Climate forecast data (Nino3.4 SST, Arctic sea ice extent) and observational references, link to files in Rdata format

Observational estimates of the climate system are essential to monitoring and understanding ongoing climate change and to assessing the quality of climate models used to produce near- and long-term climate information. This study poses the dual and unconventional question: Can climate models be used to assess the quality of observational references? We show that this question not only rests on solid theoretical grounds but also offers insightful applications in practice. By comparing four observational products of sea surface temperature with a large multimodel climate forecast ensemble, we find compelling evidence that models systematically score better against the most recent, advanced, but also most independent product. These results call for generalized procedures of model-observation comparison and provide guidance for a more objective observational data set selection.

气候系统的观测估算，对于监测、认知当前正在发生的气候变化，以及评估用于生成近、长期气候信息的气候模型质量而言，均至关重要。本研究提出了一个兼具双重属性且非传统的问题：能否借助气候模型来评估观测参考数据集的质量？本研究表明，该问题不仅具备坚实的理论基础，同时在实际应用中也能带来富有洞见的成果。本研究通过将四份海表温度（sea surface temperature）观测产品与大型多模式气候预报集合（multimodel climate forecast ensemble）进行对比，找到了确凿证据：相较于最新、最先进但同时也最具独立性的那份观测产品，气候模型的系统性评分表现更优。上述研究结果呼吁建立通用化的模式-观测对比流程，并为更客观地遴选观测数据集提供了指导方向。