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With the aim of studying the recent Greenland ice sheet (GrIS) surface mass balance (SMB) decrease relative to the last century, we have forced the regional climate MAR (Modèle Atmosphérique Régional; version 3.5.2) model with the ERA-Interim (ECMWF Interim Re-Analysis; 1979–2015), ERA-40 (1958–2001), NCEP–NCARv1 (National Centers for Environmental Prediction–National Center for Atmospheric Research Reanalysis version 1; 1948–2015), NCEP–NCARv2 (1979–2015), JRA-55 (Japanese 55-year Reanalysis; 1958–2014), 20CRv2(c) (Twentieth Century Reanalysis version 2; 1900–2014) and ERA-20C (1900–2010) reanalyses. While all these forcing products are reanalyses that are assumed to represent the same climate, they produce significant differences in the MAR-simulated SMB over their common period. A temperature adjustment of +1 °C (respectively −1 °C) was, for example, needed at the MAR boundaries with ERA-20C (20CRv2) reanalysis, given that ERA-20C (20CRv2) is ∼ 1 °C colder (warmer) than ERA-Interim over Greenland during the period 1980–2010. Comparisons with daily PROMICE (Programme for Monitoring of the Greenland Ice Sheet) near-surface observations support these adjustments. Comparisons with SMB measurements, ice cores and satellite-derived melt extent reveal the most accurate forcing datasets for the simulation of the GrIS SMB to be ERA-Interim and NCEP–NCARv1. However, some biases remain in MAR, suggesting that some improvements are still needed in its cloudiness and radiative schemes as well as in the representation of the bare ice albedo. Results from all MAR simulations indicate that (i) the period 1961–1990, commonly chosen as a stable reference period for Greenland SMB and ice dynamics, is actually a period of anomalously positive SMB (∼ +40 Gt yr−1) compared to 1900–2010; (ii) SMB has decreased significantly after this reference period due to increasing and unprecedented melt reaching the highest rates in the 120-year common period; (iii) before 1960, both ERA-20C and 20CRv2-forced MAR simulations suggest a significant precipitation increase over 1900–1950, but this increase could be the result of an artefact in the reanalyses that are not well-enough constrained by observations during this period and (iv) since the 1980s, snowfall is quite stable after having reached a maximum in the 1970s. These MAR-based SMB and accumulation reconstructions are, however, quite similar to those from Box (2013) after 1930 and confirm that SMB was quite stable from the 1940s to the 1990s. Finally, only the ERA-20C-forced simulation suggests that SMB during the 1920–1930 warm period over Greenland was comparable to the SMB of the 2000s, due to both higher melt and lower precipitation than normal.

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.

A porous layer of multi-year snow known as firn covers the Greenland-ice-sheet interior. The firn layer buffers the ice-sheet contribution to sea-level rise by retaining a fraction of summer melt as liquid water and refrozen ice. In this study we quantify the Greenland ice-sheet firn air content (FAC), an indicator of meltwater retention capacity, based on 360 point observations. We quantify FAC in both the uppermost 10 m and the entire firn column before interpolating FAC over the entire ice-sheet firn area as an empirical function of long-term mean air temperature (Ta‾) and net snow accumulation (c˙‾). We estimate a total ice-sheet-wide FAC of 26 800±1840 km3, of which 6500±450 km3 resides within the uppermost 10 m of firn, for the 2010–2017 period. In the dry snow area (Ta‾≤-19 ∘C), FAC has not changed significantly since 1953. In the low-accumulation percolation area (Ta‾>-19 ∘C and c˙‾≤600 mm w.e. yr−1), FAC has decreased by 23±16 % between 1998–2008 and 2010–2017. This reflects a loss of firn retention capacity of between 150±100 Gt and 540±440 Gt, respectively, from the top 10 m and entire firn column. The top 10 m FACs simulated by three regional climate models (HIRHAM5, RACMO2.3p2, and MARv3.9) agree within 12 % with observations. However, model biases in the total FAC and marked regional differences highlight the need for caution when using models to quantify the current and future FAC and firn retention capacity.

We present a 1986 through 2017 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 end with near-complete spatial coverage and 6 d updates to velocity. The 2010 through 2017 average ice discharge through the flux gates is ∼488±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 NW (northwestern) region. As part of the journal's living archive option, all input data, code, and results from this study will be updated when new input data are accessible and made freely available at https://doi.org/10.22008/promice/data/ice_discharge.

