Warm Greenland during the last interglacial: the role of regional changes in sea ice cover

Merz, Niklaus; Born, Andreas; Raible, Christoph C.; Stocker, Thomas F.

doi:10.5194/cp-12-2011-2016

Cited by 19 publications

(14 citation statements)

References 54 publications

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“…During summer, Rennermalm et al (2009) also find local correlations between sea ice cover and GrIS melt on selected parts of the east coast. Atmospheric model studies (Merz et al, 2016;Screen, 2017) also show that GS ice loss causes warming on the eastern and southern parts of Greenland; Merz et al (2016) even illustrate how GS ice loss may cause atmospheric circulation changes that causes substantial warming over Greenland (albeit under Last Interglacial climate conditions).…”

Section: 1029/2019gl083828mentioning

confidence: 99%

Attributing Greenland Warming Patterns to Regional Arctic Sea Ice Loss

Pedersen

Christensen

2019

Geophysical Research Letters

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Observed and model‐projected sea ice loss enhances warming in the Arctic. We investigate to what extent warming on Greenland can be attributed to changes in the sea ice cover in different parts of the Arctic. Using Climate Model Intercomparison Project phase 5 model projections of the future, we perform multilinear regressions to separate the simulated warming on Greenland in two parts; one following global warming and one following regional sea ice changes. This reveals the magnitude and spatial pattern of warming on Greenland, which can be attributed to sea ice loss in different Arctic regions. The results indicate that the impact of sea ice loss is largely confined to the coastal parts of Greenland. We find the strongest links to sea ice loss in adjacent regions; remote regions only have a limited impact. Overall, warming attributable to sea ice variability is a minor contribution but can be a dominant signal locally in coastal regions.

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Section: 1029/2019gl083828mentioning

confidence: 99%

Attributing Greenland Warming Patterns to Regional Arctic Sea Ice Loss

Pedersen

Christensen

2019

Geophysical Research Letters

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“…MAR is a regional atmospheric model fully coupled to the land surface model SISVAT (Soil Ice Snow Vegetation Atmosphere Transfer) which includes a detailed snow energy balance model (Gallée and Duynkerke, 1997). The atmospheric part of MAR uses the solar radiation scheme of Morcrette et al (2008) and accounts for the atmospheric hydrological cycle (including a cloud microphysical model) based on Lin et al (1983) and Kessler (1969). The snow-ice part of MAR is derived from the snowpack model Crocus (Brun et al, 1992).…”

Section: Modèle Atmosphérique Régional (Mar)mentioning

confidence: 99%

Eemian Greenland SMB strongly sensitive to model choice

et al. 2018

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Abstract. Understanding the behavior of the Greenland ice sheet in a warmer climate, and particularly its surface mass balance (SMB), is important for assessing Greenland's potential contribution to future sea level rise. The Eemian interglacial period, the most recent warmer-than-present period in Earth's history approximately 125 000 years ago, provides an analogue for a warm summer climate over Greenland. The Eemian is characterized by a positive Northern Hemisphere summer insolation anomaly, which complicates Eemian SMB calculations based on positive degree day estimates. In this study, we use Eemian global and regional climate simulations in combination with three types of SMB models – a simple positive degree day, an intermediate complexity, and a full surface energy balance model – to evaluate the importance of regional climate and model complexity for estimates of Greenland's SMB. We find that all SMB models perform well under the relatively cool pre-industrial and late Eemian. For the relatively warm early Eemian, the differences between SMB models are large, which is associated with whether insolation is included in the respective models. For all simulated time slices, there is a systematic difference between globally and regionally forced SMB models, due to the different representation of the regional climate over Greenland. We conclude that both the resolution of the simulated climate as well as the method used to estimate the SMB are important for an accurate simulation of Greenland's SMB. Whether model resolution or the SMB method is most important depends on the climate state and in particular the prevailing insolation pattern. We suggest that future Eemian climate model intercomparison studies should include SMB estimates and a scheme to capture SMB uncertainties.

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“…Several attempts to solve this paradox have been made by suggesting possible biases in the interpretation of the relationship between isotope ratio and temperature, which may not be assumed temporally and spatially constant (e.g. Merz et al, 2014;Sjolte et al, 2014;Steen-Larsen et al, 2014;Masson-Delmotte et al, 2015) or may be affected by changes in the precipitation regime and sea ice conditions (Merz et al, 2016;Pedersen et al, 2016). From a modelling point of view, the decisive question is over what spatial extent and when during the year the temperature reconstruction (and possible future reinterpretations) for the NEEM site should be assumed.…”

Section: Global Sea-level Changementioning

confidence: 99%

“…Several studies have therefore attempted to identify possible biases in the NEEM reconstructions (e.g. van de Merz et al, 2014Merz et al, , 2016Sjolte and Hoffmann, 2014;Steen-Larsen et al, 2014;Masson-Delmotte et al, 2015;Pedersen et al, 2016). Furthermore, the minimum extent and margin position of the north-eastern part of the ice sheet is not well constrained, leaving room for alternative retreat scenarios (e.g.…”

Section: Introductionmentioning

confidence: 99%

Last Interglacial climate and sea-level evolution from a coupled ice sheet-climate model

Goelzer¹,

Huybrechts²,

Loutre³

et al. 2016

Preprint

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Abstract. As the most recent warm period in Earth’s history with a sea-level stand higher than present, the Last Interglacial period (~130 to 115 kyr BP) is often considered a prime example to study the impact of a warmer climate on the two polar ice sheets remaining today. Here we simulate the Last Interglacial climate, ice sheet and sea-level evolution with the Earth system model of intermediate complexity LOVECLIM v.1.3, which includes dynamic and fully-coupled components representing the atmosphere, the ocean and sea ice, the terrestrial biosphere and the Greenland and Antarctic ice sheets. In this set-up, sea-level evolution and climate-ice sheet interactions are modelled in a consistent framework. Surface mass balance changes are the dominant forcing for the Greenland ice sheet, which shows a peak sea-level contribution of 1.4 m at 123 kyr BP in the reference experiment. Our results indicate that ice sheet-climate feedbacks play an important role to amplify climate and sea-level changes in the Northern Hemisphere. The sensitivity of the Greenland ice sheet to surface temperature changes considerably increases when interactive albedo changes are considered. Southern Hemisphere polar and sub-polar ocean warming is limited throughout the Last Interglacial and surface and sub-shelf melting exerts only a minor control on the Antarctic sea-level contribution with a peak of 4.4 m at 125 kyr BP. Retreat of the Antarctic ice sheet at the onset of the LIG is mainly forced by rising sea-level and reduced ice shelf viscosity as the surface temperature increases. Global sea level shows a peak of 5.3 m at 124.5 kyr BP, which includes a minor contribution of 0.35 m from oceanic thermal expansion. Neither the individual contributions nor the total modelled sea-level stand show multi millennial time scale variations as indicated by some reconstructions.

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Warm Greenland during the last interglacial: the role of regional changes in sea ice cover

Cited by 19 publications

References 54 publications

Attributing Greenland Warming Patterns to Regional Arctic Sea Ice Loss

Attributing Greenland Warming Patterns to Regional Arctic Sea Ice Loss

Eemian Greenland SMB strongly sensitive to model choice

Last Interglacial climate and sea-level evolution from a coupled ice sheet-climate model

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