Regional Climate Model RACMO2 Research Articles

The evolution of future Antarctic surface melt using PISM-dEBM-simple

Abstract. It is virtually certain that Antarctica's contribution to sea-level rise will increase with future warming, although competing mass balance processes hamper accurate quantification of the exact magnitudes. Today, ocean-induced melting underneath the floating ice shelves dominates mass losses, but melting at the surface will gain importance as global warming continues. Meltwater at the ice surface has crucial implications for the ice sheet's stability, as it increases the risk of hydrofracturing and ice-shelf collapse that could cause enhanced glacier outflow into the ocean. Simultaneously, positive feedbacks between ice and atmosphere can accelerate mass losses and increase the ice sheet's sensitivity to warming. However, due to long response times, it may take hundreds to thousands of years until the ice sheet fully adjusts to the environmental changes. Therefore, ice-sheet model simulations must be computationally fast and capture the relevant feedbacks, including the ones at the ice–atmosphere interface. Here we use the novel surface melt module dEBM-simple (a slightly modified version of the “simple” diurnal Energy Balance Model) coupled to the Parallel Ice Sheet Model (PISM, together referred to as PISM-dEBM-simple) to estimate the impact of 21st-century atmospheric warming on Antarctic surface melt and ice dynamics. As an enhancement compared to the widely adopted positive degree-day (PDD) scheme, dEBM-simple includes an implicit diurnal cycle and computes melt not only from the temperature, but also from the influence of solar radiation and changes in ice albedo, thus accounting for the melt–albedo feedback. We calibrate PISM-dEBM-simple to reproduce historical and present-day Antarctic surface melt rates given by the regional atmospheric climate model RACMO2.3p2 and use the calibrated model to assess the range of possible future surface melt trajectories under Shared Socioeconomic Pathway SSP5-8.5 warming projections until the year 2100. To investigate the committed impacts of the enhanced surface melting on the ice-sheet dynamics, we extend the simulations under fixed climatological conditions until the ice sheet has reached a state close to equilibrium with its environment. Our findings reveal a substantial surface-melt-induced speed-up in ice flow associated with large-scale elevation reductions in sensitive ice-sheet regions, underscoring the critical role of self-reinforcing ice-sheet–atmosphere feedbacks in future mass losses and sea-level contribution from the Antarctic Ice Sheet on centennial to millennial timescales.

A perfect model study on the reliability of the added small-scale information in regional climate change projections

The issue of the added value (AV) of high resolution regional climate models is complex and still strongly debated. Here, we approach AV in a perfect model framework within a 16-member single model initial condition ensemble with the regional climate model RACMO2 embedded in the global climate model EC-Earth2.3. In addition, we also used an ensemble produced by a pseudo global warming (PGW) approach. Results for winter temperature and precipitation are investigated from two different perspectives: (1) a signal-to-noise perspective analysing the systematic response to changing emission forcings versus internal climate variability, and (2) a prediction perspective aimed at predicting a 30-year future climate state. Systematic changes in winter temperature and precipitation contain fine-scale response patterns, but in particular for precipitation these patterns are small compared to internal variability. Therefore, single members of the ensemble provide only limited information on these systematic patterns. However, they can be estimated more reliably from PGW members because of the stronger constraints on internal variability. From the prediction perspective, we analysed AV of fine-scale information by comparing three prediction pairs. This analysis shows that there is AV in the fine-scale information for temperature, yet for precipitation adding fine-scale changes generally deteriorates the predictions. Using only the large-scale change (without fine scales) from a single ensemble member as a delta change on top of the present-day climate state, already provides a robust estimate of the future climate state and therefore can be used as a simple benchmark to measure added value.

Temporal and Spatial Variability in Contemporary Greenland Warming (1958–2020)

Abstract In this study, 2-m or near-surface air temperature (T2m) products from atmospheric reanalysis ERA5 and the regional climate model RACMO2.3p2 over Greenland are compared with observations from staffed stations and Automated Weather Stations (AWS). The results show the following: 1) Greenland experienced decadal periods of both cooling and warming during 1958–2020, with an inflection point around the mid-1990s, and no significant warming after ∼2005 except in the north and northeast. 2) In the full time series, the magnitude of the warming increases gradually from south to north, with peak warming found along the northeastern coast. 3) The most intense warming occurred in autumn and winter, notably in the northeast. 4) The correlations of T2m with the large-scale circulation indices NAO and GBI are highly significant, but they gradually weaken from southwestern to northeastern Greenland. Under the background of Greenland rapidly warming, the shift from positive to negative NAO (negative to positive GBI) is critical to the sudden warming in Greenland since the mid-1990s.

