A Bayesian approach to historical climatology for the Burgundian Low Countries in the 15th century

<p>Although collaborative efforts have been made to retrieve climate data from instrumental observations and paleoclimate records, there is still a large amount of valuable information in historical archives that has not been utilized for climate reconstruction. Due to the qualitative nature o...

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Bibliographic Details
Main Authors: C. Camenisch, F. Jaume-Santero, S. White, Q. Pei, R. Hand, C. Rohr, S. Brönnimann
Format: Article
Language:English
Published: Copernicus Publications 2022-11-01
Series:Climate of the Past
Online Access:https://cp.copernicus.org/articles/18/2449/2022/cp-18-2449-2022.pdf
Description
Summary:<p>Although collaborative efforts have been made to retrieve climate data from instrumental observations and paleoclimate records, there is still a large amount of valuable information in historical archives that has not been utilized for climate reconstruction. Due to the qualitative nature of these datasets, historical texts have been compiled and studied by historians aiming to describe the climate impact in socioeconomic aspects of human societies, but the inclusion of this information in past climate reconstructions remains fairly unexplored. Within this context, we present a novel approach to assimilate climate information contained in chronicles and annals from the 15th century to generate robust temperature and precipitation reconstructions of the Burgundian Low Countries, taking into account uncertainties associated with the descriptions of narrative sources. After data assimilation, our reconstructions present a high seasonal temperature correlation of <span class="inline-formula">∼0.8</span> independently of the climate model employed to estimate the background state of the atmosphere. Our study aims to be a first step towards a more quantitative use of available information contained in historical texts, showing how Bayesian inference can help the climate community with this endeavor.</p>
ISSN:1814-9324
1814-9332