The reliability of global and hemispheric surface temperature records

Abstract

The purpose of this review article is to discuss the development and associated estimation of uncertainties in the global and hemispheric surface temperature records. The review begins by detailing the groups that produce surface temperature datasets. After discussing the reasons for similarities and differences between the various products, the main issues that must be addressed when deriving accurate estimates, particularly for hemispheric and global averages, are then considered. These issues are discussed in the order of their importance for temperature records at these spatial scales: biases in SST data, particularly before the 1940s; the exposure of land-based thermometers before the development of louvred screens in the late 19th century; and urbanization effects in some regions in recent decades. The homogeneity of land-based records is also discussed; however, at these large scales it is relatively unimportant. The article concludes by illustrating hemispheric and global temperature records from the four groups that produce series in near-real time.

The dynamics of the warming hiatus over the Northern Hemisphere

“…The recorded sea surface temperatures (SST) suggest a bias toward colder temperatures in recent decades, and which has induced the corresponding SAT over the oceans to also become colder (Karl et al 2015). However, the bias in SAT over land was small, especially when averaged over a large scale (Karl et al 2015;Jones 2016). Our results show that approximately one-half of the recent hiatus in global mean SAT was accounted by cooling over land.…”

A Call for New Approaches to Quantifying Biases in Observations of Sea Surface Temperature

“…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).…”

“…Folland et al (1984) applied first-order SST bias adjustments, adding a constant value of 0.3°C to observations made before 1942, based on the difference between global night marine air temperature (NMAT) and SST. By the time of the Intergovernmental Panel on Climate Change (IPCC) First Assessment Report (Houghton et al 1990), more complex models of SST bias had been developed (Jones et al 1986;Bottomley et al 1990) and presently several different estimates of SST bias exist. Figure 1 shows global-mean SST anomalies for the current, commonly used, longterm gridded SST analyses: Hadley Centre SST dataset, version 3 (HadSST3; Kennedy et al 2011a,b); Extended Reconstructed SST, version 4 (ERSSTv4; Huang et al 2015); and Centennial Observation-Based Estimates of SST, version 2 (COBE-SST2; Hirahara et al 2014), along with their bias estimates and uncertainties.…”

Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

“…How good ERA-Interim is for climate monitoring has been extensively addressed recently by Simmons et al (2017). This study shows excellent agreement for global-and continental-scale trends in surface air temperatures over land with conventional station-based datasets (see Jones, 2016, for details of these datasets).…”