Modele Atmospherique Regional Research Articles

Impact of climate change on persistent cold-air pools in an alpine valley during the 21st century

Abstract. When anticyclonic conditions persist over mountainous regions in winter, cold-air pools (i.e. thermal inversions) develop in valleys and persist from a few days to a few weeks. During these persistent cold-air pool (PCAP) episodes the atmosphere inside the valley is stable and vertical mixing is prevented, promoting the accumulation of pollutants close to the valley bottom and worsening air quality. The purpose of this paper is to address the impact of climate change on PCAPs until the end of this century for the alpine Grenoble valleys. The long-term projections produced with the general circulation model MPI (from the Max Planck Institute) downscaled over the Alps with the regional climate model MAR (Modèle Atmosphérique Régional) are used to perform a statistical study of PCAPs over the period 1981–2100. The trends of the main characteristics of PCAPs, namely their intensity, duration, and frequency, are investigated for two future scenarios, SSP2–4.5 and SSP5–8.5. We find that the intensity of PCAPs displays a statistically significant decreasing trend for the SSP5–8.5 scenario only. This decay is explained by the fact that air temperature over the century increases more at 2 m above the valley bottom than in the free air at mid-altitudes in the valley; this might be due to the increase of specific humidity near the ground. The vertical structure of two PCAPs, one in the past and one around 2050, is next investigated in detail. For this purpose, the WRF (Weather Research and Forecasting) model, forced by MAR for the worst-case scenario (SSP5–8.5), is used at a high resolution (111 m). The PCAP episodes are carefully selected from the MAR data so that a meaningful comparison can be performed. The future episode is warmer at all altitudes than the past episode (by at least 4 ∘C) and displays a similar inversion height, which are very likely generic features of future PCAPs. The selected episodes also have similar along-valley wind but different stability, with the future episode being more stable than the past episode. Overall, this study shows that the atmosphere in the Grenoble valleys during PCAP episodes tends to be slightly less stable in the future under the SSP5–8.5 scenario, and statistically unchanged under the SSP2–4.5 scenario, but that very stable PCAPs can still form.

Coupling MAR (Modèle Atmosphérique Régional) with PISM (Parallel Ice Sheet Model) mitigates the positive melt–elevation feedback

Abstract. The Greenland Ice Sheet is a key contributor to sea level rise. By melting, the ice sheet thins, inducing higher surface melt due to lower surface elevations, accelerating the melt coming from global warming. This process is called the melt–elevation feedback and can be considered by using two types of models: either (1) atmospheric models, which can represent the surface mass balance (SMB), or SMB estimates resulting from simpler models such as positive degree day models or (2) ice sheet models representing the surface elevation evolution. The latter ones do not represent the surface mass balance explicitly as well as polar-oriented climate models. A new coupling between the MAR (Modèle Atmosphérique Régional) regional climate model and the PISM (Parallel Ice Sheet Model) ice sheet model is presented here following the CESM2 (Community Earth System Model; SSP5-8.5, Shared Socioeconomic Pathway) scenario until 2100 at the MAR lateral boundaries. The coupling is extended to 2200 with a stabilised climate (+7 ∘C compared to 1961–1990) by randomly sampling the last 10 years of CESM2 to force MAR and reaches a sea level rise contribution of 64 cm. The fully coupled simulation is compared to a one-way experiment where surface topography remains fixed in MAR. However, the surface mass balance is corrected for the melt–elevation feedback when interpolated on the PISM grid by using surface mass balance vertical gradients as a function of local elevation variations (offline correction). This method is often used to represent the melt–elevation feedback and prevents a coupling which is too expensive in computation time. In the fully coupled MAR simulation, the ice sheet morphology evolution (changing slope and reducing the orographic barrier) induces changes in local atmospheric patterns. More specifically, wind regimes are modified, as well as temperature lapse rates, influencing the melt rate through modification of sensible heat fluxes at the ice sheet margins. We highlight mitigation of the melt lapse rate on the margins by modifying the surface morphology. The lapse rates considered by the offline correction are no longer valid at the ice sheet margins. If used (one-way simulation), this correction implies an overestimation of the sea level rise contribution of 2.5 %. The mitigation of the melt lapse rate on the margins can only be corrected by using a full coupling between an ice sheet model and an atmospheric model.