Quantifying the role of the large-scale circulation on European summer precipitation change

Regional climate projections indicate that European summer precipitation may change considerably in the future. Southern Europe can expect substantial drying while Northern Europe could actually become wetter. Model spread and internal variability in these projections are large, however, and unravelling the processes that underlie the changes is essential to get more confidence in these projections. Large-scale circulation change is one of the contributors to model spread. In this paper we quantify the role of future large-scale circulation changes to summer precipitation change, using a 16-member single-model ensemble obtained with the regional climate model RACMO2, forced by the global climate model EC-Earth2.3 and the RCP8.5 emission scenario. Using the method of circulation analogues three contributions to the future precipitation change are distinguished. The first is the precipitation change occurring without circulation change (referred to as the thermodynamic term). This contribution is characterised by a marked drying-to-wetting gradient as one moves north from the Mediterranean. The second contribution measures the effects of changes in the mean circulation. It has a very different spatial pattern and is closely related to the development of a region of high pressure (attaining its maximum west of Ireland) and the associated anti-cyclonic circulation response. For a large area east of Ireland including parts of western Europe, it is the major contributor to the overall drying signal, locally explaining more than 90% of the ensemble-mean change. In regions where the patterns overlap, the signal-to-noise ratio of the total change is either enhanced or reduced depending on their relative signs. Although the second term is expected to be particularly model dependent, the high-pressure region west of Ireland also appears in CMIP5 and CMIP6 ensemble-mean projections. The third contribution records the effects of changes in the circulation variability. This term has the smallest net contribution, but a relatively large uncertainty. The analogues are very good in partitioning the ensemble-mean precipitation change, but describe only up to 40% of the ensemble-spread. This demonstrates that other precipitation-drivers (SST, spring soil moisture etc.) will generally strongly influence trends in single climate realisations. This also re-emphasises the need for large ensembles or using alternative methods like the Pseudo Global Warming approach where signal to noise ratios are higher. Nevertheless, identifying the change mechanisms helps to understand the future uncertainties and differences between models.

Discharge Estimation With Improved Methods Using MODIS Data in Greenland: An Application in the Watson River

Greenland's river discharge has important implications for the Greenland Ice Sheet (GrIS) mass balance, global sea-level rise, and climate change. However, long-term and continuous in-situ discharge data for Greenland are scarce. The water extent is an important proxy to estimate discharge using remote sensing, but previous studies on estimating the discharge in Greenland required in-situ reflectance data to construct the water extent and suffered from inefficient processing. Here, we derived the water extent solely from the Moderate Resolution Imaging Spectroradiometer (MODIS) daily reflectance product on the Google Earth Engine (GEE) cloud platform. To improve the accuracy and efficiency, we optimized the strategies for water extent estimation and the optimal gauge pixel selection. Our improved method was applied in the Watson River. The runoff data from the regional climate model RACMO2 were employed to compare with the estimated results. Our results provide the daily discharge of the Watson River from 2002 to 2021, covering the period when field observations are unavailable. The correlation coefficient (R) and the fractional root mean square error (fRMSE) between the daily estimated discharge and the in-situ discharge are 0.69 and 0.73, respectively, whereas the R and fRMSE are 0.85 and 0.53 at a monthly timescale, respectively. Comparisons between our results and the RACMO2 runoff data suggest that the RACMO2 may generally underestimate the annual ice sheet melt runoff but overestimates the monthly runoff in July by 30% on average. The proposed method is highly automated, efficient and has the potential to be applied in other rivers with field measurements to provide continuous and long-term discharge observations. It contributes to a better understanding of the response of the GrIS to climate change.

