Greenland Ice Sheet late-season melt: investigating multi-scale drivers of K-transect events

One consequence of recent Arctic warming is an increased occurrence and longer seasonality of above-freezing air temperature episodes.There is significant disagreement in the literature concerning potential physical connectivity between high-latitude open water duration proximate to the Greenland Ice Sheet (GrIS) and unseasonal (i.e. late summer and autumn) GrIS melt events. Here, a new date of sea ice advance (DOA) product is used to determine the occurrence of Baffin Bay sea ice growth along Greenland’s west coast for the 2011–2015 period. For the unseasonal melt period preceding the DOA, northwest Atlantic Ocean and atmospheric conditions are analyzed and linked to unseasonal melt events observed at a series of on-ice automatic weather stations (AWS) along the K-transect in southwest Greenland. Mesoscale and synoptic influences on the above and below freezing surface air temperature events are assessed through analyses of AWS wind, pressure, and humidity observations. These surface observations are further compared against Modèle Atmosphérique Régional (MAR), Regional Atmospheric Climate Model (RACMO2), and ERA-Interim reanalysis fields to understand the airmass origins and (thermo)dynamic drivers of the melt events. Results suggest that the K-transect late season, ablation zone melt events are strongly affected by ridging atmospheric circulation patterns that transport warm, moist air from the sub-polar North Atlantic toward west Greenland. While thermal conduction and advection off south Baffin Bayopen waters impact coastal air temperatures, consistent with previous studies, marine air incursions from Baffin Bay onto the ice sheet are obstructed by barrier flows and the pressure gradient-driven katabatic regime along the western GrIS margin

Recent warming trends of the Greenland ice sheet documented by historical firn and ice temperature observations and machine learning

Surface melt on the Greenland ice sheet has been increasing in intensity and extent over the last decades due to Arctic atmospheric warming. Surface melt depends on the surface energy balance, which includes the atmospheric forcing but also the thermal budget of the snow, firn and ice near the ice sheet surface. The temperature of the ice sheet subsurface has been used as an indicator of the thermal state of the ice sheet's surface. Here, we present a compilation of 4612 measurements of firn and ice temperature at 10m below the surface (T10m) across the ice sheet, spanning from 1912 to 2022. The measurements are either instantaneous or monthly averages. We train an artificial neural network model (ANN) on 4597 of these point observations, weighted by their relative representativity, and use it to reconstruct T10m over the entire Greenland ice sheet for the period 1950-2022 at a monthly timescale. We use 10-year averages and mean annual values of air temperature and snowfall from the ERA5 reanalysis dataset as model input. The ANN indicates a Greenland-wide positive trend of T10m at 0.2°C per decade during the 1950-2022 period, with a cooling during 1950-1985 (-0.4°C per decade) followed by a warming during 1985-2022 (+0.7° per decade). Regional climate models HIRHAM5, RACMO2.3p2 and MARv3.12 show mixed results compared to the observational T10m dataset, with mean differences ranging from -0.4°C (HIRHAM) to 1.2°C (MAR) and root mean squared differences ranging from 2.8°C (HIRHAM) to 4.7°C (MAR). The observation-based ANN also reveals an underestimation of the subsurface warming trends in climate models for the bare-ice and dry-snow areas. The subsurface warming brings the Greenland ice sheet surface closer to the melting point, reducing the amount of energy input required for melting. Our compilation documents the response of the ice sheet subsurface to atmospheric warming and will enable further improvements of models used for ice sheet mass loss assessment and reduce the uncertainty in projections

The AntSMB dataset: A comprehensive compilation of surface mass balance field observations over the Antarctic Ice Sheet

A comprehensive compilation of observed records is needed for accurate quantification of surface mass balance (SMB) over Antarctica, which is a key challenge for calculation of Antarctic contribution to global sea level change. Here, we present the AntSMB dataset: a new quality-controlled dataset of a variety of published field measurements of the Antarctic Ice Sheet SMB by means of stakes, snow pits, ice cores, ultrasonic sounders, and ground-penetrating radar (GPR). The dataset collects 3579 individual multi-year-averaged observations, 687 annually resolved time series from 675 sites extending back over the past 1000 years, and daily resolved records covering 245 years from 32 sites across the whole ice sheet. These records are derived from ice cores, snow pits, stakes/stake farms, and ultrasonic sounders. Furthermore, GPR multi-year-averaged measurements are included in the dataset, covering an area of 22g025gkm2. This is the first ice-sheet-scale compilation of SMB records at different temporal (daily, annual, and multi-year) resolutions from multiple types of measurement and is available at 10.11888/Glacio.tpdc.271148 (Wang et al., 2021). The database has potentially wide applications such as the investigation of temporal and spatial variability in SMB, model validation, assessment of remote sensing retrievals, and data assimilation. As a case of model estimation, records of the AntSMB dataset are used to assess the performance of ERA5 for temporal and spatial variability in SMB over Antarctica

