| 1. |
- Olonscheck, Dirk, et al.
(författare)
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Arctic sea-ice variability is primarily driven by atmospheric temperature fluctuations
- 2019
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Ingår i: Nature Geoscience. - : Springer Science and Business Media LLC. - 1752-0894 .- 1752-0908. ; 12:6, s. 430-434
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Tidskriftsartikel (refereegranskat)abstract
- The anthropogenically forced decline of Arctic sea ice is superimposed on strong internal variability. Possible drivers for this variability include fluctuations in surface albedo, clouds and water vapour, surface winds and poleward atmospheric and oceanic energy transport, but their relative contributions have not been quantified. By isolating the impact of the individual drivers in an Earth system model, we here demonstrate that internal variability of sea ice is primarily caused directly by atmospheric temperature fluctuations. The other drivers together explain only 25% of sea-ice variability. The dominating impact of atmospheric temperature fluctuations on sea ice is consistent across observations, reanalyses and simulations from global climate models. Such atmospheric temperature fluctuations occur due to variations in moist-static energy transport or local ocean heat release to the atmosphere. The fact that atmospheric temperature fluctuations are the key driver for sea-ice variability limits prospects of interannual predictions of sea ice, and suggests that observed record lows in Arctic sea-ice area are a direct response to an unusually warm atmosphere.
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| 2. |
- Mauritsen, Thorsten, et al.
(författare)
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Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and Its Response to Increasing CO2
- 2019
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 11:4, s. 998-1038
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Tidskriftsartikel (refereegranskat)abstract
- A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI-ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low-level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO2 forcing, which nonetheless can be represented by a simple two-layer model.
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| 3. |
- Notz, Dirk, et al.
(författare)
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Arctic Sea Ice in CMIP6
- 2020
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Ingår i: Geophysical Research Letters. - 0094-8276 .- 1944-8007. ; 47:10
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Tidskriftsartikel (refereegranskat)abstract
- We examine CMIP6 simulations of Arctic sea‐ice area and volume. We find that CMIP6 models produce a wide spread of mean Arctic sea‐ice area, capturing the observational estimate within the multimodel ensemble spread. The CMIP6 multimodel ensemble mean provides a more realistic estimate of the sensitivity of September Arctic sea‐ice area to a given amount of anthropogenic CO2 emissions and to a given amount of global warming, compared with earlier CMIP experiments. Still, most CMIP6 models fail to simulate at the same time a plausible evolution of sea‐ice area and of global mean surface temperature. In the vast majority of the available CMIP6 simulations, the Arctic Ocean becomes practically sea‐ice free (sea‐ice area <1 × 106 km2) in September for the first time before the Year 2050 in each of the four emission scenarios SSP1‐1.9, SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5 examined here.
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