Improved representation of the contemporary Greenland ice sheet firn layer by IMAU-FDM v1.2G

The firn layer that covers 90 % of the Greenland ice sheet (GrIS) plays an important role in determining the response of the ice sheet to climate change. Meltwater can percolate into the firn layer and refreeze at greater depths, thereby temporarily preventing mass loss. However, as global warming leads to increasing surface melt, more surface melt may refreeze in the firn layer, thereby reducing the capacity to buffer subsequent episodes of melt. This can lead to a tipping point in meltwater runoff. It is therefore important to study the evolution of the Greenland firn layer in the past, present and future. In this study, we present the latest version of our firn model, IMAU-FDM (Firn Densification Model) v1.2G, with an application to the GrIS. We improved the density of freshly fallen snow, the dry-snow densification rate and the firn's thermal conductivity using recently published parametrizations and by calibration to an extended set of observations of firn density, temperature and liquid water content at the GrIS. Overall, the updated model settings lead to higher firn air content and higher 10 m firn temperatures, owing to a lower density near the surface. The effect of the new model settings on the surface elevation change is investigated through three case studies located at Summit, KAN-U and FA-13. Most notably, the updated model shows greater inter- and intra-annual variability in elevation and an increased sensitivity to climate forcing

Characteristics of the 1979–2020 Antarctic firn layer simulated with IMAU-FDM v1.2A

Firn simulations are essential for understanding Antarctic ice sheet mass change, as they enable us to convert satellite altimetry observed volume changes to mass changes and column thickness to ice thickness and to quantify the meltwater buffering capacity of firn. Here, we present and evaluate a simulation of the contemporary Antarctic firn layer using the updated semi-empirical IMAU Firn Densification Model (IMAU-FDM) for the period 1979–2020. We have improved previous fresh-snow density and firn compaction parameterizations and used updated atmospheric forcing. In addition, the model has been calibrated and evaluated using 112 firn core density observations across the ice sheet. We found that 62 % of the seasonal and 67 % of the decadal surface height variability are due to variations in firn air content rather than firn mass. Comparison of simulated surface elevation change with a previously published multi-mission altimetry product for the period 2003–2015 shows that performance of the updated model has improved, notably in Dronning Maud Land and Wilkes Land. However, a substantial trend difference (>10 cm yr−1) remains in the Antarctic Peninsula and Ellsworth Land, mainly caused by uncertainties in the spin-up forcing. By estimating previous climatic conditions from ice core data, these trend differences can be reduced by 38 %

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

From snowflake to ice sheet: Climatic drivers of Greenland’s firn

Sea levels are currently rising, which may lead to an increased likelihood of flooding in many parts of the world, as well as a plethora of other problems. One of the biggest contributors to the rise in sea levels is the melting of the Greenland ice sheet. Large portions of the ice sheet are covered by old snow, called firn. Here, we investigate the role that firn plays on the melting of the ice sheet. Firn acts as a sponge that can absorb meltwater into its pores, which prevents it from running off into the ocean. It is thus important to understand how firn interacts with meltwater, and what may lead to an increase or decrease in firn cover. We find that the position of the polar jet stream, a band of strong westerly winds encircling the Northern hemisphere, plays a large role in determining if a region gains or loses firn. Changes in the jet stream caused firn loss in the beginning of this century, but lead to more firn after 2012. When meltwater is absorbed into the firn, it can either refreeze into layers of ice, which are called ice slabs, or large amounts of water can be stored inside the firn as a liquid. Locations of firn that hold water year-round are called firn aquifers. Ice slabs and firn aquifers impact the runoff of meltwater very differently. Our research finds that the amount of snowfall and melt determine whether ice slabs or aquifers form, and that they are likely much more widespread than previously assumed. In a warmer climate, these phenomena may appear more often and accelerate ice-sheet mass loss

Improved representation of the contemporary Greenland ice sheet firn layer by IMAU-FDM v1.2G

The firn layer that covers 90 % of the Greenland ice sheet (GrIS) plays an important role in determining the response of the ice sheet to climate change. Meltwater can percolate into the firn layer and refreeze at greater depths, thereby temporarily preventing mass loss. However, as global warming leads to increasing surface melt, more surface melt may refreeze in the firn layer, thereby reducing the capacity to buffer subsequent episodes of melt. This can lead to a tipping point in meltwater runoff. It is therefore important to study the evolution of the Greenland firn layer in the past, present and future. In this study, we present the latest version of our firn model, IMAU-FDM (Firn Densification Model) v1.2G, with an application to the GrIS. We improved the density of freshly fallen snow, the dry-snow densification rate and the firn's thermal conductivity using recently published parametrizations and by calibration to an extended set of observations of firn density, temperature and liquid water content at the GrIS. Overall, the updated model settings lead to higher firn air content and higher 10 m firn temperatures, owing to a lower density near the surface. The effect of the new model settings on the surface elevation change is investigated through three case studies located at Summit, KAN-U and FA-13. Most notably, the updated model shows greater inter- and intra-annual variability in elevation and an increased sensitivity to climate forcing