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Annual or summer (JJA)  mean variables from two CESM2-CISM2 simulations: 'F09' uses the f09 grid for the atmosphere and land components, 'ARCTIC' uses the variable-resolution arctic grid. Three periods - piControl, 1pctCO2 and 4xext are included.  CAM variables: CLDTOT, PHIS, PS, T, TGCLDLWP, TREFHT, Z3 CLM variables: EFLX_LH_TOT, FGR, FIRA, FLDS, FSDS, FSH, FSM, FSR, PCT_LANDUNIT, QFLX_EVAP_TOT, QICE_MELT, QRUNOFF, QSNOMELT, RAIN, SNOW CISM variables: iarea, ice_sheet_mask, ivol, thk, total_bmb_flux, total_calving_flux, total_smb_flux POP variables: MOC CICE variables: aice, hi 

Abstract. Atmospheric rivers (ARs) are synoptic-scale features that transport moisture poleward and may cause short-duration, high-volume melt events on the Greenland ice sheet (GrIS). In contrast with traditional climate modeling studies that rely on coarse (1 to 2°) grids, this project investigates the effectiveness of variable-resolution (VR) grids in modeling ARs and their subsequent precipitation using refined grid spacing (0.25 and 0.125°) around the GrIS and 1° grid spacing for the rest of the globe in a coupled land–atmosphere model simulation. VR simulations from the Community Earth System Model version 2.2 (CESM2.2) bridge the gap between the limitations of global and regional climate models while maximizing computational efficiency. ARs from CESM2.2 simulations using three grid types (VR, latitude–longitude, and quasi-uniform) with varying resolutions are compared to outputs from two observation-based reanalysis products, ERA5 and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), using a study period of 1 January 1979 to 31 December 1998. The VR grids produce ARs with smaller areal extents and lower area-integrated precipitation over the GrIS compared to latitude–longitude and quasi-uniform grids. We hypothesize that the smaller areal AR extents in VR grids are due to the refined topography resolved in these grids. In contrast, topographic smoothing in coarser-resolution latitude–longitude and quasi-uniform grids allows ARs to penetrate further inland on the GrIS. Precipitation rates are similar for the VR, latitude–longitude, and quasi-uniform grids; thus the reduced areal extent in VR grids produces lower area-integrated precipitation. The VR grids most closely match the AR overlap extent and precipitation in ERA5 and MERRA-2, suggesting the most realistic behavior among the three configurations. 

The simulation of ice sheet-climate interaction such as surface massbalance fluxes are sensitive to model grid resolution. Here we simulatethe multicentury evolution of the Greenland Ice Sheet (GrIS) and itsinteraction with the climate using the Community Earth System Modelversion 2.2 (CESM2.2) including an interactive GrIS component (theCommunity Ice Sheet Model v2.1 [CISM2.1]) under an idealized warmingscenario (atmospheric CO2 increases by 1% yr−1 until quadrupling thepre-industrial level and then is held fixed). A variable-resolution (VR)grid with 1/4◦ regional refinement over broader Arctic and 1◦ resolutionelsewhere is applied to the atmosphere and land components, and theresults are compared to conventional 1◦ lat-lon grid simulations toinvestigate the impact of grid refinement. An acceleration of GrIS massloss is found at around year 110, caused by rapidly increasing surfacemelt as the ablation area expands with associated albedo feedback andincreased turbulent fluxes. Compared to the 1◦ runs, the VR run featuresslower melt increase, especially over Western and Northern Greenland,which slope gently towards the peripheries. This difference patternoriginates primarily from the weaker albedo feedback in the VR run,complemented by its smaller cloud longwave radiation. The steeper VRGreenland surface topography favors slower ablation zone expansion, thusleading to its weaker albedo feedback. The sea level rise contributionfrom the GrIS in the VR run is 53 mm by year 150 and 831 mm by year 350,approximately 40% and 20% smaller than the 1◦ runs, respectively. 

