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Here, we present a compilation of 95 ice temperature profiles from 85 boreholes from the Greenland ice sheet and peripheral ice caps, as well as local ice caps in the Canadian Arctic. Profiles from only 31 boreholes (36 %) were previously available in open-access data repositories. The remaining 54 borehole profiles (64 %) 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 95 profiles are now made available in both absolute (meters) and normalized (0 to 1 ice thickness) depth scales and are accompanied by extensive metadata. These metadata include 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.

Here, we present a compilation of 95 ice temperature profiles from 85 boreholes from the Greenland ice sheet and peripheral ice caps, as well as local ice caps in the Canadian Arctic. Profiles from only 31 boreholes (36 %) were previously available in open-access data repositories. The remaining 54 borehole profiles (64 %) 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 95 profiles are now made available in both absolute (meters) and normalized (0 to 1 ice thickness) depth scales and are accompanied by extensive metadata. These metadata include 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.

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., Physical and Space Geodesy

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.

Each summer, surface melting of the margin of the Greenland Ice Sheet exposes a distinctive visible stratigraphy that is related to past variability in subaerial dust deposition across the accumulation zone and subsequent ice flow toward the margin. Here we map this surface stratigraphy along the northern margin of the ice sheet using mosaicked Sentinel-2 multispectral satellite imagery from the end of the 2019 melt season and finer-resolution WorldView-2/3 imagery for smaller regions of interest. We trace three distinct transitions in apparent dust concentration and the top of a darker basal layer. The three dust transitions have been identified previously as representing late-Pleistocene climatic transitions, allowing us to develop a coarse margin chronostratigraphy for northern Greenland. Substantial folding of late-Pleistocene stratigraphy is observed but uncommon. The oldest conformal surface-exposed ice in northern Greenland is likely located adjacent to Warming Land and may be up to ~55 thousand years old. Basal ice is commonly exposed hundreds of metres from the ice margin and may indicate a widespread frozen basal thermal state. We conclude that the ice margin across northern Greenland offers multiple opportunities to recover paleoclimatically distinct ice relative to previously studied regions in southwestern Greenland.

Key observational indicators of climate change in the Arctic, most spanning a 47 year period (1971–2017) demonstrate fundamental changes among nine key elements of the Arctic system. We find that, coherent with increasing air temperature, there is an intensification of the hydrological cycle, evident from increases in humidity, precipitation, river discharge, glacier equilibrium line altitude and land ice wastage. Downward trends continue in sea ice thickness (and extent) and spring snow cover extent and duration, while near-surface permafrost continues to warm. Several of the climate indicators exhibit a significant statistical correlation with air temperature or precipitation, reinforcing the notion that increasing air temperatures and precipitation are drivers of major changes in various components of the Arctic system. To progress beyond a presentation of the Arctic physical climate changes, we find a correspondence between air temperature and biophysical indicators such as tundra biomass and identify numerous biophysical disruptions with cascading effects throughout the trophic levels. These include: increased delivery of organic matter and nutrients to Arctic near‐coastal zones; condensed flowering and pollination plant species periods; timing mismatch between plant flowering and pollinators; increased plant vulnerability to insect disturbance; increased shrub biomass; increased ignition of wildfires; increased growing season CO2 uptake, with counterbalancing increases in shoulder season and winter CO2 emissions; increased carbon cycling, regulated by local hydrology and permafrost thaw; conversion between terrestrial and aquatic ecosystems; and shifting animal distribution and demographics. The Arctic biophysical system is now clearly trending away from its 20th Century state and into an unprecedented state, with implications not only within but beyond the Arctic. The indicator time series of this study are freely downloadable at AMAP.no.

