000125849 001__ 125849 000125849 005__ 20241125101154.0 000125849 0247_ $$2doi$$a10.1038/s41597-022-01919-w 000125849 0248_ $$2sideral$$a133194 000125849 037__ $$aART-2023-133194 000125849 041__ $$aeng 000125849 100__ $$aLundstad, Elin 000125849 245__ $$aThe global historical climate database HCLIM 000125849 260__ $$c2023 000125849 5060_ $$aAccess copy available to the general public$$fUnrestricted 000125849 5203_ $$aThere 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. 000125849 536__ $$9info:eu-repo/grantAgreement/EC/H2020/787574/EU/A Palaeoreanalysis To Understand Decadal Climate Variability/PALAEO-RA$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 787574-PALAEO-RA 000125849 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000125849 590__ $$a5.8$$b2023 000125849 592__ $$a1.937$$b2023 000125849 591__ $$aMULTIDISCIPLINARY SCIENCES$$b16 / 134 = 0.119$$c2023$$dQ1$$eT1 000125849 593__ $$aEducation$$c2023$$dQ1 000125849 593__ $$aComputer Science Applications$$c2023$$dQ1 000125849 593__ $$aStatistics, Probability and Uncertainty$$c2023$$dQ1 000125849 593__ $$aLibrary and Information Sciences$$c2023$$dQ1 000125849 593__ $$aStatistics and Probability$$c2023$$dQ1 000125849 593__ $$aInformation Systems$$c2023$$dQ1 000125849 594__ $$a11.2$$b2023 000125849 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000125849 700__ $$aBrugnara, Yuri 000125849 700__ $$aPappert, Duncan 000125849 700__ $$aKopp, Jérôme 000125849 700__ $$aSamakinwa, Eric 000125849 700__ $$aHürzeler, André 000125849 700__ $$aAndersson, Axel 000125849 700__ $$aChimani, Barbara 000125849 700__ $$aCornes, Richard 000125849 700__ $$aDemarée, Gaston 000125849 700__ $$aFilipiak, Janusz 000125849 700__ $$aGates, Lydia 000125849 700__ $$aIves, Gemma L. 000125849 700__ $$aJones, Julie M. 000125849 700__ $$aJourdain, Sylvie 000125849 700__ $$aKiss, Andrea 000125849 700__ $$aNicholson, Sharon E. 000125849 700__ $$aPrzybylak, Rajmund 000125849 700__ $$aJones, Philip 000125849 700__ $$aRousseau, Daniel 000125849 700__ $$aTinz, Birger 000125849 700__ $$aRodrigo, Fernando S. 000125849 700__ $$aGrab, Stefan 000125849 700__ $$0(orcid)0000-0003-3085-7040$$aDomínguez-Castro, Fernando 000125849 700__ $$aSlonosky, Victoria 000125849 700__ $$aCooper, Jason 000125849 700__ $$aBrunet, Manola 000125849 700__ $$aBrönnimann, Stefan 000125849 773__ $$g10, 1 (2023), [16 pp.]$$pSci. data$$tSCIENTIFIC DATA$$x2052-4463 000125849 8564_ $$s8463655$$uhttps://zaguan.unizar.es/record/125849/files/texto_completo.pdf$$yVersión publicada 000125849 8564_ $$s2655630$$uhttps://zaguan.unizar.es/record/125849/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000125849 909CO $$ooai:zaguan.unizar.es:125849$$particulos$$pdriver 000125849 951__ $$a2024-11-22-12:08:22 000125849 980__ $$aARTICLE