radar altimetry and ICESat-2 laser altimetry using regionally varying kriging of elevation anomalies relative to ArcticDEM. The PRODEMs are validated using leave-one-out cross-validation, and PRODEM19 is further validated against an external data set, showcasing their ability to correctly represent surface elevations within the associated spatially varying prediction uncertainties. We observe a general lowering of surface elevations during the 4-year PRODEM period, but the spatial pattern of change is highly complex and with annual changes superimposed. The PRODEMs enable detailed studies of the marginal ice sheet elevation changes. With their high spatio-temporal resolution, the PRODEMs will be of value to a wide range of researchers and users studying ice sheet dynamics and monitoring how the ice sheet responds to changing environmental conditions.

The negative surface mass balance of glaciers and ice caps under a warming climate impacts local ecosystems, influencing the volume and timing of water flow in local catchments while also contributing to global sea level rise. Peripheral glaciers distinct to the Greenland ice sheet respond faster to climate change than the main ice sheet. Accurate assessment of surface mass balance depends on in situ observations of near-surface climate and ice ablation, but very few in situ observations of near-surface climate and ice ablation are freely available for Greenland's peripheral glaciers. The transect of three automated weather and ablation stations on the peripheral A. P. Olsen Ice Cap in northeast Greenland is an example of these much needed data. The transect has been monitored since 2008, and in 2022, the old weather and ablation stations were replaced by a new standardized setup. In order to ensure comparable data quality of the old and new monitoring station setups, it is necessary to re-evaluate the data collected between 2008 and 2022. This paper presents the fully reprocessed near-surface climate and ablation data from the A. P. Olsen Ice Cap transect from 2008 to 2022, with a focus on data quality and the usability in ice ablation process studies. The usability of the data is exemplified by the data in an energy balance melt model for two different years. We show that the inherent uncertainties in the data result in an accurate reproduction of ice ablation for just one of the two years. A transect of three automatic ablation and weather stations of this length is unique to Greenland's peripheral glaciers, and it has a broad scale of usage from input to climate reanalysis and detailed surface ablation studies. The dataset can be downloaded at https://doi.org/10.22008/FK2/X9X9GN (Larsen and Citterio, 2023).

The firn layer on the Greenland Ice Sheet (GrIS) plays a crucial role in buffering surface meltwater runoff, which is constrained by the available firn pore space and impermeable ice layers that limit deeper meltwater percolation. Understanding these firn properties is essential for predicting current and future meltwater runoff and its contribution to global sea-level rise. While very-high-frequency (VHF) radars have been extensively used for surveying the GrIS, their lower bandwidth restricts direct firn stratigraphy extraction. In this study, we use concurrent VHF airborne radar and laser altimetry data collected as part of Operation IceBridge over the 2011–2019 period to investigate our hypothesis that vertical heterogeneities in firn (i.e. ice layers) cause vertical offsets in the radar surface reflection (dz). Our results, corroborated by modelling and firn core analyses, show that a dz larger than 1 m is strongly related to the vertical heterogeneity of a firn profile and effectively delineates between vertically homogeneous and vertically heterogeneous firn profiles over a depth range of ∼ 4 m. Temporal variations in dz align with climatic events and reveal an expansion of heterogeneous firn between 2011–2013 covering an area of ∼ 350 815 km2, followed by firn replenishment over the years 2014–2019 spanning an area of ∼ 667 725 km2. Our approach reveals the firn evolution of key regions on the Greenland Ice Sheet, providing valuable insights for detecting potential alterations in meltwater runoff patterns.

Surface melt on the Greenland ice sheet has been increasing in intensity and extent over the last decades due to Arctic atmospheric warming. Surface melt depends on the surface energy balance, which includes the atmospheric forcing but also the thermal budget of the snow, firn and ice near the ice sheet surface. The temperature of the ice sheet subsurface has been used as an indicator of the thermal state of the ice sheet's surface. Here, we present a compilation of 4612 measurements of firn and ice temperature at 10 m below the surface (T10 m) across the ice sheet, spanning from 1912 to 2022. The measurements are either instantaneous or monthly averages. We train an artificial neural network model (ANN) on 4597 of these point observations, weighted by their relative representativity, and use it to reconstruct T10 m over the entire Greenland ice sheet for the period 1950–2022 at a monthly timescale. We use 10-year averages and mean annual values of air temperature and snowfall from the ERA5 reanalysis dataset as model input. The ANN indicates a Greenland-wide positive trend of T10 m at 0.2 ∘C per decade during the 1950–2022 period, with a cooling during 1950–1985 (−0.4 ∘C per decade) followed by a warming during 1985–2022 (+0.7 ∘ per decade). Regional climate models HIRHAM5, RACMO2.3p2 and MARv3.12 show mixed results compared to the observational T10 m dataset, with mean differences ranging from −0.4 ∘C (HIRHAM) to 1.2 ∘C (MAR) and root mean squared differences ranging from 2.8 ∘C (HIRHAM) to 4.7 ∘C (MAR). The observation-based ANN also reveals an underestimation of the subsurface warming trends in climate models for the bare-ice and dry-snow areas. The subsurface warming brings the Greenland ice sheet surface closer to the melting point, reducing the amount of energy input required for melting. Our compilation documents the response of the ice sheet subsurface to atmospheric warming and will enable further improvements of models used for ice sheet mass loss assessment and reduce the uncertainty in projections.