Abstract. Earth system models are essential tools for understandingthe impacts of a warming world, particularly on the contribution of polarice sheets to sea level change. However, current models lack full couplingof the ice sheets to the ocean and are typically run at a coarse resolution(1∘ grid spacing or coarser). Coarse spatial resolution isparticularly a problem over Antarctica, where sub-grid-scale orography iswell-known to influence precipitation fields, and glacier models requirehigh-resolution atmospheric inputs. This resolution limitation has beenpartially addressed by regional climate models (RCMs), which must be forcedat their lateral and ocean surface boundaries by (usually coarser) globalatmospheric datasets, However, RCMs fail to capture the two-way couplingbetween the regional domain and the global climate system. Conversely,running high-spatial-resolution models globally is computationallyexpensive and can produce vast amounts of data. Alternatively, variable-resolution grids can retain the benefits of highresolution over a specified domain without the computational costs ofrunning at a high resolution globally. Here we evaluate a historicalsimulation of the Community Earth System Model version 2 (CESM2)implementing the spectral element (SE) numerical dynamical core (VR-CESM2)with an enhanced-horizontal-resolution (0.25∘) grid over theAntarctic Ice Sheet and the surrounding Southern Ocean; the rest of theglobal domain is on the standard 1∘ grid. We compare it to1∘ model runs of CESM2 using both the SE dynamical core and thestandard finite-volume (FV) dynamical core, both with identical physics andforcing, including prescribed sea surface temperatures (SSTs) and sea ice concentrations fromobservations. Our evaluation reveals both improvements and degradations inVR-CESM2 performance relative to the 1∘ CESM2. Surface massbalance estimates are slightly higher but within 1 standard deviation ofthe ensemble mean, except for over the Antarctic Peninsula, which isimpacted by better-resolved surface topography. Temperature and windestimates are improved over both the near surface and aloft, although theoverall correction of a cold bias (within the 1∘ CESM2 runs) hasresulted in temperatures which are too high over the interior of the icesheet. The major degradations include the enhancement of surface melt aswell as excessive cloud liquid water over the ocean, with resultant impactson the surface radiation budget. Despite these changes, VR-CESM2 is avaluable tool for the analysis of precipitation and surface mass balanceand thus constraining estimates of sea level rise associated with theAntarctic Ice Sheet. 

Abstract. Global climate models (GCMs) have advanced in many ways ascomputing power has allowed more complexity and finer resolutions. As GCMsreach storm-resolving scales, they need to be able to produce realisticprecipitation intensity, duration, and frequency at fine scales withconsideration of scale-aware parameterization. This study uses astate-of-the-art storm-resolving GCM with a nonhydrostatic dynamical core – theModel for Prediction Across Scales (MPAS), incorporated in the atmosphericcomponent (Community Atmosphere Model, CAM) of the open-source CommunityEarth System Model (CESM), within the System for Integrated Modeling of theAtmosphere (SIMA) framework (referred to as SIMA-MPAS). At uniform coarse (here, at 120 km) gridresolution, the SIMA-MPAS configuration is comparable to the standardhydrostatic CESM (with a finite-volume (FV) dynamical core) with reasonableenergy and mass conservation on climatological timescales. With thecomparable energy and mass balance performance between CAM-FV (workhorse dynamical core) and SIMA-MPAS (newly developed dynamical core), it gives confidence inSIMA-MPAS's applications at a finer resolution. To evaluate this, we focuson how the SIMA-MPAS model performs when reaching a storm-resolving scale at3 km. To do this efficiently, we compose a case study using a SIMA-MPASvariable-resolution configuration with a refined mesh of 3 km covering thewestern USA and 60 km over the rest of the globe. We evaluated the modelperformance using satellite and station-based gridded observations withcomparison to a traditional regional climate model (WRF, the WeatherResearch and Forecasting model). Our results show realistic representationsof precipitation over the refined complex terrains temporally and spatially.Along with much improved near-surface temperature, realistic topography, andland–air interactions, we also demonstrate significantly enhanced snowpackdistributions. This work illustrates that the global SIMA-MPAS atstorm-resolving resolution can produce much more realistic regional climatevariability, fine-scale features, and extremes to advance both climate andweather studies. This next-generation storm-resolving model could ultimatelybridge large-scale forcing constraints and better inform climate impactsand weather predictions across scales. 

Abstract Advances in high‐performance computing make it possible to run atmospheric general circulation models (AGCMs) over an increasingly wider range of grid resolutions, using either globally uniform or variable‐resolution grids. In principle, this is an exciting opportunity to resolve atmospheric process and scales in a global model and in unprecedented detail, but in practice this grid flexibility is incompatible with the non‐ or weakly converging solutions with increasing horizontal resolution that have long characterized AGCMs. In the the Community Atmosphere Model (CAM), there are robust sensitivities to horizontal resolution that have persisted since the model was first introduced over thirty years ago; the atmosphere progressively dries and becomes less cloudy with resolution, and parametrized deep convective precipitation decreases at the expense of stratiform precipitation. This study documents a convergence experiment using CAM, version 6, and argues that a unifying cause, the sensitivity of resolved dynamical modes to native grid resolution, feeds back into other model components and explains these robust sensitivities to resolution. The increasing magnitudes of resolved vertical velocities with resolution are shown to fit an analytic scaling derived for the equations of motion at hydrostatic scales. This trend in vertical velocities results in an increase in resolved upward moisture fluxes at cloud base, balanced by an increase in stratiform precipitation rates with resolution. Compensating, greater magnitude subsiding motion with resolution has previously been shown to dry out the atmosphere and reduce cloud cover. Here, it is shown that both the increase in condensational heating from stratiform cloud formation and greater subsidence drying contribute to an increase in atmospheric stability with resolution, reducing the activity of parametrized convection. The impact of changing the vertical velocity field with native grid resolution cannot be ignored in any effort to recover convergent solutions in AGCMs, and, in particular, the development of scale‐aware physical parametrizations.