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  • 1
    Online Resource
    Online Resource
    Effekte der Wechselwirkung zwischen Ozean und Atmosphäre auf die Nordatlantische Oszillation (2003)
    Details Availability
    Keywords: Hochschulschrift ; Nordatlantik-Oszillation
    Description / Table of Contents: Zs.-Fassung ; Abstract
    Type of Medium: Online Resource
    Pages: Online-Ressource (XIII, 88, [8] S. = 8.09 MB, Text) , Ill., graph. Darst
    Edition: [Electronic ed.]
    URL: http://eldiss.uni-kiel.de/macau/receive/dissertation_diss_954
    URL: http://nbn-resolving.de/urn:nbn:de:gbv:8-diss-9549
    URN: urn:nbn:de:gbv:8-diss-9549
    Language: German
    Note: Kiel, Univ., Diss., 2003
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  • 2
    Online Resource
    Online Resource
    Cyclone life cycle characteristics over the Northern Hemisphere in coupled GCMs /Ulrike Löptien... (2008)
    Associated volumes
    Details Availability
    In: Climate dynamics, Berlin : Springer, 1986, (2008), 1432-0894
    In: year:2008
    In: extent:26
    Type of Medium: Online Resource
    Pages: 26 , graph. Darst
    ISSN: 1432-0894
    DOI: 10.1007/s00382-007-0355-5
    Language: English
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    GEOMAR CATALOGUE
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  • 3
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    Historical sea ice of the Baltic Sea (1960/61-78/79) (2014)
    PANGAEA
    In:  Supplement to: Löptien, Ulrike; Dietze, Heiner (2014): Sea ice in the Baltic Sea - revisiting BASIS ice, a historical data set covering the period 1960/1961 - 1978/1979. Earth System Science Data, 6(2), 367-374, https://doi.org/10.5194/essd-6-367-2014
    Details
    Publication Date: 2023-02-24
    Description: The Baltic Sea is a seasonally ice-covered, marginal sea in central northern Europe. It is an essential waterway connecting highly industrialised countries. Because ship traffic is intermittently hindered by sea ice, the local weather services have been monitoring sea ice conditions for decades. In the present study we revisit a historical monitoring data set, covering the winters 1960/1961 to 1978/1979. This data set, dubbed Data Bank for Baltic Sea Ice and Sea Surface Temperatures (BASIS) ice, is based on hand-drawn maps that were collected and then digitised in 1981 in a joint project of the Finnish Institute of Marine Research (today the Finnish Meteorological Institute (FMI)) and the Swedish Meteorological and Hydrological Institute (SMHI). BASIS ice was designed for storage on punch cards and all ice information is encoded by five digits. This makes the data hard to access. Here we present a post-processed product based on the original five-digit code. Specifically, we convert to standard ice quantities (including information on ice types), which we distribute in the current and free Network Common Data Format (NetCDF). Our post-processed data set will help to assess numerical ice models and provide easy-to-access unique historical reference material for sea ice in the Baltic Sea. In addition we provide statistics showcasing the data quality. The website http://www.baltic-ocean.org hosts the post-processed data and the conversion code.
    Keywords: GEOMAR; Helmholtz Centre for Ocean Research Kiel
    Type: Dataset
    Format: application/zip, 2.5 MBytes
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    DATA PANGAEA
  • 4
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    Effects of parameter indeterminacy in pelagic biogeochemical modules of Earth System Models on projections into a warming future: The scale of the problem (2017)
    AGU (American Geophysical Union) | Wiley
    In:  Global Biogeochemical Cycles, 31 (7). pp. 1155-1172.
    Details
    Publication Date: 2020-02-06
    Description: Numerical Earth System Models are generic tools used to extrapolate present climate conditions into a warming future and to explore geoengineering options. Most of the current-generation models feature a simple pelagic biogeochemical model component that is embedded into a three-dimensional ocean general circulation model. The dynamics of these biogeochemical model components is essentially controlled by so-called model parameters most of which are poorly known. Here we explore the feasibility to estimate these parameters in a full-fledged three-dimensional Earth System Model by minimizing the misfit to noisy observations. The focus is on parameter identifiability. Based on earlier studies, we illustrate problems in determining a unique estimate of those parameters that prescribe the limiting effect of nutrient- and light-depleted conditions on carbon assimilation by autotrophic phytoplankton. Our results showcase that for typical models and evaluation metrics no meaningful “best” unique parameter set exists. We find very different parameter sets which are, on the one hand, equally consistent with our (synthetic) historical observations while, on the other hand, they propose strikingly differing projections into a warming climate.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.1002/2017GB005690
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 5
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    Sea-ice evaluation of NEMO-Nordic 1.0: a NEMO–LIM3.6-based ocean–sea-ice model setup for the North Sea and Baltic Sea (2017)
    Copernicus Publications (EGU)
    In:  Geoscientific Model Development, 10 (8). pp. 3105-3123.
