Mass balance of the ice sheets and glaciers – Progress since AR5 and challenges

Hanna, Edward; Pattyn, Frank; Navarro, Francisco; Favier, Vincent; Goelzer, Heiko; Broeke, M. R. van den; Vizcaíno, Miren; Whitehouse, Pippa; Ritz, Catherine; Bulthuis, Kevin; Smith, Ben

doi:10.1016/j.earscirev.2019.102976

Cited by 66 publications

(65 citation statements)

References 251 publications

(276 reference statements)

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“…The Greenland Ice Sheet has experienced substantial mass loss during the past two decades, resulting in an increased contribution to global mean sea level rise (Bamber et al 2018;Mouginot et al 2019;Hanna et al 2020;Shepherd et al 2020). This mass loss exhibits a large degree of interannual variability, especially pronounced during a period of accelerating mass loss over roughly 2000(van den Broeke et al 2016.…”

Section: Introductionmentioning

confidence: 99%

Strong Summer Atmospheric Rivers Trigger Greenland Ice Sheet Melt through Spatially Varying Surface Energy Balance and Cloud Regimes

et al. 2020

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ABSTRACT Mass loss from the Greenland Ice Sheet (GrIS) has accelerated over the past two decades, coincident with rapid Arctic warming and increasing moisture transport over Greenland by atmospheric rivers (ARs). Summer ARs affecting western Greenland trigger GrIS melt events, but the physical mechanisms through which ARs induce melt are not well understood. This study elucidates the coupled surface–atmosphere processes by which ARs force GrIS melt through analysis of the surface energy balance (SEB), cloud properties, and local- to synoptic-scale atmospheric conditions during strong summer AR events affecting western Greenland. ARs are identified in MERRA-2 reanalysis (1980–2017) and classified by integrated water vapor transport (IVT) intensity. SEB, cloud, and atmospheric data from regional climate model, observational, reanalysis, and satellite-based datasets are used to analyze melt-inducing physical processes during strong, >90th percentile “AR90+” events. Near AR “landfall,” AR90+ days feature increased cloud cover that reduces net shortwave radiation and increases net longwave radiation. As these oppositely signed radiative anomalies partly cancel during AR90+ events, increased melt energy in the ablation zone is primarily provided by turbulent heat fluxes, particularly sensible heat flux. These turbulent heat fluxes are driven by enhanced barrier winds generated by a stronger synoptic pressure gradient combined with an enhanced local temperature contrast between cool over-ice air and the anomalously warm surrounding atmosphere. During AR90+ events in northwest Greenland, anomalous melt is forced remotely through a clear-sky foehn regime produced by downslope flow in eastern Greenland.

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Section: Introductionmentioning

confidence: 99%

Strong Summer Atmospheric Rivers Trigger Greenland Ice Sheet Melt through Spatially Varying Surface Energy Balance and Cloud Regimes

et al. 2020

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“…Mass loss from the Greenland Ice Sheet (GrIS) has been accelerating since the 1990s (Enderlin et al, 2014;Mouginot et al, 2019;Hanna et al, 2019). Over the period 1991-2015, roughly 60% of the total mass loss can be ascribed to reduced GrIS surface mass balance (SMB; see Eq.…”

Section: Introductionmentioning

confidence: 99%

GrSMBMIP: Intercomparison of the modelled 1980-2012 surface mass balance over the Greenland Ice sheet

Fettweis¹

2020

Preprint

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The Greenland Ice Sheet (GrIS) mass loss has been accelerating at a rate of about 20 +/- 10 Gt/yr2 since the end of the 1990's, with around 60% of this mass loss directly attributed to enhanced surface meltwater runoff. However, in the climate and glaciology communities, different approaches exist on how to model the different surface mass balance (SMB) components using: (1) complex physically-based climate models which are computationally expensive; (2) intermediate complexity energy balance models; (3) simple and fast positive degree day models which base their inferences on statistical principles and are computationally highly efficient. Additionally, many of these models compute the SMB components based on different spatial and temporal resolutions, with different forcing fields as well as different ice sheet topographies and extents, making inter-comparison difficult. In the GrIS SMB model intercomparison project (GrSMBMIP) we address these issues by forcing each model with the same data (i.e., the ERA-Interim reanalysis) except for two global models for which this forcing is limited to the oceanic conditions, and at the same time by interpolating all modelled results onto a common ice sheet mask at 1 km horizontal resolution for the common period 1980-2012. The SMB outputs from 13 models are then compared over the GrIS to (1) SMB estimates using a combination of gravimetric remote sensing data from GRACE and measured ice discharge, (2) ice cores, snow pits, in-situ SMB observations, and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Our results reveal that the mean GrIS SMB of all 13 models has been positive between 1980 and 2012 with an average of 340 +/- 112 Gt/yr, but has decreased at an average rate of -7.3 Gt/yr2 (with a significance of 96%), mainly driven by an increase of 8.0 Gt/yr2 (with a significance of 98%) in meltwater runoff. Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting the need for accurate representation of the GrIS ablation zone extent and processes driving the surface melt. In addition, a higher density of in-situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 mWE/yr due to large discrepancies in modelled snowfall accumulation. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of same order than RCMs with observations and remain then useful tools for long-term simulations. It is also interesting to note that the ensemble mean of the 13 models produces the best estimate of the present day SMB relative to observations, suggesting that biases are not systematic among models. Finally, results from MAR forced by ERA5 will be added in this intercomparison to evaluate the added value of using this new reanalysis as forcing vs the former ERA-Interim reanalysis (used in SMBMIP).&#160;

