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  • 2020-2023  (10)
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  • 1
    Publication Date: 2022-04-01
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 2
    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
    Publication Date: 2022-07-05
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
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  • 4
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    AMER METEOROLOGICAL SOC
    In:  EPIC3Journal of Climate, AMER METEOROLOGICAL SOC, 35(8), pp. 2373-2390, ISSN: 0894-8755
    Publication Date: 2022-07-05
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
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  • 5
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    In:  EPIC3EGU General Assembly 2022, 2022-05-23-2022-05-27
    Publication Date: 2022-10-04
    Description: The Sea Ice Drift Forecast Experiment (SIDFEx) database comprises more than 180,000 forecasts for trajectories of single sea-ice buoys in the Arctic and Antarctic, collected since 2017. SIDFEx is a community effort originating from the Year Of Polar Prediction. Forecasts are provided by various forecast centres and collected, and archived by the Alfred Wegener Institute (AWI). AWI provides a dedicated software package and an interactive online platform for analysing the forecasts. Their lead times range from daily to seasonal scales. Among the buoys targeted by SIDFEx are the buoys of the Distributed Network (DN) array which was deployed during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. In this contribution, we show to what extent the deformation (divergence, shear and vorticity) of the DN can be forecasted by the SIDFEx forecasts. We investigate the performance of single models as well as a consensus forecast which merges the single forecasts to a seamless best-guess forecast.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 6
    Publication Date: 2022-10-04
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 7
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    In:  EPIC3EGU General Assembly, Vienna, 2022Impact of the atmospheric circulation on the Arctic snow cover and ice thickness variability 
    Publication Date: 2022-10-04
    Description: The Arctic sea ice cover and thickness have significantly declined since the 1970s, while exhibiting large interannual variability. Snow cover on sea ice, acting as an insulating barrier, was shown to be instrumental in driving the variability and trends in sea-ice thickness. Yet, the Arctic snow depth remains scarcely measured and overlooked in climate models, which translates to “very limited predictive skill” according to the IPCC (Special Report on the Ocean and Cryosphere in a Changing Climate). Moreover, sea-ice thickness initialization has been shown to be an important element for skilful sea-ice forecasts, and it appears plausible that the same holds for the snow layer on top. Here, we investigate the role of atmospheric circulation anomalies in shaping the Arctic snow-cover and sea-ice thickness anomalies. In this preparatory work, spectral nudging of the large-scale atmospheric circulation towards ERA5 reanalysis data is applied to the fully coupled AWI Climate Model (AWI-CM-3). We examine the variability and trends of Arctic snowfall, snow depth, sea ice cover and thickness over a 42-year period (1979-2021), and in particular the reproduction of observed anomalies. Two nudging configurations are used, differing in strength by their relaxation timescale τ and spectral truncation wavenumber T (namely τ=24 h, T20 and τ=1 h, T159). We demonstrate the importance of atmospheric circulation anomalies in shaping variations of snow and ice thickness at sub-seasonal to interannual scales, and discuss the potential of spectral nudging as a tool to improve the initialization of sea ice forecasts.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 8
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    Wiley
    In:  EPIC3Journal of Geophysical Research-Oceans, Wiley, 126(12), pp. e2021JC017633, ISSN: 0148-0227
    Publication Date: 2022-06-29
    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.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
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  • 9
    Publication Date: 2022-06-29
    Description: We developed a new version of the Alfred Wegener Institute Climate Model (AWI-CM3), which has higher skills in representing the observed climatology and better computational efficiency than its predecessors. Its ocean component FESOM2 has the multi-resolution functionality typical for unstructured-mesh models while still featuring a scalability and efficiency similar to regular-grid models. The atmospheric component OpenIFS (CY43R3) enables the use of latest developments in the numerical weather prediction community in climate sciences. In this paper we describe the coupling of the model components and evaluate the model performance on a variable resolution (25–125 km) ocean mesh and a 61 km atmosphere grid, which serves as a reference and starting point for other on-going research activities with AWI-CM3. This includes the exploration of high and variable resolution, the development of a full Earth System Model as well as the creation of a new sea ice prediction system. At this early development stage and with the given coarse to medium resolutions, the model already features above CMIP6-average skills in representing the climatology and competitive model throughput. Finally we identify remaining biases and suggest further improvements to be made to the model.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
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  • 10
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    In:  EPIC3Journal of Geophysical Research: Oceans, 126(12), ISSN: 2169-9275
    Publication Date: 2022-11-07
    Description: Accelerated loss of the sea-ice cover and increased human activities in the Arctic emphasize the need for skillful prediction of sea-ice conditions at subseasonal to seasonal (S2S) timescales. To assess the quality of predictions, dynamical forecast systems can be benchmarked against reference forecasts based on present and past observations of the ice edge. However, the simplest types of reference forecasts—persistence of the present state and climatology—do not exploit the observations optimally and thus lead to an overestimation of forecast skill. For spatial objects such as the ice-edge location, the development of damped-persistence forecasts that combine persistence and climatology in a meaningful way poses a challenge. We have developed a probabilistic reference forecast method that combines the climatologically derived probability of ice presence with initial anomalies of the ice-edge location, both derived from satellite sea-ice concentration data. No other observations, such as sea-surface temperature or sea-ice thickness, are used. We have tested and optimized the method based on minimization of the Spatial Probability Score. The resulting Spatial Damped Anomaly Persistence forecasts clearly outperform both simple persistence and climatology at subseasonal timescales. The benchmark is about as skillful as the best-performing dynamical forecast system in the S2S database. Despite using only sea-ice concentration observations, the method provides a challenging benchmark to assess the added value of dynamical forecast systems.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
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