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The magnitude and azimuth of horizontal ice flow at Camp Century, Greenland have been measured several times since 1963. Here, we provide a further two independent measurements over the 2017–21 period. Our consensus estimate of horizontal ice flow from four independent satellite-positioning solutions is 3.65 ± 0.13 m a−1 at an azimuth of 236 ± 2°. A portion of the small, but significant, differences in ice velocity and azimuth reported between studies likely results from spatial gradients in ice flow. This highlights the importance of restricting inter-study comparisons of ice flow estimates to measurements surveyed within a horizontal distance of one ice thickness from each other. We suggest that ice flow at Camp Century is stable on seasonal to multi-decadal timescales. The airborne and satellite laser altimetry record indicates an ice thickening trend of 1.1 ± 0.3 cm a−1 since 1994. This thickening trend is qualitatively consistent with previously inferred ongoing millennial-scale ice thickening at Camp Century. The ice flow divide immediately north of Camp Century may now be migrating southward, although the reasons for this divide migration are poorly understood. The Camp Century flowlines presently terminate in the vicinity of Innaqqissorsuup Oqquani Sermeq (Gade Gletsjer) on the Melville Bay coast.

Remotely sensed land surface temperature (LST) data, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) LST thermal infrared products, are useful for monitoring surface processes on the Greenland Ice Sheet in remote areas but must be validated to ensure accuracy. Using data from the Programme for Monitoring the Greenland Ice Sheet (PROMICE), we conducted a MODIS LST validation (MOD/MYD11 C6 swath level product) using radiometric in-situ skin temperature records from 2014 to 2017 over 17 PROMICE sites mostly in the ice sheet's ablation zone. There is a significant cold bias in MODIS LST when compared to PROMICE skin temperature, particularly when PROMICE records temperatures below 0°C (mean bias: 2.4 ± 0.01°C mean ± standard error, RMSE = 3.2°C). Multiple linear regression analysis reveals the difference between MODIS LST and PROMICE skin temperature is larger at lower temperatures, lower latent heat fluxes and higher specific humidity. Our results confirm the presence of a progressive cold bias in the MODIS LST that should be considered in use of this product, and we identify and corroborate areas for ongoing algorithm development.

The Greenland ice sheet mass loss is one of the main sources of contemporary sea-level rise. The mass loss is primarily caused by surface melt and the resulting runoff. During the melt season, the ice sheet’s surface receives energy from sunlight absorption and sensible heating, which subsequently heats the subsurface snow and ice. The energy from the previous melt season can also enhance melting in the following summer as less heating is required to bring the snow and ice to the melting point. Subsurface temperatures are therefore both a result and a driver of the timing and magnitude of surface melt on the ice sheet. We present a dataset of more than 3900 measurements of ice, snow and firn temperature at 10 m depth across the Greenland ice sheet spanning the years from 1912 to 2022. We construct an artificial neural network (ANN) model that takes as input the ERA5 reanalysis monthly near-surface air temperature and snowfall for the 1954-2022 period and train it on our compilation of observed 10-meter temperature. We use our dataset and the ANN to evaluate three broadly used regional climate models (RACMO, MAR and HIRHAM). Our ANN model provides an unprecedented and observation-based description of the recent warming of the ice sheet’s near-surface and our evaluation of the three climate models highlights future development for the models. Overall, these findings improve our understanding of the ice sheet’s response to recent atmospheric warming and will help reduce uncertainties of ice sheet surface mass balance estimates.

The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheet properties since 2007. Currently, the PROMICE automatic weather station network includes 25 instrumented sites in Greenland. Accurate measurements of the surface and near-surface atmospheric conditions in a changing climate are important for reliable present and future assessment of changes in the Greenland Ice Sheet. Here, we present the PROMICE vision, methodology, and each link in the production chain for obtaining and sharing quality-checked data. In this paper, we mainly focus on the critical components for calculating the surface energy balance and surface mass balance. A user-contributable dynamic web-based database of known data quality issues is associated with the data products at https://github.com/GEUS-Glaciology-and-Climate/PROMICE-AWS-data-issues/ (last access: 7 April 2021). As part of the living data option, the datasets presented and described here are available at https://doi.org/10.22008/promice/data/aws (Fausto et al., 2019).

