Thomas Dethinne

Intense warming events (IWE) and intense precipitation events (IPE) and their impacts on ice bodies remain overlooked. Using in situ observations, a high-resolution regional circulation model and catalogue of atmospheric river (AR) occurrences, we investigate concurrent IWE over the Patagonian Icefields and IPE over the Antarctic Peninsula Ice Sheet associated with landfalling ARs. Our study focuses on summers (November–March) from 1980 to 2022. We identified 127 compound events linked to a dipole circulation pattern characterized by a ridge over southern South America and a low-pressure system over the Bellingshausen Sea. Both regions experience pronounced surface warming and enhanced melt leading to a negative Surface Mass Balance over the Patagonian Icefields, while positive anomalies still prevailed over the Antarctic Peninsula Ice Sheet were related with increased snowfall associated with AR activity. Surface Energy Balance anomalies were mainly driven by enhanced incoming shortwave radiation over Patagonia but increased longwave radiation over the Antarctic Peninsula, whereas sensible heat flux positively contributed in both regions. These findings highlight the interconnected influence of intense events and AR-driven dipole circulation patterns on the Southern Hemisphere cryosphere, even though individual events exhibit substantial thermodynamic variability and distinct life-cycle characteristics.

Accurately estimating the surface mass balance (SMB) of the Greenland Ice Sheet (GrIS) is essential to quantify its contribution to sea-level rise. The polar regional atmospheric climate model MAR is widely used to simulate GrIS SMB and to force ice sheet dynamics models, highlighting the need for a thorough evaluation. Here, we evaluate the latest MAR version (MARv3.14) over Greenland at 5 km spatial resolution and examine the impact of coarser resolutions (10–30 km) on the simulated SMB and its components. MAR outputs are compared to a range of independent observations, including in situ SMB measurements, automatic weather station (AWS) records of near-surface meteorological variables, satellite-derived melt extent, and albedo products. At 5 km, MAR reproduces the observed SMB with a root-mean-square error (RMSE) of 0.51 m and a correlation of 0.93. For near-surface meteorological variables and surface energy budget fluxes, the model RMSE is smaller than the corresponding observed natural variability (i.e., standard deviation), indicating non-significant model error. Prescribing bare-ice albedo improves the model performance in the ablation zone, while biases remain in the accumulation zone, suggesting that further improvements are required in the snow albedo scheme. In addition, simulated melt timing is consistent with satellite-based melt extent products. Sensitivity experiments reveal that discrepancies between simulations at different spatial resolutions are mostly limited to the ice sheet margins where strong SMB and topographic gradients occur, notably in the southeast of Greenland where precipitation peaks. Differences in integrated SMB generally remain small and mostly non-significant, while individual components, i.e., precipitation and runoff, exhibit larger resolution-dependent variations. We find that a resolution of at least 10 km is required to accurately capture the GrIS climate and SMB. Reducing computation time about 10-fold relative to 5 km simulation, a 10 km grid makes a good compromise for long-term climate projections.

Accurately estimating the surface mass balance (SMB) of the Greenland Ice Sheet (GrIS) is essential to quantify its contribution to sea-level rise. The polar regional atmospheric climate model MAR is widely used to simulate GrIS SMB and to force ice sheet dynamics models, highlighting the need for a thorough evaluation. Here, we evaluate the latest MAR version (MARv3.14) over Greenland at 5 km spatial resolution and examine the impact of coarser resolutions (10–30 km) on the simulated SMB and its components. MAR outputs are compared to a range of independent observations, including in situ SMB measurements, automatic weather station (AWS) records of near-surface meteorological variables, satellite-derived melt extent, and albedo products. At 5 km, MAR reproduces the observed SMB with a root-mean-square error (RMSE) of 0.51 m and a correlation of 0.93. For near-surface meteorological variables and surface energy budget fluxes, the model RMSE is smaller than the corresponding observed natural variability (i.e., standard deviation), indicating non-significant model error. Prescribing bare-ice albedo improves the model performance in the ablation zone, while biases remain in the accumulation zone, suggesting that further improvements are required in the snow albedo scheme. In addition, simulated melt timing is consistent with satellite-based melt extent products. Sensitivity experiments reveal that discrepancies between simulations at different spatial resolutions are mostly limited to the ice sheet margins where strong SMB and topographic gradients occur, notably in the southeast of Greenland where precipitation peaks. Differences in integrated SMB generally remain small and mostly non-significant, while individual components, i.e., precipitation and runoff, exhibit larger resolution-dependent variations. We find that a resolution of at least 10 km is required to accurately capture the GrIS climate and SMB. Reducing computation time about 10-fold relative to 5 km simulation, a 10 km grid makes a good compromise for long-term climate projections.

