Multistressor Observations of Coastal Hypoxia and Acidification (MOCHA) Synthesis (NCEI Accession 0277984)

The California Current System (CCS) is a highly complex upwelling system supporting productive fisheries and high biodiversity, but it is vulnerable to warming, deoxygenation, and acidification. Data fragmentation and limited data availability constrain our understanding of when and where stressful coastal conditions manifest. Here, we present a large synthesis of compiled, formatted, and quality-controlled publicly available temperature, dissolved oxygen, and carbonate-system observations to create an accessible, high-resolution database for mapping marine climate stress in U.S. waters along the CCS. Only direct observations were included in this synthesis; no calculated data was retained. The synthesis includes 71 distinct data sources with observations from high resolution autonomous sensors, synoptic oceanographic cruises, and shore samples. Data has been organized across 16.2 million rows and 41 columns. Each row includes one or more individual oceanic parameter measurements accompanied by a dataset ID, which ties observations to their sources in the accompanying dataset Metadata Table, spatial and temporal information about the observations, the data collection method (cruise, mooring, etc.), and a habitat tag to identify estuarine datasets. Rows also include temperature, salinity, dissolved oxygen, carbonate-system, nutrient, and chlorophyll observations as available, along with quality flags and data collection methods for each included observation. Overall, this synthesis includes 15.9 million temperature observations, 5.0 million salinity, 3.9 million dissolved oxygen, 2.3 million pH, 8,368 dissolved inorganic carbon, 10,144 total alkalinity, and 505,000 pCO2/fCO2 observations, with limited additional chlorophyll and nutrient observations. A summary dataset that provides daily averages of observations by location, depth, and project is also available (aggregated_daily_dataset.csv), along with geographic subsets of the full dataset. This synthesis dataset has been optimized for high-resolution coastal multiparameter investigations and will provide a valuable tool for assessing regional and local climate risk, evaluating the efficacy and completeness of CCS monitoring efforts, and investigating spatiotemporal scales of coastal oceanographic variability.