\enspaceA simple two-box model of the hemispheric thermohaline circulation (THC) is considered. The model parameterizes fluctuations in the freshwater forcing by a stochastic process. The dependence of the power spectral density and the lifetime of quasistationary states of the THC on the distance to the bifurcation point, where the THC collapses, is calculated analytically. It is shown that power spectral properties change as the system is moved closer to the bifurcation point. These changes allow an estimate of the distance to the bifurcation point

No abstract

An approach to considering changes in flooding probability in the integrated assessment of climate change is introduced. A reduced-form hydrological model for flood prediction and a downscaling approach suitable for integrated assessment modeling are presented. Based on these components, the fraction of world population living in river basins affected by changes in flooding probability in the course of climate change is determined. This is then used as a climate impact response function in order to derive emission corridors limiting the population affected. This approach illustrates the consideration of probabilistic impacts within the framework of the tolerable windows approach. Based on the change in global mean temperature, as calculated by the simple climate models used in integrated assessment, spatially resolved changes in climatic variables are determined using pattern scaling, while natural variability in these variables is considered using twentieth century deviations from the climatology. Driven by the spatially resolved climate change, the hydrological model then aggregates these changes to river basin scale. The hydrological model is subjected to a sensitivity analysis with regard to the water balance, and the uncertainty arising through the different projections of changes in mean climate by differing climate models is considered by presenting results based on different models. The results suggest that up to 20% of world population live in river basins that might inevitably be affected by increased flood events in the course of global warming, depending on the climate model used to estimate the regional distribution of changes in climate

A novel transdisciplinary description of the mega-process called Global Change" in terms of functional patterns Syndromes" is presented. This approach to environmental analysis is inspired by medical sciences, where syndromes are perceived as typical combinations of pertinent co-factors. Sixteen main syndromes are identi ed as the subdynamics generating the worldwide environment and development process with all its negative aspects and impacts. The analysis relies on a speci c semi-qualitative methodology, which brings together elements from complex systems theory, fuzzy logic and expert-judgment e v aluations. The concept is illustrated by in-depth treatment and comparison of the syndromes Sahel" and Green Revolution". As a corollary of the syndrome approach, a simple operational de nition of Sustainable Development" is suggested.

Ecological and environmental sciences need new approaches to meet a two-fold challenge: first, analysing the tightly coupled system of human civilisation and its natural environment and, secondly, generating action-oriented knowledge in order to deal with global change. The syndrome approach meets this challenge by formulating a set of typical problematic man-environment interaction patterns. After shortly reviewing the basic concepts of the approach, this paper presents the global distribution of seven syndromes that were present around 1990 based on 56 indicators. Besides large regions dominated by just one problematic pattern, typical "pairs" of syndromes occur, indicating mutual reinforcement mechanisms. A discussion follows covering the implication of these multiple-syndrome situations and the need for actions to mitigate global change and its negative effects.

In order to assess the agricultural potential of regions and to evaluate the risk of environmental degradation due to agriculture, we define a marginality index for agricultural land use which is based on available global data sets and takes into account various environmental conditions. Influencing factors taken into consideration are the general climatic conditions for plant growth, the soil fertility, the soil moisture availability, the precipitation uncertainty and the erosion risk due to the steepness of slopes. Comparison of our marginality index with present global assessments of agricultural land use shows that about 30% of agricultural land currently in use can be identified as marginal, in other words as having a disposition towards overuse and potential environmental degradation. The validity of our approach is strengthened by the fact that agriculturally used areas identified as marginal are described as vulnerable in the literature. The risk of degradation wlth a further intensification of agriculture on existing crop land and the potential for the cultivation of previously unused land can be identified using our fuzzy logic technique.

No abstract

No abstract