Cloud- and ice-albedo feedbacks drive greater Greenland Ice Sheet sensitivity to warming in CMIP6 than in CMIP5

Abstract. The Greenland Ice Sheet (GrIS) has been losing mass since the 1990s as a direct consequence of rising temperatures and has been projected to continue to lose mass at an accelerating pace throughout the 21st century, making it one of the largest contributors to future sea-level rise. The latest Coupled Model Intercomparison Project Phase 6 (CMIP6) models produce a greater Arctic amplification signal and therefore also a notably larger mass loss from the GrIS when compared to the older CMIP5 projections, despite similar forcing levels from greenhouse gas emissions. However, it is also argued that the strength of regional factors, such as melt–albedo feedbacks and cloud-related feedbacks, will partly impact future melt and sea-level rise contribution, yet little is known about the role of these regional factors in producing differences in GrIS surface melt projections between CMIP6 and CMIP5. In this study, we use high-resolution (15 km) regional climate model simulations over the GrIS performed using the Modèle Atmosphérique Régional (MAR) to physically downscale six CMIP5 Representative Concentration Pathway (RCP) 8.5 and five CMIP6 Shared Socioeconomic Pathway (SSP) 5-8.5 extreme high-emission-scenario simulations. Here, we show a greater annual mass loss from the GrIS at the end of the 21st century but also for a given temperature increase over the GrIS, when comparing CMIP6 to CMIP5. We find a greater sensitivity of Greenland surface mass loss in CMIP6 centred around summer and autumn, yet the difference in mass loss is the largest during autumn with a reduction of 27.7 ± 9.5 Gt per season for a regional warming of +6.7 ∘C and 24.6 Gt per season more mass loss than in CMIP5 RCP8.5 simulations for the same warming. Assessment of the surface energy budget and cloud-related feedbacks suggests a reduction in high clouds during summer and autumn – despite enhanced cloud optical depth during autumn – to be the main driver of the additional energy reaching the surface, subsequently leading to enhanced surface melt and mass loss in CMIP6 compared to CMIP5. Our analysis highlights that Greenland is losing more mass in CMIP6 due to two factors: (1) a (known) greater sensitivity to greenhouse gas emissions and therefore warmer temperatures and (2) previously unnotified cloud-related surface energy budget changes that enhance the GrIS sensitivity to warming.

What recent global atmospheric reanalyses and regional climate models can represent observed snow accumulation on Antarctica?

Recent compiled surface mass balance observations on the Antarctic ice sheet are used to examine the performance of four global reanalysis products and two regional climate models (RCMs), i.e., the European Center for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERAI), the fifth generation ECMWF reanalysis (ERA5), the Climate Forecast System Reanalysis (CFSR), Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA2), Modèle Atmosphérique Régional (MAR), and the Regional Atmospheric Climate Model (RACMO). All these models perform similarly well in reproducing spatial patterns of snow accumulation from the coast to inland plateau. But they differ in their magnitude with respective to in-situ observations with either evident overestimation (MAR) or underestimation (ERAI and CFSR) in the interior of the Antarctica. By comparison, MERRA2 and ERA5 at each elevation bin of 200 m match best with observations. Among the models, ERAI shows the smallest amount of snow accumulation averaged over the entire ice sheet. All models present some skills for reproducing the inter-annual variability in observed snow accumulation. By comparison, ERA5 probably provides the most realistic representation of variability in Antarctic snow accumulation since 1979.

