Drought Code - ERA-Interim
Creators
- 1. European Centre for Medium-Range Weather Forecasts
- 2. European Centre for Medium-range Weather Forecasts
Description
The Drought Code (DC) is a numeric rating of the average moisture content of deep, compact organic layers. This code is a useful indicator of seasonal drought effects on forest fuels and the amount of smoldering in deep duff layers and large logs.
This is part of a larger dataset providing gridded field calculations from the Canadian Fire Weather Index System using weather forcings from the European Centre for Medium-range Weather Forecast (ECMWF) ERA-Interim reanalysis dataset (Vitolo et al., 2019; Di Giuseppe et al., 2016). The dataset has been developed through a collaboration between the Joint Research Centre and ECMWF under the umbrella of the Global Wildfires Information System (GWIS), a joint initiative of the GEO and the Copernicus Work Programs. The whole dataset consists of seven indices, each of which describes a different aspect of the effect that fuel moisture and wind have on fire ignition probability and its behavior, if started. The indices are called: Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build Up Index (BUI), Fire Weather Index (FWI) and Daily Severity Rating (DSR). For convenience, each index is archived separately.
Data are generated using the open source software GEFF v3.0 (https://git.ecmwf.int/projects/CEMSF/repos/geff), which now uses settings and parameters provided by the JRC (more info here https://git.ecmwf.int/projects/CEMSF/repos/geff/browse/NEWS.md).
This dataset can be manipulated using the caliver R package (Vitolo et al. 2017, 2018).
Details:
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File format: netcdf4
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Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326).
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Longitude range: [-180, +180]
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Latitude range: [-90, +90]
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Temporal resolution: 1 day
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Spatial resolution: 0.7 degrees (~80 Km)
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Spatial coverage: Global
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Time span: from 1980-01-01 to 2018-12-31
Notes
Files
Files
(7.5 GB)
Name | Size | Download all |
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md5:3f2820c17e5a874564c915f1a2dfe59e
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7.5 GB | Download |
Additional details
Related works
- Is referenced by
- 10.1038/sdata.2019.32 (DOI)
- References
- 10.1175/JAMC-D-15-0297.1 (DOI)
- 10.5281/zenodo.582416 (DOI)
- 10.1371/journal.pone.0189419 (DOI)
Funding
References
- Di Giuseppe, F., Pappenberger, F., Wetterhall, F., Krzeminski, B., Camia, A., Libertá, G. and San Miguel, J., 2016. The potential predictability of fire danger provided by numerical weather prediction. Journal of Applied Meteorology and Climatology, 55(11), pp.2469-2491. DOI: https://doi.org/10.1175/JAMC-D-15-0297.1
- Vitolo C., Di Giuseppe F., D'Andrea M., 2018. Caliver: An R package for CALIbration and VERification of forest fire gridded model outputs. PLoS ONE 13(1): e0189419. https://doi.org/10.1371/journal.pone.0189419
- Vitolo C., Di Giuseppe F., D'Andrea M., 2017. caliver R package version 1.0. URL: https://github.com/ecmwf/caliver, DOI: https://doi.org/10.5281/zenodo.582416.
- Vitolo C., Di Giuseppe F., Krzeminski B., San-Miguel-Ayanz J., 2019. A 1980–2018 global fire danger re-analysis dataset for the Canadian Fire Weather Indices, Scientific Data. https://doi.org/10.1038/sdata.2019.32