in Cryosphere (2019)
The Antarctic ice sheet mass balance is a major component of the sea level budget and results from the difference of two fluxes of a similar magnitude: ice flow discharging in the ocean and net snow accumulation on the ice sheet surface, i.e. the surface mass balance (SMB). Separately modelling ice dynamics and SMB is the only way to project future trends. In addition, mass balance studies frequently use regional climate models (RCMs) outputs as an alternative to observed fields because SMB observations are particularly scarce on the ice sheet. Here we evaluate new simulations of the polar RCM MAR forced by three reanalyses, ERA-Interim, JRA-55, and MERRA-2, for the period 1979–2015, and we compare MAR results to the last outputs of the RCM RACMO2 forced by ERA-Interim. We show that MAR and RACMO2 perform similarly well in simulating coast-to-plateau SMB gradients, and we find no significant differences in their simulated SMB when integrated over the ice sheet or its major basins. More importantly, we outline and quantify missing or underestimated processes in both RCMs. Along stake transects, we show that both models accumulate too much snow on crests, and not enough snow in valleys, as a result of drifting snow transport fluxes not included in MAR and probably underestimated in RACMO2 by a factor of 3. Our results tend to confirm that drifting snow transport and sublimation fluxes are much larger than previous model-based estimates and need to be better resolved and constrained in climate models. Sublimation of precipitating particles in low-level atmospheric layers is responsible for the significantly lower snowfall rates in MAR than in RACMO2 in katabatic channels at the ice sheet margins. Atmospheric sublimation in MAR represents 363 Gt yr−1 over the grounded ice sheet for the year 2015, which is 16 % of the simulated snowfall loaded at the ground. This estimate is consistent with a recent study based on precipitation radar observations and is more than twice as much as simulated in RACMO2 because of different time residence of precipitating particles in the atmosphere. The remaining spatial differences in snowfall between MAR and RACMO2 are attributed to differences in advection of precipitation with snowfall particles being likely advected too far inland in MAR.
in Atmosphere (2019), 10(1), 34
The aim of this study is to assess the sensitivity of convective precipitation modelled by the regional climate model MAR (Modèle Atmosphérique Régional) over 1987–2017 to four newly implemented convective schemes: the Bechtold scheme coming from the MESO-NH regional model and the Betts-Miller-Janjić, Kain-Fritsch and modified Tiedtke schemes coming from the WRF regional model. MAR version 3.9 is used here at a resolution of 10 km over a domain covering Belgium using the ERA-Interim reanalysis as forcing. The simulated precipitation is compared against SYNOP and E-OBS gridded precipitation data. Trends in total and convective precipitation over 1987–2017 are discussed. None of the MAR experiments compares better with observations than the others and they all show the same trends in (extreme) precipitation. Over the period 1987–2017, MAR suggests a significant increase in the mean annual precipitation amount over the North Sea but a significant decrease over High Belgium.
Due to their ability to produce climate projections, General circulation models (GCM) are often used to provide estimates of the surface mass balance (SMB) of the Antarctic ice sheet that can be used to constrain ice sheet models. However, GCM still benefit from a poor representation of polar climate specificities such as stable boundary layers, polar clouds or interactions between snow-covered surfaces and the atmosphere. In this study, we highlight the importance of downscaling GCM outputs from the Fifth Climate Model Intercomparison Project (CMIP5) with a regional climate model to provide accurate estimates of the Antarctic SMB. For that purpose, the regional climate model MAR is forced by 6-hourly outputs from ACCESS1.3 that is currently considered as one of the best GCM from CMIP5 over the Antarctic ice sheet. Estimates of the SMB computed by MAR and ACCESS1.3 are evaluated against SMB observations. Even if the temporal variability of the SMB is forced by the driving GCM, the comparison shows that MAR improves the spatial variability of the Antarctic SMB, emphasizing the added value of using a polar RCM for downscaling GCM outputs at high latitudes.
