We discuss Greenland Ice Sheet (GrIS) surface mass balance (SMB) differences between the updated polar version of the RACMO climate model (RACMO2.3) and the previous version (RACMO2.1). Among other revisions, the updated model includes an adjusted rainfall-to-snowfall conversion that produces exclusively snowfall under freezing conditions; this especially favours snowfall in summer. Summer snowfall in the ablation zone of the GrIS has a pronounced effect on melt rates, affecting modelled GrIS SMB in two ways. By covering relatively dark ice with highly reflective fresh snow, these summer snowfalls have the potential to locally reduce melt rates in the ablation zone of the GrIS through the snow-albedo-melt feedback. At larger scales, SMB changes are driven by differences in orographic precipitation following a shift in large-scale circulation, in combination with enhanced moisture to precipitation conversion for warm to moderately cold conditions. A detailed comparison of model output with observations from automatic weather stations, ice cores and ablation stakes shows that the model update generally improves the simulated SMB-elevation gradient as well as the representation of the surface energy balance, although significant biases remain.
Since the mid-1990s, atmospheric and oceanic warming in the Arctic has led to
accelerated Greenland ice sheet (GrIS) mass loss
Since surface melt over the GrIS is mainly driven by the absorption of
shortwave radiation
Summer snowfall events can interrupt this feedback, by covering dark ice
and/or metamorphosed snow with a highly reflective fresh snow layer.
Therefore, an accurate representation of (summer) snowfall events is
essential to model the SMB of the GrIS
The Regional Atmospheric Climate Model (RACMO2) is developed and maintained
at the Royal Netherlands Meteorological Institute (KNMI)
The RACMO2 physics package has recently been updated from cycle CY23r4 used
in RACMO2.1
The new cloud scheme includes an ice supersaturation parameterisation, which
prolongs the vapour phase at low temperatures
In the polar version of RACMO2.3, identical domain and resolutions
(
In both RACMO2 versions, Moderate Resolution Imaging Spectroradiometer
(MODIS) albedo products
MODIS background ice albedo prescribed in RACMO2.3. The RACMO2 integration domain is displayed as well as the location of the K-transect (white dots, see also inset) and accumulation zone sites (yellow dots).
For model evaluation, we use long-term measurements from the K-transect,
operated by the Institute for Marine and Atmospheric Research of Utrecht
University in the Netherlands. The K-transect runs for a distance of
approximately 140 km from the ice margin through the ablation zone and into
the lower accumulation zone of the west Greenland ice sheet along
To compare model results to observations, we apply different selection methods in the ablation and accumulation zones of the GrIS. In the accumulation zone, modelled SMB is obtained by selecting the closest RACMO2 grid cell. Due to significant dependence of ablation terms on elevation, modelled SMB and SEB components were retrieved by successively selecting the nearest grid cell and then applying an altitude correction. To do so, we select a grid cell, among the closest pixel and its eight adjacent neighbours, which minimizes the elevation bias between the model and the stations.
Figure
The SMB fields from RACMO2.1 and RACMO2.3 are qualitatively similar, but two
patterns of difference can be discerned (Fig.
Secondly, superimposed on this large-scale pattern, Fig.
The average mid-tropospheric circulation at 500 hPa is directed from
south-west to north-east over Greenland (Fig.
Relative to RACMO2.1, RACMO2.3 is 0.1 to 0.3
The large-scale circulation anomaly also reduces evaporation over the north
Atlantic Ocean, by up to 200 mmWE per year (not shown). Moreover, because
condensation in the updated scheme is enhanced for moderately cold conditions
(
Owing to an increase of the cloud water-to-snowfall conversion coefficient,
the revised physics in RACMO2.3 favours solid precipitation at the expense of
liquid precipitation, especially for cloud temperatures between
The regions experiencing increased summer snowfall coincide with positive
changes in JJA surface albedo (Fig.
In this section, we compare modelled and observed monthly mean SEB components
(2004–2012) along the K-transect, conveniently situated in a region of west
Greenland where there are significant differences in SMB between the two
model versions (Fig.
Change in JJA mean
SEB data from the AWS at S6 are not used because of gaps in the time series.
Figure
Observed and modelled turbulent and net shortwave/longwave fluxes
(W m
At station S5, Table 1 shows that both RACMO2 versions significantly
overestimate SWd and underestimate LW
At S9, RACMO2.3 reduces the bias in most SEB components (Table 2). The 2
metre temperature bias has almost vanished, which has improved the
representation of SHF. Despite a notable improvement of winter
LW
Differences in monthly mean surface albedo between models and S9
measurements, and monthly mean modelled snowfall for the periods
The bias in surface albedo between model and observations (Fig.
At S10, biases in shortwave fluxes are greatly reduced but again the negative
LW
The generally improved representation of surface snow albedo is attributed to
enhanced summer snowfall in RACMO2.3 (see Sect. 3.3), thickening the melting
snow cover and allowing the snow layer to persist longer over bare ice areas
in summer. As a result, snowmelt decreases, further delaying snow cover
disappearance and maintaining the surface albedo high until summer snowfall
events cease (Fig.
Table 4 compares time series of modelled and measured annual SMB values
(1990–2012) collected at seven stake sites, ranging from station S5 in the lower
ablation zone to station S10 in the accumulation zone (Fig.
Figure
Table 4 and Fig.
Modelled and observed annual mean SEB components
and statistics of the differences (2004–2012) at station S5
(67
Same as Table 1 but for station S9 (67
Same as Table 1 but for station S10 (67
Modelled and observed mean annual SMB (mWE yr
In the lower ablation zone, between 500 to 800 m a.s.l., RACMO2.3 simulates
lower (more negative) SMB values than RACMO2.1, which better matches
observations. This improvement can be ascribed to a smaller bias in melt
energy (Table 1) and hence a more realistic runoff. Correcting the persistent
overestimation of SMB between 500 and 800 m a.s.l. will require a better
representation of SHF which, in combination with SWd and LW
An alternative way to assess model performance is to quantify SMB gradients,
here determined by simple least-squares fitting of a linear function. This
yields 3.15
Time series of observed (AWS) and modelled (RACMO2.3 and 2.1)
annual mean SMB along the K-transect (mWE yr
Observed and simulated SMB (mWE yr
Observed and simulated SMB (mWE yr
An updated physics package has been implemented in the regional climate model
RACMO2.3. Among other changes, the rainfall-to-snowfall conversion has been
revised and an ice supersaturation parameterization included to favour solid
over liquid precipitation in summer and reduce the overestimated coastal
cloud cover and precipitation simulated in previous versions, respectively
Two remaining problems require particular attention in future model updates.
Current RCMs still struggle to model the correct cloud cover and cloud type
(ice/water) over the GrIS
Another revision that is simpler to implement is improvement of the background ice albedo, that is currently too low at the ice sheet margin. However, at this point, it is also important to realize that point AWS (SEB) and stake (SMB) measurements may not be representative for a wider area, especially for a spatially heterogeneous variable such as surface albedo. Sub-grid albedo variability should therefore become an important future topic of study. To assess the quality of the simulated SMB in the ablation zone elsewhere in Greenland, an evaluation of downscaled RACMO2.3 data against a much larger data set of ablation measurements, covering all sectors of the Greenland ice sheet, is currently being conducted.
B. Noël, W. J. van de Berg, P. Kuipers Munneke, R. S. W. van de Wal, and M. R. van den Broeke acknowledge support from the Polar Programme of the Netherlands Organization for Scientific Research (NWO/ALW)Edited by: M. Sharp