Here, we present a compilation of 85 ice temperature profiles from 79 boreholes from the Greenland Ice Sheet and peripheral ice caps, as well as local ice caps in the Canadian Arctic. Only 25 profiles (32 %) were previously available in open-access data repositories. The remaining 54 profiles (68 %) are being made digitally available here for the first time. These newly available profiles, which are associated with pre-2010 boreholes, have been submitted by community members or digitized from published graphics and/or data tables. All 85 profiles are now made available in both absolute (meters) and normalized (0 to 1 ice thickness) depth scales, and are accompanied by extensive metadata. This metadata includes a transparent description of data provenance. The ice temperature profiles span 70 years, with the earliest profile being from 1950 at Camp VI, West Greenland. To highlight the value of this database in evaluating ice flow simulations, we compare the ice temperature profiles from the Greenland Ice Sheet with an ice flow simulation by the Parallel Ice Sheet Model (PISM). We find a cold bias in modeled near-surface ice temperatures within the ablation area, a warm bias in modeled basal ice temperatures at inland cold-bedded sites, and an apparent underestimation of deformational heating in high-strain settings. These biases provide process-level insight on simulated ice temperatures., The Cryosphere Discussions, ISSN:1994-0432, ISSN:1994-0440

Mass loss from the Greenland Ice Sheet (GrIS) has accelerated over the past two decades, coincident with rapid Arctic warming and increasing moisture transport over Greenland by atmospheric rivers (ARs). Summer ARs affecting western Greenland trigger GrIS melt events, but the physical mechanisms through which ARs induce melt are not well understood. This study elucidates the coupled surface–atmosphere processes by which ARs force GrIS melt through analysis of the surface energy balance (SEB), cloud properties, and local- to synoptic-scale atmospheric conditions during strong summer AR events affecting western Greenland. ARs are identified in MERRA-2 reanalysis (1980–2017) and classified by integrated water vapor transport (IVT) intensity. SEB, cloud, and atmospheric data from regional climate model, observational, reanalysis, and satellite-based datasets are used to analyze melt-inducing physical processes during strong, >90th percentile “AR90+” events. Near AR “landfall,” AR90+days feature increased cloud cover that reduces net shortwave radiation and increases net longwave radiation. As these oppositely signed radiative anomalies partly cancel during AR90+events, increased melt energy in the ablation zone is primarily provided by turbulent heat fluxes, particularly sensible heat flux. These turbulent heat fluxes are driven by enhanced barrier winds generated by a stronger synoptic pressure gradient combined with an enhanced local temperature contrast between cool over-ice air and the anomalously warm surrounding atmosphere. During AR90+events in northwest Greenland, anomalous melt is forced remotely through a clear-sky foehn regime produced by downslope flow in eastern Greenland.

We present a 1986 through March 2020 estimate of Greenland Ice Sheet ice discharge. Our data include all discharging ice that flows faster than 100 m yr−1 and are generated through an automatic and adaptable method, as opposed to conventional handpicked gates. We position gates near the present-year termini and estimate problematic bed topography (ice thickness) values where necessary. In addition to using annual time-varying ice thickness, our time series uses velocity maps that begin with sparse spatial and temporal coverage and end with near-complete spatial coverage and 12 d updates to velocity. The 2010 through 2019 average ice discharge through the flux gates is ∼487±49 Gt yr−1. The 10 % uncertainty stems primarily from uncertain ice bed location (ice thickness). We attribute the ∼50 Gt yr−1 differences among our results and previous studies to our use of updated bed topography from BedMachine v3. Discharge is approximately steady from 1986 to 2000, increases sharply from 2000 to 2005, and then is approximately steady again. However, regional and glacier variability is more pronounced, with recent decreases at most major glaciers and in all but one region offset by increases in the northwest region through 2017 and in the southeast from 2017 through March 2020. As part of the journal's living archive option and our goal to make an operational product, all input data, code, and results from this study will be updated as needed (when new input data are available, as new features are added, or to fix bugs) and made available at https://doi.org/10.22008/promice/data/ice_discharge (Mankoff, 2020a) and at https://github.com/mankoff/ice_discharge (last access: 6 June 2020, Mankoff, 2020e).