We evaluate modelled Greenland ice sheet (GrIS) near-surface climate, surface energy balance (SEB) and surface mass balance (SMB) from the updated regional climate model RACMO2 (1958–2016). The new model version, referred to as RACMO2.3p2, incorporates updated glacier outlines, topography and ice albedo fields. Parameters in the cloud scheme governing the conversion of cloud condensate into precipitation have been tuned to correct inland snowfall underestimation: snow properties are modified to reduce drifting snow and melt production in the ice sheet percolation zone. The ice albedo prescribed in the updated model is lower at the ice sheet margins, increasing ice melt locally. RACMO2.3p2 shows good agreement compared to in situ meteorological data and point SEB/SMB measurements, and better resolves the spatial patterns and temporal variability of SMB compared with the previous model version, notably in the north-east, south-east and along the K-transect in south-western Greenland. This new model version provides updated, high-resolution gridded fields of the GrIS present-day climate and SMB, and will be used for projections of the GrIS climate and SMB in response to a future climate scenario in a forthcoming study.

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.

Surface melt and mass loss of the Greenland Ice Sheet may play crucial roles in global climate change due to their positive feedbacks and large fresh-water storage. With few other regular meteorological observations available in this extreme environment, measurements from automatic weather stations (AWS) are the primary data source for studying surface energy budgets, and for validating satellite observations and model simulations. Station tilt, due to irregular surface melt, compaction and glacier dynamics, causes considerable biases in the AWS shortwave radiation measurements. In this study, we identify tilt-induced biases in the climatology of surface shortwave radiative flux and albedo, and retrospectively correct these by iterative application of solar geometric principles. We found, over all the AWS from the Greenland Climate Network (GC-Net), the Kangerlussuaq transect (K-transect) and the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) networks, insolation on fewer than 40 % of clear days peaks within 0.5 h of solar noon time, with the largest shift exceeding 3 h due to tilt. Hourly absolute biases in the magnitude of surface insolation can reach up to 200 W m−2, with respect to the well-understood clear-day insolation. We estimate the tilt angles and their directions based on the solar geometric relationship between the simulated insolation at a horizontal surface and the observed insolation by these tilted AWS under clear-sky conditions. Our adjustment reduces the root mean square error (RMSE) against references from both satellite observation and reanalysis by 16 W m−2 (24 %), and raises the correlation coefficients with them to above 0.95. Averaged over the whole Greenland Ice Sheet in the melt season, the adjustment in insolation to compensate station tilt is  ∼  11 W m−2, enough to melt 0.24 m of snow water equivalent. The adjusted diurnal cycles of albedo are smoother, with consistent semi-smiling patterns. The seasonal cycles and inter-annual variabilities of albedo agree better with previous studies. This tilt-corrected shortwave radiation data set derived using the Retrospective, Iterative, Geometry-Based (RIGB) method provide more accurate observations and validations for surface energy budgets studies on the Greenland Ice Sheet, including albedo variations, surface melt simulations and cloud radiative forcing estimates.

Ice ablation rates measured on four glaciers in south-east Greenland in summer 1933 are recovered from an old field book of geologist K. Milthers. These unpublished ablation data are among the first measured in Greenland and were obtained during a warm period comparable to that of recent years. Ablation rates of up to 45 mm ice eq. d −1 were observed. Using the Tasiilaq meteorological record, we calculate degree-day factors of ca. 3-5 mm ice eq. d −1 °C −1 . Comparing these results with 1996-2012 observations at one of Milthers' glaciers (Mittivakkat), we find that ablation rates and degree-day factors are significantly higher (61±50%) in recent years. We speculate this to be due to a reduction in surface albedo, and perhaps the retreat of the glaciers out of the cold maritime inversion layer. Our findings suggest that using a temperature-index method that assumes constant degree-day factors may produce inaccurate long-term ablation estimates for south-east Greenland glaciers, further emphasizing the value of the rare 1933 measurements for validation of ablation models.

At high elevations on the Greenland ice sheet meltwater percolates and refreezes in place, and hence does not contribute to mass loss. However, meltwater generation and associated surface runoff is occurring from increasingly higher altitudes, causing changes in firn stratigraphy that have led to the presence of near-surface ice slabs. These ice slabs force meltwater to flow laterally instead of percolating downwards. Here we present a simple, physics-based quasi-2-D model to simulate lateral meltwater runoff and superimposed ice (SI) formation on top of ice slabs. Using an Eulerian Darcy flow scheme, the model calculates how far meltwater can travel within a melt season and when it appears at the snow surface. Results show that lateral flow is a highly efficient runoff mechanism, as lateral outflow exceeds locally generated meltwater in all model gridcells, with total meltwater discharge sometimes reaching more than 30 times the average amount of in situ generated melt. SI formation, an important process in the formation and thickening of the ice slabs, can retain up to 40% of the available meltwater, and generally delays the appearance of visible runoff. Validating the model against field- or remote-sensing data remains challenging, but the results presented here are a first step towards a more comprehensive understanding and description of the hydrological system in the accumulation zone of the southwestern Greenland ice sheet.

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).