Intense warming events (IWE) and intense precipitation events (IPE) and their impacts on ice bodies remain overlooked. Using in situ observations, a high-resolution regional circulation model and catalogue of atmospheric river (AR) occurrences, we investigate concurrent IWE over the Patagonian Icefields and IPE over the Antarctic Peninsula Ice Sheet associated with landfalling ARs. Our study focuses on summers (November–March) from 1980 to 2022. We identified 127 compound events linked to a dipole circulation pattern characterized by a ridge over southern South America and a low-pressure system over the Bellingshausen Sea. Both regions experience pronounced surface warming and enhanced melt leading to a negative Surface Mass Balance over the Patagonian Icefields, while positive anomalies still prevailed over the Antarctic Peninsula Ice Sheet were related with increased snowfall associated with AR activity. Surface Energy Balance anomalies were mainly driven by enhanced incoming shortwave radiation over Patagonia but increased longwave radiation over the Antarctic Peninsula, whereas sensible heat flux positively contributed in both regions. These findings highlight the interconnected influence of intense events and AR-driven dipole circulation patterns on the Southern Hemisphere cryosphere, even though individual events exhibit substantial thermodynamic variability and distinct life-cycle characteristics.

Accurately estimating the surface mass balance (SMB) of the Greenland Ice Sheet (GrIS) is essential to quantify its contribution to sea-level rise. The polar regional atmospheric climate model MAR is widely used to simulate GrIS SMB and to force ice sheet dynamics models, highlighting the need for a thorough evaluation. Here, we evaluate the latest MAR version (MARv3.14) over Greenland at 5 km spatial resolution and examine the impact of coarser resolutions (10–30 km) on the simulated SMB and its components. MAR outputs are compared to a range of independent observations, including in situ SMB measurements, automatic weather station (AWS) records of near-surface meteorological variables, satellite-derived melt extent, and albedo products. At 5 km, MAR reproduces the observed SMB with a root-mean-square error (RMSE) of 0.51 m and a correlation of 0.93. For near-surface meteorological variables and surface energy budget fluxes, the model RMSE is smaller than the corresponding observed natural variability (i.e., standard deviation), indicating non-significant model error. Prescribing bare-ice albedo improves the model performance in the ablation zone, while biases remain in the accumulation zone, suggesting that further improvements are required in the snow albedo scheme. In addition, simulated melt timing is consistent with satellite-based melt extent products. Sensitivity experiments reveal that discrepancies between simulations at different spatial resolutions are mostly limited to the ice sheet margins where strong SMB and topographic gradients occur, notably in the southeast of Greenland where precipitation peaks. Differences in integrated SMB generally remain small and mostly non-significant, while individual components, i.e., precipitation and runoff, exhibit larger resolution-dependent variations. We find that a resolution of at least 10 km is required to accurately capture the GrIS climate and SMB. Reducing computation time about 10-fold relative to 5 km simulation, a 10 km grid makes a good compromise for long-term climate projections.