Current sea-level rise partly stems from increased surface melting and meltwater runoff from the Greenland ice sheet. Multi-year snow, also known as firn, covers about 80% of the ice sheet and retains part of the surface meltwater. Since the firn cold content integrates its physical and thermal characteristics, it is a valuable tool for determining the meltwater-retention potential of firn. We use gap-filled climatological data from nine automatic weather stations in the ice-sheet accumulation area to drive a surface-energy-budget and firn model, validated against firn density and temperature observations, over the 1998-2017 period. Our results show a stable top 20 m firn cold content (CC20) at most sites. Only at the lower-elevation Dye-2 site did CC20 decrease, by 24% in 2012, before recovering to its original value by 2017. Heat conduction towards the surface is the main process feeding CC20 at all nine sites, while CC20 reduction occurs through low-cold-content fresh-snow addition at the surface during snowfall and latent-heat release when meltwater refreezes. Our simulations suggest that firn densification, while reducing pore space for meltwater retention, increases the firn cold content, enhances near-surface meltwater refreezing and potentially sets favourable conditions for ice-slab formation., SCOPUS: ar.j, info:eu-repo/semantics/published

The Greenland ice sheet outputs freshwater into the Greenlandic fjords in the form of icebergs and liquid meltwater. This freshwater flux affects the fjords’ water circulation and ecosystems. In recent decades, the mass loss from the ice sheet has increased causing an increasing volume of liquid and solid freshwater to enter the fjords and ocean around Greenland. The total volume of freshwater is currently challenging to determine on a fjord-basin scale due to disparate products that are difficult to compare and combine into a cohesive product. This entails that the effect of the glacially derived freshwater on fjord circulation and ecosystem is not well constrained.Here, we present a new glacier-basin scale product that combines three existing products into a shared temporal and spatial framework. We use publicly available datasets of solid ice discharge (icebergs), surface meltwater run-off, and basal melt to present a cohesive overview of the influx of freshwater to the Greenlandic fjords. We then quantify the different dominant term for each glacier. The dataset will be freely available and will be of use to, for example, oceanographic and marine biological research activities.This work was supported by PROMICE (Programme for Monitoring the Greenland Ice Sheet, GEUS) and ESA Polar+ 4D Greenland.

The turbulent exchange of heat at the surface, including the sensible heat flux (SHF), is an important component of the surface energy balance (SEB) over glaciers and ice sheets. Yet, the turbulent heat fluxes are parameterized in all SEB models, which makes their contribution to the modelled ice ablation uncertain.In this study, we present several years of continuous, daily, in situ observations of SHF (eddy-covariance) and ice ablation, taken at multiple contrasting sites across the ablation area of the Greenland ice sheet. We then compare these measurements to several SEB models with different settings for the surface roughness lengths.We show that it is possible to accurately model the SHF and the daily ice ablation, provided that the prescribed surface roughness lengths, for both heat and momentum, are accurate. We propose a simple parameterization of these roughness lengths, based on both in-situ measurements and remotely sensed data (UAV, ICESat-2). This updated parameterization can be implemented in SEB- and climate- models for improved simulations of ice sheet ablation and surface mass balance.

