, Volume 65, Issue 3, pp 287-299
Date: 26 Apr 2009

Reevaluation of historical ocean heat content variations with time-varying XBT and MBT depth bias corrections

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Abstract

As reported in former studies, temperature observations obtained by expendable bathythermographs (XBTs) and mechanical bathythermographs (MBTs) appear to have positive biases as much as they affect major climate signals. These biases have not been fully taken into account in previous ocean temperature analyses, which have been widely used to detect global warming signals in the oceans. This report proposes a methodology for directly eliminating the biases from the XBT and MBT observations. In the case of XBT observation, assuming that the positive temperature biases mainly originate from greater depths given by conventional XBT fall-rate equations than the truth, a depth bias equation is constructed by fitting depth differences between XBT data and more accurate oceanographic observations to a linear equation of elapsed time. Such depth bias equations are introduced separately for each year and for each probe type. Uncertainty in the gradient of the linear equation is evaluated using a non-parametric test. The typical depth bias is +10 m at 700 m depth on average, which is probably caused by various indeterminable sources of error in the XBT observations as well as a lack of representativeness in the fall-rate equations adopted so far. Depth biases in MBT are fitted to quadratic equations of depth in a similar manner to the XBT method. Correcting the historical XBT and MBT depth biases by these equations allows a historical ocean temperature analysis to be conducted. In comparison with the previous temperature analysis, large differences are found in the present analysis as follows: the duration of large ocean heat content in the 1970s shortens dramatically, and recent ocean cooling becomes insignificant. The result is also in better agreement with tide gauge observations.

On leave from the Meteorological Research Institute of the Japan Meteorological Agency.