Purpose of review

The Arctic and Antarctic are among the regions most exposed to climate change, but ironically, they are also the ones for which the least observations are available. Climate models have been instrumental in completing the big picture. It is generally accepted that observations feed the development of climate models: parameterizations are designed based on empirically observed relationships, climate model predictions are initialized using observational products, and numerical simulations are evaluated given matching observational datasets.

Recent findings

Recent research suggests that the opposite also holds: climate models can feed the development of polar observational networks by indicating the type, location, frequency, and timing of measurements that would be most useful for answering a specific scientific question.

Summary

Here, we review the foundations of this emerging notion with five cases borrowed from the field of polar prediction with a focus on sea ice (sub-seasonal to centennial time scales). We suggest that climate models, besides their usual purposes, can be used to objectively prioritize future observational needs – if, of course, the limitations of the realism of these models have been recognized. This idea, which has been already extensively exploited in the context of Numerical Weather Prediction, reinforces the notion that observations and models are two sides of the same coin rather than distinct conceptual entities.

中文翻译：

---

气候模型作为观测系统设计的指导：以极地气候和海冰预报为例

审查目的

北极和南极是最容易受到气候变化影响的地区，但具有讽刺意味的是，它们也是观测最少的地区。气候模型在完成总体规划方面发挥了作用。人们普遍认为，观测结果为气候模型的发展提供了动力：基于经验观测关系设计参数化，使用观测产品初始化气候模型预测，并根据匹配的观测数据集对数值模拟进行评估。

最近的发现

最近的研究表明，相反的情况也成立：气候模型可以通过指示对回答特定科学问题最有用的测量类型，位置，频率和时间来满足极地观测网络的发展。

概要

在这里，我们回顾了这一新兴概念的基础，从极地预测领域借来了五个案例，重点关注海冰（亚季节到百年时间尺度）。我们建议，除了通常的目的之外，还可以使用气候模型来客观地确定未来的观测需求的优先顺序-当然，如果这些模型的现实性存在局限性，则应予以考虑。这个想法已经在数值天气预报的背景下得到了广泛的利用，它强化了这样的观念，即观测和模型是同一枚硬币的两个方面，而不是不同的概念实体。