Programme For Monitoring Of The Greenland Ice Sheet Research Articles

The apparent effect of orbital drift on time series of MODIS MOD10A1 albedo on the Greenland ice sheet

The NASA MODIS MOD10A1 snow albedo product has enabled numerous glaciological applications. The temporal consistency of MODIS albedo is critical to obtaining reliable results from this 22-year time series. The orbit of Terra began to drift toward earlier acquisition times after the final inclination adjustment maneuver to maintain its nominal orbit by NASA on 27 February 2020, which may introduce biases that compromise the accuracy of quantitative time series analysis as the drift continues. Here, we evaluate the impact of Terra's orbital drift by comparing the differences between the Terra MODIS albedo and albedo products derived from Aqua MODIS, harmonized Landsat and Sentinel 2, Sentinel 3, and PROMICE (Programme for Monitoring of the Greenland Ice Sheet) ground measurements over the Greenland ice sheet. Our results suggest that the influence of orbital drift on albedo is small (+0.01 in 2020), but potentially biased for time series analysis. Our analysis also finds that the drift effect that causes earlier image acquisition time may lead to more apparently cloudy pixels and thus effectively reduce the Terra MODIS temporal resolution over Greenland.

Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals

Abstract. Greenland ice sheet mass loss continues to accelerate as global temperatures increase. The surface albedo of the ice sheet determines the amount of absorbed solar energy, which is a key factor in driving surface snow and ice melting. Satellite-retrieved snow albedo allows us to compare and optimise modelled albedo over the entirety of the ice sheet. We optimise the parameters of the albedo scheme in the ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) land surface model for 3 random years taken over the 2000–2017 period and validate over the remaining years. In particular, we want to improve the albedo at the edges of the ice sheet, since they correspond to ablation areas and show the greatest variations in runoff and surface mass balance. By giving a larger weight to points at the ice sheet's edge, we improve the model–data fit by reducing the root-mean-square deviation by over 25 % for the whole ice sheet for the summer months. This improvement is consistent for all years, even those not used in the calibration step. We also show the optimisation successfully improves the model–data fit at 87.5 % of in situ sites from the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) network. We conclude by showing which additional model outputs are impacted by changes to the albedo parameters, encouraging future work using multiple data streams when optimising these parameters.

A new Level 4 multi-sensor ice surface temperature product for the Greenland Ice Sheet

Abstract. The Greenland Ice Sheet (GIS) is subject to amplified impacts of climate change and its monitoring is essential for understanding and improving scenarios of future climate conditions. Surface temperature over the GIS is an important variable, regulating processes related to the exchange of energy and water between the surface and the atmosphere. Few local observation sites exist; thus spaceborne platforms carrying thermal infrared instruments offer an alternative for surface temperature observations and are the basis for deriving ice surface temperature (IST) products. In this study several satellite IST products for the GIS were compared, and the first multi-sensor, gap-free (Level 4, L4) product was developed and validated for 2012. High-resolution Level 2 (L2) products from the European Space Agency (ESA) Land Surface Temperature Climate Change Initiative (LST_cci) project and the Arctic and Antarctic Ice Surface Temperatures from Thermal Infrared Satellite Sensors (AASTI) dataset were assessed using observations from the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) stations and IceBridge flight campaigns. AASTI showed overall better performance compared to LST_cci data, which had superior spatial coverage and availability. Both datasets were utilised to construct a daily, gap-free L4 IST product using the optimal interpolation (OI) method. The resulting product performed satisfactorily when compared to surface temperature observations from PROMICE and IceBridge. Combining the advantages of satellite datasets, the L4 product allowed for the analysis of IST over the GIS during 2012, when a significant melt event occurred. Mean summer (June–August) IST was −5.5 ± 4.5 ∘C, with an annual mean of −22.1 ± 5.4 ∘C. Mean IST during the melt season (May–August) ranged from −15 to −1 ∘C, while almost the entire GIS experienced at least between 1 and 5 melt days when temperatures were −1 ∘C or higher. Finally, this study assessed the potential for using the satellite L4 IST product to improve model simulations of the GIS surface mass balance (SMB). The L4 IST product was assimilated into an SMB model of snow and firn processes during 2012, when extreme melting occurred, to assess the impact of including a high-resolution IST product on the SMB model. Compared with independent observations from PROMICE and IceBridge, inclusion of the L4 IST dataset improved the SMB model simulated IST during the key onset of the melt season, where model biases are typically large and can impact the amount of simulated melt.