Key observational indicators of climate change in the Arctic, most spanning a 47 year period (1971–2017) demonstrate fundamental changes among nine key elements of the Arctic system. We find that, coherent with increasing air temperature, there is an intensification of the hydrological cycle, evident from increases in humidity, precipitation, river discharge, glacier equilibrium line altitude and land ice wastage. Downward trends continue in sea ice thickness (and extent) and spring snow cover extent and duration, while near-surface permafrost continues to warm. Several of the climate indicators exhibit a significant statistical correlation with air temperature or precipitation, reinforcing the notion that increasing air temperatures and precipitation are drivers of major changes in various components of the Arctic system. To progress beyond a presentation of the Arctic physical climate changes, we find a correspondence between air temperature and biophysical indicators such as tundra biomass and identify numerous biophysical disruptions with cascading effects throughout the trophic levels. These include: increased delivery of organic matter and nutrients to Arctic near‐coastal zones; condensed flowering and pollination plant species periods; timing mismatch between plant flowering and pollinators; increased plant vulnerability to insect disturbance; increased shrub biomass; increased ignition of wildfires; increased growing season CO2 uptake, with counterbalancing increases in shoulder season and winter CO2 emissions; increased carbon cycling, regulated by local hydrology and permafrost thaw; conversion between terrestrial and aquatic ecosystems; and shifting animal distribution and demographics. The Arctic biophysical system is now clearly trending away from its 20th Century state and into an unprecedented state, with implications not only within but beyond the Arctic. The indicator time series of this study are freely downloadable at AMAP.no., Physical and Space Geodesy

The perennial snow, or firn, on the Greenland ice sheet each summer stores part of the meltwater formed at the surface, buffering the ice sheet’s contribution to sea level. We gathered observations of firn air content, indicative of the space available in the firn to retain meltwater, and find that this air content remained stable in cold regions of the firn over the last 65 years but recently decreased significantly in western Greenland.

The firn covering the Greenland ice sheet interior can retain part of the surface melt, buffering the ice sheet’s contribution to sea level, but its characteristics are still little known. Using remote-sensing observations from 2000- 2017, we estimate that firn covers 1,405,500 ±17,250 km2 of the ice sheet. We present 344 firn-core-derived observations of the top 10 m firn air content (FAC10), indicative of the firn’s meltwater retention capacity. FAC10 remained stable in the coldest 74% of the firn area during 1953-2017, while FAC10 decreased in the warmest and driest 12% of the firn area between 1997-2008 and 2011-2017, resulting in a loss of 180 ±78 km3 (-26 ±11%) of air from the near-surface firn.

With nine southern Greenland ice sheet ablation area locations, the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) “Q-transect” is a source of snow accumulation and ice ablation data spanning 17 years (2000 to present). Snow water equivalence measurements below equilibrium line altitude enable resolving the location and magnitude of an orographic precipitation maximum. Snow depth skillfully predicts snow water equivalence in this region, for which we find no evidence of change 2001-2017. After describing observed accumulation and ablation spatiotemporal patterns, we examine surface mass balance (SMB) in 5.5-km HIRHAM5, 7.5-km Modèle Atmosphèrique Régional (MAR) v3.7, and 1-km Regional Atmospheric Climate Model (RACMO2.3p2) regional climate model (RCM) output. HIRHAM5 and RACMO2.3p2 overestimate accumulation below equilibrium line altitude by 2 times. MAR SMB is closer to observations but lacks a distinct orographic peak. RCM ablation underestimation is attributable to overestimated snowfall (HIRHAM5 and RACMO2.3p2), overestimated bare ice albedo (MAR), and underestimation of downward turbulent heat fluxes. Calibrated ablation area RCM SMB data yield -0.3 ± 0.5 Gt/a SMB of the 559-km2 marine-terminating Sermilik glacier (September 2000 to October 2012). Using Enderlin et al. (2014, https://doi.org/10.1002/2013GL059010) ice discharge data, Sermilik glacier’s total mass balance is -1.3 ± 0.5 Gt/a with interannual variability dominated by SMB. The area specific mass loss is 17 to 20 times greater than the whole ice sheet mass loss after Andersen et al. (2015, https://doi.org/10.1016/j.epsl.2014.10.015) and Colgan et al. (2015, https://doi.org/10.1016/j.rse.2015.06.016), highlighting the Q-transect’s situation in an ice mass loss hot spot.

