We evaluate modelled SMB using 132 in situ observations, originating from various sources and methods, e.g. ice cores, stake arrays and bomb horizons (Fig. ) . Included in these data are five unpublished in situ observations from high elevations, obtained from a shallow ice core, sonic snow height measurements and camera observations of a snow stake over time (T. A. Scambos, personal communication, 2014). Also included are six ice core accumulation records: James Ross Island , Gomez , two cores from Dyer Plateau, one to the east of the ice divide , one to the west of the ice divide (, E. R. Thomas, unpublished data), Bryan Coast and Ferrigno (E. R. Thomas, unpublished data). These records are additionally used to assess model interannual variability in Sect. 3.2.

We compare modelled SMB with in situ observations only for overlapping time periods, when available. When observations date from before 1979, or when the time of measurement is not known, they are compared with the climatological (1979–2014) modelled SMB. Only 38 SMB observations have an observation length >5 years and these are used for model evaluation in Sect. . Note that for all comparisons, the observational data are compared with data from the nearest model grid point; no interpolation is performed.

We evaluate modelled SMB using 1995 pre-collapse discharge (D) estimates of six Larsen B outlet glaciers in the north-eastern AP. We assume these to be in balance (SMB-D=0), as the data date from well before the significant thinning and retreat of the Larsen B ice shelf, that culminated in its disintegration in 2002 ; we exclude basins that are too small to be resolved by the model resolution, or were not in balance. This leaves six basins: Starbuck, Flask, Leppard, Crane, Jorum and Hektoria-Green, shown in Fig. . Assuming balance of these basins, a comparison with the climate average SMB for 1979–2014 is justified, and we directly compare discharge with RACMO2.3 SMB for this period.

Figure  presents average 1979–2014 AP SMB components (Eq. ) and Fig. a the resulting SMB. Total precipitation (PR = snowfall + rainfall, Fig. a) dominates the AP SMB with values that are typically 1 order of magnitude larger than the other components, which is also the case for the whole AIS . PR shows large gradients (note the nonlinear scale in Figs. a and ), with values ranging from >1000 mmweyr-1 on the western slopes and the adjacent ocean, towards low values (<300 mmweyr-1) on the eastern slopes and ice shelves. In particular the modelled precipitation rates in the north-western AP are extreme with rates of up to 5000 mmweyr-1 on the lower windward slopes, equivalent to ∼15 m of snowfall each year. This makes the AP among the wettest regions (in terms of snowfall) on Earth, comparable with the high snowfall rates (3500 mmwey-1) for Patagonia simulated with the same model . These mountainous regions represent a steep barrier that is almost perpendicular to the strong circumpolar westerlies, causing very efficient orographically induced precipitation over the windward mountain slopes, and a strong precipitation shadow on the leeward slopes. These sharp gradients are widespread, especially in the WAP: for instance, precipitation rates towards the south are high as well, varying from 2500 mmweyr-1 on the Elgar Uplands towards 1000–2000 mmweyr-1 on the western slopes of Palmer Land, with a distinct minimum over George VI ice shelf situated at the lee side of Alexander Island.

The second largest component is drifting snow sublimation (SUds, Fig. e), removing ∼50 mmweyr-1 of snowfall, peaking in regions of high wind speed . SUds is smaller at high elevations and the (western) mountain slopes, where winds are weaker; here a surface-based temperature inversion, and the associated increasing humidity with height, favours surface deposition (SUs ≃ -20 mmweyr-1, Fig. d). Surface sublimation (SUs > 0) mainly occurs over the flat ice shelves and the lower mountain slopes, typically removing ∼20 mmweyr-1. The erosion of drifting snow (ERds) does not significantly contribute to the (integrated) SMB, but redistributes mass on a local scale with snow divergence/convergence rates up to 100 mmweyr-1 on the AP slopes, closely following the topography. Snowmelt (M) is widespread below 2000 ma.s.l., showing large spatial variability, with maxima up to 500 mmweyr-1 over the north-eastern ice shelves, and with decreasing values towards higher elevations and/or latitudes. Most meltwater refreezes or is retained in the snowpack, and only a fraction runs off into the ocean. This happens mainly over Larsen B and northern Larsen C ice shelves, but also over Wilkins and northern George VI ice shelves, with runoff (RU) fluxes up to 300 mmweyr-1. Over the lower slopes of the north-western mountain range, where both PR and M are large, the model also simulates small amounts of runoff (∼50 mmweyr-1).

