Bias estimation for sea surface temperature is discussed and recommendations for improving data, observational metadata, and uncertainty modeling are given. T he global surface temperature record is constructed by blending sea surface temperature (SST) with air temperature over land and ice (see also section S1 of the supplement , which is available online at http://dx.doi.org/10.1175/BAMS-D-15-00251.2). Both SST and land air temperature require adjustments to account for changes in, for example, depth or height of measurement, instrumentation, and siting. Improvement of estimated biases in historical measurements of SST will have a major effect on estimates of global surface temperature change and their uncertainty (Jones 2016).

Lack of reliable observational metadata represents a key barrier to understanding sea surface temperature (SST) measurement biases, a large contributor to uncertainty in the global surface record. We present a method to identify SST measurement practice by comparing the observed SST diurnal cycle from individual ships with a reference from drifting buoys under similar conditions of wind and solar radiation. Compared to existing estimates, we found a larger number of engine room‐intake (ERI) reports post–World War II and in the period 1960–1980. Differences in the inferred mixture of observations lead to a systematic warmer shift of the bias adjusted SST anomalies from 1980 compared to previous estimates, while reducing the ensemble spread. Changes in mean field differences between bucket and ERI SST anomalies in the Northern Hemisphere over the period 1955–1995 could be as large as 0.5°C and are not well reproduced by current bias adjustment models.