Systematic Differences in Bucket Sea Surface Temperatures Caused by Misclassification of Engine Room Intake Measurements

Author:

Chan Duo1,Huybers Peter1

Affiliation:

1. Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts

Abstract

AbstractDifferences in sea surface temperature (SST) biases among groups of bucket measurements in the International Comprehensive Ocean–Atmosphere Dataset, version 3.0 (ICOADS3.0), were recently identified that introduce offsets of as much as 1°C and have first-order implications for regional temperature trends. In this study, the origin of these groupwise offsets is explored through covariation between offsets and diurnal cycle amplitudes. Examination of an extended bucket model leads to expectations for offsets and amplitudes to covary in either sign, whereas misclassified engine room intake (ERI) temperatures invariably lead to negative covariance on account of ERI measurements being warmer and having a smaller diurnal amplitude. An analysis of ICOADS3.0 SST measurements that are inferred to come from buckets indicates that offsets after the 1930s primarily result from the misclassification of ERI measurements in points of five lines of evidence. 1) Prior to when ERI measurements become available in the 1930s, offset–amplitude covariance is weak and generally positive, whereas covariance is stronger and generally negative subsequently. 2) The introduction of ERI measurements in the 1930s is accompanied by a wider range of offsets and diurnal amplitudes across groups, with 3) approximately 20% of estimated diurnal amplitudes being significantly smaller than buoy and drifter observations. 4) Regressions of offsets versus amplitudes intersect independently determined end-member values of ERI measurements. 5) Offset-amplitude slopes become less negative across all regions and seasons between 1960 and 1980, when ERI temperatures were independently determined to become less warmly biased. These results highlight the importance of accurately determining measurement procedures for bias corrections and reducing uncertainty in historical SST estimates.

Funder

Harvard Global Institute

Publisher

American Meteorological Society

Subject

Atmospheric Science

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