In recent decades, the Greenland Ice Sheet (GrIS) has experienced a significant increase in surface melting and meltwater runoff, which is now the main contributor to GrIS mass loss. In areas covered by firn, meltwater percolation and refreezing processes can significantly buffer meltwater runoff to the ocean. However, this process leads to the formation of ice layers and an overall firn densification, which is predicted to limit the firns’ meltwater storage capacity in the future. Additionally, the high spatial and temporal variability of ice layer formation and subsequent firn densification can cause large uncertainties in altimetry-derived mass balance estimates. Thus, understanding the spatial and vertical extent of ice layers in the firn is important to estimate the GrIS contribution to sea-level rise.Due to limited direct observations of firn properties, modeling future meltwater runoff and processes over the rapidly changing GrIS firn facies remains challenging. Here, we present a prospective new technique that leverages concurrent airborne radar sounding and laser altimetry measurements to characterize near-surface firn over spatially extensive areas. We hypothesize that due to their different depth sensitivities, the presence of ice layers in the firn yields an offset between radar sounding- and laser-derived surface elevations (differential altimetry). We compare existing airborne radar and laser measurements to in-situ firn observations and use one-dimensional radar sounding simulations to investigate 1) the sensitivity of the differential altimetry technique to different firn facies, and 2) the techniques’ capability to estimate firn density and firn ice content. Preliminary results over the western GrIS show good correlations between differential altimetry signatures and areas of firn affected by percolation and refreezing processes.Through this technique, we explore the potential to leverage a wealth of radar sounding measurements conducted at low frequencies (< 200 MHz), that typically do not resolve the firn structure, to derive near-surface firn properties. Finally, we apply the differential altimetry technique to data collected as part of NASA’s Operation IceBridge between 2009-2019 to derive spatio-temporal changes in the GrIS firn in response to climatic conditions, in particular the formation of ice layers and changes in firn ice content. Our results can help reduce uncertainties in satellite-derived mass balance measurements and improve firn models, which both contribute to reducing uncertainties in current and projected GrIS contributions to global sea-level rise.

We compile and analyze all available geothermal heat flow measurements collected in and around Greenland into a new database of 419 sites and generate an accompanying spatial map. This database includes 290 sites previously reported by the International Heat Flow Commission (IHFC), for which we now standardize measurement and metadata quality. This database also includes 129 new sites, which have not been previously reported by the IHFC. These new sites consist of 88 offshore measurements and 41 onshore measurements, of which 24 are subglacial. We employ machine learning to synthesize these in situ measurements into a gridded geothermal heat flow model that is consistent across both continental and marine areas in and around Greenland. This model has a native horizontal resolution of 55 km. In comparison to five existing Greenland geothermal heat flow models, our model has the lowest mean geothermal heat flow for Greenland onshore areas. Our modeled heat flow in central North Greenland is highly sensitive to whether the NGRIP (North GReenland Ice core Project) elevated heat flow anomaly is included in the training dataset. Our model's most distinctive spatial feature is pronounced low geothermal heat flow (

The Greenland ice sheet has been one of the largest sources of sea-level rise since the early 2000s. However, basal melt has not been included explicitly in assessments of ice-sheet mass loss so far. Here, we present the first estimate of the total and regional basal melt produced by the ice sheet and the recent change in basal melt through time. We find that the ice sheet’s present basal melt production is 21.4 +4.4/−4.0 Gt per year, and that melt generated by basal friction is responsible for about half of this volume. We estimate that basal melting has increased by 2.9 ± 5.2 Gt during the first decade of the 2000s. As the Arctic warms, we anticipate that basal melt will continue to increase due to faster ice flow and more surface melting thus compounding current mass loss trends, enhancing solid ice discharge, and modifying fjord circulation., Melting at the base of the Greenland Ice Sheet is often disregarded as a source of quantifiable mass loss. In this study, the authors find the basal mass loss is equivalent to 8% of the ice sheet’s present imbalance, and that the loss of mass from basal melt is likely to increase in the future.

