Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends

TLDR

Incomplete global coverage, especially at the poles and Africa, can bias temperature reconstructions; HadCRUT4 covers ~84 % of the globe and the bias is worsened by the 1997–98 El Niño event. The study evaluates three near‑global reconstructions to determine whether HadCRUT4’s treatment of unobserved regions introduces bias. Two alternative methods—an optimal‑interpolation algorithm and a hybrid approach that incorporates satellite data—were developed and validated against omitted‑observation skill, and their temperature trends were compared to raw HadCRUT4. Both methods outperform the exclusion of unsampled regions, with the hybrid approach yielding a 2.5‑fold larger trend since 1997 and revealing a cool bias that grows from 1998 onward, especially for trends beginning in 1997–98.

Abstract

Incomplete global coverage is a potential source of bias in global temperature reconstructions if the unsampled regions are not uniformly distributed over the planet's surface. The widely used Hadley Centre–Climatic Reseach Unit Version 4 (HadCRUT4) dataset covers on average about 84% of the globe over recent decades, with the unsampled regions being concentrated at the poles and over Africa. Three existing reconstructions with near-global coverage are examined, each suggesting that HadCRUT4 is subject to bias due to its treatment of unobserved regions. Two alternative approaches for reconstructing global temperatures are explored, one based on an optimal interpolation algorithm and the other a hybrid method incorporating additional information from the satellite temperature record. The methods are validated on the basis of their skill at reconstructing omitted sets of observations. Both methods provide results superior to excluding the unsampled regions, with the hybrid method showing particular skill around the regions where no observations are available. Temperature trends are compared for the hybrid global temperature reconstruction and the raw HadCRUT4 data. The widely quoted trend since 1997 in the hybrid global reconstruction is two and a half times greater than the corresponding trend in the coverage-biased HadCRUT4 data. Coverage bias causes a cool bias in recent temperatures relative to the late 1990s, which increases from around 1998 to the present. Trends starting in 1997 or 1998 are particularly biased with respect to the global trend. The issue is exacerbated by the strong El Niño event of 1997–1998, which also tends to suppress trends starting during those years.