The forgotten drought of 1765-1768: Reconstructing and re-evaluating historical droughts in the British and Irish Isles

Abstract

<p>Historical precipitation records are fundamental for the management of water resources, yet rainfall observations typically span 100 – 150 years at most, with considerable uncertainties surrounding earlier records. Here, we analyse some of the longest available precipitation records globally, for England and Wales, Scotland and Ireland. To assess the credibility of these records and extend them further back in time, we statistically reconstruct (using independent predictors) monthly precipitation series representing these regions for the period 1748-2000. By applying the Standardised Precipitation Index at 12-month accumulations (SPI-12) to the observed and our reconstructed series we re-evaluate historical meteorological droughts. We find strong agreement between observed and reconstructed drought chronologies in post-1870 records, but divergence in earlier series due to biases in early precipitation observations. Hence, the 1800s decade was less drought prone in our reconstructions relative to observations. Overall, the drought of 1834-1836 was the most intense SPI-12 event in our reconstruction for England and Wales. Newspaper accounts and documentary sources confirm the extent of impacts across England in particular. We also identify a major, ‘forgotten’ drought in 1765-1768 that affected the British-Irish Isles. This was the most intense event in our reconstructions for Ireland and Scotland, and ranks first for accumulated deficits across all three regional series. Moreover, the 1765-1768 event was also the most extreme multi-year drought across all regional series when considering 36-month accumulations (SPI-36). Newspaper and other sources confirm the occurrence and major socio-economic impact of this drought, such as major rivers like the Shannon being fordable by foot. Our results provide new insights into historical droughts across the British Irish Isles. Given the importance of historical droughts for stress-testing the resilience of water resources, drought plans and supply systems, the forgotten drought of 1765-1768 offers perhaps the most extreme benchmark scenario in more than 250-years.</p>

A weather diary from Donegal, Ireland, 1846–1875

“…Murphy et al . (2020) identify a severe drought event for Ireland and England and Wales for the period September 1864 to June 1866 using the Standardised Precipitation Index (SPI) at 12‐month accumulations (i.e. SPI‐12), which coincides with and adds confidence to these observations.…”

“…Again Murphy et al . (2020) identify a severe drought in the England and Wales precipitation series for the period June 1868 to February 1869 using SPI‐12, while for the same period they identify moderate drought conditions over Ireland.…”

An open workflow to gain insights about low‐likelihood high‐impact weather events from initialized predictions

“…Furthermore, UNSEEN is one tool within many available tools to study plausible low‐likelihood high‐impact weather events. There is scope to assess the mutual benefit of various approaches, as is common for event attribution (Philip et al, 2020; van Oldenborgh et al, 2021), including ensembles of opportunity (e.g., King et al, 2017; Lewis et al, 2017), single‐model initial‐condition large ensembles (e.g., Suarez‐Gutierrez et al, 2020a, 2020b), ensemble reinitialization methods (e.g., Gessner et al, 2021), targeted large ensemble experiments (e.g., Guillod et al, 2017; Mitchell et al, 2017), pooling of observations (e.g., Berghuijs et al, 2017; Robinson et al, 2021), long archives (Hawkins et al, 2019; Murphy et al, 2020), paleoclimatic records (Yan et al, 2020), and statistical weather generators (Brunner & Gilleland, 2020; Wilks & Wilby, 1999; Yiou, 2014). Seasonal and decadal prediction systems may, furthermore, contribute additional lines of evidence to event attribution statement if their trend estimates can be extrapolated to represent pre‐industrial climates.…”

“…Many approaches have been developed to reduce sampling uncertainties, ranging from traditional statistical weather generators (Brunner & Gilleland, 2020; Wilks & Wilby, 1999; Yiou, 2014), extreme value approaches (Coles, 2001; Katz, 2013), and dynamical systems theory (De Luca et al, 2020; Faranda et al, 2017); through pooling of observations (e.g., Berghuijs et al, 2017; Robinson et al, 2021), the use of long archives (Hawkins et al, 2019; Murphy et al, 2020), and paleoclimatic records (Yan et al, 2020); to probing ensemble members from weather and climate models (Box 1). Ensembles of opportunity (e.g., King et al, 2017; Lewis et al, 2017), single‐model initial‐condition large ensembles (SMILEs) (e.g., Suarez‐Gutierrez et al, 2020a, 2020b), ensemble reinitialization methods (e.g., Gessner et al, 2021), and targeted large ensemble experiments (e.g., Guillod et al, 2017; Hall et al, 2019; Mitchell et al, 2017), have all been used for the study of low‐likelihood high‐impact hydro‐climatic events.…”

Nonstationary weather and water extremes: a review of methods for their detection, attribution, and management

“…O'Connor et al, 2020;Smith et al, 2017;Bonnet et al, 2020). Although such datasets lengthen the period available for analysis and better reflect ranges of variability in extremes such as drought (Murphy et al, 2020a), they are subject to limitations from changes in measurement practice, decreasing density of observations in early records, and a lack of consideration of issues such as changes in land cover and shifts in channel capacity (Slater et al, 2015).…”