Internal climate variability plays an important role in the abundance and distribution of phytoplankton in the global ocean. Previous studies using large ensembles of Earth system models (ESMs) have demonstrated their utility in the study of marine phytoplankton variability. These ESM large ensembles simulate the evolution of multiple alternate realities, each with a different phasing of internal climate variability. However, ESMs may not accurately represent real world variability as recorded via satellite and in situ observations of ocean chlorophyll over the past few decades. Observational records of surface ocean chlorophyll equate to a single ensemble member in the large ensemble framework, and this can cloud the interpretation of long-term trends: are they externally forced, caused by the phasing of internal variability, or both? Here, we use a novel statistical emulation technique to place the observational record of surface ocean chlorophyll into the large ensemble framework. Much like a large initial condition ensemble generated with an ESM, the resulting synthetic ensemble represents multiple possible evolutions of ocean chlorophyll concentration, each with a different sampling of internal climate variability. We further demonstrate the validity of our statistical approach by recreating an ESM ensemble of chlorophyll using only a single ESM ensemble member. We use the synthetic ensemble to explore the interpretation of long-term trends in the presence of internal variability and find a wider range of possible trends in chlorophyll due to the sampling of internal variability in subpolar regions than in subtropical regions.

中文翻译：

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交替历史：海洋叶绿素浓度的合成集合

内部气候变异在全球海洋中浮游植物的丰度和分布中起着重要作用。先前使用地球系统模型 (ESM) 的大型集合的研究已经证明了它们在海洋浮游植物变异性研究中的实用性。这些 ESM 大型集合模拟了多个交替现实的演变，每个现实都有不同的内部气候变率阶段。然而，ESM 可能无法准确代表过去几十年通过卫星和原位海洋叶绿素观测记录的真实世界变化。表层海洋叶绿素的观测记录相当于大型集合框架中的单个集合成员，这可能会影响对长期趋势的解释：它们是外部强迫的，由内部变化的相位引起的，还是两者兼而有之？这里，我们使用一种新颖的统计仿真技术将表层海洋叶绿素的观测记录放入大型集合框架中。与 ESM 生成的大型初始条件集合非常相似，由此产生的合成集合代表了海洋叶绿素浓度的多种可能演变，每个演变都有不同的内部气候变异采样。我们通过仅使用单个 ESM 集合成员重新创建叶绿素的 ESM 集合，进一步证明了我们的统计方法的有效性。我们使用合成集合来探索在存在内部变异的情况下对长期趋势的解释，并发现由于次极地地区内部变异的采样比亚热带地区更广泛的叶绿素可能趋势。