The Arctic Monitoring and Assessment Program (AMAP 2017) report identifies the Arctic as the largest regional source of land ice to global sea-level rise in the 2003–2014 period. Yet, this contextualization ignores the longer perspective from in situ records of glacier mass balance. Here, using 17 (>55 °N latitude) glacier and ice cap mass balance series in the 1971–2017 period, we develop a semi-empirical estimate of annual sea-level contribution from seven Arctic regions by scaling the in situ records to GRACE averages. We contend that our estimate represents the most accurate Arctic land ice mass balance assessment so far available before the 1992 start of satellite altimetry. We estimate the 1971–2017 eustatic sea-level contribution from land ice north of ∼55 °N to be 23.0 ± 12.3 mm sea-level equivalent (SLE). In all regions, the cumulative sea-level rise curves exhibit an acceleration, starting especially after 1988. Greenland is the source of 46% of the Arctic sea-level rise contribution (10.6 ± 7.3 mm), followed by Alaska (5.7 ± 2.2 mm), Arctic Canada (3.2 ± 0.7 mm) and the Russian High Arctic (1.5 ± 0.4 mm). Our annual results exhibit co-variability over a 43 year overlap (1971–2013) with the alternative dataset of Marzeion et al (2015 Cryosphere 9 2399–404) (M15). However, we find a 1.36× lower sea-level contribution, in agreement with satellite gravimetry. The IPCC Fifth Assessment report identified constraining the pre-satellite era sea-level budget as a topic of low scientific understanding that we address and specify sea-level contributions coinciding with IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) ‘present day’ (2005–2015) and ‘recent past’ (1986–2005) reference periods. We assess an Arctic land ice loss of 8.3 mm SLE during the recent past and 12.4 mm SLE during the present day. The seven regional sea-level rise contribution time series of this study are available from AMAP.no.

The Arctic Monitoring and Assessment Program (AMAP) (AMAP, 2017) identifies the Arctic as the largest regional source of land ice to global sea-level rise in the 2003 to 2014 period. Yet, this contextualization ignores the longer perspective from in-situ records of glacier mass balance. Here, using 18 (> 55 °N latitude) glacier and ice cap mass balance series in the 1971 to 2017 period, we develop a semi-empirical estimate of annual sea-level contribution from seven Arctic regions by scaling the in-situ records to GRACE averages. We contend that our estimate represents the most accurate mass balance assessment so far available before the 1992 start of satellite altimetry. We estimate the 1971 to 2017 eustatic sea-level contribution from land ice north of ~55° N to be 23.0±12.3 mm sea-level equivalent (SLE). In all regions, the cumulative sea-level rise curves exhibit an acceleration, especially after 1988. Greenland is the source of 46% of the Arctic sea-level rise contribution (10.6±7.3 mm), followed by Alaska (5.7±2.2 mm), Arctic Canada (3.2±0.7 mm) and the Russian High Arctic (1.5±0.4 mm). Our annual results exhibit co-variability over a 43 year overlap (1971 to 2013) with the alternative dataset of Marzeion et al (2015) (M15). However, we find a 1.36x lower sea-level contribution, in agreement with satellite gravimetry. The IPCC Fifth Assessment report identified constraining the pre-satellite era sea-level budget as a topic of low scientific understanding that we address and specify sea-level contributions coinciding with IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) “present day” (2005-2015) and “recent past” (1986-2005) reference periods. We assess an Arctic land ice loss of 8.3 mm SLE during the recent past and 12.4 mm SLE during the present day. The seven regional sea-level rise contribution time series of this study are available from AMAP.no.