A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR

Abstract. The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise, and this contribution is projected to accelerate over the next decades. A crucial tool for studying the evolution of surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs), which can provide current estimates and future projections of sea level rise associated with such losses. However, one of the main limitations of RCMs is the relatively coarse horizontal spatial resolution at which outputs are currently generated. Here, we report results concerning the statistical downscaling of the SMB modeled by the Modèle Atmosphérique Régional (MAR) RCM from the original spatial resolution of 6 km to 100 m building on the relationship between elevation and mass losses in Greenland. To this goal, we developed a geospatial framework that allows the parallelization of the downscaling process, a crucial aspect to increase the computational efficiency of the algorithm. Using the results obtained in the case of the SMB, surface and air temperature are assessed through the comparison of the modeled outputs with in situ and satellite measurement. The downscaled products show a considerable improvement in the case of the downscaled product with respect to the original coarse output, with the coefficient of determination (R2) increasing from 0.868 for the original MAR output to 0.935 for the SMB downscaled product. Moreover, the value of the slope and intercept of the linear regression fitting modeled and measured SMB values shifts from 0.865 for the original MAR to 1.015 for the downscaled product in the case of the slope and from the value −235 mm w.e. yr−1 (original) to −57 mm w.e. yr−1 (downscaled) in the case of the intercept, considerably improving upon results previously published in the literature.

Spatially heterogeneous effect of climate warming on the Arctic land ice

Abstract. Global warming has already substantially altered the Arctic cryosphere. Due to the Arctic warming amplification, the temperature is increasing more strongly, leading to pervasive changes in this area. Recent years were notably marked by melt records over the Greenland Ice Sheet, while other regions such as Svalbard seem to remain less influenced. This raises the question of the current state of the Greenland Ice Sheet and the various ice caps in the Arctic for which few studies are available. Here, we run the regional climate model (RCM) Modèle Atmosphérique Régional (MAR) at a resolution of 6 km over four different domains covering all Arctic land ice to produce a unified surface mass balance product from 1950 to the present day. We also compare our results to large-scale indices to better understand the heterogeneity of the evolutions across the Arctic and their links to recent climate change. We find a sharp decrease of surface mass balance (SMB) over the western Arctic (Canada and Greenland) in relationship with the atmospheric blocking situations that have become more frequent in summer, resulting in a 41 % increase of the melt rate since 1950. This increase is not seen over the Russian Arctic permanent ice areas, where melt rates have increased by only 3 % on average, illustrating a heterogeneity in the Arctic SMB response to global warming.

Snow stratigraphy observations from Operation IceBridge surveys in Alaska using S and C band airborne ultra-wideband FMCW (frequency-modulated continuous wave) radar

Abstract. During the concluding phase of the NASA Operation IceBridge (OIB), we successfully completed two airborne measurement campaigns (in 2018 and 2021, respectively) using a compact S and C band radar installed on a Single Otter aircraft and collected data over Alaskan mountains, ice fields, and glaciers. This paper reports seasonal snow depths derived from radar data. We found large variations in seasonal radar-inferred depths with multi-modal distributions assuming a constant relative permittivity for snow equal to 1.89. About 34 % of the snow depths observed in 2018 were between 3.2 and 4.2 m, and close to 30 % of the snow depths observed in 2021 were between 2.5 and 3.5 m. We observed snow strata in ice facies, combined percolation and wet-snow facies, and dry-snow facies from radar data and identified the transition areas from wet-snow facies to ice facies for multiple glaciers based on the snow strata and radar backscattering characteristics. Our analysis focuses on the measured strata of multiple years at the caldera of Mount Wrangell (K'elt'aeni) to estimate the local snow accumulation rate. We developed a method for using our radar readings of multi-year strata to constrain the uncertain parameters of interpretation models with the assumption that most of the snow layers detected by the radar at the caldera are annual accumulation layers. At a 2004 ice core and 2005 temperature sensor tower site, the locally estimated average snow accumulation rate is ∼2.89 m w.e. a−1 between the years 2003 and 2021. Our estimate of the snow accumulation rate between 2005 and 2006 is 2.82 m w.e. a−1, which matches closely to the 2.75 m w.e. a−1 inferred from independent ground-truth measurements made the same year. The snow accumulation rate between the years 2003 and 2021 also showed a linear increasing trend of 0.011 m w.e. a−2. This trend is corroborated by comparisons with the surface mass balance (SMB) derived for the same period from the regional atmospheric climate model MAR (Modèle Atmosphérique Régional). According to MAR data, which show an increase of 0.86 ∘C in this area for the period of 2003–2021, the linear upward trend is associated with the increase in snowfall and rainfall events, which may be attributed to elevated global temperatures. The findings of this study confirmed the viability of our methodology, as well as its underlying assumptions and interpretation models.

