Institute of Philosophy & Oeschger Center for Climate Change Research, University of Bern, Switzerland.
UCLouvain, Earth and Life Institute, Belgium.
Stud Hist Philos Sci. 2020 Oct;83:44-52. doi: 10.1016/j.shpsa.2020.03.001. Epub 2020 Mar 13.
Projections of future climate change cannot rely on a single model. It has become common to rely on multiple simulations generated by Multi-Model Ensembles (MMEs), especially to quantify the uncertainty about what would constitute an adequate model structure. But, as Parker points out (2018), one of the remaining philosophically interesting questions is: "How can ensemble studies be designed so that they probe uncertainty in desired ways?" This paper offers two interpretations of what General Circulation Models (GCMs) are and how MMEs made of GCMs should be designed. In the first interpretation, models are combinations of modules and parameterisations; an MME is obtained by "plugging and playing" with interchangeable modules and parameterisations. In the second interpretation, models are aggregations of expert judgements that result from a history of epistemic decisions made by scientists about the choice of representations; an MME is a sampling of expert judgements from modelling teams. We argue that, while the two interpretations involve distinct domains from philosophy of science and social epistemology, they both could be used in a complementary manner in order to explore ways of designing better MMEs.
未来气候变化的预测不能仅依赖于单一模型。多模式集合（Multi-Model Ensembles，MME）生成的多个模拟已被广泛应用，特别是为了量化模型结构的不确定性。但是，正如 Parker（2018）所指出的，一个在哲学上仍然有趣的问题是：“如何设计集合研究，以便以期望的方式探测不确定性？”本文提供了对地球气候模式（General Circulation Models，GCM）的两种解释，以及应该如何设计由 GCM 组成的多模式集合。在第一种解释中，模型是模块和参数化的组合；多模式集合是通过“插拔”可互换的模块和参数化来获得的。在第二种解释中，模型是由科学家在选择表示形式方面的认知决策历史所产生的专家判断的聚合；多模式集合是建模团队的专家判断的抽样。我们认为，虽然这两种解释涉及到科学哲学和社会认识论的不同领域，但它们都可以以互补的方式使用，以探索设计更好的多模式集合的方法。