Three-decade spatial patterns in surface mass balance of the Nivlisen Ice Shelf, central Dronning Maud Land, East Antarctica

AbstractThe coastal Droning Maud Land in East Antarctica is characterized by small ice shelves with numbers of promontories and locally grounded isles, both called ice rises. These ice rises are typically dome-shaped and surface elevations are hundreds of meters above the surrounding ice shelves, which cause strong orographic effects on surface mass balance (SMB). We conducted shallow ice-penetrating radar sounding to visualize firn stratigraphy in the top 35 m over ~400 km of profiles across the Nivlisen Ice Shelf, and in a grid pattern over two adjacent ice rises (Djupranen and Leningradkollen). We tracked six reflectors (isochrones) and dated them using two ice cores taken at the ice rise summits, from which SMB over six periods in the past three decades was retrieved. The overall SMB pattern across the ice shelf remained similar for all periods; however, the eastwest contrast in SMB varies by a factor of 1.5–2 between the Leningradkollen and Djupranen grounding lines. The SMB patterns over the ice rises are more varied owing to complex interactions between topography, snowfall and wind. We use our results to evaluate the regional climate model RACMO2.3p2 in terms of the spatial SMB distribution and temporal changes over the ice shelf and ice rises at regional scale.

Quantifying rainfall in Greenland: a combined observational and modelling approach

AbstractThis paper estimates rainfall totals at 17 Greenland meteorological stations, subjecting data from in-situ precipitation gauge measurements to seven different precipitation phase schemes to separate rain- and snowfall amounts. To correct the resulting snow/rain fractions for undercatch, we subsequently use a Dynamic Correction Model (DCM) for Automatic Weather Stations (AWS, Pluvio gauges) and a regression analysis correction method for staffed stations (Hellmann gauges). With observations ranging from 5% to 57% for cumulative totals, rainfall accounts for a considerable fraction of total annual precipitation over Greenland’s coastal regions, with the highest rain fraction in the south (Narsarsuaq). Monthly precipitation and rainfall totals are used to evaluate the regional climate model RACMO2.3. The model realistically captures monthly rainfall and total precipitation (R=0.3-0.9), with generally higher correlations for rainfall for which the undercatch correction factors (1.02-1.40) are smaller than those for snowfall (1.27-2.80), and hence the observations more robust. With a horizontal resolution of 5.5 km and simulation period from 1958-present, RACMO2.3 therefore is a useful tool to study spatial and temporal variability of rainfall in Greenland, although further statistical downscaling may be required to resolve the steep rainfall gradients.

Impact of updated radiative transfer scheme in snow and ice in RACMO2.3p3 on the surface mass and energy budget of the Greenland ice sheet

Abstract. Radiative transfer in snow and ice is often not modeled explicitly in regional climate models. In this study, we evaluate a new englacial radiative transfer scheme and assess the surface mass and energy budget for the Greenland ice sheet in the latest version of the regional climate model RACMO2, version 2.3p3. We also evaluate the modeled (sub)surface temperature and melt, as radiation penetration now enables internal heating. The results are compared to the previous model version and are evaluated against stake measurements and automatic weather station data of the K-transect and PROMICE projects. In addition, subsurface snow temperature profiles are compared at the K-transect, Summit, and southeast Greenland. The surface mass balance is in good agreement with observations, with a mean bias of −31 mm w.e. yr−1 (−2.67 %), and only changes considerably with respect to the previous RACMO2 version around the ice margins and near the percolation zone. Melt and refreezing, on the other hand, are changed more substantially in various regions due to the changed albedo representation, subsurface energy absorption, and meltwater percolation. Internal heating leads to higher snow temperatures in summer, in agreement with observations, and introduces a shallow layer of subsurface melt. Hence, this study shows the consequences and necessity of radiative transfer in snow and ice for regional climate modeling of the Greenland ice sheet.

