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.

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Clouds exert a pivotal control on the mass balance of the Greenland and Antarctic Ice Sheet and therefore their contribution to global sea level. Clouds transport moisture onto the marginal ice sheet, where steep topographic gradients force the air to rise and cool, inducing strong orographic precipitation and leaving the interior ice sheet dry (polar desert). Clouds further regulate the radiation balance at the surface and, consequently, surface melt. Depending on their frequency, phase, and structure, clouds not only mute incoming solar radiation but also enhance longwave radiation at the surface. With the advent of novel observations from space (CloudSat-CALIPSO) and in the field, we now have tools to start evaluating the representation of clouds, precipitation, and ice sheet surface radiation in climate models. Here we evaluate the Community Earth System Model version 1 (CESM1(CAM5)) to represent (1) precipitation frequency and phase, using a CALIPSO cloud simulator; (2) cloud radiative effect comparing to a CloudSat-CALIPSO based product; and (3) snowfall amounts and surface mass balance, comparing to CloudSat, in-situ observations, and regional climate model results. After discussing outstanding cloud biases in CESM1(CAM5), we present our efforts to reduce these in the recently released version 2 (CESM2). We show that clouds are considerably better represented in CESM2, leading to improvements in surface radiation, melt, and surface mass balance, although biases in precipitation phase persist. Our work demonstrates the need for high-quality, long-term observations of clouds and their effect on the ice sheet surface to enable continued climate model improvement.@en

The presence of meltwater influences Antarctic ice shelf dynamics in a way that is poorly understood. In addition to surface meltwater, subsurface meltwater lakes have been discovered close to the ice shelf grounding line. Drainage and collapse of these subsurface lakes may induce hydrofracturing and poses a potential threat to ice shelf stability. Here, we present direct observations of the near-surface firn and ice shelf structure before and after the collapse of a subsurface meltwater lake near the grounding line of the Roi Baudouin Ice Shelf (RBIS). In February 2016, ground penetrating radar (GPR) data were collected of the subsurface lake, highlighting its depth and extent. Surprisingly, when the field team returned to the site in December 2017 to repeat the GPR surveying, they found that the lake had collapsed. These unique GPR and GPS observations highlight the heterogeneity of the lake structure after collapse and allow us to see structural differences before and after collapse. Continued geophysical monitoring and analysis could provide important information to estimate the volume and hydrodynamics of the interglacial lake (e.g. horizontal vs. vertical drainage). In addition to field data, we use a regional climate model and remote sensing observations to provide an analysis of the climate forcing that may have contributed to the lake collapse. We show that anomalously high surface melting in the summer season of 2016-2017 likely contributed to the collapse. Our results shed light on the impact of subsurface lake collapse on the ice shelf structure, dynamics, and surface height changes, which is essential to understand the impact of meltwater drainage on ice shelf stability.@en