Sea Ice Targeted Geoengineering Can Delay Arctic Sea Ice Decline but not Global Warming

Zampieri, Lorenzo; Goessling, Helge

doi:10.1029/2019ef001230

Cited by 17 publications

(21 citation statements)

References 45 publications

(48 reference statements)

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“…Surface albedo changes, in particular in the polar regions where sea ice declines, are projected to contribute substantially to a strong positive shortwave feedback. Note however that a recent geoengineering study based on AWI-CM indicates a small impact of the Arctic ice-albedo feedback on temperatures outside the Arctic (Zampieri & Goessling, 2019).…”

Section: Discussionmentioning

confidence: 95%

Simulations for CMIP6 with the AWI climate model AWI-CM-1-1

Semmler

Danilov

Gierz

et al. 2020

Preprint

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The Alfred Wegener Institute Climate Model (AWI-CM) participates for the first time in the Coupled Model Intercomparison Project (CMIP), CMIP6. The sea ice-ocean component, FESOM, runs on an unstructured mesh with horizontal resolutions ranging from 8 to 80 km. FESOM is coupled to the Max Planck Institute atmospheric model ECHAM 6.3 at a horizontal resolution of about 100 km. Using objective performance indices, it is shown that AWI-CM performs better than the average of CMIP5 models. AWI-CM shows an equilibrium climate sensitivity of 3.2°C, which is similar to the CMIP5 average, and a transient climate response of 2.1°C which is slightly higher than the CMIP5 average. The negative trend of Arctic sea-ice extent in September over the past 30 years is 20-30% weaker in our simulations compared to observations. With the strongest emission scenario, the AMOC decreases by 25% until the end of the century which is less than the CMIP5 average of 40%. Patterns and even magnitude of simulated temperature and precipitation changes at the end of this century compared to present-day climate under the strong emission scenario SSP585 are similar to the multi-model CMIP5 mean. The simulations show a 11°C warming north of the Barents Sea and around 2°C to 3°C over most parts of the ocean as well as a wetting of the Arctic, subpolar, tropical, and Southern Ocean. Furthermore, in the northern middle latitudes in boreal summer and autumn as well as in the southern middle latitudes, a more zonal atmospheric flow is projected throughout the year.Plain Language Summary The Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI) participates for the first time with a global climate model in the Coupled Model Intercomparison Project 6 (CMIP6). The results of CMIP6 and previous model comparison projects feed into the next assessment report of the Intergovernmental Panel on Climate Change (IPCC). The IPCC assessment reports include information on past and expected climate change in the future and is written for policy-and decision-makers as well as for the general public. The main characteristics of the AWI climate model are described and compared to models from previous intercomparison projects. The projected global warming in AWI-CM is similar to the average warming predicted by climate models in the previous intercomparison project. However, the Arctic sea-ice extent declines faster than typical previous estimates. Areas that are wet in present-day climate become wetter, and areas that are dry in present-day climate become drier in the future-consistent with previous climate model simulations. The ocean currents remain rather stable in the AWI climate projections, which leads to a continued warm Gulf stream and therefore an only slightly reduced warming of the North Atlantic and parts of Europe compared to other middle-latitude regions.

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Section: Discussionmentioning

confidence: 95%

Simulations for CMIP6 with the AWI climate model AWI-CM-1-1

Semmler

Danilov

Gierz

et al. 2020

Preprint

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“…Increasing Arctic sea ice simply by pumping sea water to the surface and allowing it to freeze was examined in detail by Desch et al (2017). Further modelling (Zampieri and Goessling, 2019) suggests it would in principle be feasible to increase ice thickness, and Desch et al (2017) estimate that a 1m increase in thickness over 10% of the Arctic using local wind power from buoy-mounted turbines would cost about $50 billion per year. However, Zampieri and Goessling (2019) report no cooling of lower latitudes in simulations using the Alfred Wegener Institute Climate Model as a consequence of the intervention in the ice-albedo feedback, and hence 'cast doubt on the potential of sea ice targeted geoengineering as a meaningful contribution to mitigate climate change' (p. 8).…”