in Cryosphere (2018), 12
Estimates for the recent period and projections of the Antarctic surface mass balance (SMB) often rely on high-resolution polar-oriented regional climate models (RCMs). However, RCMs require large-scale boundary forcing fields prescribed by reanalyses or general circulation models (GCMs). Since the recent variability of sea surface conditions (SSCs, namely sea ice concentration, SIC, and sea surface temperature, SST) over the Southern Ocean is not reproduced by most GCMs from the 5th phase of the Coupled Model Intercomparison Project (CMIP5), RCMs are then subject to potential biases. We investigate here the direct sensitivity of the Antarctic SMB to SSC perturbations around the Antarctic. With the RCM “Modèle Atmosphérique Régional” (MAR), different sensitivity experiments are performed over 1979–2015 by modifying the ERA-Interim SSCs with (i) homogeneous perturbations and (ii) mean anomalies estimated from all CMIP5 models and two extreme ones, while atmospheric lateral boundary conditions remained unchanged. Results show increased (decreased) precipitation due to perturbations inducing warmer, i.e. higher SST and lower SIC (colder, i.e. lower SST and higher SIC), SSCs than ERA-Interim, significantly affecting the SMB of coastal areas, as precipitation is mainly related to cyclones that do not penetrate far into the continent. At the continental scale, significant SMB anomalies (i.e greater than the interannual variability) are found for the largest combined SST/SIC perturbations. This is notably due to moisture anomalies above the ocean, reaching sufficiently high atmospheric levels to influence accumulation rates further inland. Sensitivity experiments with warmer SSCs based on the CMIP5 biases reveal integrated SMB anomalies (+5 % to +13 %) over the present climate (1979–2015) in the lower range of the SMB increase projected for the end of the 21st century.
in Cryosphere (2018)
Since the 2000s, a change in the atmospheric circulation over the North Atlantic resulting in more frequent blocking events has favoured warmer and sunnier weather conditions over the Greenland Ice Sheet (GrIS) in summer, enhancing the melt increase. This circulation change is not represented by general circulation models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), which do not predict any circulation change for the next century over the North Atlantic. The goal of this study is to evaluate the impact of an atmospheric circulation change (as currently observed) on projections of the future GrIS surface mass balance (SMB). We compare GrIS SMB estimates simulated by the regional climate model MAR forced by perturbed reanalysis (ERA-Interim with a temperature correction of +1, +1.5, and +2°C at the MAR lateral boundaries) over 1980–2016 to projections of the future GrIS SMB from MAR simulations forced by three GCMs over selected periods for which a similar temperature increase of +1, +1.5, and +2°C is projected by the GCMs in comparison to 1980–1999. Mean SMB anomalies produced with perturbed reanalysis over the climatologically stable period 1980–1999 are similar to those produced with MAR forced by GCMs over future periods characterised by a similar warming over Greenland. However, over the 2 last decades (2000–2016) when an increase in the frequency of blocking events has been observed in summer, MAR forced by perturbed reanalysis suggests that the SMB decrease could be amplified by a factor of 2 if such atmospheric conditions persist compared to projections forced by GCMs for the same temperature increase but without any circulation change.
Conference (2018, June 22)
With the aim of evaluating the added value of a regional climate model in downscaled future projections over the Greenland Ice Sheet, we have compared the surface fields (snowfall and summer near-surface temperature) coming from the “best” CMIP5 and CMIP6 global models (GCMs) with these fields simulated by the MAR model forced by the same GCMs. These "best" GCMS were selected according to their ability to simulate the summer temperature at 700 hPa and the general circulation at 500 hPa over Greenland with respect to ERA-Interim over 1980-1999. However, despite their ability to correctly represent the free atmosphere, the selected GCMs present significant biases at the surface of the ice sheet. The comparison shows that MAR is however able to strongly reduce these GCM surface biases. We then forced the lateral boundaries of MAR with ERA-Interim to which we applied temperature corrections of +1°C and +2°C. The outputs were compared to MAR forced by GCM future projections corresponding to a climate about 1 and 2°C warmer than the current climate. The results of the different GCM-forced runs and sensitivity experiments are very similar to each other as the GCMs do not project general circulation changes. Moreover, the sensitivity experiments forced by modified ERA-Interim reveal that the projected SMB decrease is exponentially amplified if the increased occurrence of blocking events over Greenland in summer that has been observed since the 2000´s continues in the future.