Figure  presents the average modelled (1979–2014) SMB at 5.5 km (panel a) and 27 km (panel b) horizontal resolution, together with the in situ SMB observations with time spans >5 years. SMB is largely similar to PR (Fig. a), with large west-to-east gradients, and peak SMB values around the WAP coastal regions, with large spatial variability that is controlled by the orography. Although a limited number of multi-year in situ observations are available, the modelled SMB patterns generally match with the observations: the large SMB values found only in a few observations are simulated well by the model, as well as the lower SMB values on the George VI and Larsen ice shelves. Over the former Larsen B ice shelf there is a mismatch: here, simulated RU reaches its maximum, and modelled SMB is negative (up to -100 mmweyr-1). This negative SMB is not found in the pre-break-up observations, which show small but positive values. However, the model does agree that the minimum in SMB lies in this area. Furthermore, for unknown reasons, the SMB is considerably overestimated at two locations, on Adelaide Island, and slightly eastwards, a region of large variability .

At 27 km horizontal resolution (Fig. ) the spatial pattern in SMB is largely similar to that at 5.5 km (also see Fig. ). The main advantage of the high-resolution product is that it better resolves the SMB gradients, the peak SMB, as well as the small islands and narrow ice-shelves.

Figure  shows yearly average SMB values and the largest SMB components; for integrated values after 2003 we exclude Larsen B ice shelf. Total AP SMB (Fig. a) has an interannual variability of 58 Gtyr-1 (15 % of mean SMB, absolute values shown in Table ) and shows no significant trend. Precipitation has a similar interannual variability of 57 Gtyr-1. The most positive SMB year is 1989 with 445 Gtyr-1, being significantly wetter than the driest year (1980, 246 Gtyr-1), relatively a much larger difference than for the whole AIS , which is expected as over larger regions differences cancel out. Variability in sublimation and drifting snow sublimation is low, and comparable for the WAP and the EAP (1 Gtyr-1). Of the SMB components (other than RU, that is small), the variability of M is the largest (15 Gtyr-1, 45 % of the mean), reaching its peak in 1992 (73 Gtyr-1), and minima (∼11 Gtyr-1) in 1986 and 2014. EAP melt rates are higher by 3 Gtyr-1 (relatively even higher as the area of the EAP is smaller than that of the WAP), but the timing of the maxima in M is similar. Simulated integrated AP snowmelt is lower than, but the variability and maxima are comparable to, the melt rates from , (34 ± 15 and 57 ± 21 Gtyr-1, respectively) that were calculated with RACMO2.1 at 27 km horizontal resolution. Even though the model physics has been updated and RACMO2.3 generally simulates less melt over the AIS , differences between both studies are explained by the use of a more sophisticated snowpack initialization in this study, and a different integration domain; i.e. in Larsen B is included for the whole period and the domain extends further south.

For none of the variables a significant trend is simulated, except for snowmelt (significance level >99 %). Snowmelt has decreased by the same amount (-0.35 Gtyr-2) over the WAP and the EAP, which is likely related to the significant and widespread cooling over most of the AP in the last decade . Runoff of meltwater is small but its variability is as high as its mean (4 Gtyr-1); peak years, 1992 and 1995 in particular, reach values of up to 15 Gtyr-1, following the peaks in snowmelt. In contrast to M, RU over the WAP and EAP shows large differences. Despite the higher temperatures, a thick firnpack exists over the WAP, as a result of the higher snowfall rates, permitting most meltwater to refreeze in the available pore space. Over the eastern ice shelves there is hardly any pore space present in the firn and a larger fraction of meltwater runs off, especially over Larsen B ice shelf before 2003.

