Robert S. Fausto

A new present-day temperature parameterization for Greenland

Near-surface air temperature (2 m) over the Greenland ice sheet (GrIS) is parameterized using data from automatic weather stations located on land and on the ice sheet. The parameterization is expressed in terms of mean annual temperatures and mean July temperatures, both depending linearly on altitude, latitude and longitude. The temperature parameterization is compared to a previous study and is shown to be in better agreement with observations. The temperature parameterization is tested in a positive degree-day model to simulate the present (1996-2006) mean melt area extent of the GrIS. The model accounts for firn warming, rainfall and refreezing of meltwater, with different degree-day factors for ice and snow under warm and cold climate conditions. The simulated melt area extent is found to have reasonable agreement with satellite-derived observations.

Improving surface boundary conditions with focus on coupling snow densification and meltwater retention in large-scale ice-sheet models of Greenland

Snowpack changes during the melt season are often not incorporated in modelling studies of the surface mass balance of the Greenland ice sheet. Densification of snow accelerates when meltwater is present, due to percolation and subsequent refreezing, and needs to be incorporated in ice-sheet models for ablation calculations. In this study, simple parameterizations to calculate surface melt, snow densification and meltwater retention are included as surface boundary conditions in a large-scale ice-sheet model of Greenland. Coupling the snow densification and meltwater-retention processes achieves a separation of volume and mass changes of the surface layer, in order to determine the surface melt contribution to runoff. Experiments for present-day conditions show that snow depth at the onset of melt, mean annual near-surface air temperature and the mean density of the annual snow layer are key factors controlling the quantity and spatial distribution of meltwater runoff above the equilibrium line on the Greenland ice sheet.

The implication of nonradiative energy fluxes dominating Greenland ice sheet exceptional ablation area surface melt in 2012

During two exceptionally large July 2012 multiday Greenland ice sheet melt episodes, nonradiative energy fluxes (sensible, latent, rain, and subsurface collectively) dominated the ablation area surface energy budget of the southern and western ice sheet. On average the nonradiative energy fluxes contributed up to 76% of daily melt energy at nine automatic weather station sites in Greenland. Comprising 6% of the ablation period, these powerful melt episodes resulted in 12–15% of the south and west Greenland automatic weather station annual ablation totals. Analysis of high resolution (~5 km) HIRHAM5 regional climate model output indicates widespread dominance of nonradiative energy fluxes across the western ablation area during these episodes. Yet HIRHAM5 still underestimates melt by up to 56% during these episodes due to a systematic underestimation of turbulent energy fluxes typical of regional climate models. This has implications for underestimating future melt, when exceptional melt episodes are expected to occur more frequently.

Liquid Water Flow and Retention on the Greenland Ice Sheet in the Regional Climate Model HIRHAM5: Local and Large-Scale Impacts

To improve Greenland Ice Sheet surface mass balance (SMB) simulation, the subsurface scheme of the HIRHAM5 regional climate model was extended to include snow densification, varying hydraulic conductivity, irreducible water saturation and other effects on snow liquid water percolation and retention. Sensitivity experiments to investigate the effects of the additions and the impact of different parameterization choices are presented. Compared with 68 accumulation area ice cores, the simulated mean annual net accumulation bias is -5% (correlation coefficient of 0.90). Modeled SMB in the ablation area compares favorably with 1041 PROMICE observations with regression slope of 0.95-0.97 (depending on model configuration), correlation coefficient of 0.75-0.86 and mean bias -3%. Weighting ablation area SMB biases at low- and high-elevation with the amount of runoff from these areas, we estimate ice sheet-wide mass loss biases in the ablation area at -5% and -7% using observed (MODIS-derived) and internally calculated albedo, respectively. Comparison with observed melt day counts shows that patterns of spatial (correlation ~0.9) and temporal (correlation coefficient of ~0.9) variability are realistically represented in the simulations. However, the model tends to underestimate the magnitude of inter-annual variability (regression slope ~0.7) and overestimate that of spatial variability (slope ~1.2). In terms of subsurface temperature structure and occurrence of perennial firn aquifers and perched ice layers, the most important model choices are the albedo implementation and irreducible water saturation parameterization. At one percolation area location, for instance, the internally calculated albedo yields too high subsurface temperatures below 5 m, but when using an implementation of irreducible saturation allowing higher values, an ice layer forms in 2011, reducing the deep warm bias in subsequent years. On the other hand, prior to the formation of the ice layer, observed albedos combined with lower irreducible saturation give the smallest bias. Perennial firn aquifers and perched ice layers occur in varying thickness and area for different model parameter choices. While the occurrence of these features has an influence on the local-scale subsurface temperature, snow, ice and water fields, the Greenland-wide runoff and SMB are - in the model’s current climate - dominated by the albedo implementation.

Greenland high-elevation mass balance: inference and implication of reference period (1961–90) imbalance

Abstract We revisit the input–output mass budget of the high-elevation region of the Greenland ice sheet evaluated by the Program for Arctic Regional Climate Assessment (PARCA). Our revised reference period (1961–90) mass balance of 54±48 Gt a–1 is substantially greater than the 0±21 Gt a–1 assessed by PARCA, but consistent with a recent, fully independent, input–output estimate of high-elevation mass balance (41±61 Gt a–1). Together these estimates infer a reference period high-elevation specific mass balance of 4.8±5.4 cm w.e. a–1. The probability density function (PDF) associated with this combined input–output estimate infers an 81% likelihood of high-elevation specific mass balance being positive (>0 cm w.e. a–1) during the reference period, and a 70% likelihood that specific balance was >2 cm w.e. a–1. Given that reference period accumulation is characteristic of centurial and millennial means, and that in situ mass-balance observations exhibit a dependence on surface slope rather than surface mass balance, we suggest that millennial-scale ice dynamics are the primary driver of subtle reference period high-elevation mass gain. Failure to acknowledge subtle reference period dynamic mass gain can result in underestimating recent dynamic mass loss by ~17%, and recent total Greenland mass loss by ~7%.