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“…Earth system models (ESMs) coupled to ice sheet models are important tools to better understand how these interactions affect GrIS mass loss. There has been much recent progress in improving these tools (Goelzer et al, 2017;Hanna et al, 2020;Pollard, 2010;Rybak et al, 2018;Vizcaino, 2014). Vizcaíno et al (2013) and Alexander et al (2019) highlighted the importance of computing SMB based on the surface energy balance; melt parameterizations based on temperature cannot simulate climate feedbacks and interactions in a physically realistic way.…”

Section: Introductionmentioning

confidence: 99%

Accelerated Greenland Ice Sheet Mass Loss Under High Greenhouse Gas Forcing as Simulated by the Coupled CESM2.1‐CISM2.1

Muntjewerf

Sellevold

Vizcaíno

et al. 2020

J Adv Model Earth Syst

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The Greenland ice sheet (GrIS) is now losing mass at a rate of 0.7 mm of sea level rise (SLR) per year. Here we explore future GrIS evolution and interactions with global and regional climate under high greenhouse gas forcing with the Community Earth System Model version 2.1 (CESM2.1), which includes an interactive ice sheet component (the Community Ice Sheet Model v2.1 [CISM2.1]) and an advanced energy balance-based calculation of surface melt. We run an idealized 350-year scenario in which atmospheric CO 2 concentration increases by 1% annually until reaching four times pre-industrial values at year 140, after which it is held fixed. The global mean temperature increases by 5.2 and 8.5 K by years 131-150 and 331-350, respectively. The projected GrIS contribution to global mean SLR is 107 mm by year 150 and 1,140 mm by year 350. The rate of SLR increases from 2 mm yr −1 at year 150 to almost 7 mm yr −1 by year 350. The accelerated mass loss is caused by rapidly increasing surface melt as the ablation area expands, with associated albedo feedback and increased sensible and latent heat fluxes. This acceleration occurs for a global warming of approximately 4.2 K with respect to pre-industrial and is in part explained by the quasi-parabolic shape of the ice sheet, which favors rapid expansion of the ablation area as it approaches the interior "plateau." Plain Language Summary Observations show that the Greenland ice sheet (GrIS) has been losing mass at an accelerating rate over the last few decades and is currently one of the main contributors to global sea level rise. To understand the causes of GrIS mass loss, we must consider the Earth system as a whole. This study uses an Earth system model with an interactive GrIS model to explore (1) the extent to which the GrIS responds to warming and (2) the main processes that govern this response. The model is forced with an idealized greenhouse gas scenario in which the atmospheric CO 2 concentration increases by 1% per year until reaching four times the pre-industrial level; the CO 2 concentration is then kept constant for another two centuries. The GrIS responds nonlinearly to climate warming. The GrIS contributes about 100 mm of sea level rise by year 150, when CO 2 is stabilized and the global mean temperature has increased by 5.2 K. By year 350, when global warming has increased to 8.5 K, the GrIS contributes more than 1 m of additional sea level rise. The accelerated mass loss is mostly driven by summertime warming and increased melting of a darkening ice surface.

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Mass balance of the ice sheets and glaciers – Progress since AR5 and challenges

Cited by 66 publications

References 251 publications

Strong Summer Atmospheric Rivers Trigger Greenland Ice Sheet Melt through Spatially Varying Surface Energy Balance and Cloud Regimes

Strong Summer Atmospheric Rivers Trigger Greenland Ice Sheet Melt through Spatially Varying Surface Energy Balance and Cloud Regimes

GrSMBMIP: Intercomparison of the modelled 1980-2012 surface mass balance over the Greenland Ice sheet

Accelerated Greenland Ice Sheet Mass Loss Under High Greenhouse Gas Forcing as Simulated by the Coupled CESM2.1‐CISM2.1

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