Conference (2018, June 20)
The transport of snow by the wind is an important component of the Antarctic surface mass balance (SMB) as drifting snow counts up for a large amount of snow ablation over the ice sheet. However, this process is frequently neglected in atmospheric models. Two simulations (one with drifting snow and one without) were performed at a resolution of 8 km with the regional climate model MAR forced by ERA-Interim, in order to assess the impact of drifting snow on the SMB of Adelie Land (East Antarctica) during the period 2002 - 2016. We evaluated results against field observations (including meteorological and snow skate measurements). Besides to better represent climate surface as airborne snow particles can sublimate and interact with the lowest atmospheric levels, the drifting snow simulation improves the modelled spatial distribution of the SMB and reduces the overestimation of the accumulation in comparison with MAR results without drifting snow.
Conference (2018, April 11)
Regional Climate Models (RCM) driven by General Circulation Models (GCM) are often used to produce future projections of the surface climate and surface mass balance (SMB) of polar ice sheets. However, GCM do not represent the recent circulation change observed in summer over the Greenland Ice Sheet (GrIS) since the 2000’s and do not predict any circulation changes for the next century. The goal of this study is to evaluate the impact of an atmospheric circulation change (as currently observed) combined with a temperature increase on the future GrIS SMB. We compare here SMB results from the RCM MAR (Modèle atmosphérique régional) forced by warmer reanalyses (ERA-Interim with a temperature correction of +1, +1,5 and +2 C at the lateral boundaries) to SMB results from MAR future simulations forced with GCM during a period where there is a temperature increase of +1, +1,5 and +2 C compared to 1980-1999. Mean SMB produced with warmer reanalyses over 1980-1999 is similar to that obtained when forcing with GCM over a period characterized by a similarly warmer climate. During last years (2000-2016) when a circulation change has been observed in summer, MAR forced with warmer reanalyses shows a significant amplified SMB decrease compared to future simulations forced by GCM for the same temperature increase.
Conference (2017, December 15)
Poster (2017, December 15)
Regional climate models (RCMs) are suitable numerical tools to study the surface mass balance (SMB) of the wide polar ice sheets due to their high spatial resolution and polar-adapted physics. Nonetheless, RCMs are driven at their boundaries and over the ocean by reanalysis or global climate model (GCM) products and are thus influenced by potential biases in these large-scale fields. These biases can be significant for both the atmosphere and the sea surface conditions (i.e. sea ice concentration and sea surface temperature). With the RCM MAR, a set of sensitivity experiments has been realized to assess the direct response of the SMB of the Antarctic ice sheet to oceanic perturbations. MAR is forced by ERA-Interim and anomalies based on mean GCM biases are introduced in sea surface conditions. Results show significant increases (decreases) of liquid and solid precipitation due to biases related to warm (cold) oceans. As precipitation is mainly caused by low-pressure systems that intrude into the continent and do not penetrate far inland, coastal areas are more sensitive than inland regions. Furthermore, warm ocean representative biases lead to anomalies as large as anomalies simulated by other RCMs or GCMs for the end of the 21st century.
Conference (2017, December 10)
Conference (2017, November 17)
Interactions between atmosphere, ice sheet and ocean play a crucial role in the Antarctic climate. For example, sea-air exchanges in leads and polynyas can strengthen cyclonic activities by warming and water vapour loading of air masses while associated sea heat loss and brine rejection modify water density and contribute to the dense water formation. Due to the harsh weather conditions in Antarctica, climate and ocean models appear as suitable tools to complement the scarcity of observations and to study the Antarctic climate. Nonetheless, only few models are able to represent typical processes found at high latitudes such as katabatic winds, drifting snow for the atmosphere or sea ice formation, accretion and deformation for oceans. Furthermore, due to their high non-linearity, those processes are difficult to model as they occur at different spatial and temporal scales. Current models are often forced by outputs: atmospheric conditions are provided to ocean models and ocean models outputs are used as surface conditions in atmospheric models meaning air feedbacks on ocean (or inversely) are muted. One can think models should be coupled at each time steps to take into account instantaneous interactions. Nonetheless, this method involves (too) high computational costs. The main challenge of this coupling is to take into account air-ice-ocean interactions and the temporal scale of associated processes in order to define an appropriate coupling time step. We will present both ocean and ice-atmosphere processes relative to polar climates and the specificities of the two models as well as technical coupling aspects.
