Model global projects

The main tools used to provide global projections of future climate are general circulation models (GCMs). These are mathematical models based on fundamental physical laws and thus constitute dynamical representations of the climate system. Computational constraints impose a limitation on the resolution that it is possible to realise with such models, and so some unresolved processes are parameterised within the models. This includes many key processes that control climate sensitivity such as clouds, vegetation and oceanic convection [19] of which scientific understanding is still incomplete. 

Global sea level has been rising since the end of the last ice age about 18,000 years ago. The rate of rise has varied and for short periods of time, such as the Little Ice Age, sea level has even dropped. However, based on current climate models and projections of greenhouse gas emissions, it is expected that future sea level will rise at a greater rate than it has over the past himdred years. 

In 1985, Applied Technology Council (ATC) first published a comprehensive report (ATC-13 1985) to estimate the earthquake loss of existing buildings by developing a suite of VFs based on expert opinions. ATC considered this approach since very limited earthquake damage or loss data were available at that time. The report developed earthquake loss estimates as a function of Modified Mercalli Intensity (MMI) for different facility classes (e.g., low-rise wood frame). Recently, Global Earthquake Model (GEM) project has also followed a similar approach (Jaiswal et al. 2013) for developing VFs. 

The author list of the present issue brings together scientists from two continents, namely Europe and America. You will find two contributions each from Brazil and the United States, and one contribution each from Germany, France, and the United Kingdom. We hope to show with the distribution of authors that SPR Chemical Modelling is a truly global project. 

Another model, first introduced by Moore, et al. (2i), was used to examine the role of terrestrial vegetation and the global carbon cycle, but did not include an ocean component. This model depended on estimates of carbon pool size and rates of CO2 uptake and release. This model has been used to project the effect of forest clearing and land-use change on the global carbon cycle (22, 23, 24). 

Fig. 1 Global mean surface temperature evolution during the last century (observed) and projected for the next century. Bars on the right show the possible range of temperature increases from different AOGCM, and also from Simple Climate Models (SCM) and Earth Models of Intermediate Complexity (EMIC). Figure taken from IPCC [1]...

A. W. King, W. R. Emanuel, and W. M. Post, Projecting future concentrations of atmospheric COi with global carbon cycle models the importance of simulating historical changes. Environmental Management /6 91 (1992). 

Among nonlocal methods, those based on linear projection are the most widely used for data interpretation. Owing to their limited modeling ability, linear univariate and multivariate methods are used mainly to extract the most relevant features and reduce data dimensionality. Nonlinear methods often are used to directly map the numerical inputs to the symbolic outputs, but require careful attention to avoid arbitrary extrapolation because of their global nature. 

USEtox calculates characterization factors for human toxicity and freshwater ecotoxicity. Assessing the toxicological effects of a chemical emitted into the environment implies a cause-effect chain that links emissions to impacts through three steps environmental fate, exposure, and effects. Linking these steps, a systematic framework for toxic impacts modeling based on matrix algebra was developed to some extent within the OMNIITOX project [10]. USEtox covers two spatial scales, the continental and the global scales. 

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