Regression-based estimates of the rate of accumulation of anthropogenic CO₂ in the ocean: A fresh look
2012
Thacker, William Carlisle
Regression-based methods used for estimating the rate of increase of anthropogenic CO₂ in the ocean are reviewed and guidelines for improvement are presented. Following these guidelines leads to a local two-regression method, the first regression accounting for changes in oceanic carbon due to natural variability and the second regression associating the remaining systematic temporal variability with the anthropogenic signal to quantify the rate of accumulation. While a formal measure of the accumulation rate's uncertainty is provided by the standard error of the second regression's slope parameter, both the available data's limited ability to characterize carbon's natural variability in the absence of any anthropogenic contribution and the choice of regressors to account for that variability present significant uncertainties that are less easily quantified. An attractive feature of the method is its applicability to data other than those from repeated hydrographic surveys, such as might be provided by appropriately instrumented profiling floats.
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