Section: Arctic Sea Ice Managementmentioning

confidence: 99%

Targeted Geoengineering: Local Interventions with Global Implications

et al. 2020

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Targeted geoengineering aims to tackle a global scale impact of climate warming by addressing local or regional systemic interventions. We consider three examples: conserving the West Antarctic ice sheet by limiting rates of ice discharge or increasing snow accumulation, thereby reducing global sea level rise; transforming the Arctic permafrost zone into steppe grassland; raising the albedo of Arctic sea ice. There are important differences between targeted interventions and archetypal solar geoengineering, which ideally would have global governance structures, while some targeted interventions may be done entirely under the accepted purview of small numbers of nation states. For example, the West Antarctic ice sheet is governed by the consultative members of the Antarctic Treaty. Of the interventions we look at, only ice sheet conservation seems viable and efficient relative to solar geoengineering. Many important treaties and conventions rely on the precautionary approach. While at first glance this principle seems to argue against targeted interventions, we argue that it may in fact do the opposite. Given the existence of irreversible thresholds in many natural systems, the precautionary approach may be better upheld by a targeted intervention that prevents a system from changing in ways that cannot be undone.

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“…The availability of a more detailed sea‐ice description in a fully coupled setup will enable a better understanding of the interactions between a warming atmosphere and sea ice. At the same time, the new coupled configuration will allow us to perform sea ice‐oriented climate modeling studies (e.g., Zampieri & Goessling 2019) under more physically realistic assumptions. Finally, FESOM2‐Icepack will be integrated in the Seamless Sea Ice Prediction System (SSIPS; Mu et al., 2020) and thus equipped with the Parallel Data Assimilation Framework (PDAF; Nerger & Hiller, 2013) for assimilating ocean and sea‐ice observations with an Ensemble Kalman Filter.…”

Section: Discussionmentioning

confidence: 99%

“…However, in the framework of the Coupled Model Intercomparison Project (CMIP), the SIMIP Community (2020) (Sea Ice Model Intercomparison Project) shows that it is unclear to what degree differences between CMIP6, CMIP5, and CMIP3 sea-ice simulations are caused by better model physics versus other changes in the forcing. In the field of subseasonal and seasonal sea-ice forecasting, simple dynamical models exhibit predictive skills comparable to or even better than those of more complex forecast systems (Zampieri et al, 2018(Zampieri et al, , 2019, suggesting that the yeartoyear variability, the skill of the atmospheric models, and the quality of initial conditions dominate the variation in ensemble prediction success (Stroeve et al, 2014). In conclusion, to what extent the model complexity impacts the quality of sea-ice simulations remains an open question (Blockley et al, 2020) always evolving with our models.…”

Section: Introductionmentioning

confidence: 99%

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Impact of Sea‐Ice Model Complexity on the Performance of an Unstructured‐Mesh Sea‐Ice/Ocean Model under Different Atmospheric Forcings

Zampieri

Kauker

Fröhle

et al. 2021

J Adv Model Earth Syst

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We have equipped the unstructured-mesh global sea-ice and ocean model FESOM2 with a set of physical parameterizations derived from the single-column sea-ice model Icepack. The update has substantially broadened the range of physical processes that can be represented by the model. The new features are directly implemented on the unstructured FESOM2 mesh, and thereby benefit from the flexibility that comes with it in terms of spatial resolution. A subset of the parameter space of three model configurations, with increasing complexity, has been calibrated with an iterative Green's function optimization method to test the impact of the model update on the sea-ice representation. Furthermore, to explore the sensitivity of the results to different atmospheric forcings, each model configuration was calibrated separately for the NCEP-CFSR/CFSv2 and ERA5 forcings. The results suggest that a complex model formulation leads to a better agreement between modeled and the observed sea-ice concentration and snow thickness, while differences are smaller for sea-ice thickness and drift speed. However, the choice of the atmospheric forcing also impacts the agreement of the FESOM2 simulations and observations, with NCEP-CFSR/CFSv2 being particularly beneficial for the simulated sea-ice concentration and ERA5 for sea-ice drift speed. In this respect, our results indicate that parameter calibration can better compensate for differences among atmospheric forcings in a simpler model (i.e. sea-ice has no heat capacity) than in more realistic formulations with a prognostic ice thickness distribution and sea ice enthalpy.

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Sea Ice Targeted Geoengineering Can Delay Arctic Sea Ice Decline but not Global Warming

Cited by 17 publications

References 45 publications

Simulations for CMIP6 with the AWI climate model AWI-CM-1-1

Simulations for CMIP6 with the AWI climate model AWI-CM-1-1

Targeted Geoengineering: Local Interventions with Global Implications

Impact of Sea‐Ice Model Complexity on the Performance of an Unstructured‐Mesh Sea‐Ice/Ocean Model under Different Atmospheric Forcings

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