Abstract
This data descriptor documents a dataset containing over 38 years of global reanalysis of wildfire danger. It consists of seven fields to assess fuel moisture as well as fire behavior. The methodology employed to generate these data is based on the Canadian Forest Fire Weather Danger Rating and utilizes weather forcing from ERA-Interim, a global reanalysis dataset produced by the European Centre for Medium-range Weather Forecasts. Global fire danger reanalysis data are used to quantify the climatological expectation of fire danger at a certain time of the year and for any location on the globe. It can be regarded as a complementary product to the fire danger forecasts issued daily by the Global Wildfire Information System (GWIS) under the umbrella of the European Copernicus program.
Highlights
Background & SummaryForest fires are extremely costly hazards in terms of lives, natural resources and infrastructures
High wind variability favors the spread over larger areas, compared to cases in which wind blows mainly in one dominant direction. Most of these mechanisms are in-built in the Canadian Fire Weather Index (FWI) system[4,5] which is one of the most widely used model to estimate fire danger worldwide[6,7]
The daily forecasts of FWI model outputs are provided by the European Centre for Medium-range Weather Forecasts (ECMWF) using the atmospheric forcings calculated from its ensemble prediction system
Summary
Forest fires are extremely costly hazards in terms of lives, natural resources and infrastructures. The scientific community is actively studying (through in situ observation and remote sensing) fire behavior to better identify the atmospheric predictors that determine a sustained fire activity once an ignition has occurred These predictors are used to assess current danger condition and to forecast its evolution in the future. The FWI danger rating system was designed to exploit the information provided by in situ observations and it only depends on weather variables. It only provides a qualitative overview of where conditions could lead to uncontrollable fires. We hope that this work will boost the data uptake and visibility in the wider scientific community and beyond
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