Long-term surface energy balance of the western Greenland Ice Sheet and the role of large-scale circulation variability

Abstract. We present the surface energy balance (SEB) of the western Greenland Ice Sheet (GrIS) using an energy balance model forced with hourly observations from nine automatic weather stations (AWSs) along two transects: the Kangerlussuaq (K) transect with seven AWSs in the southwest and the Thule (T) transect with two AWSs in the northwest. Modeled and observed surface temperatures for non-melting conditions agree well with RMSEs of 1.1–1.6 K, while reasonable agreement is found between modeled and observed 10 d cumulative ice melt. Absorbed shortwave radiation (Snet) is the main energy source for melting (M), followed by the sensible heat flux (Qh). The multiyear average seasonal cycle of SEB components shows that Snet and M peak in July at all AWSs. The turbulent fluxes of sensible (Qh) and latent heat (Ql) decrease significantly with elevation, and the latter becomes negative at higher elevations, partly offsetting Qh. Average June, July and August (JJA) albedo values are <0.6 for stations below 1000 m a.s.l. and >0.7 for the higher stations. The near-surface climate variables and surface energy fluxes from reanalysis products ERA-Interim, ERA5 and the regional climate model RACMO2.3 were compared to the AWS values. The newer ERA5 product only significantly improves ERA-Interim for albedo. The regional model RACMO2.3, which has higher resolution (5.5 km) and a dedicated snow/ice module, unsurprisingly outperforms the reanalyses for (near-)surface climate variables, but the reanalyses are indispensable in detecting dependencies of west Greenland climate and melt on large-scale circulation variability. We correlate ERA5 with the AWS data to show a significant positive correlation of western GrIS summer surface temperature and melt with the Greenland Blocking Index (GBI) and weaker and opposite correlations with the North Atlantic Oscillation (NAO). This analysis may further help to explain melting patterns on the western GrIS from the perspective of circulation anomalies.

Impact of coastal East Antarctic ice rises on surface mass balance: insights from observations and modeling

Abstract. About 20 % of all snow accumulation in Antarctica occurs on the ice shelves. There, ice rises control the spatial surface mass balance (SMB) distribution by inducing snowfall variability and wind erosion due to their topography. Moreover these ice rises buttress the ice flow and represent ideal drilling locations for ice cores. In this study we assess the connection between snowfall variability and wind erosion to provide a better understanding of how ice rises impact SMB variability, how well this is captured in the regional atmospheric climate model RACMO2 and the implications of this SMB variability for ice rises as an ice core drilling site. By combining ground-penetrating radar (GPR) profiles from two ice rises in Dronning Maud Land with ice core dating, we reconstruct spatial and temporal SMB variations from 1983 to 2018 and compare the observed SMB with output from RACMO2 and SnowModel. Our results show snowfall-driven differences of up to 1.5 times higher SMB on the windward side of both ice rises than on the leeward side as well as a local erosion-driven minimum at the ice divide of the ice rises. RACMO2 captures the snowfall-driven differences but overestimates their magnitude, whereas the erosion on the peak can be reproduced by SnowModel with RACMO2 forcing. Observed temporal variability of the average SMBs, retrieved from the GPR data for four time intervals in the 1983–2018 range, are low at the peak of the easternmost ice rise (∼0.06 mw.e.yr-1), while they are higher (∼0.09 mw.e.yr-1) on the windward side of the ice rise. This implies that at the peak of the ice rise, higher snowfall, driven by orographic uplift, is balanced out by local erosion. As a consequence of this, the SMB recovered from the ice core matches the SMB from the GPR at the peak of the ice rise but not at the windward side of the ice rise, suggesting that the SMB signal is damped in the ice core.

The added value of high resolution in estimating the surface mass balance in southern Greenland