The mass of the Greenland ice sheet is declining as mass gain from snowfall is exceeded by mass loss from surface meltwater runoff, marine-terminating glacier calving and submarine melting, and basal melting. Here we use the input/output (IO) method to estimate mass change from 1840 through next week. Mass gains come from three regional climate models (RCMs; HIRHAM/HARMONIE, MAR, and RACMO) and a semi-empirical surface mass balance (SMB) model. Mass losses come from the RCMs, a statistical SMB model, ice discharge at marine terminating glaciers, and ice melted at the base of the ice sheet. From these products we provide an annual estimate of GIS mass balance from 1840 through 1985 and a daily estimate at sector and region scale from 1986 through next week. Compared to other mass balance estimates, this product updates daily, has higher temporal resolution, and is the first IO product to include the basal mass balance which is a source of an additional ~8 % mass loss. Our results demonstrate an accelerating GIS-scale mass loss and general agreement among six other products. Results from this study are available at https://dataverse01.geus.dk/privateurl.xhtml?token=d09976c4-4f89-43ef-8f91-173d269806a4 (Mankoff et al., 2021).

The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) provides surface meteorological and glaciological measurements from widespread on-ice automatic weather stations since mid-2007. In this study, we use 105 PROMICE ice-ablation time series to identify the timing of seasonal bare-ice onset preceded by snow cover conditions. From this collection, we find a bare-ice albedo at ice-ablation onset (here called bare-ice-onset albedo) of 0.565 ± 0.109 that has no apparent spatial dependence among 20 sites across Greenland. We then apply this snow-to-ice albedo transition value to measure the variations in daily Greenland bare-ice area in Sentinel-3 optical satellite imagery covering the extremely low and high respective melt years of 2018 and 2019. Daily Greenland bare-ice area peaked at 153 489 km² in 2019, 1.9 times larger than in 2018 (80 220 km²), equating to 9.0% (in 2019) and 4.7% (in 2018) of the ice sheet area.

The total mass balance of ice sheets is determined using estimates of ice volume change from satellite altimetry, measurements of gravity changes, or by differencing solid ice discharge and surface mass balance. The basal melt is only implicitly included in the first two and entirely neglected by the last method. Here, we show that the basal mass loss of the Greenland Ice Sheet is a non-negligible component of the total mass budget. We estimate that the basal melt is 21.4 +4.4/-4.0 Gt per year corresponding to 8% of the ice sheet’s total mass balance. The basal melt is composed of three separate terms; melt caused by frictional heat, geothermal heat and heat from surface meltwater, respectively, and the basal friction term is responsible for half of the basal melt.Importantly, the geothermal and friction heat are active year round. This implies that a quantifiable volume of freshwater is discharged into the Greenlandic fjords during the winter where the ice-fjord interactions often are assumed dormant. Here, we present basal melt volumes from different outlet glaciers that discharge into Greenlandic fjords. We compare the basal melt to the freshwater volumes generated by surface meltwater, and identify locations where basal melt volumes are comparable to surface meltwater during the winter.

We present the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) Ice Velocity product (https://doi.org/10.22008/promice/data/sentinel1icevelocity/greenlandicesheet, Solgaard and Kusk, 2021), which is a time series of Greenland Ice Sheet ice velocity mosaics spanning September 2016 through to the present. The product is based on Sentinel-1 synthetic aperture radar data and has a 500 m grid spacing. A new mosaic is available every 12 d and spans two consecutive Sentinel-1 cycles (24 d). The product is made available within ∼ 10 d of the last acquisition and includes all possible 6 and 12 d pairs within the two Sentinel-1A cycles. We describe our operational processing chain from data selection, mosaicking, and error estimation to final outlier removal. The product is validated against in situ GPS measurements. We find that the standard deviation of the difference between satellite- and GPS-derived velocities (and bias) is 20 m yr−1 (−3 m yr−1) and 27 m yr−1 (−2 m yr−1) for the components in an eastern and northern direction, respectively. Over stable ground the values are 8 m yr−1 (0.1 m yr−1) and 12 m yr−1 (−0.6 m yr−1) in an eastern and northern direction, respectively. This is within the expected values; however, we expect that the GPS measurements carry a considerable part of this uncertainty. We investigate variations in coverage from both a temporal and spatial perspective. The best spatial coverage is achieved in winter due to the comprehensive data coverage by Sentinel-1 and high coherence, while summer mosaics have the lowest coverage due to widespread melt. The southeast Greenland Ice Sheet margin, along with other areas of high accumulation and melt, often has gaps in the ice velocity mosaics. The spatial comprehensiveness and temporal consistency make the product ideal both for monitoring and for studying ice-sheet-wide and glacier-specific ice discharge and dynamics of glaciers on seasonal scales.

