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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.

Ice loss from the Greenland ice sheet is one of the largest sources of contemporary sea-level rise (SLR). While process-based models place timescales on Greenland’s deglaciation, their confidence is obscured by model shortcomings including imprecise atmospheric and oceanic couplings. Here, we present a complementary approach resolving ice sheet disequilibrium with climate constrained by satellite-derived bare-ice extent, tidewater sector ice flow discharge and surface mass balance data. We find that Greenland ice imbalance with the recent (2000–2019) climate commits at least 274 ± 68 mm SLR from 59 ± 15 × 103 km2 ice retreat, equivalent to 3.3 ± 0.9% volume loss, regardless of twenty-first-century climate pathways. This is a result of increasing mass turnover from precipitation, ice flow discharge and meltwater run-off. The high-melt year of 2012 applied in perpetuity yields an ice loss commitment of 782 ± 135 mm SLR, serving as an ominous prognosis for Greenland’s trajectory through a twenty-first century of warming.Greenland ice sheet melt is currently the largest single contributor to sea-level rise. This work combines observations and theory to show that Greenland ice sheet imbalance with recent climate (2000–2019) has already committed at least 3.3% ice volume loss, equivalent to 274 mm of global sea-level rise.

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 satellitebased 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 AR901 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 northwestGreenland, anomalousmelt 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).

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.

Greenland runoff, from ice mass loss and increasing rainfall, is increasing. That runoff, as discharge, impacts the physical, chemical, and biological properties of the adjacent fjords. However, where and when the discharge occurs is not readily available in an open database. Here we provide data sets of high-resolution Greenland hydrologic outlets, basins, and streams, as well as a daily 1958 through 2019 time series of Greenland liquid water discharge for each outlet. The data include 24 507 ice marginal outlets and upstream basins and 29 635 land coast outlets and upstream basins, derived from the 100 m ArcticDEM and 150 m BedMachine. At each outlet there are daily discharge data for 22 645 d – ice sheet runoff routed subglacially to ice margin outlets and land runoff routed to coast outlets – from two regional climate models (RCMs; MAR and RACMO). Our sensitivity study of how outlet location changes for every inland cell based on subglacial routing assumptions shows that most inland cells where runoff occurs are not highly sensitive to those routing assumptions, and outflow location does not move far. We compare RCM results with 10 gauges from streams with discharge rates spanning 4 orders of magnitude. Results show that for daily discharge at the individual basin scale the 5 % to 95 % prediction interval between modeled discharge and observations generally falls within plus or minus a factor of 5 (half an order of magnitude, or +500 %/-80 %). Results from this study are available at https://doi.org/10.22008/promice/freshwater (Mankoff, 2020a) and code is available at http://github.com/mankoff/freshwater (last access: 6 November 2020) (Mankoff, 2020b).

Perennial snow, or firn, covers 80 % of the Greenland ice sheet and has the capacity to retain surface meltwater, influencing the ice sheet mass balance and contribution to sea-level rise. Multilayer firn models are traditionally used to simulate firn processes and estimate meltwater retention. We present, intercompare and evaluate outputs from nine firn models at four sites that represent the ice sheet's dry snow, percolation, ice slab and firn aquifer areas. The models are forced by mass and energy fluxes derived from automatic weather stations and compared to firn density, temperature and meltwater percolation depth observations. Models agree relatively well at the dry-snow site while elsewhere their meltwater infiltration schemes lead to marked differences in simulated firn characteristics. Models accounting for deep meltwater percolation overestimate percolation depth and firn temperature at the percolation and ice slab sites but accurately simulate recharge of the firn aquifer. Models using Darcy's law and bucket schemes compare favorably to observed firn temperature and meltwater percolation depth at the percolation site, but only the Darcy models accurately simulate firn temperature and percolation at the ice slab site. Despite good performance at certain locations, no single model currently simulates meltwater infiltration adequately at all sites. The model spread in estimated meltwater retention and runoff increases with increasing meltwater input. The highest runoff was calculated at the KAN_U site in 2012, when average total runoff across models (±2σ) was 353±610 mm w.e. (water equivalent), about 27±48 % of the surface meltwater input. We identify potential causes for the model spread and the mismatch with observations and provide recommendations for future model development and firn investigation.

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.

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).

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.