Contribution du bilan de masse de surface antarctique à l’évolution du niveau des mers avec le modèle atmosphérique régional MAR

peer reviewe

Evolution of Antarctic Surface Mass Balance by high-resolution downscaling of LMDZ4 AGCM and contribution to sea-level change

Most of the IPCC-AR4 Atmospheric Global Circulation Models (AGCM) predict an increase of the Antarctic Surface Mass Balance (SMB) during the 21st century that would mitigate global sea level rise. Present accumulation and predicted change are largest at the ice sheet margins because they are driven by snowfall, which mostly comes from warm, moist air arising over the land slopes. The coastal belt is also where complex processes of sublimation, melt and redistribution by the wind occur. Thus, high-resolution modelling (5 to 15 km) is necessary to adequately capture the effects of small-scale variations in topography on the atmospheric variables in this area, but limitations in computing resources prevent such resolution at the scale of Antarctica in full climate models. We present here a downscaling method leading to 15-km SMB resolution for century time-scales over Antarctica. We compute precipitation fields by considering orographic processes induced by the broad-scale and the fine-scale topography, and we estimate sublimation, melting and refreezing with a surface scheme validated for snow and ice-covered land surface. We display the SMB downscaled from LMDZ4 AGCM outputs (~60-km resolution), and compare the agreement of the broad-scale SMB and the downscaled SMB with 20th century observations. Then, we present hi-resolution features of the Antarctic SMB evolution during the 21st century downscaled from LMDZ4 and discuss the effect of the resolution on the Antarctic SMB contribution to sea level change. The downscaling model is a powerful tool that will be applied to others climate models for a better assessment of future sea level rise

Understanding mercury oxidation and air–snow exchange on the East Antarctic Plateau: a modeling study

Distinct diurnal and seasonal variations of mercury (Hg) have been observed in near-surface air at Concordia Station on the East Antarctic Plateau, but the processes controlling these characteristics are not well understood. Here, we use a box model to interpret the Hg0 (gaseous elemental mercury) measurements in thes year 2013. The model includes atmospheric Hg0 oxidation (by OH, O3, or bromine), surface snow HgII (oxidized mercury) reduction, and air-snow exchange, and is driven by meteorological fields from a regional climate model. The simulations suggest that a photochemically driven mercury diurnal cycle occurs at the air-snow interface in austral summer. The fast oxidation of Hg0 in summer may be provided by a two-step bromine-initiated scheme, which is favored by low temperature and high nitrogen oxides at Concordia. The summertime diurnal variations of Hg0 (peaking during daytime) may be confined within several tens of meters above the snow surface and affected by changing mixed layer depths. Snow re-emission of Hg0 is mainly driven by photoreduction of snow HgII in summer. Intermittent warming events and a hypothesized reduction of HgII occurring in snow in the dark may be important processes controlling the mercury variations in the non-summer period, although their relative importance is uncertain. The Br-initiated oxidation of Hg0 is expected to be slower at Summit Station in Greenland than at Concordia (due to their difference in temperature and levels of nitrogen oxides and ozone), which may contribute to the observed differences in the summertime diurnal variations of Hg0 between these two polar inland stations.National Science Foundation (U.S.) (Grant ACP-1053648

Evaluation of a high-resolution regional climate simulation over Greenland

A simulation of the 1991 summer has been performed over south Greenland with a coupled atmosphere–snow regional climate model (RCM) forced by the ECMWF re-analysis. The simulation is evaluated with in-situ coastal and ice-sheet atmospheric and glaciological observations. Modelled air temperature, specific humidity, wind speed and radiative fluxes are in good agreement with the available observations, although uncertainties in the radiative transfer scheme need further investigation to improve the model’s performance. In the sub-surface snow-ice model, surface albedo is calculated from the simulated snow grain shape and size, snow depth, meltwater accumulation, cloudiness and ice albedo. The use of snow metamorphism processes allows a realistic modelling of the temporal variations in the surface albedo during both melting periods and accumulation events. Concerning the surface albedo, the main finding is that an accurate albedo simulation during the melting season strongly depends on a proper initialization of the surface conditions which mainly result from winter accumulation processes. Furthermore, in a sensitivity experiment with a constant 0.8 albedo over the whole ice sheet, the average amount of melt decreased by more than 60%, which highlights the importance of a correctly simulated surface albedo. The use of this coupled atmosphere–snow RCM offers new perspectives in the study of the Greenland surface mass balance due to the represented feedback between the surface climate and the surface albedo, which is the most sensitive parameter in energy-balance-based ablation calculations.Peer reviewe

Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model

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

Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979-2015) and identification of dominant processes

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&ndash;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&thinsp; Gt &thinsp; yr&minus;1 over the grounded ice sheet for the year 2015, which is 16&thinsp;% 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.</p

Mass balance of the Greenland and Antarctic ice sheets from 1992 to 2020

Ice losses from the Greenland and Antarctic ice sheets have accelerated since the 1990s, accounting for a significant increase in the global mean sea level. Here, we present a new 29-year record of ice sheet mass balance from 1992 to 2020 from the Ice Sheet Mass Balance Inter-comparison Exercise (IMBIE). We compare and combine 50 independent estimates of ice sheet mass balance derived from satellite observations of temporal changes in ice sheet flow, in ice sheet volume, and in Earth's gravity field. Between 1992 and 2020, the ice sheets contributed 21.0±1.9g€¯mm to global mean sea level, with the rate of mass loss rising from 105g€¯Gtg€¯yr-1 between 1992 and 1996 to 372g€¯Gtg€¯yr-1 between 2016 and 2020. In Greenland, the rate of mass loss is 169±9g€¯Gtg€¯yr-1 between 1992 and 2020, but there are large inter-annual variations in mass balance, with mass loss ranging from 86g€¯Gtg€¯yr-1 in 2017 to 444g€¯Gtg€¯yr-1 in 2019 due to large variability in surface mass balance. In Antarctica, ice losses continue to be dominated by mass loss from West Antarctica (82±9g€¯Gtg€¯yr-1) and, to a lesser extent, from the Antarctic Peninsula (13±5g€¯Gtg€¯yr-1). East Antarctica remains close to a state of balance, with a small gain of 3±15g€¯Gtg€¯yr-1, but is the most uncertain component of Antarctica's mass balance. The dataset is publicly available at 10.5285/77B64C55-7166-4A06-9DEF-2E400398E452 (IMBIE Team, 2021)