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  • Author or Editor: Susan E. Wijffels x
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Ann Gronell and Susan E. Wijffels

Abstract

This paper describes a method consisting of both automated statistical screening and manual quality control through expert visual inspection, which produces a historical ocean temperature archive of high quality—that is, nearly all profiles are unique (duplicate elimination) and 95% of bad data is eliminated. The complete process involves comprehensive duplicate elimination, an unreasonable gradient check, and statistical screening to distill out suspect profiles, which are then only eliminated (or partially so) during an expert manual visual inspection step. Statistical screening was optimized using an archive of known quality. Two iterations of statistical screening were required to identify the bulk of the bad data. Of an archive of about 121 000 profiles, the authors found they had to manually inspect 35% of profiles to remove 95% of the bad data. While costly, they argue such an effort is worthwhile so that the historical ocean temperature archives, which have cost the global community millions of dollars to obtain, are made more immediately useful for climate and ocean sciences. An archive of upper ocean temperature profiles from the Indian Ocean is near completion and extensions into the Pacific Ocean have begun.

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Paul M. Barker, Jeff R. Dunn, Catia M. Domingues, and Susan E. Wijffels

Abstract

In recent years, autonomous profiling floats have become the prime component of the in situ ocean observing system through the implementation of the Argo program. These data are now the dominant input to estimates of the evolution of the global ocean heat content and associated thermosteric sea level rise. The Autonomous Profiling Explorer (APEX) is the dominant type of Argo float (~62%), and a large portion of these floats report pressure measurements that are uncorrected for sensor drift, the size and source of which are described herein. The remaining Argo float types are designed to automatically self-correct for any pressure drift. Only about 57% of the APEX float profiles (or ~38% Argo profiles) can be corrected, but this typically has not been done by the data centers that distribute the data (as of January 2009). A pressure correction method for APEX floats is described and applied to the Argo dataset. A comparison between estimates using the corrected Argo dataset and the publically available uncorrected dataset (as of January 2009) reveals that the pressure corrections remove significant regional errors from ocean temperature, salinity, and thermosteric sea level fields. In the global mean, 43% of uncorrectable APEX float profiles (or ~28% Argo profiles) appear to largely offset the effect of the correctable APEX float profiles with positive pressure drifts. While about half of the uncorrectable APEX profiles can, in principle, be recovered in the near future (after inclusion of technical information that allows for corrections), the other half have negative pressure drifts truncated to zero (resulting from firmware limitations), which do not allow for corrections. Therefore, any Argo pressure profile that cannot be corrected for biases should be excluded from global change research. This study underscores the ongoing need for careful analyses to detect and remove subtle but systematic errors in ocean observations.

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