We provide high-resolution datasets of Greenland hydrologic outlets, basins, and streams, and a 1979 through 2017 time series of Greenland liquid water runoff for each outlet. Outlets, basins, and streams are derived from traditional hydrologic routing algorithms over the surface of a 100 m ArcticDEM digital elevation model (DEM) twice: Once to the ice margin and once to the coast. We then partition liquid water runoff from both ice and land from two regional climate models (RCMs; MAR and RACMO) into each basin and at each outlet location. The data include 18903 ice basins and outlets (614 basins greater than 10 km2), 30241 land basins and outlets (958 basins greater than 10 km2), major streams in each basin, and daily runoff water volume flow rate at each outlet from each of two RCMs. We perform a sensitivity study of outlet location change for every ice sheet location over a range of hydrologic routing assumptions and data sets. Annual runoff from the ice ranges from ~136 km3 in 1992 to ~785 km3 in 2012. Daily maximum ice runoff from one basin is as large as 4380 m3 s−1. Both ice runoff magnitude and variability increase over the time series. Land runoff contributes an additional ∼ 35 % to the ice runoff. Comparison with 9 basins instrumented with stream gauges shows a range of (dis)agreement from poor to excellent between our estimated discharge and observations. As part of the journal’s living archive option, and our goal to make an operational product, all input data, code, and results from this study will be updated as needed (when new input data are available, as new features are added, or to fix bugs) and made available at https://doi.org/10.22008/promice/data/freshwater_runoff/v01 (Mankoff, 2020) and at http://github.com/mankoff/freshwater.

Alfred Wegener contributed extraordinarily to early days of scientific explorations in Greenland. Involved in three expeditions, we present unique historical data that is stored at Graz University, where Wegener filled his last academic position until his tragic death in Greenland in 1930. In this contribution we reevaluate data from his last expedition 1929-1931 acquired at the Qaamarujuup Glacier in West Greenland (71°09'N; 51°11'W). Sub-weekly ablation measurements along with air temperature, humidity, pressure, wind and short-wave radiation data exist for two full ablation seasons both near sea level and in 950 m a.s.l.. The 20th Century reanalysis product of the nearest grid-point performs well reproducing air temperature variability. Coincidentally, this expedition was carried out during a very warm period that was in fact comparable to recent years. We compare vertical ablation gradients from the years 1929/1930 obtained at Qaamarujuup in West Greenland with recent observations from the closest PROMICE automated weather station and discuss differences in a centennial perspective. Furthermore, we present a time-series of glacier stages from the little ice age (LIA) maximum up to present and quantify area and volume changes since. The glacier margin was in close proximity (