    Details
    Publication Date: 2020-02-06
    Description: The Baltic Sea is a seasonally ice-covered marginal sea in northern Europe with intense wintertime ship traffic and a sensitive ecosystem. Understanding and modeling the evolution of the sea-ice pack is important for climate effect studies and forecasting purposes. Here we present and evaluate the sea-ice component of a new NEMO–LIM3.6-based ocean–sea-ice setup for the North Sea and Baltic Sea region (NEMO-Nordic). The setup includes a new depth-based fast-ice parametrization for the Baltic Sea. The evaluation focuses on long-term statistics, from a 45-year long hindcast, although short-term daily performance is also briefly evaluated. We show that NEMO-Nordic is well suited for simulating the mean sea-ice extent, concentration, and thickness as compared to the best available observational data set. The variability of the annual maximum Baltic Sea ice extent is well in line with the observations, but the 1961–2006 trend is underestimated. Capturing the correct ice thickness distribution is more challenging. Based on the simulated ice thickness distribution we estimate the undeformed and deformed ice thickness and concentration in the Baltic Sea, which compares reasonably well with observations.
    Type: Article , PeerReviewed
    Format: text
    Format: archive
    DOI: 10.5194/gmd-10-3105-2017
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 6
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    Error assessment of biogeochemical models by lower bound methods (NOMMA-1.0) (2018)
    Copernicus Publications (EGU)
    In:  Geoscientific Model Development, 11 (3). pp. 1181-1198.
    Details
    Publication Date: 2021-02-08
    Description: Biogeochemical models, capturing the major feedbacks of the pelagic ecosystem of the world ocean, are today often embedded into Earth system models which are increasingly used for decision making regarding climate policies. These models contain poorly constrained parameters (e.g., maximum phytoplankton growth rate), which are typically adjusted until the model shows reasonable behavior. Systematic approaches determine these parameters by minimizing the misfit between the model and observational data. In most common model approaches, however, the underlying functions mimicking the biogeochemical processes are nonlinear and non-convex. Thus, systematic optimization algorithms are likely to get trapped in local minima and might lead to non-optimal results. To judge the quality of an obtained parameter estimate, we propose determining a preferably large lower bound for the global optimum that is relatively easy to obtain and that will help to assess the quality of an optimum, generated by an optimization algorithm. Due to the unavoidable noise component in all observations, such a lower bound is typically larger than zero. We suggest deriving such lower bounds based on typical properties of biogeochemical models (e.g., a limited number of extremes and a bounded time derivative). We illustrate the applicability of the method with two real-world examples. The first example uses real-world observations of the Baltic Sea in a box model setup. The second example considers a three-dimensional coupled ocean circulation model in combination with satellite chlorophyll a.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.5194/gmd-2017-133
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 7
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    Long-term characteristics of simulated ice deformation in the Baltic Sea (1962–2007) (2013)
    AGU (American Geophysical Union) | Wiley
    In:  Journal of Geophysical Research: Oceans, 118 (2). pp. 801-815.
    Details
    Publication Date: 2019-07-08
    Description: [1] The North Atlantic Oscillation (NAO) index is a frequently used measure for the mean winter conditions in Northern Europe. A positive, high index is associated with strong westerlies and anomalous warm temperatures. The effects on sea ice conditions in the Baltic Sea are twofold. Warm temperatures prevent sea ice formation. If ice is present nevertheless, the strong winds can promote the formation of ice ridges which hinders ship traffic. We use an ocean-sea ice model to investigate the NAO impact on the ridged ice area fraction in the Baltic during 1962–2007. Our simulations indicate that in the northern Bothnian Bay, a high NAO index is related to an anomalous accumulation of ridges, while in the rest of the Baltic Sea, the relationship is contrary. The NAO explains locally at most only 20–25% of the ridged ice fraction interannual variability which indicates the systems complexity. However, we find high skill with local correlations around 0.8 for annually averaged ridged ice fraction reconstructed from multilinear regression using winter averaged wind extremes, surface air temperature, and sea surface temperature (SST). This suggests that the amount of ridged ice in late winter can be derived from these routinely measured quantities. In large parts of the basin, it is sufficient to use the atmospheric parameters as a predictor, while in the eastern Bothnian Bay and southern Gulf of Finland, the SST is required to reconstruct the bulk of the ridged ice fraction.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.1002/jgrc.20089
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 8
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    Constraining parameters in marine pelagic ecosystem models – is it actually feasible with typical observations of standing stocks? (2015)
    Copernicus Publications (EGU)
    In:  Ocean Science, 11 (4). pp. 573-590.