Accurately estimating the surface mass balance (SMB) of the Greenland Ice Sheet (GrIS) is essential to quantify its contribution to sea-level rise. The polar regional atmospheric climate model MAR is widely used to simulate GrIS SMB and to force ice sheet dynamics models, highlighting the need for a thorough evaluation. Here, we evaluate the latest MAR version (MARv3.14) over Greenland at 5 km spatial resolution and examine the impact of coarser resolutions (10–30 km) on the simulated SMB and its components. MAR outputs are compared to a range of independent observations, including in situ SMB measurements, automatic weather station (AWS) records of near-surface meteorological variables, satellite-derived melt extent, and albedo products. At 5 km, MAR reproduces the observed SMB with a root-mean-square error (RMSE) of 0.51 m and a correlation of 0.93. For near-surface meteorological variables and surface energy budget fluxes, the model RMSE is smaller than the corresponding observed natural variability (i.e., standard deviation), indicating non-significant model error. Prescribing bare-ice albedo improves the model performance in the ablation zone, while biases remain in the accumulation zone, suggesting that further improvements are required in the snow albedo scheme. In addition, simulated melt timing is consistent with satellite-based melt extent products. Sensitivity experiments reveal that discrepancies between simulations at different spatial resolutions are mostly limited to the ice sheet margins where strong SMB and topographic gradients occur, notably in the southeast of Greenland where precipitation peaks. Differences in integrated SMB generally remain small and mostly non-significant, while individual components, i.e., precipitation and runoff, exhibit larger resolution-dependent variations. We find that a resolution of at least 10 km is required to accurately capture the GrIS climate and SMB. Reducing computation time about 10-fold relative to 5 km simulation, a 10 km grid makes a good compromise for long-term climate projections.

Intense warming events (IWE) and intense precipitation events (IPE) and their impacts on ice bodies remain overlooked. Using in situ observations, a high-resolution regional circulation model and catalogue of atmospheric river (AR) occurrences, we investigate concurrent IWE over the Patagonian Icefields and IPE over the Antarctic Peninsula Ice Sheet associated with landfalling ARs. Our study focuses on summers (November–March) from 1980 to 2022. We identified 127 compound events linked to a dipole circulation pattern characterized by a ridge over southern South America and a low-pressure system over the Bellingshausen Sea. Both regions experience pronounced surface warming and enhanced melt leading to a negative Surface Mass Balance over the Patagonian Icefields, while positive anomalies still prevailed over the Antarctic Peninsula Ice Sheet were related with increased snowfall associated with AR activity. Surface Energy Balance anomalies were mainly driven by enhanced incoming shortwave radiation over Patagonia but increased longwave radiation over the Antarctic Peninsula, whereas sensible heat flux positively contributed in both regions. These findings highlight the interconnected influence of intense events and AR-driven dipole circulation patterns on the Southern Hemisphere cryosphere, even though individual events exhibit substantial thermodynamic variability and distinct life-cycle characteristics.

Accurately estimating the surface mass balance (SMB) of the Greenland Ice Sheet (GrIS) is essential to quantify its contribution to sea-level rise. The polar regional atmospheric climate model MAR is widely used to simulate GrIS SMB and to force ice sheet dynamics models, highlighting the need for a thorough evaluation. Here, we evaluate the latest MAR version (MARv3.14) over Greenland at 5 km spatial resolution and examine the impact of coarser resolutions (10–30 km) on the simulated SMB and its components. MAR outputs are compared to a range of independent observations, including in situ SMB measurements, automatic weather station (AWS) records of near-surface meteorological variables, satellite-derived melt extent, and albedo products. At 5 km, MAR reproduces the observed SMB with a root-mean-square error (RMSE) of 0.51 m and a correlation of 0.93. For near-surface meteorological variables and surface energy budget fluxes, the model RMSE is smaller than the corresponding observed natural variability (i.e., standard deviation), indicating non-significant model error. Prescribing bare-ice albedo improves the model performance in the ablation zone, while biases remain in the accumulation zone, suggesting that further improvements are required in the snow albedo scheme. In addition, simulated melt timing is consistent with satellite-based melt extent products. Sensitivity experiments reveal that discrepancies between simulations at different spatial resolutions are mostly limited to the ice sheet margins where strong SMB and topographic gradients occur, notably in the southeast of Greenland where precipitation peaks. Differences in integrated SMB generally remain small and mostly non-significant, while individual components, i.e., precipitation and runoff, exhibit larger resolution-dependent variations. We find that a resolution of at least 10 km is required to accurately capture the GrIS climate and SMB. Reducing computation time about 10-fold relative to 5 km simulation, a 10 km grid makes a good compromise for long-term climate projections.