We thank the authors for this interesting paper that highlights important ideas and concepts for the future of climate model ensembles and their storage, as well as future uses of stochastic emulators. Stochastic emulators are particularly relevant because of the statistical nature of climate model ensembles, as discussed in previous work of the authors (Castruccio et al. in J Clim 32:8511–8522, 2019; Hu and Castruccio in J Clim 34:8409–8418, 2021). We thank the authors for sharing of some of their data with us in order to illustrate this discussion. In the following, in Sect. 1 we discuss alternative techniques currently used and studied, namely lossy compression and ideas emerging from the climate modeling community, that could feed the discussion on ensemble and storage. In that section, we also present numerical results of compression performed on the data shared by the authors. In Sect. 2, we discuss the current statistical model proposed by the authors and its context. We discuss other potential uses of stochastic emulators in climate and Earth modeling.

我们感谢作者发表这篇有趣的论文，该论文强调了气候模型集合及其存储的未来以及随机仿真器的未来使用的重要想法和概念。由于气候模型集合的统计性质，随机模拟器特别相关，正如作者之前的工作中所讨论的那样（Castruccio 等人在 J Clim 32:8511–8522, 2019；Hu 和 Castruccio 在 J Clim 34:8409–8418 , 2021). 我们感谢作者与我们分享他们的一些数据，以说明这一讨论。在下文中，在 Sect. 1 我们讨论了当前使用和研究的替代技术，即有损压缩和气候建模界出现的想法，这些技术可以为关于集合和存储的讨论提供支持。在那个部分，我们还展示了对作者共享的数据执行压缩的数值结果。昆虫。2，我们讨论了作者提出的当前统计模型及其背景。我们讨论了随机仿真器在气候和地球建模中的其他潜在用途。