As Arctic temperatures have increased, the Greenland Ice Sheet has exhibited a negative mass balance, with a substantial and increasing fraction of mass loss due to surface melt. Understanding surface energy exchange processes in Greenland is critical for our ability to predict changes in mass balance. In-situ and remotely sensed surface temperatures are useful for monitoring trends, melt events, and surface energy balance processes, but these observations are complicated by the fact that surface temperatures and near surface air temperatures can significantly differ due to the presence of inversions that exist across the Arctic. Our previous work shows that even in the summer, very near surface inversions are present between the 2m air and surface temperatures a majority of the time at Summit, Greenland. In this study, we expand upon these results and combine a variety of data sources to quantify differences between surface snow/ice temperatures and 2m air temperatures across the Greenland Ice Sheet and investigate controls on the magnitude of these near surface temperature inversions. In-situ temperatures, wind speed, specific humidity, and albedo data are provided from automatic weather stations operated by the Programme for Monitoring of the Greenland Ice Sheet (PROMICE). We use the Clouds and the Earth's Radiant Energy System (CERES) cloud area fraction data to analyze effects of cloud presence on near surface temperature gradients. The in-situ temperatures are compared to Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) and Moderate Resolution Imaging Spectrometer (MODIS) ice surface temperature data to extend findings across the ice sheet. Using PROMICE in-situ data from 2015, we find that these 2m temperature inversions are present 77% of the time, with a median strength of 1.7°C. The data confirm that the presence of clouds weakens inversions. Initial results indicate a RMSE of 3.9°C between MERRA-2 and PROMICE 2m air temperature, and a RMSE of 5.6°C between the two datasets for surface temperature. Improved understanding of controls on near surface inversions is important for use of remotely sensed snow surface temperatures and for modeling of surface mass and energy exchange processes.

The Greenland ice sheet has been one of largest sources of sea-level rise since the early 2000s. The total mass balance of the ice sheet is typically determined using one of the following methods: estimates of ice volume change from satellite altimetry, measurements of changes in gravity, and by considering the difference between solid ice discharge and surface mass balance (often referred to as the input–output method). In spite of an overall agreement between the different methods, uncertainties remain regarding the relative contribution from individual processes, and to date the basal melt has never been explicitly included in total mass balance estimates. Here, we present the first estimate of the contribution from basal melting to the total mass balance. We partition the basal melt into three terms; melt caused by frictional heat, geothermal heat and viscous heat dissipation, respectively. Combined, the three terms contribute approximately 25 Gt per year of basal melt to the total mass loss equivalent to 5% of the average solid ice discharge (average value of 1986-2018 discharge). This is equivalent to the ice discharge from the entire northeastern sector. We find that basal melting also accounts for between 5% and 30% of observed thinning in most major glacier outlets. Over our observation period (winter 2017/18), close to 2/3 of the basal melt is due to frictional heating from fast moving ice. This term is expected to increase in the future, as ice streams are likely to expand and speed up in response to rising temperatures.

Mass loss from glacier surface melt is buffered by percolation and refreezing in the underlying snowpack, processes of particular importance in the percolation zone of the Greenland ice sheet and increasingly in Antarctica under a warming climate. Retention and refreezing is dependent on a number of micro-scale factors such as snow grain size, density and temperature that are heavily parameterized in models. Melt and snowfall in preceding seasons are also important in determining retention rates in the current season due to initialization of the snowpack .In the retention model intercomparison project (RetMIP) we use a common atmospheric forcing from the HIRHAM5 regional climate model to drive participating models, to study the effect of different internal parameterisations. We compare 9 different 1D models and four 2D models with each other and with observations from 4 key field sites. We show that initialisation of snowpack models is important but evolution of retention through time is strongly determined by melt rates.Models that explicitly account for deep meltwater percolation tend to overestimate percolation depth and consequently firn temperature at the percolation and ice slab sites although they simulate accurately the recharge of the firn aquifer. Models using Darcy’s law and bucket scheme compare favourably to observations at the percolation site but only the Darcy models accurately simulate firn temperature and thus meltwater percolation at the ice slab site. We find that Eulerian models that transfer firn through fixed layers, diffuse over time the gradients in firn temperature and density. No model outperforms all others at our four test sites indicating that all models have potential for development.A first look at Antarctic firn processes emphasises the importance of long spin-up times to initialise the snowpack and as the ice sheet surface evolves in the future parameterising the specific Antarctic retention process is likely to become more important.