Abstract. The polar version of the regional climate model RACMO2, version 2.3p1, is used to study the effect of model resolution on the simulated climate and surface mass balance (SMB) of south Greenland for the current climate (2007–2014). The model data at resolutions of 60, 20, 6.6, and 2.2 km are intercompared and compared to SMB observations using three different data refinement methods: nearest neighbour, bilinear interpolation, and a statistical downscaling method utilising the local dependency of fields on elevation. Furthermore, it is estimated how the errors induced by model resolution compare to errors induced by the model physics and initialisation. The results affirm earlier studies that SMB components which are tightly linked to elevation, like runoff, can be refined successfully, as soon as the ablation zone is reasonably well resolved in the source dataset. Precipitation fields are also highly elevation dependent, but precipitation has no systematic correlation with elevation, which inhibits statistical downscaling to work well. If refined component-wise, 20 km resolution model simulations can reproduce the SMB ablation observations almost as well as the finer-resolution model simulations. Nonetheless, statistical downscaling and regional climate modelling are complementary; the best results are obtained when high-resolution RACMO2 data are statistically refined. Model estimates in the accumulation zone do not benefit from statistical downscaling; hence, a resolution of about 20 km is sufficient to resolve the majority of the accumulation zone of the Greenland Ice Sheet with respect to the limited measurements we have. Furthermore, we demonstrate that using RACMO2, a hydrostatic model, at 2.2 km resolution led to invalid results as topographic and synoptic vertical winds exceed 10 m s−1, which violates the hydrostatic model assumptions. Finally, additional tests show that model resolution is as important as properly resolving spatial albedo patterns, correctly initialising the firn column, and uncertainties in the modelled precipitation and turbulent exchange.

A benchmark dataset of in situ Antarctic surface melt rates and energy balance

AbstractSurface melt on the coastal Antarctic ice sheet (AIS) determines the viability of its ice shelves and the stability of the grounded ice sheet, but very few in situ melt rate estimates exist to date. Here we present a benchmark dataset of in situ surface melt rates and energy balance from nine sites in the eastern Antarctic Peninsula (AP) and coastal Dronning Maud Land (DML), East Antarctica, seven of which are located on AIS ice shelves. Meteorological time series from eight automatic and one staffed weather station (Neumayer), ranging in length from 15 months to almost 24 years, serve as input for an energy-balance model to obtain consistent surface melt rates and energy-balance results. We find that surface melt rates exhibit large temporal, spatial and process variability. Intermittent summer melt in coastal DML is primarily driven by absorption of shortwave radiation, while non-summer melt events in the eastern AP occur during föhn events that force a large downward directed turbulent flux of sensible heat. We use the in situ surface melt rate dataset to evaluate melt rates from the regional atmospheric climate model RACMO2 and validate a melt product from the QuikSCAT satellite.

Present‐Day Greenland Ice Sheet Climate and Surface Mass Balance in CESM2

The response of the Greenland Ice Sheet (GrIS) to a warmer climate is uncertain on long time scales. Climate models, such as those participating in the Coupled Model Intercomparison Project phase 6 (CMIP6), are used to assess this uncertainty. The Community Earth System Model version 2.1 (CESM2) is a CMIP6 model capable of running climate simulations with either one‐way coupling (fixed ice sheet geometry) or two‐way coupling (dynamic geometry) to the GrIS. The model features prognostic snow albedo, online downscaling using elevation classes, and a firn pack to refreeze percolating melt water. Here we evaluate the representation of the GrIS surface energy balance and surface mass balance in CESM2 at 1° resolution with fixed GrIS geometry. CESM2 agrees closely with ERA‐Interim reanalysis data for key controls on GrIS SMB: surface pressure, sea ice extent, 500 hPa geopotential height, wind speed, and 700 hPa air temperature. Cloudsat‐CALIPSO data show that supercooled liquid‐containing clouds are adequately represented, whereas comparisons to Moderate Resolution Imaging Spectroradiometer and CM SAF Cloud, Albedo, and Surface Radiation data set from Advanced Very High Resolution Radiometer data second edition data suggest that CESM2 underestimates surface albedo. The seasonal cycle and spatial patterns of surface energy balance and surface mass balance components in CESM2 agree well with regional climate model RACMO2.3p2, with GrIS‐integrated melt, refreezing, and runoff bracketed by RACMO2 counterparts at 11 and 1 km. Time series of melt, runoff, and SMB show a break point around 1990, similar to RACMO2. These results suggest that GrIS SMB is realistic in CESM2, which adds confidence to coupled ice sheet‐climate experiments that aim to assess the GrIS contribution to future sea level rise.