The Arctic Monitoring and Assessment Program (AMAP 2017) report identifies the Arctic as the largest regional source of land ice to global sea-level rise in the 2003-2014 period. Yet, this contextualization ignores the longer perspective from in situ records of glacier mass balance. Here, using 17 (>55°N latitude) glacier and ice cap mass balance series in the 1971-2017 period, we develop a semi-empirical estimate of annual sea-level contribution from seven Arctic regions by scaling the in situ records to GRACE averages. We contend that our estimate represents the most accurate Arctic land ice mass balance assessment so far available before the 1992 start of satellite altimetry. We estimate the 1971-2017 eustatic sea-level contribution from land ice north of ∼55°N to be 23.0 ±12.3mm sea-level equivalent (SLE). In all regions, the cumulative sea-level rise curves exhibit an acceleration, starting especially after 1988. Greenland is the source of 46% of the Arctic sea-level rise contribution (10.6±7.3 mm), followed by Alaska (5.7±2.2 mm), Arctic Canada (3.2 ±0.7 mm) and the Russian High Arctic (1.5 ±0.4 mm). Our annual results exhibit co-variability over a 43 year overlap (1971-2013) with the alternative dataset of Marzeion et al (2015 Cryosphere 9 2399-404) (M15). However, we find a 1.36×lower sea-level contribution, in agreement with satellite gravimetry. The IPCC Fifth Assessment report identified constraining the pre-satellite era sea-level budget as a topic of low scientific understanding that we address and specify sea-level contributions coinciding with IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) 'present day' (2005-2015) and 'recent past' (1986-2005) reference periods. We assess an Arctic land ice loss of 8.3 mm SLE during the recent past and 12.4 mm SLE during the present day. The seven regional sea-level rise contribution time series of this study are available from AMAP.no., Physical and Space Geodesy

We present in situ firn temperatures from the extreme 2012 melt season in the southwestern lower accumulation area of the Greenland ice sheet. The upper 2.5 m of snow and firn was temperate during the melt season, when vertical meltwater percolation was inefficient due to a c. 5.5 m thick ice layer underlying the temperate firn. Meltwater percolation and refreezing beneath 2.5 m depth only occurred after the melt season. Deviations from temperatures predicted by pure conductivity suggest that meltwater refroze in discrete bands at depths of 2.0–2.5, 5.0–6.0 and 8.0–9.0 m. While we find no indication of meltwater percolation below 9 m depth or complete filling of pore volume above, firn at 10 and 15 m depth was respectively 4.2–4.5 degrees C and 1.7 degrees C higher than in a conductivity-only simulation. Even though meltwater percolation in 2012 was inefficient, firn between 2 and 15 m depth the following winter was on average 4.7 degrees C warmer due to meltwater refreezing. Our observations also suggest that the 2012 firn conditions were preconditioned by two warm summers and ice layer formation in 2010 and 2011. Overall, firn temperatures during the years 2009–13 increased by 0.6 degrees C., Stability and Variations of Arctic Land Ice (SVALI), Programme for Monitiring of the Greenland Ice Sheet (PROMICE), Greenland Analogue Project (GAP)

The Greenland ice sheet is an excellent observatory for global climate change. Meltwater from the 1.8 million km2 large ice sheet influences oceanic temperature and salinity, nutrient fluxes and global sea level (IPCC 2013). Surface reflectivity is a key driver of surface melt rates (Box et al. 2012). Mapping of different ice-sheet surface types provides a clear indicator of where changes in ice-sheet surface reflectivity are most prominent. Here, we present an updated version of a surface classification algorithm that utilises NASA’s Moderateresolution Imaging Spectroradiometer (MODIS) sensor on the Terra satellite to systematically monitor ice-sheet surface melt (Fausto et al. 2007). Our aim is to determine the areal extent of three surface types over the 2000–2014 period: glacier ice, melting snow (including percolation areas) and dry snow (Cuff ey & Paterson 2010). Monthly 1 km2 resolution surface-type grids can be downloaded via the CryoClim internet portal (www.cryoclim.net). In this report, we briefly describe the updated classification algorithm, validation of surface types and inter-annual variability in surface types., Programme for Monitoring of the Greenland Ice Sheet (PROMICE)

Since the early 1980s, the Geological Survey of Denmark and Greenland (GEUS) glaciology group has developed automatic weather stations (AWSs) and operated them on the Greenland ice sheet and on local glaciers to support glaciological research and monitoring projects (e.g. Olesen & Braithwaite 1989; Ahlstrøm et al. 2008). GEUS has also operated AWSs in connection with consultancy services in relation to mining and hydropower pre-feasibility studies (Colgan et al. 2015). Over the years, the design of the AWS has evolved, partly due to technological advances and partly due to lessons learned in the field. At the same time, we have kept the initial goal in focus: long-term, year-round accurate recording of ice ablation, snow depth and the physical parameters that determine the energy budget of glacierised surfaces. GEUS has an extensive record operating AWSs in the harsh Arctic environment of the diverse ablation areas of the Greenland ice sheet, glaciers and ice caps [...]. The GEUS AWS model in use now is a reliable tool that is adapted to the environmental and logistical conditions of polar regions. It has a proven record of more than 150 stationyears of deployment in Greenland since its introduction in 2007–2008, and a success rate of c. 90% defined as the fraction of months with more than 80% valid air-temperature measurements over the total deployment time of the 25 stations in the field. The rest of this paper focuses on the technical aspects of the GEUS AWS, and provides an overview of its design and capabilities., Programme for Monitoring of the Greenland Ice Sheet (PROMICE)

