Automated Homogenisation of Early Instrumental Temperature Data at the Global Scale Using the HCLIM Dataset

Abstract. Early instrumental observations provide a unique opportunity to investigate climate variability before the establishment of modern meteorological networks. However, their effective use is often hindered by incomplete records, uneven spatial coverage, and non-climatic inhomogeneities. The HCLIM dataset provides a recently compiled global collection of early instrumental temperature records, yet systematic evaluations of automated homogenisation methods for such data remain limited. Here, we evaluate three widely used homogenisation methods, CLIMATOL, PHA, and BART, applied to the HCLIM dataset. The assessment considers data retention following pre-processing, breakpoint detection in the homogenised series, and agreement with the Twentieth Century Reanalysis version 3 (20CRv3), using French and Southeast Asian station networks as representative case studies. The pre-processed datasets differ only modestly in overall structure, although BART retains fewer records (80 %) than CLIMATOL (96 %) and PHA (99 %) because of its stricter requirement for a minimum record length of 15 consecutive years. Consequently, BART preserves longer average record lengths and detects substantially more breakpoints, indicating greater sensitivity to potential inhomogeneities. Breakpoint occurrence varies considerably across regions and time periods, reflecting differences in station density and observational coverage. Comparisons with 20CRv3 show generally high agreement for all methods, with stronger consistency in the dense French network than in the sparser Southeast Asian network. Despite differences in data retention, breakpoint detection, and adjustment strategy, the homogenised datasets show strong agreement with one another and preserve the principal climatic signal. Notably, differences among the homogenisation methods are consistently smaller than the differences between the original and homogenised datasets, indicating that the primary challenge is not selecting a single optimal algorithm but reconstructing temporally coherent climate information from incomplete historical observations. The homogenised datasets produced in this study constitute HOM-HCLIM, a new global database of homogenised early instrumental temperature records that provides an important resource for climate reconstruction, reanalysis, and long-term climate variability studies.