ABSTRACT The paper discusses modelling uncertainties in climate models and how they can be addressed based on physical principles as well as based on how the models perform in light of empirical data. We argue that the reliability of climate models can be judged by three kinds of standards: striking confirmation, supplementing independent causal arguments, and judging the causal core of models by establishing model robustness. We also use model robustness for delimiting confirmational holism. We survey recent results of climate modelling and identify salient results that fulfil each of the three standards. Our conclusion is that climate models can be considered reliable for some qualitative gross features and some long-term tendencies of the climate system as well as for quantitative aspects of some smaller-scale mechanisms. The adequacy of climate models for other purposes is less convincing. Among the latter are probability estimates, in particular, those concerning rare events. On the whole, climate models suffer from important deficits and are difficult to verify, but are still better confirmed and more reliable than parts of the methodological literature suggest.

中文翻译：

---

气候模型：如何评估其可靠性

摘要本文讨论了气候模型中的建模不确定性，以及如何根据物理原理以及根据经验数据如何执行模型来解决这些不确定性。我们认为，可以通过三种标准来判断气候模型的可靠性：敲击确认，补充独立的因果论据以及通过建立模型的鲁棒性来判断模型的因果核心。我们还使用模型鲁棒性来确定确认整体性。我们调查了气候模型的最新结果，并确定了符合这三个标准的显着结果。我们的结论是，对于某些定性的总体特征，气候系统的某些长期趋势以及某些小规模机制的定量方面，气候模型可以被认为是可靠的。气候模型用于其他目的的充分性令人信服。后者包括概率估计，特别是涉及罕见事件的概率估计。总体而言，气候模型存在重大缺陷，难以验证，但仍比部分方法论文献所建议的更好地被证实和更可靠。