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
Summary
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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