    Details
    Publication Date: 2019-09-23
    Description: In a changing climate, marine pelagic biogeochemistry may modulate the atmospheric concentrations of climate-relevant species such as CO2 and N2O. To date, projections rely on earth system models, featuring simple pelagic biogeochemical model components, embedded into 3-D ocean circulation models. Most of these biogeochemical model components rely on the hyperbolic Michaelis–Menten (MM) formulation which specifies the limiting effect of light and nutrients on carbon assimilation by autotrophic phytoplankton. The respective MM constants, along with other model parameters, of 3-D coupled biogeochemical ocean-circulation models are usually tuned; the parameters are changed until a "reasonable" similarity to observed standing stocks is achieved. Here, we explore with twin experiments (or synthetic "observations") the demands on observations that allow for a more objective estimation of model parameters. We start with parameter retrieval experiments based on "perfect" (synthetic) observations which we distort, step by step, by low-frequency noise to approach realistic conditions. Finally, we confirm our findings with real-world observations. In summary, we find that MM constants are especially hard to constrain because even modest noise (10 %) inherent to observations may hinder the parameter retrieval already. This is of concern since the MM parameters are key to the model's sensitivity to anticipated changes in the external conditions. Furthermore, we illustrate problems caused by high-order parameter dependencies when parameter estimation is based on sparse observations of standing stocks. Somewhat counter to intuition, we find that more observational data can sometimes degrade the ability to constrain certain parameters.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.5194/os-11-573-2015
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 9
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    Ice and AIS: ship speed data and sea ice forecasts in the Baltic Sea (2014)
    Copernicus Publications (EGU)
    In:  The Cryosphere, 8 . pp. 2409-2418.
    Details
    Publication Date: 2015-02-05
    Description: The Baltic Sea is a seasonally ice-covered marginal sea located in a densely populated area in northern Europe. Severe sea ice conditions have the potential to hinder the intense ship traffic considerably. Thus, sea ice fore- and nowcasts are regularly provided by the national weather services. Typically, the forecast comprises several ice properties that are distributed as prognostic variables, but their actual usefulness is difficult to measure, and the ship captains must determine their relative importance and relevance for optimal ship speed and safety ad hoc. The present study provides a more objective approach by comparing the ship speeds, obtained by the automatic identification system (AIS), with the respective forecasted ice conditions. We find that, despite an unavoidable random component, this information is useful to constrain and rate fore- and nowcasts. More precisely, 62–67% of ship speed variations can be explained by the forecasted ice properties when fitting a mixed-effect model. This statistical fit is based on a test region in the Bothnian Sea during the severe winter 2011 and employs 15 to 25 min averages of ship speed.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    DOI: 10.5194/tc-8-2409-2014
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 10
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    Effect of Synoptic Systems on the Variability of the North Atlantic Oscillation (2005)
    American Meteorological Society, AMS
    In:  Monthly Weather Review, 133 (10). pp. 2894-2904.
    Details
    Publication Date: 2019-01-23
    Description: The North Atlantic Oscillation (NAO) represents the dominant mode of atmospheric variability in the North Atlantic region. In the present study, the role of the synoptic systems (cyclones and anticyclones) in generating the NAO pattern is investigated. To study the intermonthly variations of the NAO, NCEP–NCAR reanalysis data are used, and for the interdecadal variations the results of a 300-yr control integration under present-day conditions of the coupled model ECHAM4/OPYC3 are analyzed. A filtering method is developed for the sea level pressure anomalies. Application of this method to each grid point yields the low-frequency variability in the sea level pressure field that is due to the synoptic systems. The low-frequency variability of the filtered and the original data are in high agreement. This indicates that the low-frequency pressure variability, and with it the variability of the NAO, is essentially caused by the distribution of the synoptic systems. The idea that the distribution of the synoptic systems is the cause of the variation of the NAO is confirmed by high correlation between the latitudinal position of the polar front over the North Atlantic and the NAO index. Since most of the low-frequency variability in sea level pressure can be explained through the distribution of the synoptic systems, the NAO seems to be a reflection of the distribution of the synoptic systems, rather than the source for variations in the cyclone tracks.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.1175/MWR3007.1
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    OceanRep: Article in a Scientific Journal - peer-reviewed
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