Snow Depth Measurements by GNSS-IR at an Automatic Weather Station, NUK-K

Studies have shown that geodetic Global Navigation Satellite System (GNSS) stations can be used to measure snow depths using GNSS interferometric reflectometry (GNSS-IR). Here, we study the results from a customized GNSS setup installed in March through August 2020 at the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station NUK-K located on a small glacier outside Nuuk, Greenland. The setup is not optimized for reflectometry purposes. The site is obstructed between 85 and 215 degrees, and as the power supply is limited due to the remote location, the logging time is limited to 3 h per day. We estimate reflector heights using GNSS-IR and compare the results to a sonic ranger also placed on the weather station. We find that the snow melt measured by GNSS-IR is comparable to the melt measured by the sonic ranger. We expect that a period of up to 45 cm difference between the two is likely related to the much larger footprint GNSS-IR and the topography of the area. The uncertainty on the GNSS-IR reflector heights increase from approximately 2 cm for a snow surface to approximately 5 cm for an ice surface. If reflector height during snow free periods are part of the objective of a similar setup, we suggest increasing the logging time to reduce the uncertainty on the daily estimates.

Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station data

Abstract. 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).

Greenland ice velocity maps from the PROMICE project

Abstract. 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.

Greenland bare-ice albedo from PROMICE automatic weather station measurements and Sentinel-3 satellite observations

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.

Evaluation of a new snow albedo scheme for the Greenland ice sheet in the Regional Atmospheric Climate Model (RACMO2)

Abstract. Snow and ice albedo schemes in present-day climate models often lack a sophisticated radiation penetration scheme and do not explicitly include spectral albedo variations. In this study, we evaluate a new snow albedo scheme in the Regional Atmospheric Climate Model (RACMO2) for the Greenland ice sheet, version 2.3p3, that includes these processes. The new albedo scheme uses the Two-streAm Radiative TransfEr in Snow (TARTES) model and the Spectral-to-NarrOWBand ALbedo (SNOWBAL) module, version 1.2. Additionally, the bare-ice albedo parameterization has been updated. The snow and ice broadband and narrowband albedo output of the updated version of RACMO2 is evaluated using the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and Kangerlussuaq transect (K-transect) in situ data and Moderate Resolution Imaging Spectroradiometer (MODIS) remote-sensing observations. Generally, the modeled narrowband and broadband albedo is in very good agreement with satellite observations, leading to a negligible domain-averaged broadband albedo bias for the interior. Some discrepancies are, however, observed close to the ice margin. Compared to the previous model version, RACMO2.3p2, the broadband albedo is considerably higher in the bare-ice zone during the ablation season, as atmospheric conditions now alter the bare-ice broadband albedo. For most other regions, however, the updated broadband albedo is lower due to spectral effects, radiation penetration or enhanced snow metamorphism.

Greenland ice sheet mass balance assessed by PROMICE (1995–2015)

The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has measured ice-sheet elevation and thickness via repeat airborne surveys circumscribing the ice sheet at an average elevation of 1708 ± 5 m (Sørensen et al. 2018). We refer to this 5415 km survey as the ‘PROMICE perimeter’. Here, we assess ice-sheet mass balance following the input-output approach of Andersen et al. (2015). We estimate ice-sheet output, or the ice discharge across the ice-sheet grounding line, by applying downstream corrections to the ice flux across the PROMICE perimeter. We subtract this ice discharge from ice-sheet input, or the area-integrated, ice sheet surface mass balance, estimated by a regional climate model. While Andersen et al. (2015) assessed ice-sheet mass balance in 2007 and 2011, this updated input-output assessment now estimates the annual sea-level rise contribution from eighteen sub-sectors of the Greenland ice sheet over the 1995–2015 period.