Variability in Antarctic surface climatology across regional climate models and reanalysis datasets

Abstract. Regional climate models (RCMs) and reanalysis datasets provide valuable information for assessing the vulnerability of ice shelves to collapse over Antarctica, which is important for future global sea level rise estimates. Within this context, this paper examines variability in snowfall, near-surface air temperature and melt across products from the Met Office Unified Model (MetUM), Regional Atmospheric Climate Model (RACMO) and Modèle Atmosphérique Régional (MAR) RCMs, as well as the ERA-Interim and ERA5 reanalysis datasets. Seasonal and trend decomposition using LOESS (STL) is applied to split the monthly time series at each model grid cell into trend, seasonal and residual components. Significant systematic differences between outputs are shown for all variables in the mean and in the seasonal and residual standard deviations, occurring at both large and fine spatial scales across Antarctica. Results imply that differences in the atmospheric dynamics, parametrisation, tuning and surface schemes between models together contribute more significantly to large-scale variability than differences in the driving data, resolution, domain specification, ice sheet mask, digital elevation model and boundary conditions. Despite significant systematic differences, high temporal correlations are found for snowfall and near-surface air temperature across all products at fine spatial scales. For melt, only moderate correlation exists at fine spatial scales between different RCMs and low correlation between RCM and reanalysis outputs. Root mean square deviations (RMSDs) between all outputs in the monthly time series for each variable are shown to be significant at fine spatial scales relative to the magnitude of annual deviations. Correcting for systematic differences results in significant reductions in RMSDs, suggesting the importance of observations and further development of bias-correction techniques.

Assessment of future wind speed and wind power changes over South Greenland using the Modèle Atmosphérique Régional regional climate model

AbstractWind is an infinitely renewable energy source that is not evenly distributed in space and time. The interconnection of energy‐demanding and energy‐resourceful (yet remote) regions would help prevent energy scarcity in a world where fossil fuels are no longer used. Previous studies have shown that South Greenland and West Europe have complementary wind regimes. In particular, the southern tip of Greenland, Cape Farewell, has gained growing interest for wind farm development as it is one of the windiest places on Earth. In order to gain new insights about future wind speed variations over South Greenland, the Modèle Atmosphérique Régional (MAR), validated against in situ observations over the tundra where wind turbines are most likely to be installed, is used to build climate projections under the emission scenario SSP5‐8.5 by downscaling an ensemble of CMIP6 Earth System Models (ESMs). It appeared that between 1981 and 2100, the wind speed is projected to decrease by ~−0.8 m·s−1 at 100 m a.g.l. over the tundra surrounding Cape Farewell. This decrease is particularly marked in winter while in summer, a wind speed acceleration is projected along the ice sheet margins. An analysis of two‐dimensional wind speed changes at different vertical levels indicates that the winter decrease is likely due to a large‐scale circulation change while in summer, the katabatic winds flowing down the ice sheet are expected to increase due to an enhanced temperature contrast between the ice sheet and the surroundings. As for the mean annual maximum wind power a turbine can yield, a decrease of ~−178.1 W is projected at 100 m a.g.l. Again, the decrease is especially pronounced in winter. Considering the very high winter wind speeds occurring in South Greenland which can cut off wind turbines if too intense, the projected wind speed decrease might be beneficial for the establishment of wind farms near Cape Farewell.

