DOCU-CLIM: A global documentary climate dataset for climate reconstructions
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Published:2023-06-23
Issue:1
Volume:10
Page:
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ISSN:2052-4463
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Container-title:Scientific Data
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language:en
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Short-container-title:Sci Data
Author:
Burgdorf Angela-Maria, Brönnimann StefanORCID, Adamson George, Amano TatsuyaORCID, Aono YasuyukiORCID, Barriopedro David, Bullón Teresa, Camenisch Chantal, Camuffo Dario, Daux ValérieORCID, del Rosario Prieto María, Dobrovolný Petr, Gallego DavidORCID, García-Herrera RicardoORCID, Gergis Joelle, Grab Stefan, Hannaford Matthew J., Holopainen Jari, Kelso Clare, Kern Zoltán, Kiss AndreaORCID, Kuan-Hui Lin Elaine, Loader Neil J., Možný Martin, Nash David, Nicholson Sharon E., Pfister Christian, Rodrigo Fernando S.ORCID, Rutishauser This, Sharma SapnaORCID, Takács Katalin, Vargas Ernesto T., Vega Inmaculada
Abstract
AbstractDocumentary climate data describe evidence of past climate arising from predominantly written historical documents such as diaries, chronicles, newspapers, or logbooks. Over the past decades, historians and climatologists have generated numerous document-based time series of local and regional climates. However, a global dataset of documentary climate time series has never been compiled, and documentary data are rarely used in large-scale climate reconstructions. Here, we present the first global multi-variable collection of documentary climate records. The dataset DOCU-CLIM comprises 621 time series (both published and hitherto unpublished) providing information on historical variations in temperature, precipitation, and wind regime. The series are evaluated by formulating proxy forward models (i.e., predicting the documentary observations from climate fields) in an overlapping period. Results show strong correlations, particularly for the temperature-sensitive series. Correlations are somewhat lower for precipitation-sensitive series. Overall, we ascribe considerable potential to documentary records as climate data, especially in regions and seasons not well represented by early instrumental data and palaeoclimate proxies.
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
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