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The Ross Ice Shelf, West Antarctica, experienced an extensive melt event in January 2016. We examine the representation of this event by the HIRHAM5 and MetUM high-resolution regional atmospheric models, as well as a sophisticated offline-coupled firn model forced with their outputs. The model results are compared with satellite-based estimates of melt days. The firn model estimates of the number of melt days are in good agreement with the observations over the eastern and central sectors of the ice shelf, while the HIRHAM5 and MetUM estimates based on their own surface schemes are considerably underestimated, possibly due to deficiencies in these schemes and an absence of spin-up. However, the firn model simulates sustained melting over the western sector of the ice shelf, in disagreement with the observations that show this region as being a melt-free area. This is attributed to deficiencies in the HIRHAM5 and MetUM output and particularly a likely overestimation of night-time net surface radiative flux. This occurs in response to an increase in night-time downwelling longwave flux from around 180–200 to 280 W m−2 over the course of a few days, leading to an excessive amount of energy at the surface available for melt. Satellite-based observations show that this change coincides with a transition from clear-sky to cloudy conditions, with clouds containing both liquid water and ice water. The models capture the initial clear-sky conditions but seemingly struggle to correctly represent cloud properties associated with the cloudy conditions, which we suggest is responsible for the radiative flux errors.

Regional climate models compute ice sheet surface mass balance (SMB) over a mask that defines the area covered by glacier ice, but ice masks have not been harmonised between models. Intercomparison studies of modelled SMB therefore use a common ice mask. The SMB in areas outside the common ice mask, which are typically coastal and high-precipitation regions, is discarded. Ice mask differences change integrated SMB by between 40.5 and 140.6 Gt yr−1 (1.8 % to 6.0 % of ensemble mean SMB), equivalent to the entire Antarctic mass imbalance. We conclude there is a pressing need for a common ice mask protocol.

The future rates of ice sheet melt in Greenland and Antarctica are an important factor when making estimates of the likely rate of sea level rise. Global climate models that took part in the fifth Coupled Model Intercomparison Project (CMIP5) have generally been unable to replicate observed rates of ice sheet melt. With the advent of the sixth Coupled Model Intercomparison Project (CMIP6), with a general increase in the equilibrium climate sensitivity, we here compare two versions of the global climate model EC-Earth using the regional climate model HIRHAM5 downscaling of EC-Earth for Greenland and Antarctica. One version (v2) of EC-Earth is taken from CMIP5 for the high-emissions Representative Concentration Pathway 8.5 (RCP8.5) scenario and the other (v3) from CMIP6 for the comparable high-emissions Shared Socioeconomic Pathway 5-8.5 (SSP5-8.5) scenario. For Greenland, we downscale the two versions of EC-Earth for the historical period 1991–2010 and for the scenario period 2081–2100. For Antarctica, the periods are 1971–2000 and 2071–2100, respectively. For the Greenland Ice Sheet, we find that the mean change in temperature is 5.9 ∘C when downscaling EC-Earth v2 and 6.8 ∘C when downscaling EC-Earth v3. Corresponding values for Antarctica are 4.1 ∘C for v2 and 4.8 ∘C for v3. The mean change in surface mass balance at the end of the century under these high-emissions scenarios is found to be −290 Gt yr−1 (v2) and −1640 Gt yr−1 (v3) for Greenland and 420 Gt yr−1 (v2) and 80 Gt yr−1 (v3) for Antarctica. These distinct differences in temperature change and particularly surface mass balance change are a result of the higher equilibrium climate sensitivity in EC-Earth v3 (4.3 K) compared with 3.3 K in EC-Earth v2 and the differences in greenhouse gas concentrations between the RCP8.5 and the SSP5-8.5 scenarios.

Antarctic surface mass balance (SMB) is largely determined by precipitation over the continent and subject to regional climate variability related to the Southern Annular Mode (SAM) and other climatic drivers at the large scale. Locally however, firn and snowpack processes are important in determining SMB and the total mass balance of Antarctica and global sea level. Here, we examine factors that influence Antarctic SMB and attempt to reconcile the outcome with estimates for total mass balance determined from the GRACE satellites. This is done by having the regional climate model HIRHAM5 forcing two versions of an offline subsurface model, to estimate Antarctic ice sheet (AIS) SMB from 1980 to 2017. The Lagrangian subsurface model estimates Antarctic SMB of 2473.5±114.4 Gt yr−1, while the Eulerian subsurface model variant results in slightly higher modelled SMB of 2564.8±113.7 Gt yr−1. The majority of this difference in modelled SMB is due to melt and refreezing over ice shelves and demonstrates the importance of firn modelling in areas with substantial melt. Both the Eulerian and the Lagrangian SMB estimates are within uncertainty ranges of each other and within the range of other SMB studies. However, the Lagrangian version has better statistics when modelling the densities. Further, analysis of the relationship between SMB in individual drainage basins and the SAM is carried out using a bootstrapping approach. This shows a robust relationship between SAM and SMB in half of the basins (13 out of 27). In general, when SAM is positive there is a lower SMB over the plateau and a higher SMB on the westerly side of the Antarctic Peninsula, and vice versa when the SAM is negative. Finally, we compare the modelled SMB to GRACE data by subtracting the solid ice discharge, and we find that there is a good agreement in East Antarctica but large disagreements over the Antarctic Peninsula. There is a large difference between published estimates of discharge that make it challenging to use mass reconciliation in evaluating SMB models on the basin scale.

