Behaviour of rubble-mound breakwater in directional and uni-directional waves

The application of directional waves in design processes has clearly received much interest during recent years. Thus, in model testing with moored ships and offshore structures, significant deviations have been revealed between results obtained in traditional uni-directional wave trains and those obtained in directional wave fields. Whether the same tendency is valid in connection with the design of rubble mound breakwaters is studied in the present project. A breakwater with a front slope of 1:2 is tested at the scale 1:40. The weight and diameter of the stones in the core, filter and armour layers were carefully selected, and the sources of scatter in repeated tests were minimized. Furthermore, the incident wave energy was accurately adjusted to keep the same level in both uni-directional and directional waves. For the actual rubble-mound breakwater unambiguous results were obtained. When uni-directional waves were applied, the damage increased by 30–50% relative to the directional wave situation.     

Velocities of a natural mid-ocean ridge basalt glass

We report, for the first time, ultrasonic velocity values for a pure (>95%), natural, submarine basalt glass of mid-ocean ridge basalt composition, from 10 to 1000 MPa at room temperature. These new data show that basalt glass, abundant in the upper oceanic crust, has the lowest velocity of any primary solid component of the oceanic crust. In addition, natural basalt glass has a steeper pressure-dependence of velocity than previously measured in more crystalline samples, indicating that cracks in natural basalt glass are weaker than in more crystalline rocks. To obtain values for the pure glass phase, we correct the natural glass data for the low-pressure closure of cracks, and the presence of minor mineralogic components and vesicles. These new data provide a baseline for evaluating the effect of abundant basalt glass and glassy mesostasis in oceanic upper crust on in situ seismic velocities. In addition, data on the elastic and seismic properties of natural glasses are useful for a better understanding of glass structure, and glass relaxation, with potential applications to submarine volcanology.     

Evaluation of water and energy budgets in regional climate models applied over Europe

This study presents a model intercomparison of four regional climate models (RCMs) and one variable resolution atmospheric general circulation model (AGCM) applied over Europe with special focus on the hydrological cycle and the surface energy budget. The models simulated the 15 years from 1979 to 1993 by using quasi-observed boundary conditions derived from ECMWF re-analyses (ERA). The model intercomparison focuses on two large atchments representing two different climate conditions covering two areas of major research interest within Europe. The first is the Danube catchment which represents a continental climate dominated by advection from the surrounding land areas. It is used to analyse the common model error of a too dry and too warm simulation of the summertime climate of southeastern Europe. This summer warming and drying problem is seen in many RCMs, and to a less extent in GCMs. The second area is the Baltic Sea catchment which represents maritime climate dominated by advection from the ocean and from the Baltic Sea. This catchment is a research area of many studies within Europe and also covered by the BALTEX program. The observed data used are monthly mean surface air temperature, precipitation and river discharge. For all models, these are used to estimate mean monthly biases of all components of the hydrological cycle over land. In addition, the mean monthly deviations of the surface energy fluxes from ERA data are computed. Atmospheric moisture fluxes from ERA are compared with those of one model to provide an independent estimate of the convergence bias derived from the observed data. These help to add weight to some of the inferred estimates and explain some of the discrepancies between them. An evaluation of these biases and deviations suggests possible sources of error in each of the models. For the Danube catchment, systematic errors in the dynamics cause the prominent summer drying problem for three of the RCMs, while for the fourth RCM this is related to deficiencies in the land surface parametrization. The AGCM does not show this drying problem. For the Baltic Sea catchment, all models similarily overestimate the precipitation throughout the year except during the summer. This model deficit is probably caused by the internal model parametrizations, such as the large-scale condensation and the convection schemes.     

Summer algal blooms in a coastal ecosystem: the role of atmospheric deposition versus entrainment fluxes

The nitrogen inputs from atmospheric deposition and bottom water entrainment to the surface layer were modelled in the summer period (May–September) over a 11-year period (1989–1999) and compared to investigate the significance of these fluxes for generating blooms in the Kattegat. In the summer periods the average atmospheric deposition was 2.81 mg N m⁻² d⁻¹ compared to average entrainment fluxes of 5.42 mg N m⁻² d⁻¹, 1.21 mg N m⁻² d⁻¹ and 1.15 mg N m⁻² d⁻¹ for the northern, central and southern part of the Kattegat, respectively. Atmospheric nitrogen deposition alone could not sustain biomass increases associated with observed blooms and entrainment fluxes dominated the high nitrogen inputs to the surface layer. The potential for a bloom through growth was typically obtained after several days of high nitrogen inputs from entrainment in the frontal area of the northern Kattegat and to some extent from atmospheric deposition. The modelled nitrogen input in this area could account directly for 30% of the observed blooms in the Northern sub-basin, and through advective transport 24% and 19% of the observed blooms in the central and southern Kattegat. The direct nitrogen inputs through atmospheric deposition and entrainment to the central and southern sub-basins were small and could not be linked to any bloom observation.     

