Impact of prescribed Arctic sea ice thickness in simulations of the present and future climate

Krinner, Gerhard; Rinke, Annette; Dethloff, Klaus; Gorodetskaya, Irina

doi:10.1007/s00382-009-0587-7

Cited by 22 publications

(35 citation statements)

References 43 publications

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“…However, we have seen that the frequency distribution of future SIC obtained using this method is different from the original distribution in the AOGCM and unavoidably exhibits some peaks due to the structure of LUT (Figure 7). Moreover, 10 the absence of SIC above 90% in the Antarctic is also a considerable limitation to the method considering the large differences in terms of heat and moisture exchanges in winter between an ocean fully covered by sea-ice and an ocean that exhibits some ice-free channels (Krinner et al, 2010). In addition, the use of SST as a proxy for SIC is physically questionable, as we should expect a large SIC gradient around the freezing point.…”

Section: Sea-ice Concentrationmentioning

confidence: 99%

“…Gerdes (2006) and Krinner et al (2010) have shown that the atmospheric response to changes in Arctic sea-ice thickness is substantial. In most AGCMs, sea-ice thickness will also need to be prescribed along with sea-surface temperature and sea-ice concentration.…”

Section: A Note On Sea-ice Thicknessmentioning

confidence: 99%

“…evaluation and further refinement of a simple parameterization of sea-ice thickness as a function of instantaneous and annual minimum SIC, initially suggested by Krinner et al (1997) and used by Krinner et al (2010), is presented in the supplementary 10 material of this paper.…”

Section: A Note On Sea-ice Thicknessmentioning

confidence: 99%

“…FORTRAN code enabling the generation of bias-corrected future SST and SIC using CMIP5 scenarios and (Gerdes, 2006;Krinner et al, 2010;Semmler et al, 2016). Gerdes (2006) concluded that "realistic sea ice thickness changes can induce atmospheric signals that are of similar magnitude as those due to changes in sea ice cover", while Krinner et al (2010) show that the impact of a variable sea-ice thickness compared to a uniform value is essentially limited to the cold seasons and the lower troposphere, and that sea-ice thickness changes have a significant impact 5 also in the context of climate change simulations. Near-surface temperature changes of the order of a few°C are observed in response to the replacement of a uniform thick Arctic sea-ice cover by variable sea-ice thickness.…”

mentioning

confidence: 99%

“…As described by Krinner et al (2010), the parameterization of sea-ice thickness h S as a function of the local instantaneous sea-ice fraction f is designed such as to yield h S of the order of 3 meters for multi-year sea ice (deemed to be dominant when the local annual minimum fraction f min 0) and h S below 60cm (with a stronger annual cycle) in regions where sea-ice completely disappears in summer (that is, f min = 0), and intermediate values for intermediate cases:…”

mentioning

confidence: 99%

See 4 more Smart Citations

Assessing bias-corrections of oceanic surface conditions for atmospheric models

Beaumet¹,

Krinner²,

Déqué³

et al. 2017

Preprint

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Abstract. Future sea-surface temperature and sea-ice concentration from coupled ocean-atmosphere general circulation models such as those from the CMIP5 experiment are often used as boundary forcing for the downscaling of future climate experiment.Yet, these models show some considerable biases when compared to the observations over present climate. In this paper, existing methods such as an absolute anomaly and a quantile-quantile method for sea surface temperature (SST) as well as a look-up table and a relative anomaly method for sea-ice concentration (SIC) are presented. For SIC, we also propose a new 5 analog method. Each method is objectively evaluated with a perfect model test using CMIP5 model experiment and some real-case applications using observations. With respect to other previously existing methods for SIC, the analog method is a substantial improvement for the bias correction of future sea-ice concentrations.

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Section: Sea-ice Concentrationmentioning

confidence: 99%

Section: A Note On Sea-ice Thicknessmentioning

confidence: 99%

Section: A Note On Sea-ice Thicknessmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Assessing bias-corrections of oceanic surface conditions for atmospheric models

Beaumet¹,

Krinner²,

Déqué³

et al. 2017

Preprint

Self Cite

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show abstract

Sea ice thickness and recent Arctic warming

Lang

Yang

Kaas

2017

Geophysical Research Letters

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The climatic impact of increased Arctic sea ice loss has received growing attention in the last years. However, little focus has been set on the role of sea ice thickness, although it strongly determines surface heat fluxes. Here ensembles of simulations using the EC‐Earth atmospheric model (Integrated Forecast System) are performed and analyzed to quantify the atmospheric impacts of Arctic sea ice thickness change since 1982 as revealed by the sea ice model assimilation Global Ice‐Ocean Modeling and Assimilation System. Results show that the recent sea ice thinning has significantly affected the Arctic climate, while remote atmospheric responses are less pronounced owing to a high internal atmospheric variability. Locally, the sea ice thinning results in enhancement of near‐surface warming of about 1°C per decade in winter, which is most pronounced over marginal sea ice areas with thin ice. This leads to an increase of the Arctic amplification factor by 37%.

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Influence of the Arctic on the Predictability of Eurasian Winter Extreme Weather Events

Dai

2020

Adv. Atmos. Sci.

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The linkage between the Arctic and midlatitudes has received much attention recently due to the rapidly changing climate. Many investigations have been conducted to reveal the relationship between the Arctic and Eurasian extreme events from the perspective of climatological statistics. As a prediction source for extreme events in Eurasia, Arctic conditions are crucial for extreme event predictions. Therefore, it is urgent to explore the Arctic influence on the predictability of Eurasian extreme events due to the large uncertainties in Arctic conditions. Considering the sensitivity and nonlinearity of the atmospheric circulations in midlatitude to Arctic conditions, it is necessary to investigate the Arctic influences on Eurasian extreme weather events in case studies at weather time scales. Previous studies indicate that only perturbations in specific patterns have fast growth. Thus, the conditional nonlinear optimal perturbation approach is recommended for exploring the uncertainties in Arctic initial and boundary conditions and their synergistic effect on Eurasian extreme events. Moreover, the mechanism for extreme event formation may differ in different cases. Therefore, more extreme cases should be investigated to reach robust conclusions.

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Impact of prescribed Arctic sea ice thickness in simulations of the present and future climate

Cited by 22 publications

References 43 publications

Assessing bias-corrections of oceanic surface conditions for atmospheric models

Assessing bias-corrections of oceanic surface conditions for atmospheric models

Sea ice thickness and recent Arctic warming

Influence of the Arctic on the Predictability of Eurasian Winter Extreme Weather Events

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