Clouds drive differences in future surface melt over the Antarctic ice shelves

Abstract. Recent warm atmospheric conditions have damaged the ice shelves of the Antarctic Peninsula through surface melt and hydrofracturing and could potentially initiate future collapse of other Antarctic ice shelves. However, model projections with similar greenhouse gas scenarios suggest large differences in cumulative 21st-century surface melting. So far it remains unclear whether these differences are due to variations in warming rates in individual models or whether local feedback mechanisms of the surface energy budget could also play a notable role. Here we use the polar-oriented regional climate model MAR (Modèle Atmosphérique Régional) to study the physical mechanisms that would control future surface melt over the Antarctic ice shelves in high-emission scenarios RCP8.5 and SSP5-8.5. We show that clouds enhance future surface melt by increasing the atmospheric emissivity and longwave radiation towards the surface. Furthermore, we highlight that differences in meltwater production for the same climate warming rate depend on cloud properties and particularly cloud phase. Clouds containing a larger amount of supercooled liquid water lead to stronger melt, subsequently favouring the absorption of solar radiation due to the snowmelt–albedo feedback. As liquid-containing clouds are projected to increase the melt spread associated with a given warming rate, they could be a major source of uncertainties in projections of the future Antarctic contribution to sea level rise.

Processes and Mechanisms of Persistent Extreme Rainfall Events in the Antarctic Peninsula during Austral Summer

Abstract Using ERA-Interim and output of the regional climate model MAR (Modèle Atmosphérique Régional) forced by ERA-Interim, this study investigates the mechanisms governing the persistent extreme rainfall events (PEREs) in the Antarctic Peninsula (AP) during austral summer (December–February) for the period 1980–2017. Due to the topography’s blocking effect on the warm and humid airflow, the increase in the rainfall is concentrated over the western AP during the periods of the PEREs. Contributed mainly by the low-frequency variations, the positive rainfall anomalies on the western AP can persist for multiple days, leading to the persistence of the extreme rainfall events. The additional rainfall anomalies can be attributed to the increase in the total precipitation. Through regulating the total precipitation, the low-frequency atmospheric circulation anomalies are vital to the formation of the PEREs. Specifically, a persistent circulation pattern with an anomalous cyclone (anticyclone) to the east (west) of the AP is conductive to the enhancement of poleward moisture fluxes. As a result, the total precipitation around the AP is strengthened, as well as the rainfall. Further investigation reveals that the barotropic feedback of the high-frequency eddies plays an important role in maintaining the low-frequency circulation anomalies.

Comparison between surface melt estimation from Sentinel-1 synthetic aperture radar and a regional climate model. Case study over the Roi Baudouin ice shelf, East Antarctica

Antarctica is the largest potential contributor to sea-level rise and needs to be monitored. It is also one of the first victims of global warming. However, it is often difficult to obtain high-resolution data on this vast and distant continent. Thanks to the Copernicus space program providing free and open access to high-quality data, this paper aims to show the complementarity between Sentinel-1 images and Modèle Atmosphérique régional (MAR) data over Antarctica. This study is conducted over Roi Baudouin Ice Shelf. The complementarity between the two datasets is established by a quantitative, temporal, and spatial comparison of the amplitude information of the radar signal and several variables modelled by MAR. Comparisons show strong spatial correlations between MAR variables representing melt and the backscatter coefficient recorded by the satellite. While temporal and quantitative analyses also give impressive results, further investigations are required to explain contrasting behaviors in other different areas of the ice shelf.