Update of annual calving front lines for 47 marine terminating outlet glaciers in Greenland (1999–2018)

The Greenland ice sheet has been losing mass in response to increased surface melting (Khan et al. 2015; van den Broeke et al. 2017) as well as discharge of ice from marine terminating outlet glaciers (van den Broeke et al. 2009; Box et al. 2018). Marine terminating outlet glaciers flow to the ocean where they lose mass by e.g. iceberg calving. Currently, the mass loss from the Greenland ice sheet is the largest Arctic contributor to global sea-level rise (van den Broeke et al. 2009, 2017; Box et al. 2018). Therefore, monitoring changes in the Greenland ice sheet is essential to provide policy makers with reliable data.
 There is a consensus that most marine terminating outlet glaciers have retreated in recent decades, and that the increased calving rates are a response to recent atmospheric and oceanic warming (e.g. Box et al. 2018; Moon et al. 2018). The rate of dynamic mass loss is determined by changes of the glacier calving front (i.e. its terminus) position, ice thickness and changes in ice flow. Ocean temperature and fjord circulation also influence the calving front stability by melting the glacier below the water line, thinning the ice that is in contact with water (Moon et al. 2014). Change in calving front position is therefore an important indicator for monitoring the dynamic behaviour of the upstream area of the ice sheet, which is further modulated by local topographic features and buttressing effects (Rignot & Kanagaratnam 2006; Nick et al. 2009).
 The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) is dedicated to monitoring changes in the mass budget of the Greenland ice sheet, including monitoring of the calving front lines of marine terminating outlet glaciers. Here, we present an updated collection of annual measurements of end-of-melt-season calving front lines for 47 marine terminating outlet glaciers in Greenland between 1999 and 2018. We also present an example application of the data set, in which we estimate area changes for this group of glaciers since 1999. The Greenland calving front lines were measured from optical satellite imagery obtained from Landsat, Aster, and Sentinel-2 (Table 1). The PROMICE calving front product is freely available for download as ESRI shapefiles.

The VIIRS Sea-Ice Albedo Product Generation and Preliminary Validation

Ice albedo feedback amplifies climate change signals and thus affects the global climate. Global long-term records on sea-ice albedo are important to characterize the regional or global energy budget. As the successor of MODIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite) started its observation from October 2011 on S-NPP (Suomi National Polar-orbiting Partnership). It has improved upon the capabilities of the operational Advanced Very High Resolution Radiometer (AVHRR) and provides observation continuity with MODIS. We used a direct estimation algorithm to produce a VIIRS sea-ice albedo (VSIA) product, which will be operational in the National Oceanic and Atmospheric Administration’s (NOAA) S-NPP Data Exploration (NDE) version of the VIIRS albedo product. The algorithm is developed from the angular bin regression method to simulate the sea-ice surface bidirectional reflectance distribution function (BRDF) from physical models, which can represent different sea-ice types and vary mixing fractions among snow, ice, and seawater. We compared the VSIA with six years of ground measurements at 30 automatic weather stations from the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and the Greenland Climate Network (GC-NET) as a proxy for sea-ice albedo. The results show that the VSIA product highly agreed with the station measurements with low bias (about 0.03) and low root mean square error (RMSE) (about 0.07) considering the Joint Polar Satellite System (JPSS) requirement is 0.05 and 0.08 at 4 km scale, respectively. We also evaluated the VSIA using two datasets of field measured sea-ice albedo from previous field campaigns. The comparisons suggest that VSIA generally matches the magnitude of the ground measurements, with a bias of 0.09 between the instantaneous albedos in the central Arctic and a bias of 0.077 between the daily mean albedos near Alaska. The discrepancy is mainly due to the scale difference at both spatial and temporal dimensions and the limited sample size. The VSIA data will serve for weather prediction applications and climate model calibrations. Combined with the historical observations from MODIS, current S-NPP VIIRS, and NOAA-20 VIIRS observations, VSIA will dramatically contribute to providing high-accuracy routine sea-ice albedo products and irreplaceable records for monitoring the long-term sea-ice albedo for climate research.

Application of PROMICE Q‐Transect in Situ Accumulation and Ablation Measurements (2000–2017) to Constrain Mass Balance at the Southern Tip of the Greenland Ice Sheet

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.

Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model

Abstract. 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.

A Retrospective, Iterative, Geometry-Based (RIGB) tilt-correction method for radiation observed by automatic weather stations on snow-covered surfaces: application to Greenland

Abstract. 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.

Darkening of the Greenland ice sheet due to the melt albedo feedback observed at PROMICE weather stations

The Greenland ice sheet is losing mass (Barletta et al. 2012) and at least half of this loss is caused by an increase in surface melt (e.g. Tedesco et al. 2013). The other part is caused by increased dynamic mass loss, as marine-terminating glaciers lose resistive stresses (Nick et al. 2009) due to both retreat and meltwater lubrication at the bed (Sasgen et al. 2012). In 2007, the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) was initiated with the aim of gaining an insight into the causes of the ice-mass budget changes based on quantitative observations. This is primarily done by assessing how much mass is gained as snow accumulation on the surface versus how much is lost by calving and surface ablation (Ahlstrøm et al. 2008). PROMICE monitors the surface mass balance by means of automatic weather stations (AWSs) designed to quantify accumulation and ablation, as well as the specific energy sources contributing to ablation. These observations are vital to interpreting the physical mechanisms for ice-sheet response to climate change and for the calibration and validation of both satellite observations and climate models.