Figure  shows maps of interannual variability in SMB and M. SMB variability (Fig. a) shows no unexpected patterns for most of the domain, mostly following the regions of high absolute SMB. Relatively, SMB variability peaks over George VI, Larsen B and the northern part of Larsen C ice shelves (>40 %). This is clearly related to RU (not shown), which in turn is controlled by snowmelt variability (Fig. b), that peaks towards the northern parts of the ice shelves. It is clear that dry regions, which experience significant melt, show the largest interannual (relative) SMB variability. Interestingly, these coincide with the EAP ice shelves, which are also sensitive to disintegration. The other SMB components (not shown) have low variability and show no pronounced patterns.

There are no trends in integrated precipitation, but Fig. c shows that large significant trends exist locally, e.g. on Alexander Island and in the Weddell Sea. The model simulates large positive trends over the northerly slopes of the WAP (15 mmweyr-2), but these are not significant as these locations also experience large interannual variability. These trends are related to enhanced upper atmosphere northerly winds . Negative trends in snowmelt (Fig. d) are more significant on the WAP than on the EAP ice shelves, and show a uniform pattern.

Figure  shows the average seasonal cycle (1979–2014) of SMB components. Integrated AP precipitation has a pronounced seasonality, with considerably larger values in winter than in summer. In winter, the stronger westerlies create more orographic precipitation over the WAP mountain slopes. In addition, WAP (and hence total) precipitation shows two peaks in March and in October, that are related to the semiannual oscillation , in agreement with observational data from surface stations . Over the EAP, the precipitation seasonality is reversed: here precipitation peaks in summer, reaching values almost as high as in the WAP summer, and decreases to a relatively constant minimum in winter 1 order of magnitude lower than over the WAP. Over the EAP, most summer precipitation originates from the Weddell Sea; when a minimum of sea-ice cover is reached in summer, moist ocean air is transported to the eastern ice shelves.

The other SMB components have lower magnitudes and show varying seasonal patterns. Snowmelt is absent in winter, and reaches its peak (13 Gtyr-1) in December and January. SUs is negative in winter (-1 Gtyr-1), when a persistent surface-based temperature inversion favours surface deposition. This positive contribution to the SMB is compensated by the stronger wintertime winds removing mass by SUds. In summer, SUds drops off as winds are weaker and the snowpack gets warmer and denser. SUs increases with surface temperature, and up to 3 Gtyr-1 of snow is removed. Finally, ERds is very low year-round (<0.1 Gtyr-1).

To illustrate the spatial coherence of AP SMB, Fig.  shows the spatial correlation of the modelled yearly time series at the six ice core locations of Sect. 3.2, with all other points in the model domain. Figure a shows that the SMB simulated at the location of the Gomez ice core, in south-western Palmer Land, is strongly and significantly (>99 %) correlated over the whole WAP, supporting the strong spatial coherence that was also found for (observed) temperature in . Simultaneously there is a negative correlation over the north-eastern AP, and Larsen B and C ice shelves, showing that high WAP SMB rates are coinciding with dry conditions over this region, a coherence not found in . Figure b identifies the spatial coherence of this location as well: when SMB is large at James Ross Island, it is large over the northern EAP ice shelves and sea-ice, while over the WAP an insignificant correlation is found. Figure c shows that the SMB time series simulated at the Dyer Plateau ice core location, slightly east of the ice divide, is highly correlated with and representative of the adjacent EAP. Simultaneously, the second ice core at Dyer Plateau (Fig. d), located only 30 km westwards, and the Bryan Coast and Ferrigno ice cores (Fig. e and f), all located on the WAP, show completely opposite correlations, that closely resemble that of the Gomez ice core. These correlation maps clearly highlight the different forcing mechanisms of SMB on the WAP and EAP and the distinct and sharp climatic differences between both sides of the AP: over the WAP, snowfall is orographically induced, while over the EAP snowfall events are triggered by low pressure systems over the Weddell Sea.