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  • 1
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    Improving the ocean and atmosphere in a coupled ocean–atmosphere model by assimilating satellite sea‐surface temperature and subsurface profile data (2020)
    Wiley
    Details
    Publication Date: 2020-09-14
    Print ISSN: 0035-9009
    Electronic ISSN: 1477-870X
    Topics: Geography , Physics
    Published by Wiley
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  • 2
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    Influence of a salt plume parameterization in a coupled climate model (2018)
    Wiley
    In:  EPIC3Journal of Advances in Modeling Earth Systems, Wiley, ISSN: 1942-2466
    Details
    Publication Date: 2019-04-11
    Description: Sea ice formation is accompanied by the rejection of salt which in nature tends to be mixed vertically by the formation of convective plumes. Here we analyze the influence of a salt plume parameterization (SPP) in an atmosphere-sea ice-ocean model. Two 330 years long simulations have been conducted with the AWI Climate Model. In the reference simulation, the rejected salt in the Arctic Ocean is added to the upper-most ocean layer. This approach is commonly used in climate modelling. In another experiment, employing SPP, the rejected salt is vertically redistributed within the mixed layer based on a power law profile that mimics the penetration of salt plumes. We discuss the effects of this redistribution on the simulated mean state and on atmosphere-ocean linkages associated with the intensity of deep water formation. We find that the salt plume parametrization leads to simultaneous increase of sea ice (volume and concentration) and decrease of sea surface salinity in the Arctic. The SPP considerably alters the interplay between the atmosphere and the ocean in the Nordic Seas. The parameterization modifies the ocean ventilation; however, resulting changes in temperature and salinity largely compensate each other in terms of density so that the overturning circulation is not significantly affected.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 3
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    Fast EVP Solutions in a High‐Resolution Sea Ice Model (2019)
    Wiley
    In:  EPIC3Journal of Advances in Modeling Earth Systems, Wiley, ISSN: 1942-2466
    Details
    Publication Date: 2020-08-27
    Description: Sea ice dynamics determine the drift and deformation of sea ice. Nonlinear physics, usually expressed in a viscous‐plastic rheology, makes the sea ice momentum equations notoriously difficult to solve. At increasing sea ice model resolution the nonlinearities become stronger as linear kinematic features (leads) appear in the solutions. Even the standard elastic‐viscous‐plastic (EVP) solver for sea ice dynamics, which was introduced for computational efficiency, becomes computationally very expensive, when accurate solutions are required, because the numerical stability requires very short, and hence more, subcycling time steps at high resolution. Simple modifications to the EVP solver have been shown to remove the influence of the number of subcycles on the numerical stability. At low resolution appropriate solutions can be obtained with only partial convergence based on a significantly reduced number of subcycles as long as the numerical procedure is kept stable. This previous result is extended to high resolution where linear kinematic features start to appear. The computational cost can be strongly reduced in Arctic Ocean simulations with a grid spacing of 4.5 km by using modified and adaptive EVP versions because fewer subcycles are required to simulate sea ice fields with the same characteristics as with the standard EVP.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 4
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    Evaluation of FESOM2.0 Coupled to ECHAM6.3: Preindustrial and HighResMIP Simulations (2019)
    Wiley
    In:  EPIC3Journal of Advances in Modeling Earth Systems, Wiley, 11(11), pp. 3794-3815, ISSN: 1942-2466
    Details
    Publication Date: 2021-02-16
    Description: A new global climate model setup using FESOM2.0 for the sea ice‐ocean component and ECHAM6.3 for the atmosphere and land surface has been developed. Replacing FESOM1.4 by FESOM2.0 promises a higher efficiency of the new climate setup compared to its predecessor. The new setup allows for long‐term climate integrations using a locally eddy‐resolving ocean. Here it is evaluated in terms of (1) the mean state and long‐term drift under preindustrial climate conditions, (2) the fidelity in simulating the historical warming, and (3) differences between coarse and eddy‐resolving ocean configurations. The results show that the realism of the new climate setup is overall within the range of existing models. In terms of oceanic temperatures, the historical warming signal is of smaller amplitude than the model drift in case of a relatively short spin‐up. However, it is argued that the strategy of “de‐drifting” climate runs after the short spin‐up, proposed by the HighResMIP protocol, allows one to isolate the warming signal. Moreover, the eddy‐permitting/resolving ocean setup shows notable improvements regarding the simulation of oceanic surface temperatures, in particular in the Southern Ocean.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev , info:eu-repo/semantics/article
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  • 5
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    Predictability of the Arctic sea ice edge (2016)
    Wiley
    In:  EPIC3Geophysical Research Letters, Wiley, ISSN: 0094-8276
    Details
    Publication Date: 2016-02-29
    Description: Skillful sea ice forecasts from days to years ahead are becoming increasingly important for the operation and planning of human activities in the Arctic. Here we analyze the potential predictability of the Arctic sea ice edge in six climate models. We introduce the integrated ice-edge error (IIEE), a user-relevant verification metric defined as the area where the forecast and the “truth” disagree on the ice concentration being above or below 15%. The IIEE lends itself to decomposition into an absolute extent error, corresponding to the common sea ice extent error, and a misplacement error. We find that the often-neglected misplacement error makes up more than half of the climatological IIEE. In idealized forecast ensembles initialized on 1 July, the IIEE grows faster than the absolute extent error. This means that the Arctic sea ice edge is less predictable than sea ice extent, particularly in September, with implications for the potential skill of end-user relevant forecasts.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 6
