As climate change continues, the likelihood of passing critical thresholds or tipping points increases. Hence, there is a need to advance the science for detecting such thresholds. In this paper, we assess the needs and opportunities for Earth Observation (EO, here understood to refer to satellite observations) to inform society in responding to the risks associated with ten potential large-scale ocean tipping elements: Atlantic Meridional Overturning Circulation; Atlantic Subpolar Gyre; Beaufort Gyre; Arctic halocline; Kuroshio Large Meander; deoxygenation; phytoplankton; zooplankton; higher level ecosystems (including fisheries); and marine biodiversity. We review current scientific understanding and identify specific EO and related modelling needs for each of these tipping elements. We draw out some generic points that apply across several of the elements. These common points include the importance of maintaining long-term, consistent time series; the need to combine EO data consistently with in situ data types (including subsurface), for example through data assimilation; and the need to reduce or work with current mismatches in resolution (in both directions) between climate models and EO datasets. Our analysis shows that developing EO, modelling and prediction systems together, with understanding of the strengths and limitations of each, provides many promising paths towards monitoring and early warning systems for tipping, and towards the development of the next generation of climate models.

随着气候变化的持续，通过临界阈值或临界点的可能性会增加。因此，有必要推进检测此类阈值的科学。在本文中，我们评估了地球观测（EO，此处理解为卫星观测）的需求和机会，以告知社会应对与十个潜在的大尺度海洋倾翻因素相关的风险：大西洋经向翻转环流;大西洋亚极地环流;博福特环流;北极盐跃层;黑潮大蜿蜒;脱氧;浮游植物;浮游动物;更高级别的生态系统（包括渔业）;以及海洋生物多样性。我们回顾了当前的科学理解，并确定了每个 TIP 要素的具体 EO 和相关建模需求。我们列出了一些适用于多个元素的通用点。这些共同点包括保持长期、一致的时间序列的重要性;需要将 EO 数据与原位数据类型（包括地下）一致地组合在一起，例如通过数据同化;以及需要减少或解决当前气候模型和 EO 数据集之间分辨率（双向）的不匹配。我们的分析表明，同时开发 EO、建模和预测系统，并了解每个系统的优势和局限性，为监测和早期预警系统以及开发下一代气候模型提供了许多有前途的途径。