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  • 1
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    Sea‐Ice Forecasts With an Upgraded AWI Coupled Prediction System (2022)
    Mu, Longjiang ; Nerger, Lars ; Streffing, Jan ; [et al.]
    Details
    Publication Date: 2024-02-05
    Description: A new version of the AWI Coupled Prediction System is developed based on the Alfred Wegener Institute Climate Model v3.0. Both the ocean and the atmosphere models are upgraded or replaced, reducing the computation time by a factor of 5 at a given resolution. This allowed us to increase the ensemble size from 12 to 30, maintaining a similar resolution in both model components. The online coupled data assimilation scheme now additionally utilizes sea‐surface salinity and sea‐level anomaly as well as temperature and salinity profile observations. Results from the data assimilation demonstrate that the sea‐ice and ocean states are reasonably constrained. In particular, the temperature and salinity profile assimilation has mitigated systematic errors in the deeper ocean, although issues remain over polar regions where strong atmosphere‐ocean‐ice interaction occurs. One‐year‐long sea‐ice forecasts initialized on 1 January, 1 April, 1 July and 1 October from 2003 to 2019 are described. To correct systematic forecast errors, sea‐ice concentration from 2011 to 2019 is calibrated by trend‐adjusted quantile mapping using the preceding forecasts from 2003 to 2010. The sea‐ice edge raw forecast skill is within the range of operational global subseasonal‐to‐seasonal forecast systems, outperforming a climatological benchmark for about 2 weeks in the Arctic and about 3 weeks in the Antarctic. The calibration is much more effective in the Arctic: Calibrated sea‐ice edge forecasts outperform climatology for about 45 days in the Arctic but only 27 days in the Antarctic. Both the raw and the calibrated forecast skill exhibit strong seasonal variations.
    Description: Plain Language Summary: Ocean data sparseness and systematic model errors pose problems for the initialization of coupled seasonal forecasts, especially in polar regions. Our global forecast system follows a seamless approach with refined ocean resolution in the Arctic. The new version presented here features higher computational efficiency and utilizes more ocean and sea‐ice observations. Ice‐edge forecasts outperform a climatological benchmark for about 1 month, comparable to established systems.
    Description: Key Points: We describe an upgrade of the AWI Coupled Prediction System with new ocean and atmosphere models and more observations assimilated. Independent evaluations show advances in the new version on the analysis of the sea‐ice and ocean states against the old one. Calibrated sea‐ice edge forecasts outperform a climatological benchmark for around 1 month in both hemispheres.
    Description: National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Description: Deutsche Forschungsgemeinschaft
    Description: https://doi.org/10.5281/zenodo.6335383
    Description: https://github.com/FESOM/fesom2/releases/tag/AWI-CM3_v3.0
    Description: https://doi.org/10.5281/zenodo.6335498
    Description: https://oasis.cerfacs.fr/en/
    Description: https://doi.org/10.5281/zenodo.4905653
    Description: http://forge.ipsl.jussieu.fr/ioserver
    Description: https://doi.org/10.5281/zenodo.6335474
    Description: http://pdaf.awi.de/
    Description: https://doi.org/10.5281/zenodo.6481116
    Keywords: ddc:551.6 ; seamless sea ice forecast ; multivariate data assimilation ; forecast calibration ; spatial probability score
    Language: English
    Type: doc-type:article
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  • 2
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    Ocean Model Formulation Influences Transient Climate Response (2021)
    Details
    Publication Date: 2022-04-01
    Description: The transient climate response (TCR) is 20% higher in the Alfred Wegener Institute Climate Model (AWI‐CM) compared to the Max Planck Institute Earth System Model (MPI‐ESM) whereas the equilibrium climate sensitivity (ECS) is by up to 10% higher in AWI‐CM. These results are largely independent of the two considered model resolutions for each model. The two coupled CMIP6 models share the same atmosphere‐land component ECHAM6.3 developed at the Max Planck Institute for Meteorology (MPI‐M). However, ECHAM6.3 is coupled to two different ocean models, namely the MPIOM sea ice‐ocean model developed at MPI‐M and the FESOM sea ice‐ocean model developed at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI). A reason for the different TCR is related to ocean heat uptake in response to greenhouse gas forcing. Specifically, AWI‐CM simulations show stronger surface heating than MPI‐ESM simulations while the latter accumulate more heat in the deeper ocean. The vertically integrated ocean heat content is increasing slower in AWI‐CM model configurations compared to MPI‐ESM model configurations in the high latitudes. Weaker vertical mixing in AWI‐CM model configurations compared to MPI‐ESM model configurations seems to be key for these differences. The strongest difference in vertical ocean mixing occurs inside the Weddell and Ross Gyres and the northern North Atlantic. Over the North Atlantic, these differences materialize in a lack of a warming hole in AWI‐CM model configurations and the presence of a warming hole in MPI‐ESM model configurations. All these differences occur largely independent of the considered model resolutions.