Spatial extent and temporal variability of Greenland firn aquifers detected by ground and airborne radars

We document the existence of widespread firn aquifers in an elevation range of ~1200–2000 m, in the high snow-accumulation regions of the Greenland ice sheet. We use NASA Operation IceBridge accumulation radar data from five campaigns (2010–2014) to estimate a firn-aquifer total extent of 21,900 km2. We investigate two locations in Southeast Greenland, where repeated radar profiles allow mapping of aquifer-extent and water table variations. In the upper part of Helheim Glacier the water table rises in spring following above-average summer melt, showing the direct firn-aquifer response to surface meltwater production changes. After spring 2012, a drainage of the firn-aquifer lower margin (5 km) is inferred from both 750 MHz accumulation radar and 195 MHz multicoherent radar depth sounder data. For 2011–2014, we use a ground-penetrating radar profile located at our Ridgeline field site and find a spatially stable aquifer with a water table fluctuating less than 2.5 m vertically. When combining radar data with surface topography, we find that the upper elevation edge of firn aquifers is located directly downstream of locally high surface slopes. Using a steady state 2-D groundwater flow model, water is simulated to flow laterally in an unconfined aquifer, topographically driven by ice sheet surface undulations until the water encounters crevasses. Simulations suggest that local flow cells form within the Helheim aquifer, allowing water to discharge in the firn at the steep-to-flat transitions of surface topography. Supported by visible imagery, we infer that water drains into crevasses, but its volume and rate remain unconstrained.

Present-day temperature standard deviation parameterization for Greenland

Modelling the surface mass balance of the Greenland ice sheet (GrIS) in large-scale ice-sheet models using temperature parameterizations in relation with the positive degreeday (PDD) approach is highly sensitive to a parameter: the temperature standard deviation (Braithwaite, 1984; Reeh, 1991). The PDD method is a statistical approach that relates the totals of positive near-surface air temperatures to the amount of snow or ice that melts. The standard deviation of the near-surface air temperature, pdd, is important for PDD modelling because it indicates whether the temperature has been above freezing during a month even though the mean monthly near-surface air temperature value is below. Fausto and others (2009a) demonstrated that a uniform increase of pdd from 2.58C to 4.58C results in a 33% increase in the modelled melt area over Greenland where melt is >1mm. It is therefore important to constrain the pdd value with observations. In large-scale ice-sheet and surface massbalance models of Greenland, it is common that pdd is assigned a single value which typically spans the interval 4.5–5.58C (Greve, 2005; Goelzer and others, 2010; Greve and others, 2011; Sundal and others, 2011). The value of pdd is often used as a tuning parameter, instead of using the temperature standard deviations observed at the automatic weather stations (AWSs) on the ice sheet. To add to the temperature parameterization presented by Fausto and others (2009a), it is proposed to construct a similar distributed parameterization for the temperature standard deviation using the same dataset. Commonly, large-scale ice-sheet models over Greenland calculate the amount of melt using the PDD method by assuming an annual sinusoidal evolution of the near-surface air temperature (Reeh, 1991). The number of PDDs from the normal probability distribution around the monthly mean temperatures during the years, following Reeh (1991), is given as

Thermal tracing of retained meltwater in the lower accumulation area of the Southwestern Greenland ice sheet

ABSTRACT 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 ~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°C and 1.7°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°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°C.

Satellite-derived surface type and melt area of the Greenland ice sheet using MODIS data from 2000 to 2005

Abstract A new surface classification algorithm for monitoring snow and ice masses based on data from the moderate-resolution imaging spectroradiometer (MODIS) is presented. The algorithm is applied to the Greenland ice sheet for the period 2000–05 and exploits the spectral variability of ice and snow reflectance to determine the surface classes dry snow, wet snow and glacier ice. The result is a monthly glacier surface type (GST) product on a 1 km resolution grid. The GST product is based on a grouped criteria technique with spectral thresholds and normalized indices for the classification on a pixel-by-pixel basis. The GST shows the changing surface classes, revealing the impact of climate variations on the Greenland ice sheet over time. The area of wet snow and glacier ice is combined into the glacier melt area (GMA) product. The GMA is analyzed in relation to the different surface classes in the GST product. The results are validated with data from weather stations and similar types of satellite-derived products. The validation shows that the automated algorithm successfully distinguishes between the different surface types, implying that the product is a promising indicator of climate change impact on the Greenland ice sheet.

Quantifying the Surface Energy Fluxes in South Greenland during the 2012 High Melt Episodes Using In-situ Observations

Two high melt episodes occurred on the Greenland ice sheet in July 2012, during which nearly the entire ice sheet surface experienced melting. Observations from an automatic weather station (AWS) in the lower ablation area in South Greenland reveal the largest daily melt rates (up to 28 cm d-1 ice equivalent) ever recorded on the ice sheet. The two melt episodes lasted 6 days, equivalent to 6% of the June-August melt period, but contributed 14 % to the total annual ablation of 8.5 m ice equivalent. We employ a surface energy balance model driven by AWS data to quantify the relative importance of the energy budget components contributing to melt through the melt season. During the days with largest daily melt rates, surface turbulent heat input peaked at 552 Wm-2, 77 % of the surface melt energy, which is otherwise typically dominated by absorbed solar radiation. We find that rain contributed ca. 7 % to melt during these episodes.