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- Koenigk, Torben, et al.
(författare)
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Impact of Arctic sea ice variations on winter temperature anomalies in northern hemispheric land areas
- 2019
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Ingår i: Climate Dynamics. - : Springer Science and Business Media LLC. - 0930-7575 .- 1432-0894. ; 52:5-6, s. 3111-3137
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Tidskriftsartikel (refereegranskat)abstract
- Coordinated numerical ensemble experiments with six different state-of-the-art atmosphere models have been used in order to evaluate the respective impact of the observed Arctic sea ice and sea surface temperature (SST) variations on air temperature variations in mid and high latitude land areas. Two sets of experiments have been designed; in the first set (EXP1), observed daily sea ice concentration and SST variations are used as lower boundary forcing over 1982-2014 while in the second set (EXP2) the SST variations are replaced by the daily SST climatology. The observed winter 2m air temperature (T2m) variations are relatively well reproduced in a number of mid and high latitude land areas in EXP1, with best agreement in southwestern North America and northern Europe. Sea ice variations are important for the interannual T2m variations in northern Europe but have limited impact on all other mid and high latitude land regions. In particular, sea ice variations do not contribute to the observed opposite variations in the Arctic and mid latitude in our model experiments. The spread across ensemble members is large and many ensemble members are required to reproduce the observed T2m variations over northern Europe in our models. The amplitude of T2m anomalies in the coldest observed winters over northern Europe is not reproduced by our multi-model ensemble means. However, the sea ice conditions in these respective winters and mainly the thermodynamic response to the ice anomalies lead to an enhanced likelihood for occurrence of colder than normal winters and extremely cold winters. Still, the main reason for the observed extreme cold winters is internal atmospheric dynamics. The coldest simulated northern European winters in EXP1 and EXP2 between 1982 and 2014 show the same large scale T2m and atmospheric circulation anomaly patterns as the observed coldest winters, indicating that the models are well able to reproduce the processes, which cause these cold anomalies. The results are robust across all six models used in this study.
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2. |
- Akperov, M., et al.
(författare)
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Trends of intense cyclone activity in the Arctic from reanalyses data and regional climate models (Arctic-CORDEX)
- 2019. - 1
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Ingår i: Turbulence, Atmosphere and Climate Dynamics. - : IOP Publishing. - 1755-1307. ; 231
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Konferensbidrag (refereegranskat)abstract
- The ability of state-of-the-art regional climate models (RCMs) to simulate the trends of intense cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic-CORDEX initiative. Some models employ large-scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble in winter and summer are compared with the results from four reanalyses (ERA-Interim, NCEP-CFSR, NASA-MERRA2 and JMA-JRA55) in winter and summer for 1981-2010 period.
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3. |
- Zhang, W., et al.
(författare)
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The Interplay of Recent Vegetation and Sea Ice Dynamics—Results From a Regional Earth System Model Over the Arctic
- 2020
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Ingår i: Geophysical Research Letters. - 0094-8276. ; 47:6
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Tidskriftsartikel (refereegranskat)abstract
- Recent accelerated warming over the Arctic coincides with sea ice reduction and shifting patterns of land cover. We use a state-of-the-art regional Earth system model, RCAO-GUESS, which comprises a dynamic vegetation model (LPJ-GUESS), a regional atmosphere model (RCA), and an ocean sea ice model (RCO), to explore the dynamic coupling between vegetation and sea ice during 1989–2011. Our results show that RCAO-GUESS captures recent trends in observed sea ice concentration and extent, with the inclusion of vegetation dynamics resulting in larger, more realistic variations in summer and autumn than the model that does not account for vegetation dynamics. Vegetation feedbacks induce concomitant changes in downwelling longwave radiation, near-surface temperature, mean sea level pressure, and sea ice reductions, suggesting a feedback chain linking vegetation change to sea ice dynamics. This study highlights the importance of including interactive vegetation dynamics in modeling the Arctic climate system, particularly when predicting sea ice dynamics.
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