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Abstract. Global trends of ocean warming, deoxygenation, and acidification are not easily extrapolated to coastal environments. Local factors, including intricate hydrodynamics, high primary productivity, freshwater inputs, and pollution, can exacerbate or attenuate global trends and produce complex mosaics of physiologically stressful or favorable conditions for organisms. In the California Current System (CCS), coastal oceanographic monitoring programs document some of this complexity; however, data fragmentation and limited data availability constrain our understanding of when and where intersecting stressful temperatures, carbonate system conditions, and reduced oxygen availability manifest. Here, we undertake a large data synthesis to compile, format, and quality-control publicly available oceanographic data from the US West Coast to create an accessible database for coastal CCS climate risk mapping, available from the National Centers for Environmental Information (accession 0277984) at https://doi.org/10.25921/2vve-fh39 (Kennedy et al., 2023). With this synthesis, we combine publicly available observations and data contributed by the author team from synoptic oceanographic cruises, autonomous sensors, and shore samples with relevance to coastal ocean acidification and hypoxia (OAH) risk. This large-scale compilation includes 13.7 million observations from 66 sources and spans 1949 to 2020. Here, we discuss the quality and composition of the synthesized dataset, the spatial and temporal distribution of available data, and examples of potential analyses. This dataset will provide a valuable tool for scientists supporting policy- and management-relevant investigations including assessing regional and local climate risk, evaluating the efficacy and completeness of CCS monitoring efforts, and elucidating spatiotemporal scales of coastal oceanographic variability. 

Abstract A critical tool in assessing ecosystem change is the analysis of long‐term data sets, yet such information is generally sparse and often unavailable for many habitats. Kelp forests are an example of rapidly changing ecosystems that are in most cases data poor. Because kelp forests are highly dynamic and have high intrinsic interannual variability, understanding how regional‐scale drivers are driving kelp populations—and particularly how kelp populations are responding to climate change—requires long‐term data sets. However, much of the work on kelp responses to climate change has focused on just a few, relatively long‐lived, perennial, canopy‐forming species. To understand how kelp populations with different life history traits are responding to climate‐related variability, we leverage 35 yr of Landsat satellite imagery to track the population size of an annual, ruderal kelp,Nereocystis luetkeana, across Oregon. We found high levels of interannual variability inNereocystiscanopy area and varying population trajectories over the last 35 yr. Surprisingly, OregonNereocystispopulation sizes were unresponsive to a 2014 marine heat wave accompanied by increases in urchin densities that decimated northern CaliforniaNereocystispopulations. Some OregonNereocystis populations have even increased in area relative to pre‐2014 levels. Analysis of environmental drivers found thatNereocystispopulation size was negatively correlated with estimated nitrate levels and positively correlated with winter wave height. This pattern is the inverse of the predicted relationship based on extensive prior work on the perennial kelpMacrocystis pyriferaand may be related to the annual life cycle ofNereocystis. This article demonstrates (1) the value of novel remote sensing tools to create long‐term data sets that may challenge our understanding of nearshore marine species and (2) the need to incorporate life history traits into our theory of how climate change will shape the ocean of the future.