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.
The rate of growth or retreat of the Greenland and Antarctic ice sheets remains a highly uncertain component of future sea level change. Here we examine the simulation of Greenland ice sheet surface mass balance (GrIS SMB) in a development branch of the ModelE2 version of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM). GCMs are often limited in their ability to represent SMB compared with polar region regional climate models. We compare ModelE2‐simulated GrIS SMB for present‐day (1996–2005) simulations with fixed ocean conditions, at a spatial resolution of 2° latitude by 2.5° longitude (~200 km), with SMB simulated by the Modèle Atmosphérique Régionale (MAR) regional climate model (1996–2005 at a 25‐km resolution). ModelE2 SMB agrees well with MAR SMB on the whole, but there are distinct spatial patterns of differences and large differences in some SMB components. The impacts of changes to the ModelE2 surface are tested, including a subgrid‐scale representation of SMB with surface elevation classes. This has a minimal effect on ice sheet‐wide SMB but corrects local biases. Replacing fixed surface albedo with satellite‐derived values and an age‐dependent scheme has a larger impact, increasing simulated melt by 60%–100%. We also find that lower surface albedo can enhance the effects of elevation classes. Reducing ModelE2 surface roughness length to values closer to MAR reduces sublimation by ~50%. Further work is required to account for meltwater refreezing in ModelE2 and to understand how differences in atmospheric processes and model resolution influence simulated SMB.
more » « less- Award ID(s):
- 1713072
- NSF-PAR ID:
- 10375147
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Earth Surface
- Volume:
- 124
- Issue:
- 3
- ISSN:
- 2169-9003
- Page Range / eLocation ID:
- p. 750-765
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
-
Modèle Atmosphérique Régional (MAR) is a regional climate model that is fully coupled to a one-dimensional surface-atmosphere energy and mass transfer scheme, SISVAT (Soil Ice Snow Vegetation Atmosphere Transfer) (Fettweis et al., 2005, 2020; Lefebre et al., 2005). SISVAT employs a multilayered snowpack model, CROCUS, that simulates meltwater production, percolation, and refreeze (Brun et al., 1989), while also accounting for changes in albedo due to snow metamorphism (Brun et al., 1992). MAR has been extensively verified over the Greenland Ice Sheet and is therefore particularly well suited for analyses of Greenland ice sheet surface mass balance (Fettweis et al., 2011; Fettweis et al., 2020; Lefebre et al. 2005; Mattingly et al. 2020). Brun, E., Martin, E., Simon, V., Gendre, C., and Coléou, C. (1989). An energy and mass model of snow cover suitable for operational avalanche forecasting. Journal of Glaciology, 35, 333. https://doi.org/10.1017/S0022143000009254 Brun, E., David, P., Sudul, M., and Brunot, G. (1992). A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting. Journal of Glaciology, 38(128), 13–22. https://doi.org/10.3189/S0022143000009552 Fettweis, X., Gallée, H., Lefebre, F., and van Ypersele, J.-P. (2005). Greenland surface mass balance simulated by a regional climate model and comparison with satellite-derived data in 1990–1991. Climate Dynamics, 24(6), 623–640. https://doi.org/10.1007/s00382-005-0010-y Fettweis, X., Tedesco, M., van den Broeke, M., and Ettema, J. (2011). Melting trends over the Greenland ice sheet (1958–2009) from spaceborne microwave data and regional climate models. The Cryosphere, 5(2), 359–375. https://doi.org/10.5194/tc-5-359-2011 Fettweis, X., Hofer, S., Krebs-Kanzow, U., Amory, C., Aoki, T., Berends, C. J., et al. (2020). GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice Sheet. The Cryosphere, 14(11), 3935–3958. https://doi.org/10.5194/tc-14-3935-2020 Lefebre, F., Fettweis, X., Gallée, H., Van Ypersele, J.-P., Marbaix, P., Greuell, W., and Calanca, P. (2005). Evaluation of a high-resolution regional climate simulation over Greenland. Climate Dynamics, 25(1), 99–116. https://doi.org/10.1007/s00382-005-0005-8 Mattingly, K. S., Mote, T. L., Fettweis, X., van As, D., Van Tricht, K., Lhermitte, S., et al. (2020). Strong summer atmospheric rivers trigger Greenland ice sheet melt through spatially varying surface energy balance and cloud regimes. Journal of Climate, 33(16), 6809–6832. https://doi.org/10.1175/JCLI-D-19-0835.1more » « less
-
