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：

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气候模型作为观测系统设计的指导：极地气候和海冰预测的案例

审查目的

北极和南极是受气候变化影响最严重的地区之一，但讽刺的是，它们也是可观测到的最少的地区。气候模型对于完成整体图景发挥了重要作用。人们普遍认为，观测数据促进了气候模型的发展：参数化是根据经验观测的关系设计的，气候模型预测是使用观测产品初始化的，数值模拟是根据匹配的观测数据集进行评估的。

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于回答特定科学问题最有用的测量类型、位置、频率和时间来促进极地观测网络的发展。

概括

在这里，我们借用极地预测领域的五个案例来回顾这一新兴概念的基础，重点关注海冰（次季节到百年时间尺度）。我们建议，气候模型除了其通常的用途外，还可以用于客观地优先考虑未来的观测需求——当然，如果这些模型的现实性的局限性已得到认识。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：观测和模型是同一枚硬币的两面，而不是不同的概念实体。