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Data pro článek. Reliability of fire danger forecasts for Czech agricultural and forestry landscapes
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SYSNO ASEP 0619176 Zařazení RIV Záznam nebyl označen do RIV Název Data pro článek. Reliability of fire danger forecasts for Czech agricultural and forestry landscapes Překlad názvu Data for the article. Reliability of fire danger forecasts for Czech agricultural and forestry landscapes Tvůrce(i) Kudláčková, Lucie (UEK-B) ORCID, RID, SAI Jazyk dok. cze - čeština Klíč. slova Fire danger ; Weather forecast ; Number of wildfires Obor OECD Climatic research Institucionální podpora UEK-B - RVO:86652079 DOI https://doi.org/10.57680/asep.0619176 Anotace This dataset encompasses analytical outputs evaluating the reliability of fire danger forecasts in the Czech Republic using the Canadian Fire Weather Index (FWI) and the Australian Forest Fire Danger Index (FFDI). The dataset includes seasonal distributions of wildfire occurrences from 2018 to 2022, highlighting the bimodal nature of fire seasons with peaks in spring and summer. It provides comparative analyses of FWI and FFDI values. Linear regression models estimating fire occurrences based on individual and combined index values are presented. Inclusion of random effects to account for regional variability (NUTS 3 level) further enhances prediction accuracy. Additionally, the dataset assesses the performance of five numerical weather prediction models in forecasting fire danger, identifying the IFS model as the most suitable for Czech conditions and dataset provides information about fire occurrence stratified by land cover type, distinguishing agricultural areas and forested landscapes. Překlad anotace This dataset encompasses analytical outputs evaluating the reliability of fire danger forecasts in the Czech Republic using the Canadian Fire Weather Index (FWI) and the Australian Forest Fire Danger Index (FFDI). The dataset includes seasonal distributions of wildfire occurrences from 2018 to 2022, highlighting the bimodal nature of fire seasons with peaks in spring and summer. It provides comparative analyses of FWI and FFDI values. Linear regression models estimating fire occurrences based on individual and combined index values are presented. Inclusion of random effects to account for regional variability (NUTS 3 level) further enhances prediction accuracy. Additionally, the dataset assesses the performance of five numerical weather prediction models in forecasting fire danger, identifying the IFS model as the most suitable for Czech conditions and dataset provides information about fire occurrence stratified by land cover type, distinguishing agricultural areas and forested landscapes. Pracoviště Ústav výzkumu globální změny Kontakt Nikola Šviková, svikova.n@czechglobe.cz, Tel.: 511 192 268 Rok sběru 2026
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