Abstract. Surface mass loss from the Greenland ice sheet (GrIS) hasaccelerated over the past decades, mainly due to enhanced surface meltingand liquid water runoff in response to atmospheric warming. A large portionof runoff from the GrIS originates from exposure of the darker bare ice inthe ablation zone when the overlying snow melts, where surface albedo playsa critical role in modulating the energy available for melting. In thisregard, it is imperative to understand the processes governing albedovariability to accurately project future mass loss from the GrIS. Bare-icealbedo is spatially and temporally variable and contingent on non-linearfeedbacks and the presence of light-absorbing constituents. An assessment ofmodels aiming at simulating albedo variability and associated impacts onmeltwater production is crucial for improving our understanding of theprocesses governing these feedbacks and, in turn, surface mass loss fromGreenland. Here, we report the results of a comparison of the bare-iceextent and albedo simulated by the regional climate model ModèleAtmosphérique Régional (MAR) with satellite imagery from theModerate Resolution Imaging Spectroradiometer (MODIS) for the GrIS below70∘ N. Our findings suggest that MAR overestimates bare-ice albedoby 22.8 % on average in this area during the 2000–2021 period with respectto the estimates obtained from MODIS. Using an energy balance model toparameterize meltwater production, we find this bare-ice albedo bias canlead to an underestimation of total meltwater production from the bare-icezone below 70∘ N of 42.8 % during the summers of 2000–2021.more » « less
-
more » « less
Abstract Earth system/ice‐sheet coupling is an area of recent, major Earth System Model (ESM) development. This work occurs at the intersection of glaciology and climate science and is motivated by a need for robust projections of sea‐level rise. The Community Ice Sheet Model version 2 (CISM2) is the newest component model of the Community Earth System Model version 2 (CESM2). This study describes the coupling and novel capabilities of the model, including: (1) an advanced energy‐balance‐based surface mass balance calculation in the land component with downscaling via elevation classes; (2) a closed freshwater budget from ice sheet to the ocean from surface runoff, basal melting, and ice discharge; (3) dynamic land surface types; and (4) dynamic atmospheric topography. The Earth system/ice‐sheet coupling is demonstrated in a simulation with an evolving Greenland Ice Sheet (GrIS) under an idealized high CO2scenario. The model simulates a large expansion of ablation areas (where surface ablation exceeds snow accumulation) and a large increase in surface runoff. This results in an elevated freshwater flux to the ocean, as well as thinning of the ice sheet and area retreat. These GrIS changes result in reduced Greenland surface albedo, changes in the sign and magnitude of sensible and latent heat fluxes, and modified surface roughness and overall ice sheet topography. Representation of these couplings between climate and ice sheets is key for the simulation of ice and climate interactions.
-
Abstract. Snowfall is the major source of mass for the Greenland ice sheet (GrIS) but the spatial and temporalvariability of snowfall and the connections between snowfall and mass balance have so far been inadequatelyquantified. By characterizing local atmospheric circulation and utilizing CloudSat spaceborne radarobservations of snowfall, we provide a detailed spatial analysis of snowfall variability and its relationshipto Greenland mass balance, presenting first-of-their-kind maps of daily spatial variability in snowfallfrom observations across Greenland. For identified regional atmospheric circulation patterns, we show that thespatial distribution and net mass input of snowfall vary significantly with the position and strength ofsurface cyclones. Cyclones west of Greenland driving southerly flow contribute significantly more snowfall thanany other circulation regime, with each daily occurrence of the most extreme southerly circulation patterncontributing an average of 1.66 Gt of snow to the Greenland ice sheet. While cyclones east of Greenland,patterns with the least snowfall, contribute as little as 0.58 Gt each day. Above 2 km on the ice sheet wheresnowfall is inconsistent, extreme southerly patterns are the most significant mass contributors, with up to1.20 Gt of snowfall above this elevation. This analysis demonstrates that snowfall over the interior ofGreenland varies by up to a factor of 5 depending on regional circulation conditions. Using independentobservations of mass changes made by the Gravity Recovery and Climate Experiment (GRACE), we verify that thelargest mass increases are tied to the southerly regime with cyclones west of Greenland. For occurrences of thestrongest southerly pattern, GRACE indicates a net mass increase of 1.29 Gt in the ice sheet accumulation zone(above 2 km elevation) compared to the 1.20 Gt of snowfall observed by CloudSat. This overall agreementsuggests that the analytical approach presented here can be used to directly quantify snowfall masscontributions and their most significant drivers spatially across the GrIS. While previous research hasimplicated this same southerly regime in ablation processes during summer, this paper shows that ablation massloss in this circulation regime is nearly an order of magnitude larger than the mass gain from associatedsnowfall. For daily occurrences of the southerly circulation regime, a mass loss of approximately 11 Gt isobserved across the ice sheet despite snowfall mass input exceeding 1 Gt. By analyzing the spatialvariability of snowfall and mass changes, this research provides new insight into connections between regionalatmospheric circulation and GrIS mass balance.more » « less
