We present a simple, generic method for parameterising the sampling and measurement uncertainty for time series data that is based on the number of observations that constitutes each data point. The method is demonstrated using basin‐averaged monthly time series of (1) the mean temperature above 220 m depth ( T 220m ); (2) the mean temperature above the 14 °C isotherm ( T 14C ) and (3) the depth of the 14 °C isotherm ( D 14C ). The T 220m and T 14C analyses are in some sense ‘equivalent’, since the spatial‐time‐mean depth of the 14 °C isotherm is approximately 220 m. In agreement with oceanographic theory, we find that the T 14C time series has a consistently lower associated sampling uncertainty than T 220m for all ocean basins considered in this study. We also note that the sampling uncertainty for all quantities for a given number of observations is dependent on ocean basin. Our results suggest that with the current observing array we are able to monitor global monthly values of T 220m , T 14C and D 14C with a measurement and sampling uncertainty of approximately ± 0.07 °C, ± 0.04 °C and ± 2.4 m, respectively. However, these estimated uncertainties will become much larger on moving to regional or smaller scales.
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Palmer et al. (2010) studied this question.
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