Scientific conference (2017, September 14)
Regional climate models (RCMs) are suitable numerical tools to study the surface mass balance (SMB) of the wide polar ice sheets due to their high spatial resolution and polaradapted physics. Nonetheless, RCMs are driven at their boundaries and over the ocean by reanalysis or global climate model (GCM) products and are thus influenced by potential biases in these largescale fields. These biases can be significant for both the atmosphere and the sea surface conditions (i.e. sea ice concentration and sea surface temperature). With the RCM MAR, a set of sensitivity experiments has been realized to assess the direct response of the SMB of the Antarctic ice sheet to oceanic perturbations. MAR is forced by ERAInterim and anomalies based on mean GCM biases are introduced in sea surface conditions. Results show significant increases (decreases) of liquid and solid precipitation due to biases related to warm (cold) oceans. As precipitation is mainly caused by lowpressure systems that intrude into the continent and do not penetrate far inland, coastal areas are more sensitive than inland regions. Furthermore, warm ocean representative biases lead to anomalies as large as anomalies simulated by other RCMs or GCMs for the end of the 21st century.
in Cryosphere (2017), 11
With the aim of studying the recent Greenland ice sheet (GrIS) surface mass balance (SMB) decrease relative to the last century, we have forced the regional climate MAR (Modèle Atmosphérique Régional; version 3.5.2) model with the ERA-Interim (ECMWF Interim Re-Analysis; 1979–2015), ERA-40 (1958–2001), NCEP–NCARv1 (National Centers for Environmental Prediction–National Center for Atmospheric Research Reanalysis version 1; 1948–2015), NCEP–NCARv2 (1979–2015), JRA-55 (Japanese 55-year Reanalysis; 1958–2014), 20CRv2(c) (Twentieth Century Reanalysis version 2; 1900–2014) and ERA-20C (1900–2010) reanalyses. While all these forcing products are reanalyses that are assumed to represent the same climate, they produce significant differences in the MAR-simulated SMB over their common period. A temperature adjustment of +1 °C (respectively −1 °C) was, for example, needed at the MAR boundaries with ERA-20C (20CRv2) reanalysis, given that ERA-20C (20CRv2) is ∼ 1 °C colder (warmer) than ERA-Interim over Greenland during the period 1980–2010. Comparisons with daily PROMICE (Programme for Monitoring of the Greenland Ice Sheet) near-surface observations support these adjustments. Comparisons with SMB measurements, ice cores and satellite-derived melt extent reveal the most accurate forcing datasets for the simulation of the GrIS SMB to be ERA-Interim and NCEP–NCARv1. However, some biases remain in MAR, suggesting that some improvements are still needed in its cloudiness and radiative schemes as well as in the representation of the bare ice albedo. Results from all MAR simulations indicate that (i) the period 1961–1990, commonly chosen as a stable reference period for Greenland SMB and ice dynamics, is actually a period of anomalously positive SMB (∼ +40 Gt yr−1) compared to 1900–2010; (ii) SMB has decreased significantly after this reference period due to increasing and unprecedented melt reaching the highest rates in the 120-year common period; (iii) before 1960, both ERA-20C and 20CRv2-forced MAR simulations suggest a significant precipitation increase over 1900–1950, but this increase could be the result of an artefact in the reanalyses that are not well-enough constrained by observations during this period and (iv) since the 1980s, snowfall is quite stable after having reached a maximum in the 1970s. These MAR-based SMB and accumulation reconstructions are, however, quite similar to those from Box (2013) after 1930 and confirm that SMB was quite stable from the 1940s to the 1990s. Finally, only the ERA-20C-forced simulation suggests that SMB during the 1920–1930 warm period over Greenland was comparable to the SMB of the 2000s, due to both higher melt and lower precipitation than normal.
