Abstract

The generation of index-based series of meteorological phenomena, derived from narrative descriptions of weather and climate in historical documentary sources, is a common method to reconstruct past climatic variability. This study is the first to explicitly examine the degree of inter-rater variability in producing such series, a potential source of bias in index-based analyses. Two teams of raters were asked to produce a five-category annual rainfall index series for the same dataset, consisting of transcribed narrative descriptions of meteorological variability for 11 ‘rain-years’ in nineteenth-century Lesotho, originally collected by Nash and Grab (2010). One group of raters (n = 71) comprised of students studying for postgraduate qualifications in climatology or a related discipline; the second group (n = 6) consisted of professional meteorologists and historical climatologists working in southern Africa. Inter-rater reliability was high for both groups, at r = 0.99 for the student raters and r = 0.94 for the professional raters, although ratings provided by the student group disproportionately averaged to the central value (0: normal/seasonal rains) where variability was high. Back-calculation of intraclass correlation using the Spearman-Brown prediction formula showed that a target reliability of 0.9 could be obtained with as few as eight student raters, and four professional raters. This number reduced to two when examining a subset of the professional group (n = 4) who had previously published historical climatology papers on southern Africa. We therefore conclude that variability between researchers should be considered minimal where index-based climate reconstructions are generated by trained historical climatologists working in groups of two or more.

Highlights

  • The generation of ordinal-scale indices from documentary sources is one of the most widely used approaches in historical climatology to transform raw weather descriptions into semi-quantitative data (Brázdil et al, 2010; Pfister et al, 2018)

  • One group of raters (n = 71) comprised of students studying for postgraduate qualifications in climatology or a related discipline; the second group (n = 6) consisted of professional meteorologists and historical climatologists working in southern Africa

  • Our findings reinforce the conclusions of Nash et al (2021) that climate indices 310 should be derived by those with training in historical climatology methods, as well as a detailed knowledge of both the climate of the area in question and the nature of the documentary sources

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Summary

Introduction

The generation of ordinal-scale indices from documentary sources is one of the most widely used approaches in historical climatology to transform raw weather descriptions into semi-quantitative data (Brázdil et al, 2010; Pfister et al, 2018). Temperature is the most commonly analysed parameter, for the northern hemisphere, with multicentennial index-based series available for various parts of Europe (e.g. Pfister, 1984; Alexandre, 1987; Pfister, 1992; Brázdil and Kotyza, 1995; Ogilvie and Farmer, 1997; Dobrovolný et al, 2009; Glaser and Riemann, 2009; Camuffo et al, 2010), China (e.g. Wang et al, 2001) and the Americas (e.g. Baron et al, 1984; Baron, 1995). Precipitation is the second most widely analysed variable, with notable regional series produced for parts of Europe (e.g. Van Engelen et al, 2001; Pfister et al, 2006; Rodrigo and Barriendos, 2008; Dobrovolný et al, 2015; Fernández-Fernández et al, 2015; Bauch et al, 2020), China (e.g. Ge et al, 2018), Africa (e.g. Nicholson et al, 2012a; Norrgård, 2015; Nash et al, 2016; Nicholson et al, 2018) and Australia (Fenby and Gergis, 2013; Gergis and Ashcroft, 2013). Index-based series have been generated for floods (e.g. Pfister, 1999; Glaser and Stangl, 2004; Prieto and Rojas, 2015; Salvisberg, 2017; Kiss, 2019), droughts (e.g. Brázdil et al, 2018; Erfurt and Glaser, 2019), snowfalls (e.g. Ge et al, 2003), storminess (e.g. Wang, 1980; Dominguez-Castro et al, 2019), dust fall

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