Abstract Ocean acidification is a growing concern for many nations around the world. However, our capacity to monitor changes in carbonate chemistry with sufficient spatial and temporal resolution, has until now, been limited, which has impeded effective action and decision‐making at international, national, and regional levels. Recent advancements in machine learning have enabled the integration of Earth observation data with in situ measurements, enhancing data coverage and improving our ability to monitor ocean acidification globally. Here, we highlight how space agencies, particularly the European Space Agency, have supported the development of such products and explore their utility for a broad spectrum of end users, ranging from scientists to resource managers to policy makers and the general public. Spatial and temporal resolution of these products is now on the order of 0.25 × 0.25° and 8‐daily, respectively; with similar or slightly enhanced accuracy compared to other methods (e.g., fCO 2 in open and coastal ocean are 13 and 25 μatm, respectively). We provide five use cases that demonstrate how the data can be used to: (a) communicate ocean acidification; (b) aid marine planning activities; (c) set up national monitoring and understand baseline conditions; (d) assess impacts of aquaculture; and (e) assess impacts to coral habitats. While these developments represent significant progress, further efforts will enhance the efficacy of observational‐data in coastal waters, and could develop complementary biological or water quality indicators. These activities will be accelerated by further building global capacity to ensure equitable access and application of these tools.
Findlay et al. (Thu,) studied this question.
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