We compare the performance of five different regional climate models (RCMs) (COSMO-CLM2, HIRHAM5, MAR3.10, MetUM, and RACMO2.3p2), forced by ERA-Interim reanalysis, in simulating the near-surface climate and surface mass balance (SMB) of Antarctica. All models simulate Antarctic climate well when compared with daily observed temperature and pressure, with nudged models matching daily observations slightly better than free-running models. The ensemble mean annual SMB over the Antarctic ice sheet (AIS) including ice shelves is 2329±94 Gt yr−1 over the common 1987–2015 period covered by all models. There is large interannual variability, consistent between models due to variability in the driving ERA-Interim reanalysis. Mean annual SMB is sensitive to the chosen period; over our 30-year climatological mean period (1980 to 2010), the ensemble mean is 2483 Gt yr−1. However, individual model estimates vary from 1961±70 to 2519±118 Gt yr−1. The largest spatial differences between model SMB estimates are in West Antarctica, the Antarctic Peninsula, and around the Transantarctic Mountains. We find no significant trend in Antarctic SMB over either period. Antarctic ice sheet (AIS) mass loss is currently equivalent to around 0.5 mm yr−1 of global mean sea level rise (Shepherd et al., 2020), but our results indicate some uncertainty in the SMB contribution based on RCMs. We compare modelled SMB with a large dataset of observations, which, though biased by undersampling, indicates that many of the biases in SMB are common between models. A drifting-snow scheme improves modelled SMB on ice sheet surface slopes with an elevation between 1000 and 2000 m, where strong katabatic winds form. Different ice masks have a substantial impact on the integrated total SMB and along with model resolution are factored into our analysis. Targeting undersampled regions with high precipitation for observational campaigns will be key to improving future estimates of SMB in Antarctica.

Severe precipitation events occur rarely and are often localised in space and of short duration, but they are important for societal managing of infrastructure. Therefore, there is a demand for estimating future changes in the statistics of the occurrence of these rare events. These are often projected using data from regional climate model (RCM) simulations combined with extreme value analysis to obtain selected return levels of precipitation intensity. However, due to imperfections in the formulation of the physical parameterisations in the RCMs, the simulated present-day climate usually has biases relative to observations; these biases can be in the mean and/or in the higher moments. Therefore, the RCM results are adjusted to account for these deficiencies. However, this does not guarantee that the adjusted projected results will match the future reality better, since the bias may not be stationary in a changing climate. In the present work, we evaluate different adjustment techniques in a changing climate. This is done in an inter-model cross-validation set-up in which each model simulation, in turn, performs pseudo-observations against which the remaining model simulations are adjusted and validated. The study uses hourly data from historical and RCP8.5 scenario runs from 19 model simulations from the EURO-CORDEX ensemble at a 0.11∘ resolution. Fields of return levels for selected return periods are calculated for hourly and daily timescales based on 25-year-long time slices representing the present-day (1981–2005) and end-21st-century (2075–2099). The adjustment techniques applied to the return levels are based on extreme value analysis and include climate factor and quantile-mapping approaches. Generally, we find that future return levels can be improved by adjustment, compared to obtaining them from raw scenario model data. The performance of the different methods depends on the timescale considered. On hourly timescales, the climate factor approach performs better than the quantile-mapping approaches. On daily timescales, the superior approach is to simply deduce future return levels from pseudo-observations, and the second-best choice is using the quantile-mapping approaches. These results are found in all European subregions considered. Applying the inter-model cross-validation against model ensemble medians instead of individual models does not change the overall conclusions much.

The outlet glacier of Basin 3 (B3) of Austfonna ice cap, Svalbard, is one of the fastest outlet glaciers in Svalbard, and shows dramatic changes since 1995. In addition to previously observed seasonal summer speed-up associated with the melt season, the winter speed of B3 has accelerated approximately fivefold since 1995. We use the Elmer/Ice full-Stokes model for ice dynamics to infer spatial distributions of basal drag for the winter seasons of 1995, 2008 and 2011. This "inverse" method is based on minimising discrepancy between modelled and observed surface velocities, using satellite remotely sensed velocity fields. We generate steady-state temperature distributions for 1995 and 2011. Frictional heating caused by basal sliding contributes significantly to basal temperatures of the B3 outlet glacier, with heat advection (a longer-timescale process than frictional heating) also being important in the steady state. We present a sensitivity experiment consisting of transient simulations under present-day forcing to demonstrate that using a temporally fixed basal drag field obtained through inversion can lead to thickness change errors of the order of 2 m year−1. Hence it is essential to incorporate the evolution of basal processes in future projections of the evolution of B3. Informed by a combination of our inverse method results and previous studies, we hypothesise a system of processes and feedbacks involving till deformation and basal hydrology to explain both the seasonal accelerations (short residence time pooling of meltwater at the ice–till interface) and the ongoing interannual speed-up (gradual penetration of water into the till, reducing till strength).

The four year "Coupling of Atmospheric Layers (CAL)" EU FP5 Research Training Network project studied unanswered questions related to transient luminous events (sprites, jets and elves) in the upper atmosphere. Consisting of ten scientific work-packages CAL also included intensive training and outreach programmes for the young scientists hired. Educational activities were based on the following elements: national PhD programmes, activities at CAL and other meetings, a dedicated summer school, and two European sprite observational campaigns. The young scientists were strongly involved in the latter and, as an example, the "EuroSprite2005" observational campaign is presented in detail. Some of the young scientists participated in the instrument set-up, others in the campaign logistics, some coordinated the observations, and others gathered the results to build a catalogue. During the four-month duration of this campaign, all of them took turns in operating the system and making their own night observations. The ongoing campaign activities were constantly advertised and communicated via an Internet blog. In summary the campaign required all the CAL young scientists to embark on experimental work, to develop their organisational skills, and to enhance their ability to communicate their activities. The campaign was a unique opportunity to train and strengthen skills that will be an asset to their future careers and, overall, was most successful.