Ice sheet mass loss caused by dust and black carbon accumulation

Goelles, Thomas; Bøggild, Carl Egede; Greve, Ralf

doi:10.5194/tc-9-1845-2015

Cited by 32 publications

(22 citation statements)

References 43 publications

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“…Algal blooms over Greenland have been shown to substantially reduce surface albedo (Lutz et al, 2016;Musilova et al, 2016;Stibal et al, 2017). Simulations show that changes in albedo due to LAI might significantly affect the surface mass balance of ice sheets during glacial times Krinner et al, 2006), at present (Dumont et al, 2014;Tedesco et al, 2016) and in future climate change scenarios (Goelles et al, 2015). In this study we explore the sensitivity of ice sheet and climate evolution over the last glacial cycle to the representation of snow albedo in the CLIMBER-2 Earth system model of intermediate complexity.…”

Section: Introductionmentioning

confidence: 99%

The importance of snow albedo for ice sheet evolution over the last glacial cycle

Willeit

Ganopolski

2018

Clim. Past

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Abstract. The surface energy and mass balance of ice sheets strongly depends on the amount of solar radiation absorbed at the surface, which is mainly controlled by the albedo of snow and ice. Here, using an Earth system model of intermediate complexity, we explore the role played by surface albedo for the simulation of glacial cycles. We show that the evolution of the Northern Hemisphere ice sheets over the last glacial cycle is very sensitive to the representation of snow albedo in the model. It is well known that the albedo of snow depends strongly on snow grain size and the content of lightabsorbing impurities. Excluding either the snow aging effect or the dust darkening effect on snow albedo leads to an excessive ice build-up during glacial times and consequently to a failure in simulating deglaciation. While the effect of snow grain growth on snow albedo is well constrained, the albedo reduction due to the presence of dust in snow is much more uncertain because the light-absorbing properties of dust vary widely as a function of dust mineral composition. We also show that assuming slightly different optical properties of dust leads to very different ice sheet and climate evolutions in the model. Conversely, ice sheet evolution is less sensitive to the choice of ice albedo in the model. We conclude that a proper representation of snow albedo is a fundamental prerequisite for a successful simulation of glacial cycles.

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Section: Introductionmentioning

confidence: 99%

The importance of snow albedo for ice sheet evolution over the last glacial cycle

Willeit

Ganopolski

2018

Clim. Past

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“…With solar irradiance of several hundreds of W m −2 during daylight, a persistent change of 1 % of the albedo represents an energy comparable with the globally averaged radiative forcing caused by CO 2 concentration increase since preindustrial time (1.82 W m −2 , Myhre et al, 2009). While planetary albedo change is not expected to exceed a 0.1 % (Myhre et al, 2009), local changes can be much larger due to the dependence of snow albedo on multiple factors including snow grain size and shape, surface roughness, snow depth, and the amount of light-absorbing impurities such as black carbon, dust, and biological pigments (e.g., Warren and Wiscombe, 1980;Warren et al, 1998;Aoki et al, 2000;Dumont et al, 2010;Zhuravleva and Kokhanovsky, 2011;Stibal et al, 2012;Goelles et al, 2015). These factors vary in space and time depending on the atmospheric conditions and are controlled by numerous processes giving rise to complex snow-albedo feedback loops between the snow cover and the atmosphere (Curry et al, 1995;Qu and Hall, 2007;Picard et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Development and calibration of an automatic spectral albedometer to estimate near-surface snow SSA time series

et al. 2016

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Abstract. Spectral albedo of the snow surface in the visible/near-infrared range has been measured for 3 years by an automatic spectral radiometer installed at Dome C (75 • S, 123 • E) in Antarctica in order to retrieve the specific surface area (SSA) of superficial snow. This study focuses on the uncertainties of the SSA retrieval due to instrumental and data processing limitations. We find that when the solar zenith angle is high, the main source of uncertainties is the imperfect angular response of the light collectors. This imperfection introduces a small spurious wavelength-dependent trend in the albedo spectra which greatly affects the SSA retrieval. By modeling this effect, we show that for typical snow and illumination conditions encountered at Dome C, retrieving SSA with an accuracy better than 15 % (our target) requires the difference of response between 400 and 1100 nm to not exceed 2 %. Such a small difference can be achieved only by (i) a careful design of the collectors, (ii) an ad hoc correction of the spectra using the actual measured angular response of the collectors, and (iii) for solar zenith angles less than 75 • . The 3-year time series of retrieved SSA features a 3-fold decrease every summer which is significantly larger than the estimated uncertainties. This highlights the high dynamics of near-surface SSA at Dome C.

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“…Such a model will be tractable but would require substantial generalizations, thus possibly introducing errors. Alternatively, whole ice sheet scale fluxes can be derived from independently run model simulations with spatially discreet initial conditions, forcings, and parameter values, or by including transport terms between model grid points informed by existing ice flow models (e.g., Goelles et al, 2015).…”

Section: Modeling the Supraglacial Ecosystemmentioning

confidence: 99%

Ecological Modeling of the Supraglacial Ecosystem: A Process-based Perspective

2017

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Glacier and ice sheet surfaces are important microbe-dominated ecosystems that are changing rapidly due to climate change, with potentially significant impacts. A theoretical framework of the supraglacial (glacier surface) ecosystem is needed to enable its mathematical modeling, a necessary tool for understanding, quantifying and predicting present day and future ecosystem dynamics. Here, we review key biological processes occurring on glacier and ice sheet surfaces and present three frameworks for constructing process-based models of the surface ecosystem, using the largest supraglacial ecosystem on Earth-the Greenland ice sheet surface-as an important example. The models are based on organic carbon transformations, but vary in numerical complexity and in the level of detail of biological processes. This perspective is intended to guide future supraglacial ecosystem model development, field data collection for parameterization and validation purposes, and encourage inter-disciplinary collaboration between modelers and experimentalists.

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Ice sheet mass loss caused by dust and black carbon accumulation

Cited by 32 publications

References 43 publications

The importance of snow albedo for ice sheet evolution over the last glacial cycle

The importance of snow albedo for ice sheet evolution over the last glacial cycle

Development and calibration of an automatic spectral albedometer to estimate near-surface snow SSA time series

Ecological Modeling of the Supraglacial Ecosystem: A Process-based Perspective

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