One Model One Vote

It should be obvious then that future scenario analysis based on a single GCM would be a dangerously narrow view of what could be possibly in store.

The IPCC report's future projections chapters, for global and regional projections (Meehl et al. 2007b; Christensen et al. 2007), have in fact adopted a multimodel approach. For the most part the results in the report consist of simple descriptive statistics of climate change across the ensemble. Maps of ensemble means, accompanied by measures of uncertainty like ensemble ranges or standard deviations, or simple measures of model consensus, like stippling indicating majority vote, are used to communicate projected changes especially when no specific region is in focus, and the aim is to paint a global picture of the future climate.

There is a justification for this one-model-one-vote approach. It can be found in the results of informal or formal assessments that have demonstrated how no model outperforms all others, when a comprehensive set of diagnostics are brought to bear (Gleckler et al. 2008). The same kind of analysis has demonstrated that the central

Fig. 3.3 Map of the geographic patterns of temperature change by the end of this century (20812100 vs 1981-2000) computed as the ensemble mean of the same set of models used for Fig. 3.1, and the same emission scenario experiment, A1B. Dots on the map mark grid boxes where 90% of the models agree over the sign of temperature change

Fig. 3.3 Map of the geographic patterns of temperature change by the end of this century (20812100 vs 1981-2000) computed as the ensemble mean of the same set of models used for Fig. 3.1, and the same emission scenario experiment, A1B. Dots on the map mark grid boxes where 90% of the models agree over the sign of temperature change

Fig. 3.4 Map of the geographic patterns of percent precipitation change by the end of this century (2081-2100 vs 1981-2000) computed as the ensemble mean of the same set of models used for Fig. 3.1, and the same emission scenario experiment, A1B. Dots on the map mark grid boxes where 90% of the models agree over the sign of precipitation change

Fig. 3.4 Map of the geographic patterns of percent precipitation change by the end of this century (2081-2100 vs 1981-2000) computed as the ensemble mean of the same set of models used for Fig. 3.1, and the same emission scenario experiment, A1B. Dots on the map mark grid boxes where 90% of the models agree over the sign of precipitation change tendency of the models, when evaluated over the current part of the integration and compared to observations, outperforms any single model simulation (Reichler and Kim 2008).

The crucial point is that if we take a multifaceted approach to validation, and if we are interested in mean climatological quantities, no model is the true model, and model means are a safer bet than any single model's output. Of course, good performance in reproducing current climate is a necessary condition for these model experiments but does not guarantee equally good performance for future climate simulations. In fact, simple tests that stratify models, and their future projections, with respect to the quality of their current simulations have shown that there is often no significant difference between the ranges of projected changes obtained by considering only "good models", or all models. The difficulty lies in defining a metric of what constitutes a good model in a situation where the same model is used to predict many different aspects of climate in different regions, and where no true independent evaluation of the forecast is possible.

Renewable Energy 101

Renewable Energy 101

Renewable energy is energy that is generated from sunlight, rain, tides, geothermal heat and wind. These sources are naturally and constantly replenished, which is why they are deemed as renewable. The usage of renewable energy sources is very important when considering the sustainability of the existing energy usage of the world. While there is currently an abundance of non-renewable energy sources, such as nuclear fuels, these energy sources are depleting. In addition to being a non-renewable supply, the non-renewable energy sources release emissions into the air, which has an adverse effect on the environment.

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