The dynamics of a low-order coupled ocean-atmosphere model

A system of five ordinary differential equations is studied which combines the Lorenz-84 model for the atmosphere and a box model for the ocean. The behaviour of this system is studied as a function of the coupling parameters. For most parameter values, the dynamics of the atmosphere model is dominant. For a range of parameter values, competing attractors exist. The Kaplan-Yorke dimension and the correlation dimension of the chaotic attractor are numerically calculated and compared to the values found in the uncoupled Lorenz model. In the transition from periodic behaviour to chaos intermittency is observed. The intermittent behaviour occurs near a Neimark-Sacker bifurcation at which a periodic solution loses its stability. The length of the periodic intervals is governed by the time scale of the ocean component. Thus, in this regime the ocean model has a considerable influence on the dynamics of the coupled system.Comment: 20 pages, 15 figures, uses AmsTex, Amssymb and epsfig package. Submitted to the Journal of Nonlinear Scienc

The role of social interaction in farmers' climate adaptation choice

Adaptation to climate change might not always occur, with potentially\ud catastrophic results. Success depends on coordinated actions at both\ud governmental and individual levels (public and private adaptation). Even for a “wet” country like the Netherlands, climate change projections show that the frequency and severity of droughts are likely to increase. Freshwater is an important factor for agricultural production. A deficit causes damage to crop production and consequently to a loss of income. Adaptation is the key to decrease farmers’ vulnerability at the micro level and the sector’s vulnerability at the macro level. Individual adaptation decision-making is determined by the behavior of economic agents and social interaction among them. This can be best studied with agentbased modelling. Given the uncertainty about future weather conditions and the costs and effectiveness of adaptation strategies, a farmer in the model uses a cognitive process (or heuristic) to make adaptation decisions. In this process, he can rely on his experiences and on information from interactions within his social network. Interaction leads to the spread of information and knowledge that causes learning. Learning changes the conditions for individual adaptation decisionmaking. All these interactions cause emergent phenomena: the diffusion of adaptation strategies and a change of drought vulnerability of the agricultural sector. In this paper, we present a conceptual model and the first implementation of an agent-based model. The aim is to study the role of interaction in a farmer’s social network on adaptation decisions and on the diffusion of adaptation strategies\ud and vulnerability of the agricultural sector. Micro-level survey data will be used to parameterize agents’ behavioral and interaction rules at a later stage. This knowledge is necessary for the successful design of public adaptation strategies, since governmental adaptation actions need to be fine-tuned to private adaptation behavior

Metabifurcation analysis of a mean field model of the cortex

Mean field models (MFMs) of cortical tissue incorporate salient features of neural masses to model activity at the population level. One of the common aspects of MFM descriptions is the presence of a high dimensional parameter space capturing neurobiological attributes relevant to brain dynamics. We study the physiological parameter space of a MFM of electrocortical activity and discover robust correlations between physiological attributes of the model cortex and its dynamical features. These correlations are revealed by the study of bifurcation plots, which show that the model responses to changes in inhibition belong to two families. After investigating and characterizing these, we discuss their essential differences in terms of four important aspects: power responses with respect to the modeled action of anesthetics, reaction to exogenous stimuli, distribution of model parameters and oscillatory repertoires when inhibition is enhanced. Furthermore, while the complexity of sustained periodic orbits differs significantly between families, we are able to show how metamorphoses between the families can be brought about by exogenous stimuli. We unveil links between measurable physiological attributes of the brain and dynamical patterns that are not accessible by linear methods. They emerge when the parameter space is partitioned according to bifurcation responses. This partitioning cannot be achieved by the investigation of only a small number of parameter sets, but is the result of an automated bifurcation analysis of a representative sample of 73,454 physiologically admissible sets. Our approach generalizes straightforwardly and is well suited to probing the dynamics of other models with large and complex parameter spaces