Electromagnetic Subsurface Imaging. A Case for an Adaptive Born Approximation

The process of interpretation of electromagnetic data has many facets of which fast approximate interpretation techniques is an intriguing one. A new variant of the Born approximation – the Adaptive Born approximation – is presented and exemplified through 1D and 2D imaging techniques for transient electromagnetic data. The Adaptive Born approximation is generally applicable in approximate inversion schemes for inductive electromagnetic data as a one-pass imaging algorithm. Though it is as simple to use as the ordinary Born approximation, it offers a more accurate inverse mapping.In the first part of this paper an attempt will be made to give an overview of fundamental concepts in electromagnetic subsurface imaging relevant for approximate inverse mappings and to outline major trends in present day modeling and inversion of electromagnetic data. This is of course an impossible task – certainly for this author – and much important work will not be mentioned in the limited space of the following. My apologies to the people who are not mentioned and whose research is not given credit here though it should have been. Naturally, my choice of references reflects the schools and circles I have been subjected to, but I hope that the list of references to developments in electromagnetic methods will point to papers of importance and thereby to other references for the interested reader.     

Lateglacial vegetation development in Denmark – New evidence based on macrofossils and pollen from Slotseng,a small-scale site in southern Jutland

This paper presents the first unambiguous terrestrial palaeoecological record for the late glacial “Bølling warming” in Denmark. Pollen and macrofossil stratigraphies from pre-Bølling to 10,800 cal yr BP are presented from a small kettle hole in Southwest Denmark, during which the lake basin developed from an immature stage after the deglaciation to complete infilling in the early Holocene. Results show that the recently deglaciated landscape bore a discontinuous vegetation of pioneer plants. After the Bølling warming, an open Dryas octopetala-Betula nana community developed with Helianthemum oelandicum. Subarctic species were dominant and local successions were probably delayed by relatively unstable and infertile soils. There is no indication of a climate cooling during the period corresponding to the Older Dryas, but the occurrence of several drought tolerant and steppe species indicates that the period was relatively dry. In the Allerød period the Dryas-B. nana vegetation was initially replaced by an open Salix and grass dominated vegetation and some 400 years later, the first tree birches were documented presumably occupying moist and sheltered soils while drier land remained open. In the Younger Dryas period trees disappeared and the vegetation became open again and dominated by subarctic species. Following climate warming at the Younger Dryas–Holocene transition a shrub community of Empetrum and Juniperus developed. After approximately 200 years it was replaced by birch forest. Overall, the late-glacial vegetation cover had a more open and patchy character than inferred from previous pollen studies as assessment of the vegetation succession based on macrofossil evidence is essential. The inferred general vegetation development corresponds well with results of other studies in the region. Canonical ordinations (RDA) indicate that vegetation changes at the landscape scale during the Lateglacial period were driven by changes in climate, soils and competition for light.     

Latent Variable Modeling for Integrating Output from Multiple Climate Models

Numerical models of atmosphere–ocean circulation are widely used to understand past climate and to project future climate change. Although the same laws of physics, chemistry, and fluid dynamics govern any general circulation model, each model’s formulations and parameterizations are different, yielding different projections. Notwithstanding, models within an ensemble will have varying degrees of similarity for different outputs of interest. Multi-model ensembles have been used to increase forecast skill by using simple or weighted averages where weights have been obtained by considering factors such as estimated model bias and consensus with other models (Giorgi and Mearns, J. Clim. 15:1141–1158, 2002, Geophys. Res. Lett. 30:1629–1632, 2003; Tebaldi et al., Geophys. Res. Lett. 31:L24213, 2004, J. Clim. 18:1524–1540, 2005). This paper considers an alternative view of multi-model ensembles. For use with the North American Regional Climate Change Assessment Program (NARCCAP), multivariate statistical models are employed to characterize modes of similarity within the members of an ensemble. Specifically, we propose a spatially-correlated latent variable model which facilitates the exploration of when, where, and how regional climate models are similar, and what factors best predict observed locations of model convergence.