ERA5-based global meteorological wildfire danger maps
| Autor: | Giorgio Libertà, Claudia Vitolo, Christopher Barnard, Jesús San-Miguel-Ayanz, Ruth Coughlan, Blazej Krzeminski, Francesca Di Giuseppe |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Statistics and Probability
Data Descriptor 010504 meteorology & atmospheric sciences Meteorology 0211 other engineering and technologies Natural Earth Poison control 02 engineering and technology Library and Information Sciences 01 natural sciences Proxy (climate) Education Environmental impact Fire protection Information system lcsh:Science 0105 earth and related environmental sciences 021110 strategic defence & security studies Emergency management business.industry Global warming Probabilistic logic Natural hazards Computer Science Applications Environmental science lcsh:Q Statistics Probability and Uncertainty business Information Systems |
| Zdroj: | Scientific Data, Vol 7, Iss 1, Pp 1-11 (2020) Scientific Data |
| ISSN: | 2052-4463 |
| Popis: | Forest fires are an integral part of the natural Earth system dynamics, however they are becoming more devastating and less predictable as anthropogenic climate change exacerbates their impacts. In order to advance fire science, fire danger reanalysis products can be used as proxy for fire weather observations with the advantage of being homogeneously distributed both in space and time. This manuscript describes a reanalysis dataset of fire danger indices based on the Canadian Fire Weather Index system and the ECMWF ERA5 reanalysis dataset, which supersedes the previous dataset based on ERA-Interim. The new fire danger reanalysis dataset provides a number of benefits compared to the one based on ERA-Interim: it relies on better estimates of precipitation, evaporation and soil moisture, it is available in a deterministic form as well as a probabilistic ensemble and it is characterised by a considerably higher spatial resolution. It is a valuable resource for forestry agencies and scientists in the field of wildfire danger modeling and beyond. The global dataset is produced by ECMWF, as the computational centre of the European Forest Fire information System (EFFIS) of the Copernicus Emergency Management Service, and it is made available free of charge through the Climate Data Store. Measurement(s)wetness of soil • wildfire • effort required for fire suppression • fire intensityTechnology Type(s)computational modeling techniqueSample Characteristic - Environmentforest ecosystemSample Characteristic - LocationEarth (planet) Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12497732 |
| Databáze: | OpenAIRE |
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