dc.contributor.author |
Lundstad, Elin |
dc.contributor.author |
Brugnara, Yuri |
dc.contributor.author |
Pappert, Duncan |
dc.contributor.author |
Kopp, Jerome |
dc.contributor.author |
Samakinwa, Eric |
dc.contributor.author |
Hurzeler, Andre |
dc.contributor.author |
Andersson, Axel |
dc.contributor.author |
Chimani, Barbara |
dc.contributor.author |
Corrnes, Richard |
dc.contributor.author |
Demaree, Gaston |
dc.contributor.author |
Filipiak, Janusz |
dc.contributor.author |
Gates, Lydia |
dc.contributor.author |
Ives, Gemma L. |
dc.contributor.author |
Jones, Julie M. |
dc.contributor.author |
Jourdain, Sylvie |
dc.contributor.author |
Kiss, Andrea |
dc.contributor.author |
Nicholson, Sharon E. |
dc.contributor.author |
Przybylak, Rajmund |
dc.contributor.author |
Jones, Philip |
dc.contributor.author |
Rousseau, Daniel |
dc.contributor.author |
Tinz, Birger |
dc.contributor.author |
Rodrigo, Fernardo S. |
dc.contributor.author |
Grab, Stefan |
dc.contributor.author |
Dominguez-Castro, Fernando |
dc.contributor.author |
Slonosky, Victoria |
dc.contributor.author |
Cooper, Jason |
dc.contributor.author |
Brunet Manolla |
dc.contributor.author |
Bronnimann, Stefan |
dc.date.accessioned |
2023-06-16T01:28:50Z |
dc.date.available |
2023-06-16T01:28:50Z |
dc.date.issued |
2023 |
dc.identifier.citation |
Scientific Data 10, Article number 44 (2023) |
dc.identifier.other |
https://doi.org/10.1038/s41597-022-01919-w |
dc.identifier.uri |
http://repozytorium.umk.pl/handle/item/6881 |
dc.description |
Long-term instrumental meteorological series are crucial for the understanding of interannual-to-decadal variations in climate. Analyzed together with model simulations and climate proxies they may provide new insight
into underlying climate mechanisms, such as long-lasting droughts, changes in atmospheric circulation, or
effects of volcanic eruptions, and may serve as a basis for the generation of more comprehensive data products
in reconstruction or data assimilation approaches. Long-term instrumental meteorological series also serve
as a reference against which human induced climate change can be compared. For instance, Hawkins et al. (2017) suggested using the period 1720–1800 as a preindustrial reference, but only few records from this period are
currently available. We define a record as a meteorological time series with one variable at one location. |
dc.description.abstract |
There is a growing need for past weather and climate data to support science and decision-making.
This paper describes the compilation and construction of a global multivariable (air temperature,
pressure, precipitation sum, number of precipitation days) monthly instrumental climate database
that encompasses a substantial body of the known early instrumental time series. The dataset contains
series compiled from existing databases that start before 1890 (though continuing to the present) as
well as a large amount of newly rescued data. All series underwent a quality control procedure and
subdaily series were processed to monthly mean values. An inventory was compiled, and the collection
was deduplicated based on coordinates and mutual correlations. The data are provided in a common
format accompanied by the inventory. The collection totals 12452 meteorological records in 118
countries. The data can be used for climate reconstructions and analyses. It is the most comprehensive
global monthly climate dataset for the preindustrial period so far. |
dc.description.sponsorship |
European Research Council (ERC) under the European Union’s Horizon 2020
research and innovation programme grant agreement No 787574 (PALAEO-RA),
the Swiss National Science Foundation (project WeaR 188701), Copernicus Climate Change Service (C3S) 311a Lot 1, the Federal Office of Meteorology and Climatology MeteoSwiss in the framework of GCOS Switzerland (project “Long Swiss
Meteorological Series, the NCN projects No. DEC 2020/37/B/ST10/00710
and No. 2020/39/B/ST10/00653, the Nicolaus Copernicus University–Emerging field: Global Environmental Changes. |
dc.language.iso |
eng |
dc.rights |
Attribution-NonCommercial-NoDerivs 3.0 Poland |
dc.rights.uri |
http://creativecommons.org/licenses/by-nc-nd/3.0/pl/ |
dc.subject |
historical climatology |
dc.subject |
global climate |
dc.subject |
datasets |
dc.subject |
data rescue |
dc.title |
The global historical climate database HCLIM |
dc.type |
info:eu-repo/semantics/article |