Scientific conference (2016, November 09)
Durant les vingt dernières années, l’inlandsis du Groenland a progressivement diminué en taille suite à une augmentation du ruissellement de l’eau de fonte en été sans compensation par une augmentation des précipitations. De plus, le taux de perte de la glace s’est aussi accéléré, ce qui a comme conséquence une élévation plus rapide du niveau général des mers et davantage d’eau douce rejetée dans l’océan. Les principales incertitudes lorsqu’on estime le bilan de mase en surface (BMS) de l’inlandsis du Groenland proviennent des marges où plusieurs processus particuliers ont lieu. Par exemple, la rétroaction de l’albédo de la neige et le regel de l’eau fondue en surface peut renforcer ou au contraire diminuer la fonte. De plus, les fortes pentes en bordure d’inlandsis sont responsables de la distribution spatiale des précipitations qui correspondent à l’accumulation de masse de l’inlandsis. En modélisation, cela signifie qu’il est nécessaire d’utiliser des modèles avec une (très) haute résolution pour résoudre ces caractéristiques, ce qui est très couteux en temps de calcul. C’est pourquoi cette étude présente l’évaluation d’une nouvelle méthode de régionalisation couplée dans le modèle MAR qui permet d’utiliser une grille à haute résolution dans le module de surface (SISVAT) couplé au module atmosphérique de MAR utilisant une résolution deux fois plus basse. La méthode corrige l’humidité spécifique et la température de proche-surface de MAR à l’aide d’un gradient d’altitude avant de forcer le module de surface. Des simulations ont été lancées avec deux résolutions différentes et sont forcées avec les réanalyses ERA-Interim sur la période allant de 1979 à 2014. La régionalisation couplée est évaluée par rapport à la base de données PROMICE et montrent de meilleurs résultats avec les observations de BMS sur l’inlandsis par rapport aux résultats de MAR dans sa version standard. La comparaison de la régionalisation couplée à une régionalisation a posteriori a révélé peu de différence significative sauf près de la ligne d’équilibre. Seule la méthode couplée permet de faire regeler entièrement l’eau fondue et la pluie en surface tandis que ce processus n’est qu’implicitement pris en compte dans la méthode a posteriori. Comparé à MAR dans sa version standard à résolution équivalente, les résultats régionalisés de façon couplée montrent une surestimation de l’accumulation au centre de l’inlandsis et une surestimation de l’ablation aux marges dus aux biais que la méthode implique sur les précipitations renforçant la rétroaction de l’albédo de la neige. En outre, les gradients de température sont légèrement trop importants entraînant plus de fonte. En conclusion, la méthode de régionalisation couplée doit encore être améliorée en intégrant une correction des précipitations. Pour ce qui est du couplage entre modèle de dynamique glaciaire à très haute résolution et modèle climatique à haute résolution, la méthode a posteriori reste suffisante.
Poster (2016, April 20)
This study presents surface mass balance (SMB) results at 10 km resolution with the regional climate MAR model over the Greenland ice sheet. Here, we use the last MAR version (v3.6) where the land-ice module (SISVAT) using a high resolution grid (10km) for surface variables is fully coupled while the MAR atmospheric module running at a lower resolution of 20km. This online downscaling technique enables to correct near-surface temperature and humidity from MAR by a gradient based on elevation before forcing SISVAT. The 20 km precipitations are not corrected. Corrections are stronger over the ablation zone where topography presents more variations. The model has been force by ERA-Interim between 1979 and 2014. We will show the advantages of using an online SMB downscaling technique in respect to an offline downscaling extrapolation based on local SMB vertical gradients. Results at 10 km show a better agreement with the PROMICE surface mass balance data base than the extrapolated 20 km MAR SMB results.