We present 5 years (2009-2013) of automatic weather station measurements from the lower accumulation area (1840 m a.s.l. - above sea level) of the Greenland ice sheet in the Kangerlussuaq region. Here, the summers of 2010 and 2012 were both exceptionally warm, but only 2012 resulted in a strongly negative surface mass budget (SMB) and surface meltwater run-off. The observed run-off was due to a large ice fraction in the upper 10 m of firn that prevented meltwater from percolating to available pore volume below. Analysis reveals an anomalously low 2012 summer-averaged albedo of 0.71 (typically similar to 0.78), as meltwater was present at the ice sheet surface. Consequently, during the 2012 melt season, the ice sheet surface absorbed 28% (213 MJ m-2) more solar radiation than the average of all other years. A surface energy balance model is used to evaluate the seasonal and interannual variability of all surface energy fluxes. The model reproduces the observed melt rates as well as the SMB for each season. A sensitivity analysis reveals that 71% of the additional solar radiation in 2012 was used for melt, corresponding to 36% (0.64 m) of the 2012 surface lowering. The remaining 64% (1.14 m) of surface lowering resulted from high atmospheric temperatures, up to a + 2.6 degrees C daily average, indicating that 2012 would have been a negative SMB year at this site even without the melt-albedo feedback. Longer time series of SMB, regional temperature, and remotely sensed albedo (MODIS) show that 2012 was the first strongly negative SMB year, with the lowest albedo, at this elevation on record. The warm conditions of recent years have resulted in enhanced melt and reduction of the refreezing capacity in the lower accumulation area. If high temperatures continue, the current lower accumulation area will turn into a region with superimposed ice in coming years., Stability and Variations of Arctic Land Ice (SVALI), Programme for Monitoring of the Greenland Ice Sheet (PROMICE), Greenland Analogue Project (GAP)

In 2007 the Programme for Monitoring the Greenland Ice Sheet (PROMICE) was initiated to observe and gain insight into the mass budget of Greenland ice masses. By means of in situ observations and remote sensing, PROMICE assesses how much mass is gained as snow accumulation on the surface versus how much is lost by iceberg calving and surface ablation (Ahlstrøm et al. 2008). A key element of PROMICE is a network of automatic weather stations (AWSs) designed to quantify components of the surface mass balance, including the energy exchanges contributing to surface ablation (Van As et al. 2013). The use of these AWS observations is not limited to studies of ice-sheet mass balance. PROMICE contributes to CryoNet (www.globalcryospherewatch.org/cryonet), the core network of surface measurement sites of the World Meteorological Organization (WMO) Global Cryosphere Watch. By real-time delivery through WMO, PROMICE observations contribute to improve both operational forecasting and climate analysis in the data-sparse Arctic. The Greenlandic population, highly dependent on accurate forecasting of weather conditions, benefits directly from these real-time observations. For instance, extreme surface wind speeds are a high-risk element in Greenland. The third-highest wind speed observed at the surface of the Earth (93 m/s or 333 km/h), was recorded in a 8–9 March 1972 storm at Thule in North-West Greenland (Stansfield 1972). In this paper, we discuss the extent to which the Greenland ice sheet generates its own near-surface wind field. We use PROMICE data to gain insight into the interaction between air temperature, radiation and gravity-driven katabatic winds. We focus on a particularly powerful spring storm in 2013 that contributed to a fatality on an ice-sheet ski traverse attempt (Linden 2013)., Programme for Monitoring of the Greenland Ice Sheet (PROMICE)