<i>Brief communication</i> "The aerophotogrammetric map of Greenland ice masses"

Abstract. The PROMICE (Programme for Monitoring of the Greenland Ice Sheet) aerophotogrammetric map of Greenland ice masses is the first high resolution dataset documenting the mid-1980s areal extent of the Greenland Ice Sheet and all the local glaciers and ice caps. The total glacierized area excluding nunataks was 1 804 638 km2 ± 2178 km2, of which 88 083 ± 1240 km2 belonged to local glaciers and ice caps (GIC) substantially independent from the Greenland Ice Sheet. This new result of GIC glacierized area is higher than most previous estimates, 81% greater than Weng's (1995) measurements, but is in line with contemporary findings based on independent data sources. A comparison between our map and the recently released Rastner et al. (2012) inventory and GIMP (Greenland Ice Mapping Project) Ice-Cover Mask (Howat and Negrete, 2013) shows potential for change-assessment studies.

Ablation observations for 2008–2011 from the Programme for Monitoring of the Greenland Ice Sheet (PROMICE)

Recent estimates from the glaciological community agree that the Greenland ice sheet is losing mass at an accelerated pace due to climate change (Velicogna 2009; Khan et al. 2010; Rignot et al. 2011). This has caught the attention of the public and policy makers due to the potential impact on sea-level rise (Dahl-Jensen et al. 2009). The mass loss can be attributed approximately equally to increases in meltwater runoff from surface melt and iceberg production (van den Broeke et al. 2009).

Programme for Monitoring of the Greenland Ice Sheet (PROMICE): first temperature and ablation records

The Greenland ice sheet is reacting to climate change. Yet, mass-budget estimates differ considerably, partly due to climatic variability and partly to uncertainties in the techniques of assessing mass change (IPCC 2007). Nevertheless, all recent estimates agree that the ice sheet is losing mass (e.g. 286 Gt/yr; Velicogna 2009) at an accelerating rate (Rignot et al. 2011). On top of this, the area with a negative mass budget is expanding rapidly (Khan et al. 2010). The mass loss is attributed equally to increases in both iceberg production and melting of the ice sheet (Van den Broeke et al. 2009). The increasing mass loss in recent years has caught public attention and given rise to concern worldwide due to its potential impact on sea level. In the light of this, the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) was initiated in 2007 (Ahlstrøm & PROMICE project team 2008), lead by the Geological Survey of Denmark and Greenland (GEUS). PROMICE undertakes surface mass-budget measurements using automatic weather stations, quantifies the mass loss by iceberg calving using remotely sensed data from satellites and airborne surveys and tracks changes in the extent of glaciers. In this paper, we focus on weather station measurements, which are crucial in calculating the energy exchange between the atmosphere and the ice sheet, and in validating model calculations of the surface mass budget. In particular, we present the observed temperatures and investigate how their high 2010 values affected ablation in southern Greenland

A new programme for monitoring the mass loss of the Greenland ice sheet

The Greenland ice sheet has been losing mass at a dramatic rate in recent years, raising political concern worldwide due to the possible impact on global sea level rise and climate dynamics (Luthcke et al. 2006; Rignot & Kanagaratnam 2006; Velicogna & Wahr 2006; IPCC 2007; Shepherd & Wingham 2007). The Arctic region as a whole is warming up much more rapidly than the globe at large (ACIA 2005) and it is desirable to quantify these changes in order to provide the decision-makers with a firm knowledge base. To cover this need, the Danish Ministry of Climate and Energy has now launched a new Programme for Monitoring of the Greenland Ice Sheet (PROMICE), designed and operated by the Geological Survey of Denmark and Greenland (GEUS) in collaboration with the National Space Institute at the Technical University of Denmark and Asiaq (Greenland Survey). The aim of the programme is to quantify the annual mass loss of the Greenland ice sheet, track changes in the extent of local glaciers and ice caps, and track changes in the position of the ice-sheet margin.