<p>With temperatures in the Arctic rising rapidly at a rate of 3-4 times the global mean, monitoring the state of the Greenland ice sheet has never been more relevant.</p> <p>In-situ observations from the Arctic, in particular from the Greenland ice sheet, are scarce due to the cost and difficulty of maintaining instrumentation in the harsh and remote environment. Yet, the fate of the ice sheet concerns 100s of millions of people living in coastal zones worldwide. To gain understanding of the ice sheet processes leading to sea level rise and increase our ability to capture those in climate models, there is an urgent need to collect in-situ observations from the ice sheet surface. Similarly, ground-truthing observations are necessary for validation and calibration of satellite-derived estimates of ice sheet change.</p> <p>The Geological Survey of Denmark and Greenland (GEUS), along with partner institutions Asiaq and DTU Space, currently operates a combined network of 40 automatic weather stations (AWS) on ice in Greenland, mainly through the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and the Greenland Climate Network (GC-Net).</p> <p>GEUS has implemented a new pipeline providing near-real-time hourly weather observations from the PROMICE and GC-Net stations to its users and the World Meteorological Organization (WMO) for use in numerical weather prediction. The satellite-transmitted AWS data is processed and submitted to the WMO via the Danish Meteorological Institute with a latency of 7 minutes after observations are recorded.</p> <p>Here, we present the recent advances in our AWS instrumentation, data processing and database solution to invite discussion on how we can best meet the community needs for in-situ observations from the ice sheet.</p>

The Greenland Climate Network (GC-Net) consists of 31 automatic weather stations (AWSs) at 30 sites across the Greenland Ice Sheet. The first site was initiated in 1990, and the project has operated almost continuously since 1995 under the leadership of the late Konrad Steffen. The GC-Net AWS measured air temperature, relative humidity, wind speed, atmospheric pressure, downward and reflected shortwave irradiance, net radiation, and ice and firn temperatures. The majority of the GC-Net sites were located in the ice sheet accumulation area (17 AWSs), while 11 AWSs were located in the ablation area, and two sites (three AWSs) were located close to the equilibrium line altitude. Additionally, three AWSs of similar design to the GC-Net AWS were installed by Konrad Steffen's team on the Larsen C ice shelf, Antarctica. After more than 3 decades of operation, the GC-Net AWSs are being decommissioned and replaced by new AWSs operated by the Geological Survey of Denmark and Greenland (GEUS). Therefore, making a reassessment of the historical GC-Net AWS data is necessary. We present a full reprocessing of the historical GC-Net AWS dataset with increased attention to the filtering of erroneous measurements, data correction and derivation of additional variables: continuous surface height, instrument heights, surface albedo, turbulent heat fluxes, and 10 m ice and firn temperatures. This new augmented GC-Net level-1 (L1) AWS dataset is now available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2023) and will continue to be refined. The processing scripts, latest data and a data user forum are available at https://github.com/GEUS-Glaciology-and-Climate/GC-Net-level-1-data-processing (last access: 30 November 2023). In addition to the AWS data, a comprehensive compilation of valuable metadata is provided: maintenance reports, yearly pictures of the stations and the station positions through time. This unique dataset provides more than 320 station years of high-quality atmospheric data and is available following FAIR (findable, accessible, interoperable, reusable) data and code practices.

Turbulent heat fluxes, that is, the sensible heat flux and latent heat flux, are important sources/sinks of energy for surface melt over glaciers and ice sheets. Therefore, credible simulations of for example, future Greenland Ice Sheet mass loss need an accurate description of these fluxes. However, the parameterization of surface turbulent heat fluxes in climate models requires knowledge about the surface roughness lengths for momentum, heat and moisture, which are currently either unknown or tuned to indirect observations. In this study we take advantage of a large data set of eddy covariance observations acquired during multiple years and at multiple sites over the Greenland Ice Sheet. These in‐situ observations are used to develop an improved parameterization for the roughness length for momentum, and update the parameterization for the roughness lengths for heat and moisture over rough ice surfaces. The newly derived parameterizations are implemented in a surface energy balance model that is used to compute surface melt. Sensitivity experiments confirm the high sensitivity of surface melt to the chosen roughness length models. The new parameterization models the sensible heat flux to within 10 W m −2 , and the cumulative ice ablation within 10% at three out of four sites. Two case studies demonstrate the important contribution of the turbulent heat fluxes to surface ablation. The presented roughness parameterizations can be implemented in climate models to improve the physical representation of surface roughness over rough snow and ice surfaces, which is expected to improve the modeled turbulent heat fluxes and thus surface melt.