Surface mass balance downscaling through elevation classes in an Earth system model: application to the Greenland ice sheet

Abstract. The modeling of ice sheets in Earth system models (ESMs) is an active area of research with applications to future sea level rise projections and paleoclimate studies. A major challenge for surface mass balance (SMB) modeling with ESMs arises from their coarse resolution. This paper evaluates the elevation class (EC) method as an SMB downscaling alternative to the dynamical downscaling of regional climate models. To this end, we compare EC-simulated elevation-dependent surface energy and mass balance gradients from the Community Earth System Model 1.0 (CESM1.0) with those from the regional climate model RACMO2.3. The EC implementation in CESM1.0 combines prognostic snow albedo, a multilayer snow model, and elevation corrections for two atmospheric forcing variables: temperature and humidity. Despite making no corrections for incoming radiation and precipitation, we find that the EC method in CESM1.0 yields similar SMB gradients to RACMO2.3, in part due to compensating biases in snowfall, surface melt, and refreezing gradients. We discuss the sensitivity of the results to the lapse rate used for the temperature correction. We also evaluate the impact of the EC method on the climate simulated by the ESM and find minor cooling over the Greenland ice sheet and Barents and Greenland seas, which compensates for a warm bias in the ESM due to topographic smoothing. Based on our diagnostic procedure to evaluate the EC method, we make several recommendations for future implementations.

Six Decades of Glacial Mass Loss in the Canadian Arctic Archipelago

The Canadian Arctic Archipelago comprises multiple small glaciers and ice caps, mostly concentrated on Ellesmere and Baffin Islands in the northern (NCAA, Northern Canadian Arctic Archipelago) and southern parts (SCAA, Southern Canadian Arctic Archipelago) of the archipelago, respectively. Because these glaciers are small and show complex geometries, current regional climate models, using 5‐ to 20‐km horizontal resolution, do not properly resolve surface mass balance patterns. Here we present a 58‐year (1958–2015) reconstruction of daily surface mass balance of the Canadian Arctic Archipelago, statistically downscaled to 1 km from the output of the regional climate model RACMO2.3 at 11 km. By correcting for biases in elevation and ice albedo, the downscaling method significantly improves runoff estimates over narrow outlet glaciers and isolated ice fields. Since the last two decades, NCAA and SCAA glaciers have experienced warmer conditions (+1.1°C) resulting in continued mass loss of 28.2 ± 11.5 and 22.0 ± 4.5 Gt/year, respectively, more than doubling (11.9 Gt/year) and doubling (11.9 Gt/year) the pre‐1996 average. While the interior of NCAA ice caps can still buffer most of the additional melt, the lack of a perennial firn area over low‐lying SCAA glaciers has caused uninterrupted mass loss since the 1980s. In the absence of significant refreezing capacity, this indicates inevitable disappearance of these highly sensitive glaciers.

Estimation and reduction of random noise in mass anomaly time-series from satellite gravity data by minimization of month-to-month year-to-year double differences

We propose a technique to regularize a GRACE-based mass-anomaly time-series in order to (i) quantify the Standard Deviation (SD) of random noise in the data, and (ii) reduce the level of that noise. The proposed regularization functional minimizes the Month-to-month Year-to-year Double Differences (MYDD) of mass anomalies. As such, it does not introduce any bias in the linear trend and the annual component, two of the most common features in GRACE-based mass anomaly time-series. In the context of hydrological and ice sheet studies, the proposed regularization functional can be interpreted as an assumption about the stationarity of climatological conditions. The optimal regularization parameter and noise SD are obtained using Variance Component Estimation. To demonstrate the performance of the proposed technique, we apply it to both synthetic and real data. In the latter case, two geographic areas are considered: the Tonlé Sap basin in Cambodia and Greenland. We show that random noise in the data can be efficiently (1.5–2 times) mitigated in this way, whereas no noticeable bias is introduced. We also discuss various findings that can be made on the basis of the estimated noise SD. We show, among others, that knowledge of noise SD facilitates the analysis of differences between GRACE-based and alternative estimates of mass variations. Moreover, inaccuracies in the latter can also be quantified in this way. For instance, we find that noise in the surface mass anomalies in Greenland estimated using the Regional Climate Model RACMO2.3 is at the level of 2–6 cm equivalent water heights. Furthermore, we find that this noise shows a clear correlation with the amplitude of annual mass variations: it is lowest in the north-west of Greenland and largest in the south. We attribute this noise to limitations in the modelling of the meltwater accumulation and run-off.

