DOCU-CLIM: A global documentary climate dataset for climate
reconstructions

J 2023

DOCU-CLIM: A global documentary climate dataset for climate reconstructions

BURGDORF, Angela-Maria; Stefan BRÖNNIMANN; George ADAMSON; Tatsuya AMANO; Yasuyuki AONO et al.

Základní údaje

Originální název

DOCU-CLIM: A global documentary climate dataset for climate reconstructions

Autoři

BURGDORF, Angela-Maria; Stefan BRÖNNIMANN; George ADAMSON; Tatsuya AMANO; Yasuyuki AONO; David BARRIOPEDRO; Teresa BULLÓN; Chantal CAMENISCH; Dario CAMUFFO; Valérie DAUX; María del Rosario PRIETO; Petr DOBROVOLNÝ; David GALLEGO; Ricardo GARCIA-HERRERA; Joelle GERGIS; Stefan GRAB; Matthew J HANNAFORD; Jari HOLOPAINEN; Clare KELSO; Zoltán KERN; Andrea KISS; Elaine Kuan-Hui LIN; Neil J LOADER; Martin MOŽNÝ; David NASH; Sharon E NICHOLSON; Christian PFISTER; Fernando S RODRIGO; This RUTISHAUSER; Sapna SHARMA; Katalin TAKÁCS; Ernesto T VARGAS a Inmaculada VEGA

Vydání

Scientific Data, Nature Research, 2023, 2052-4463

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10510 Climatic research

Stát vydavatele

Německo

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 5.800

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14310/23:00131265

Organizační jednotka

Přírodovědecká fakulta

Klíčová slova anglicky

Atmospheric science; Palaeoclimate

Štítky

14315030, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 19. 7. 2023 11:36, Mgr. Marie Novosadová Šípková, DiS.

Anotace

V originále

Documentary climate data describe evidence of past climate arising from predominantly written historical documents such as diaries, chronicles, newspapers, or logbooks.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 The dataset DOCU-CLIM comprises 621 time series (both published and hitherto unpublished) providing information on historical variations in temperature, precipitation, and wind regime.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.

Citovat

@article{2298178,
   author = {Burgdorf, AngelaandMaria and Brönnimann, Stefan and Adamson, George and Amano, Tatsuya and Aono, Yasuyuki and Barriopedro, David and Bullón, Teresa and Camenisch, Chantal and Camuffo, Dario and Daux, Valérie and Prieto, María del Rosario and Dobrovolný, Petr and Gallego, David and GarciaandHerrera, Ricardo and Gergis, Joelle and Grab, Stefan and Hannaford, Matthew J and Holopainen, Jari and Kelso, Clare and Kern, Zoltán and Kiss, Andrea and Lin, Elaine KuanandHui and Loader, Neil J and Možný, Martin and Nash, David and Nicholson, Sharon E and Pfister, Christian and Rodrigo, Fernando S and Rutishauser, This and Sharma, Sapna and Takács, Katalin and Vargas, Ernesto T and Vega, Inmaculada},
   article_number = {1},
   doi = {https://doi.org/10.1038/s41597-023-02303-y},
   keywords = {Atmospheric science; Palaeoclimate},
   language = {eng},
   issn = {2052-4463},
   journal = {Scientific Data},
   title = {DOCU-CLIM: A global documentary climate dataset for climate reconstructions},
   url = {https://doi.org/10.1038/s41597-023-02303-y},
   volume = {10},
   year = {2023}
}

TY  - JOUR
ID  - 2298178
AU  - Burgdorf, Angela-Maria - Brönnimann, Stefan - Adamson, George - Amano, Tatsuya - Aono, Yasuyuki - Barriopedro, David - Bullón, Teresa - Camenisch, Chantal - Camuffo, Dario - Daux, Valérie - Prieto, María del Rosario - Dobrovolný, Petr - Gallego, David - Garcia-Herrera, Ricardo - Gergis, Joelle - Grab, Stefan - Hannaford, Matthew J - Holopainen, Jari - Kelso, Clare - Kern, Zoltán - Kiss, Andrea - Lin, Elaine Kuan-Hui - Loader, Neil J - Možný, Martin - Nash, David - Nicholson, Sharon E - Pfister, Christian - Rodrigo, Fernando S - Rutishauser, This - Sharma, Sapna - Takács, Katalin - Vargas, Ernesto T - Vega, Inmaculada
PY  - 2023
TI  - DOCU-CLIM: A global documentary climate dataset for climate reconstructions
JF  - Scientific Data
VL  - 10
IS  - 1
SP  - 1-14
EP  - 1-14
PB  - Nature Research
SN  - 20524463
KW  - Atmospheric science
KW  - Palaeoclimate
UR  - https://doi.org/10.1038/s41597-023-02303-y
N2  - Documentary 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.
ER  -

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