Surface melting over the Greenland ice sheet derived from enhanced resolution passive microwave brightness temperatures (1979–2019)

Abstract. Surface melting is a major component of the Greenland ice sheet surface mass balance, and it affects sea level rise through direct runoff and the modulation of ice dynamics and hydrological processes, supraglacially, englacially and subglacially. Passive microwave (PMW) brightness temperature observations are of paramount importance in studying the spatial and temporal evolution of surface melting due to their long temporal coverage (1979–present) and high temporal resolution (daily). However, a major limitation of PMW datasets has been the relatively coarse spatial resolution, which has historically been of the order of tens of kilometers. Here, we use a newly released PMW dataset (37 GHz, horizontal polarization) made available through a NASA “Making Earth System Data Records for Use in Research Environments” (MeASUREs) program to study the spatiotemporal evolution of surface melting over the Greenland ice sheet at an enhanced spatial resolution of 3.125 km. We assess the outputs of different detection algorithms using data collected by automatic weather stations (AWSs) and the outputs of the Modèle Atmosphérique Régional (MAR) regional climate model. We found that sporadic melting is well captured using a dynamic algorithm based on the outputs of the Microwave Emission Model of Layered Snowpack (MEMLS), whereas a fixed threshold of 245 K is capable of detecting persistent melt. Our results indicate that, during the reference period from 1979 to 2019 (from 1988 to 2019), surface melting over the ice sheet increased in terms of both duration, up to 4.5 (2.9) d per decade, and extension, up to 6.9 % (3.6 %) of the entire ice sheet surface extent per decade, according to the MEMLS algorithm. Furthermore, the melting season started up to 4.0 (2.5) d earlier and ended 7.0 (3.9) d later per decade. We also explored the information content of the enhanced-resolution dataset with respect to the one at 25 km and MAR outputs using a semi-variogram approach. We found that the enhanced product is more sensitive to local-scale processes, thereby confirming the potential of this new enhanced product for monitoring surface melting over Greenland at a higher spatial resolution than the historical products and for monitoring its impact on sea level rise. This offers the opportunity to improve our understanding of the processes driving melting, to validate modeled melt extent at high resolution and, potentially, to assimilate these data in climate models.

Contrasting seasonal changes in total and intense precipitation in the European Alps from 1903 to 2010

Abstract. Changes in precipitation over the European Alps are investigated with the regional climate model MAR (Modèle Atmosphérique Régional) applied with a 7 km resolution over the period 1903–2010 using the reanalysis ERA-20C as forcing. A comparison with several observational datasets demonstrates that the model is able to reproduce the climatology as well as both the interannual variability and the seasonal cycle of precipitation over the European Alps. The relatively high resolution allows us to estimate precipitation at high elevations. The vertical gradient of precipitation simulated by MAR over the European Alps reaches 33% km−1 (1.21 mm d−1 km−1) in summer and 38 % km−1 (1.15 mm d−1 km−1) in winter, on average, over 1971–2008 and shows a large spatial variability. A significant (p value < 0.05) increase in mean winter precipitation is simulated in the northwestern Alps over 1903–2010, with changes typically reaching 20 % to 40 % per century. This increase is mainly explained by a stronger simple daily intensity index (SDII) and is associated with less-frequent but longer wet spells. A general drying is found in summer over the same period, exceeding 20 % to 30 % per century in the western plains and 40 % to 50 % per century in the southern plains surrounding the Alps but remaining much smaller (<10 %) and not significant above 1500 m a.s.l. Below this level, the summer drying is explained by a reduction in the number of wet days, reaching 20 % per century over the northwestern part of the Alps and 30 % to 50 % per century in the southern part of the Alps. It is associated with shorter but more-frequent wet spells. The centennial trends are modulated over the last decades, with the drying occurring in the plains in winter also affecting high-altitude areas during this season and with a positive trend of autumn precipitation occurring only over the last decades all over the Alps. Maximum daily precipitation index (Rx1day) takes its highest values in autumn in both the western and the eastern parts of the southern Alps, locally reaching 50 to 70 mm d−1 on average over 1903–2010. Centennial maxima up to 250 to 300 mm d−1 are simulated in the southern Alps, in France and Italy, as well as in the Ticino valley in Switzerland. Over 1903–2010, seasonal Rx1day shows a general and significant increase at the annual timescale and also during the four seasons, reaching local values between 20 % and 40 % per century over large parts of the Alps and the Apennines. Trends of Rx1day are significant (p value < 0.05) only when considering long time series, typically 50 to 80 years depending on the area considered. Some of these trends are nonetheless significant when computed over 1970–2010, suggesting a recent acceleration of the increase in extreme precipitation, whereas earlier periods with strong precipitation also occurred, in particular during the 1950s and 1960s.