The AntSMB dataset: A comprehensive compilation of surface mass balance field observations over the Antarctic Ice Sheet

A comprehensive compilation of observed records is needed for accurate quantification of surface mass balance (SMB) over Antarctica, which is a key challenge for calculation of Antarctic contribution to global sea level change. Here, we present the AntSMB dataset: a new quality-controlled dataset of a variety of published field measurements of the Antarctic Ice Sheet SMB by means of stakes, snow pits, ice cores, ultrasonic sounders, and ground-penetrating radar (GPR). The dataset collects 3579 individual multi-year-averaged observations, 687 annually resolved time series from 675 sites extending back over the past 1000 years, and daily resolved records covering 245 years from 32 sites across the whole ice sheet. These records are derived from ice cores, snow pits, stakes/stake farms, and ultrasonic sounders. Furthermore, GPR multi-year-averaged measurements are included in the dataset, covering an area of 22g025gkm2. This is the first ice-sheet-scale compilation of SMB records at different temporal (daily, annual, and multi-year) resolutions from multiple types of measurement and is available at 10.11888/Glacio.tpdc.271148 (Wang et al., 2021). The database has potentially wide applications such as the investigation of temporal and spatial variability in SMB, model validation, assessment of remote sensing retrievals, and data assimilation. As a case of model estimation, records of the AntSMB dataset are used to assess the performance of ERA5 for temporal and spatial variability in SMB over Antarctica

Estimating near-surface climatology of multi-reanalyses over the Greenland Ice Sheet

This study uses meteorological records from Automatic Weather Stations (AWSs) to estimate the performance of global reanalysis products for monthly air temperature, relative humidity and wind speed over the Greenland Ice Sheet (GrIS). These products include the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5), ECMWF Interim Reanalysis (ERAI), Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), Climate Forecast System Reanalysis Version 1/Climate Forecast System Version 2 (CFSRv1/CFSRv2), and Japanese 55-year Reanalysis (JRA-55). The global reanalysis products generally perform better in summer than in winter, and their qualities vary by glaciological regime. No reanalysis is clearly identified as the optimal dataset for all meteorological parameters, seasons and regions. For all reanalyses, warm biases are observed in the accumulation zone, but cold biases are observed in the ablation area of the GrIS. ERAI, ERA5 and JRA-55 underestimate relative humidity during any month. While MERRA-2 overestimates wind speeds, underestimates are found for the other reanalyses excluding JRA-55 during all months. Despite the robust agreement between the AWS time series for all three variables and each reanalysis product averaged over the ice sheet, sudden jumps occur in annual mean wind speed in CFSR, and in annual relative humidity in JRA-55 from 2010 to 2011

Estimating near-surface climatology of multi-reanalyses over the Greenland Ice Sheet

This study uses meteorological records from Automatic Weather Stations (AWSs) to estimate the performance of global reanalysis products for monthly air temperature, relative humidity and wind speed over the Greenland Ice Sheet (GrIS). These products include the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5), ECMWF Interim Reanalysis (ERAI), Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), Climate Forecast System Reanalysis Version 1/Climate Forecast System Version 2 (CFSRv1/CFSRv2), and Japanese 55-year Reanalysis (JRA-55). The global reanalysis products generally perform better in summer than in winter, and their qualities vary by glaciological regime. No reanalysis is clearly identified as the optimal dataset for all meteorological parameters, seasons and regions. For all reanalyses, warm biases are observed in the accumulation zone, but cold biases are observed in the ablation area of the GrIS. ERAI, ERA5 and JRA-55 underestimate relative humidity during any month. While MERRA-2 overestimates wind speeds, underestimates are found for the other reanalyses excluding JRA-55 during all months. Despite the robust agreement between the AWS time series for all three variables and each reanalysis product averaged over the ice sheet, sudden jumps occur in annual mean wind speed in CFSR, and in annual relative humidity in JRA-55 from 2010 to 2011