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    Bright Prospects for Arctic Sea Ice Prediction on Subseasonal Time Scales (2018)
    Wiley
    In:  EPIC3Geophysical Research Letters, Wiley, ISSN: 0094-8276
    Details
    Publication Date: 2018-10-02
    Description: With retreating sea ice and increasing human activities in the Arctic come a growing need for reliable sea ice forecasts up to months ahead. We exploit the subseasonal‐to‐seasonal prediction database and provide the first thorough assessment of the skill of operational forecast systems in predicting the location of the Arctic sea ice edge on these time scales. We find large differences in skill between the systems, with some showing a lack of predictive skill even at short weather time scales and the best producing skillful forecasts more than 1.5 months ahead. This highlights that the area of subseasonal prediction in the Arctic is in an early stage but also that the prospects are bright, especially for late summer forecasts. To fully exploit this potential, it is argued that it will be imperative to reduce systematic model errors and develop advanced data assimilation capacity.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 7
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    Potential sea ice predictability and the role of stochastic sea ice strength perturbations (2014)
    Wiley
    In:  EPIC3Geophysical Research Letters, Wiley, 41(23), pp. 8396-8403, ISSN: 0094-8276
    Details
    Publication Date: 2015-02-24
    Description: Ensemble experiments with a climate model are carried out in order to explore how incorporating a stochastic ice strength parameterization to account for model uncertainty affects estimates of potential sea ice predictability on time scales from days to seasons. The impact of this new parameterization depends strongly on the spatial scale, lead time and the hemisphere being considered: Whereas the representation of model uncertainty increases the ensemble spread of Arctic sea ice thickness predictions generated by atmospheric initial perturbations up to about 4 weeks into the forecast, rather small changes are found for longer lead times as well as integrated quantities such as total sea ice area. The regions where initial condition uncertainty generates spread in sea ice thickness on subseasonal time scales (primarily along the ice edge) differ from that of the stochastic sea ice strength parameterization (along the coast lines and in the interior of the Arctic). For the Antarctic the influence of the stochastic sea ice strength parameterization is much weaker due to the predominance of thinner first year ice. These results suggest that sea ice data assimilation and prediction on subseasonal time scales could benefit from taking model uncertainty into account, especially in the Arctic.
    Repository Name: EPIC Alfred Wegener Institut
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  • 8
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    Predictability of Antarctic Sea Ice Edge on Subseasonal Time Scales (2019)
    Wiley
    In:  EPIC3Geophysical Research Letters, Wiley, 46, ISSN: 0094-8276
    Details
    Publication Date: 2019-09-16
    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 aclimatological benchmark up to ∼30 days ahead. Skill tends to be highest in the west Antarctic sectorduring 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 redictions 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.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev , info:eu-repo/semantics/article
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  • 9
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    Ocean Model Formulation Influences Transient Climate Response (2021)
    Wiley
    In:  EPIC3Journal of Geophysical Research-Oceans, Wiley, 126(12), pp. e2021JC017633, ISSN: 0148-0227
    Details
    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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  • 10
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    Improving the ocean and atmosphere in a coupled ocean–atmosphere model by assimilating satellite sea‐surface temperature and subsurface profile data (2020)
    Wiley
    In:  EPIC3Quarterly Journal of the Royal Meteorological Society, Wiley, 146(733), pp. 4014-4029, ISSN: 0035-9009
    Details
    Publication Date: 2023-06-21
    Description: An ensemble-based data assimilation framework for a coupled ocean–atmosphere model is applied to investigate the influence of assimilating different types of ocean observations on the ocean and atmosphere simulation. The data assimilation is performed with the parallel data assimilation framework (PDAF) for the climate model AWI-CM. Observations of the ocean, namely satellite sea-surface temperature (SST) and temperature and salinity profiles, are assimilated into the ocean component. The atmospheric state is only influenced by the model dynamics. Different assimilation scenarios were carried out with different combinations of observations to investigate to what extent the assimilation into the coupled model leads to a better estimation of the state of the ocean as well as the atmosphere. The influence of the data assimilation is assessed by comparing the ocean prediction with dependent and independent ocean observations. For the atmosphere, the assimilation result is compared with the ERA-Interim atmospheric reanalysis data. The ocean temperature and salinity are improved by all the assimilation scenarios in the coupled system. The assimilation leads to a response of the atmosphere throughout the troposphere and impacts the global atmospheric circulation. Globally the temperature and wind speed are improved in the atmosphere on average.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
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