Future evolution of the hydroclimatic conditions favouring floods in the south‐east of Belgium by 2100 using a regional climate model

AbstractIn Belgium, most flood events occur in winter as a result of intense precipitation events but also through the abrupt melting of the snowpack that covers the Ardennes summits. These conditions favourable to floods exhibit a decreasing trend over 1959–2010 resulting from the reduction in snow accumulation, although extreme precipitation events show a positive, albeit non‐significant signal. In this study, the evolution of these trends in warmer climates is investigated by using future projections performed with the regional climate model MAR (‘Modèle Atmosphérique Régional’) forced by two global models NorESM1‐M and MIROC5 under the RCP8.5 scenario. These models were selected from the CMIP5 archive after evaluation of their ability to represent the current (1976–2005) mean climate over Europe. By the end of the century, the results show an acceleration of the snow depletion resulting in fewer snowmelt‐associated flood risk days depending on the warming rate from the global models forcing MAR. Regarding the impact of the evolution of extreme precipitation events on hydroclimatic conditions favouring floods, no significant change was found although these trends are subject to uncertainties due to model physics and natural variability.

A Boundary Forcing Sensitivity Analysis of the West African Monsoon Simulated by the Modèle Atmosphérique Régional

The rainfall regime of West Africa is highly variable over a large range of space and time scales. With rainfall agriculture being predominent in the region, the local population is extremely vulnerable to intraseasonal dry spells and multi-year droughts as well as to intense rainfall over small time steps. Were this variability to increase, it might render the area close from becoming unhabitable. Anticipating any change is thus crucial from both a societal and a scientific perspective. Despite continuous efforts in Global Climate Model (GCM) development, there is still no agreement on the sign of the future rainfall regime change in the region. Regional Climate Models (RCMs) are used for more accurate projections of future changes as well as end-user-oriented impact studies. In this study, the sensitivity of the Modèle Atmosphérique Régional (MAR) to homogeneous perturbations in boundary forcing air temperature and/or SST is assessed with the aim to better understand (i) the thermodynamical imprint of the recent rainfall regime changes and (ii) the impact of errors in driving data on the West African rainfall regime simulated by an RCM. After an evaluation step where the model is proved to satisfactorily simulate the West African Monsoon (WAM), sensitivity experiments display contrasted, sizable and robust responses of the simulated rainfall regime. The rainfall responses to the boundary forcing perturbations compare in magnitude with the intrinsic model bias, giving support for such an analysis. A physical interpretation of the rainfall anomalies provides confidence in the model response consistency and shows the potential of such an experimental protocol for future climate change downscalling over this region.

Greenland Ice Sheet late-season melt: investigating multiscale drivers of K-transect events