Thermal stability of ultrasoft Fe–Zr–N films

The thermal stability of nanocrystalline ultrasoft magnetic (Fe98Zr2)1−xNx films with x = 0.10–0.25 was studied using thermal desorption spectrometry, positron beam analysis and high resolution transmission electron microscopy. The results demonstrate that grain growth during the heat treatment is accompanied by an increase of the free volume and nitrogen relocation and desorption. All these phenomena can drastically degrade the ultrasoft magnetic properties. The nitrogen desorption has already started at temperatures around 400 K. Nevertheless, most of the nitrogen leaves the sample at a temperature above 800 K. We found that nitrogen out-diffusion is significantly retarded compared with the prediction of the diffusion in bulk α-Fe. A qualitative model is proposed in which the nitrogen out-diffusion in nanocrystalline material is retarded by trapping at immobile defects, namely Zr atoms, and also by voids at grain boundaries. From a certain temperature, nitrogen migrates from the interior of the nanograins to the nanovoids at the grain boundaries and the out-diffusion to the outer surface is controlled by transport between the voids.

Continuous-flow IRMS technique for determining the 17O excess of CO2 using complete oxygen isotope exchange with cerium oxide

This paper presents an analytical system for analysis of all single substituted isotopologues (¹²C¹⁶O¹⁷O, ¹²C¹⁶O¹⁸O, ¹³C¹⁶O¹⁶O) in nanomolar quantities of CO₂ extracted from stratospheric air samples. CO₂ is separated from bulk air by gas chromatography and CO₂ isotope ratio measurements (ion masses 45 / 44 and 46 / 44) are performed using isotope ratio mass spectrometry (IRMS). The ¹⁷O excess (Δ¹⁷O) is derived from isotope measurements on two different CO₂ aliquots: unmodified CO₂ and CO₂ after complete oxygen isotope exchange with cerium oxide (CeO₂) at 700 °C. Thus, a single measurement of Δ¹⁷O requires two injections of 1 mL of air with a CO₂ mole fraction of 390 μmol mol⁻¹ at 293 K and 1 bar pressure (corresponding to 16 nmol CO₂ each). The required sample size (including flushing) is 2.7 mL of air. A single analysis (one pair of injections) takes 15 minutes. The analytical system is fully automated for unattended measurements over several days. The standard deviation of the ¹⁷O excess analysis is 1.7‰. Multiple measurements on an air sample reduce the measurement uncertainty, as expected for the statistical standard error. Thus, the uncertainty for a group of 10 measurements is 0.58‰ for Δ ¹⁷O in 2.5 h of analysis. 100 repeat analyses of one air sample decrease the standard error to 0.20‰. The instrument performance was demonstrated by measuring CO₂ on stratospheric air samples obtained during the EU project RECONCILE with the high-altitude aircraft Geophysica. The precision for RECONCILE data is 0.03‰ (1σ) for δ¹³C, 0.07‰ (1σ) for δ¹⁸O and 0.55‰ (1σ) for δ¹⁷O for a sample of 10 measurements. This is sufficient to examine stratospheric enrichments, which at altitude 33 km go up to 12‰ for δ¹⁷O and up to 8‰ for δ¹⁸O with respect to tropospheric CO₂ : δ¹⁷O ~ 21‰ Vienna Standard Mean Ocean Water (VSMOW), δ¹⁸O ~ 41‰ VSMOW (Lämmerzahl et al., 2002). The samples measured with our analytical technique agree with available data for stratospheric CO₂

Development of motivation in first-year students in Dutch senior secondary vocational education

This study examined the development in motivation for school in students in senior secondary vocational education and factors related to this development. There have been many concerns about a decline in motivation after school transitions. Little about this subject is known in relation to the transition to senior secondary vocational education. Knowledge about this is necessary, as the decline is expected to be more extensive in this type of school because the percentage of dropouts is high. For this research, 614 first-year students filled out a questionnaire four times. The results showed little average change in motivation during the first school year, although there was a decrease in students' academic delay of gratification after the transition. Associations with motivation similar to those found in studies of secondary schools were found, but only at the start of the school year, not with changes in it during the remainder of the year