Variability and trends of ocean acidification in the Southern California Current System: A time series from Santa Monica Bay

Authors

  • A. Leinweber,

    Corresponding author
    1. Institute of Geophysics and Planetary Physics and Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, California, USA
    • Corresponding author: A. Leinweber, Institute of Geophysics and Planetary Physics, University of California, Los Angeles, CA 90095-1565, USA. (leinweber@igpp.ucla.edu)

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  • N. Gruber

    1. Environmental Physics, Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, Zurich, Switzerland
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Abstract

[1] We investigate the temporal variability and trends of pH and of the aragonite saturation state, Ωarag, in the southern California Current System on the basis of a 6 year time series from Santa Monica Bay, using biweekly observations of dissolved inorganic carbon and combined calculated and measured alkalinity. Median values of pH and Ωarag in the upper 20 m are comparable to observations from the subtropical gyres, but the temporal variability is at least a factor of 5 larger, primarily driven by short-term upwelling events and mesoscale processes. Ωarag and pH decrease rapidly with depth, such that the saturation horizon is reached already at 130 m, on average, but it occasionally shoals to as low as 30 m. No statistically significant linear trends emerge in the upper 100 m, but Ωarag and pH decrease, on average, at rates of −0.009±0.006 yr−1 and −0.004±0.003 yr−1 in the 100–250 m depth range. These are somewhat larger, but not statistically different from the expected trends based on the recent increase in atmospheric CO2. About half of the variability in the deseasonalized data can be explained by the El Niño Southern Oscillation, with warm phases (El Niño) being associated with above normal pH and Ωarag. The observed variability and trend in Ωarag and pH is well captured by a multiple linear regression model on the basis of a small number of readily observable independent variables. This permits the estimation of these variables for related sites in the region.

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