Brief communication: Improved simulation of the present-day Greenland firn layer (1960–2016)

Abstract. By providing pore space for storage or refreezing of meltwater, the Greenland ice sheet firn layer strongly modulates runoff. Correctly representing the firn layer is therefore crucial for Greenland (surface) mass balance studies. Here, we present a simulation of the Greenland firn layer with the firn model IMAU-FDM forced by the latest output of the regional climate model RACMO2, version 2.3p2. In the percolation zone, much improved agreement is found with firn density and temperature observations. A full simulation of Greenland firn at high temporal (10 days) and spatial (11 km) resolution is available for the period 1960–2016.

A Multidecadal Analysis of Föhn Winds over Larsen C Ice Shelf from a Combination of Observations and Modeling

The southward progression of ice shelf collapse in the Antarctic Peninsula is partially attributed to a strengthening of the circumpolar westerlies and the associated increase in föhn conditions over its eastern ice shelves. We used observations from an automatic weather station at Cabinet Inlet on the northern Larsen C ice shelf between 25 November 2014 and 31 December 2016 to describe föhn dynamics. Observed föhn frequency was compared to the latest version of the regional climate model RACMO2.3p2, run over the Antarctic Peninsula at 5.5-km horizontal resolution. A föhn identification scheme based on observed wind conditions was employed to check for model biases in föhn representation. Seasonal variation in total föhn event duration was resolved with sufficient skill. The analysis was extended to the model period (1979–2016) to obtain a multidecadal perspective of föhn occurrence over Larsen C ice shelf. Föhn occurrence at Cabinet Inlet strongly correlates with near-surface air temperature, and both are found to relate strongly to the location and strength of the Amundsen Sea Low. Furthermore, we demonstrated that föhn occurrence over Larsen C ice shelf shows high variability in space and time.

Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 1: Greenland (1958–2016)

Abstract. We evaluate modelled Greenland ice sheet (GrIS) near-surface climate, surface energy balance (SEB) and surface mass balance (SMB) from the updated regional climate model RACMO2 (1958–2016). The new model version, referred to as RACMO2.3p2, incorporates updated glacier outlines, topography and ice albedo fields. Parameters in the cloud scheme governing the conversion of cloud condensate into precipitation have been tuned to correct inland snowfall underestimation: snow properties are modified to reduce drifting snow and melt production in the ice sheet percolation zone. The ice albedo prescribed in the updated model is lower at the ice sheet margins, increasing ice melt locally. RACMO2.3p2 shows good agreement compared to in situ meteorological data and point SEB/SMB measurements, and better resolves the spatial patterns and temporal variability of SMB compared with the previous model version, notably in the north-east, south-east and along the K-transect in south-western Greenland. This new model version provides updated, high-resolution gridded fields of the GrIS present-day climate and SMB, and will be used for projections of the GrIS climate and SMB in response to a future climate scenario in a forthcoming study.

Reconstructing Greenland Ice Sheet meltwater discharge through the Watson River (1949–2017)

ABSTRACT Ice-sheet melting is the primary water source for the proglacial Watson River in southern west Greenland. Discharge from the large, approximately 12,000 km2 ice-sheet catchment draining through the Watson River has been monitored since 2006. While this record is of respectable length for a Greenland monitoring effort, it is too short to resolve climate signals. Therefore, we use observed Tasersiaq lake discharge and Kangerlussuaq air temperature to reconstruct annual Watson River discharge back to 1949. The resulting sixty-five-year record shows that average ice-sheet runoff since 2003 has roughly increased by 46 percent relative to the 1949–2002 period. The time series suggests that the five top-ranking discharge years occurred since 2003. The three top-ranking discharge years (2010, 2012, and 2016) are characterized by melt seasons that were both long and intense. Interannual variability more than doubled since 2003, which we speculate to be because of hypsometric runoff amplification enhanced by albedo decrease and decreased firn permeability. The reconstructed time series proves to be a valuable tool for long-term evaluation of Greenland Ice Sheet surface mass balance models. A comparison with freshwater fluxes calculated by a downscaled version of the regional climate model RACMO2 reveals high correlation (r = 0.89), and also shows that the model possibly underestimates runoff by up to 26 percent in above-average melt years.