Abstract. One consequence of recent Arctic warming is an increased occurrence and longer seasonality of above-freezing air temperature episodes. There is significant disagreement in the literature concerning potential physical connectivity between high-latitude open water duration proximate to the Greenland Ice Sheet (GrIS) and late-season (i.e., end-of-summer and autumn) GrIS melt events. Here, a new date of sea ice advance (DOA) product is used to determine the occurrence of Baffin Bay sea ice growth along Greenland's west coast for the 2011–2015 period. Over the 2-month period preceding the DOA, northwest Atlantic Ocean and atmospheric conditions are analyzed and linked to late-season melt events observed at a series of on-ice automatic weather stations (AWSs) along the K-transect in southwestern Greenland. Surrounding ice sheet, tundra, and coastal winds from the Modèle Atmosphérique Régional (MAR) and Regional Atmospheric Climate Model (RACMO) provide high-resolution spatial context to AWS observations and are analyzed along with ERA-Interim reanalysis fields to understand the meso-to-synoptic-scale (thermo)dynamic drivers of the melt events. Results suggest that late-season melt events, which primarily occur in the ablation area, are strongly affected by ridging atmospheric circulation patterns that transport warm, moist air from the subpolar North Atlantic toward west Greenland. Increasing concentrations of North Atlantic water vapor are shown to be necessary to produce melt conditions as autumn progresses. While thermal conduction and advection off south Baffin Bay open waters impact coastal air temperatures, local marine air incursions are obstructed by barrier flows and persistent katabatic winds along the western GrIS margin.

Cloud microphysics and circulation anomalies control differences in future Greenland melt

Recently, the Greenland Ice Sheet (GrIS) has become the main source of barystatic sea-level rise1,2. The increase in the GrIS melt is linked to anticyclonic circulation anomalies, a reduction in cloud cover and enhanced warm-air advection3–7. The Climate Model Intercomparison Project fifth phase (CMIP5) General Circulation Models (GCMs) do not capture recent circulation dynamics; therefore, regional climate models (RCMs) driven by GCMs still show significant uncertainties in future GrIS sea-level contribution, even within one emission scenario5,8–10. Here, we use the RCM Modele Atmospherique Regional to show that the modelled cloud water phase is the main source of disagreement among future GrIS melt projections. We show that, in the current climate, anticyclonic circulation results in more melting than under a neutral-circulation regime. However, we find that the GrIS longwave cloud radiative effect is extremely sensitive to the modelled cloud liquid-water path, which explains melt anomalies of +378 Gt yr–1 (+1.04 mm yr–1 global sea level equivalent) in a +2 °C-warmer climate with a neutral-circulation regime (equivalent to 21% more melt than under anticyclonic circulation). The discrepancies between modelled cloud properties within a high-emission scenario introduce larger uncertainties in projected melt volumes than the difference in melt between low- and high-emission scenarios11. Greenland Ice Sheet melt is contributing to sea-level rise; however, uncertainties exist about its future contributions. A regional climate model shows that clouds are the primary cause of this uncertainty, with melt varying significantly depending on the cloud water phase and atmospheric circulation.

Sensitivity to Convective Schemes on Precipitation Simulated by the Regional Climate Model MAR over Belgium (1987–2017)

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.

Global Radiative Flux and Cloudiness Variability for the Period 1959–2010 in Belgium: A Comparison between Reanalyses and the Regional Climate Model MAR

The use of regional climate models (RCMs) can partly reduce the biases in global radiative flux (Eg↓) that are found in reanalysis products and global models, as they allow for a finer spatial resolution and a finer parametrisation of surface and atmospheric processes. In this study, we assess the ability of the MAR («Modèle Atmosphérique Régional») RCM to reproduce observed changes in Eg↓, and we investigate the added value of MAR with respect to reanalyses. Simulations were performed at a horizontal resolution of 5 km for the period 1959–2010 by forcing MAR with different reanalysis products: ERA40/ERA-interim, NCEP/NCAR-v1, ERA-20C, and 20CRV2C. Measurements of Eg↓ from the Global Energy Balance Archive (GEBA) and from the Royal Meteorological Institute of Belgium (RMIB), as well as cloud cover observations from Belgocontrol and RMIB, were used for the evaluation of the MAR model and the forcing reanalyses. Results show that MAR enables largely reducing the mean biases that are present in the reanalyses. The trend analysis shows that only MAR forced by ERA40/ERA-interim shows historical trends, which is probably because the ERA40/ERA-interim has a better horizontal resolution and assimilates more observations than the other reanalyses that are used in this study. The results suggest that the solar brightening observed since the 1980s in Belgium has mainly been due to decreasing cloud cover.