The ERA5 reanalysis, recently made available by the European Centre for Medium-Range Weather Forecasts (ECMWF), is a new reanalysis product at a high resolution replacing ERA-Interim and is considered to provide the best climate reanalysis over Greenland to date. However, so far little is known about the performance of ERA5 over the Greenland Ice Sheet (GrIS). In this study, we compare the near-surface climate from the new ERA5 reanalysis to ERA-Interim, the Arctic System Reanalysis (ASR) as well as to a state-of-the-art polar regional climate model (MAR). The results show (1) that ERA5 does not outperform ERA-Interim significantly when compared with near-surface climate observations over GrIS, but ASR better models the near-surface temperature than both ERA reanalyses. (2) Polar regional climate models (e.g., MAR) are still a useful tool to downscale the GrIS climate compared to ERA5, as in particular the near-surface temperature in summer has a key role for representing snow and ice processes such as the surface melt. However, assimilating satellite data and using a more recent radiative scheme enable both ERA and ASR reanalyses to represent more satisfactorily than MAR the downward solar and infrared fluxes. (3) MAR near-surface climate is not affected when forced at its lateral boundaries by either ERA5 or ERA-Interim. Therefore, forcing polar regional climate models with ERA5 starting from 1950 will enable long and homogeneous surface mass balance reconstructions.

We present a 1986 through 2019 estimate of Greenland Ice Sheet ice discharge. Our data include all discharging ice that flows faster than 100 m yr−1 and are generated through an automatic and adaptable method, as opposed to conventional hand-picked gates. We position gates near the present-year termini and estimate problematic bed topography (ice thickness) values where necessary. In addition to using annual time-varying ice thickness, our time series uses velocity maps that begin with sparse spatial and temporal coverage and ends with near-complete spatial coverage and twelve-day updates to velocity. The 2010 through 2019 average ice discharge through the flux-gates is ~ 487 + −49 Gt yr−1. The 10 % uncertainty stems primarily from uncertain ice bed location (ice thickness). We attribute the ~ 50 Gt yr−1 differences among our results and previous studies to our use of updated bed topography from BedMachine v3. Discharge is approximately steady from 1986 to 2000, increases sharply from 2000 to 2005, then is approximately steady again. However, regional and glacier variability is more pronounced, with recent decreases at most major glaciers and in all but one region offset by increases in the northwest region. As part of the journal's living archive option and our goal to make an operational product, all input data, code, and results from this study will be updated as needed (when new input data are available, as new features are added, or to fix bugs) and made available at doi:10.22008/promice/data/ice_discharge and at http://github.com/mankoff/ice_discharge.

Mass‐balance estimates of the polar ice sheets presently rely on static ice masks to identify the area under investigation. However, the vintage of available ice masks can differ by more than a decade and the resolution of the imagery used to delineate ice extent can differ by an order of magnitude, despite evidence of ongoing ice‐sheet retreat. We show that using a fine‐resolution, time‐varying ice mask significantly improves mass‐balance estimates of the northwestern sector of the Greenland Ice Sheet and affects interpretation of local crustal uplift. Accounting for ice margin retreat using a time‐varying ice mask between 2003–2015 results in 1.0–6.8% less ice‐sheet mass loss relative to assuming one of several existing static ice masks. This indicates that mass‐balance estimates that use a static ice mask will progressively overestimate mass loss where the ice sheet is predominantly retreating, meaning a negative bias on mass‐balance. This trend is anticipated to be amplified in a future warming scenario unless updated ice masks are incorporated. For altimetry‐derived mass‐balance estimates, this ice‐mask‐induced bias approaches the magnitude of the ice‐sheet‐wide uncertainty presently associated with spatiotemporal variability in modeled firn compaction. Further, at five GNET stations, the ice‐mask‐induced bias is equivalent to 5–15% of the modeled uplift due to elastic deformation. Given present and projected negative trends in Greenland Ice Sheet mass‐balance and areal extent, we conclude that studies of its mass‐balance should begin incorporating dynamic, periodically updated, fine‐resolution ice masks. This methodological refinement will reduce bias in estimates of both ice‐sheet mass‐balance and crustal uplift.