    Description: Plain Language Summary: The transient climate response (TCR) describes how strongly near‐surface temperatures warm in response to gradually increasing greenhouse‐gas levels. Here we investigate the role of the ocean which takes up heat and thereby delays the surface warming. Two models of the Coupled Model Intercomparison Project Phase 6 (CMIP6), the Alfred Wegener Institute Climate Model (AWI‐CM) and the Max Planck Institute Earth System Model (MPI‐ESM), which use the same atmosphere model but different ocean models are selected for this study. In AWI‐CM the upper ocean layers heat faster than in MPI‐ESM, while the opposite is true for the deep ocean. As a consequence, the TCR is 20% stronger in AWI‐CM compared to MPI‐ESM. We find that weaker vertical ocean mixing in AWI‐CM compared to MPI‐ESM, especially over the northern North Atlantic and the Weddell and Ross Gyres, is key for these differences. Our findings corroborate the importance of realistic ocean mixing in climate models when it comes to getting the strength and timing of climate change right.
    Description: Key Points: The transient climate response in two coupled models with the same atmosphere but different ocean components differs by 20%. The upper (deeper) ocean heats faster (slower) in AWI‐CM compared to MPI‐ESM, independent of model resolution. Vertical mixing in the northern North Atlantic and the Weddell and Ross Gyres appears to be key for these differences.
    Description: Bundesministerium für Bildung und Forschung (BMBF) http://dx.doi.org/10.13039/501100002347
    Description: German Climate Computing Centre (DKRZ)
    Description: Federal Ministry of Education and Research of Germany
    Description: Helmholtz Association http://dx.doi.org/10.13039/501100009318
    Description: https://esgf-data.dkrz.de/projects/cmip6-dkrz/
    Keywords: ddc:551.6
    Language: English
    Type: doc-type:article
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  • 3
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    Sea Ice Targeted Geoengineering Can Delay Arctic Sea Ice Decline but not Global Warming (2021)
    Details
    Publication Date: 2021-07-22
    Description: To counteract global warming, a geoengineering approach that aims at intervening in the Arctic ice-albedo feedback has been proposed. A large number of wind-driven pumps shall spread seawater on the surface in winter to enhance ice growth, allowing more ice to survive the summer melt. We test this idea with a coupled climate model by modifying the surface exchange processes such that the physical effect of the pumps is simulated. Based on experiments with RCP 8.5 scenario forcing, we find that it is possible to keep the late-summer sea ice cover at the current extent for the next ∼60 years. The increased ice extent is accompanied by significant Arctic late-summer cooling by ∼1.3 K on average north of the polar circle (2021–2060). However, this cooling is not conveyed to lower latitudes. Moreover, the Arctic experiences substantial winter warming in regions with active pumps. The global annual-mean near-surface air temperature is reduced by only 0.02 K (2021–2060). Our results cast doubt on the potential of sea ice targeted geoengineering to mitigate climate change.
    Keywords: 551.68 ; sea ice ; geoengineering ; Arctic sea ice decline ; global warming ; ice-albedo feedback ; sea ice modeling
    Language: English
    Type: article
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  • 4
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    Predictability of Antarctic Sea Ice Edge on Subseasonal Time Scales (2021)
    Details
    Publication Date: 2021-09-24
    Description: Coupled subseasonal forecast systems with dynamical sea ice have the potential of providing important predictive information in polar regions. Here, we evaluate the ability of operational ensemble prediction systems to predict the location of the sea ice edge in Antarctica. Compared to the Arctic, Antarctica shows on average a 30% lower skill, with only one system remaining more skillful than a climatological benchmark up to ∼30 days ahead. Skill tends to be highest in the west Antarctic sector during the early freezing season. Most of the systems tend to overestimate the sea ice edge extent and fail to capture the onset of the melting season. All the forecast systems exhibit large initial errors. We conclude that subseasonal sea ice predictions could provide marginal support for decision-making only in selected seasons and regions of the Southern Ocean. However, major progress is possible through investments in model development, forecast initialization and calibration.
    Keywords: 551.343 ; sea ice prediction ; sea ice edge ; Antarctica ; Southern Ocean ; S2S time scale
    Language: English
    Type: map
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