The SeasFire Cube is a scientific datacube for seasonal fire forecasting around the globe. Apart from seasonal fire forecasting, which is the aim of the SeasFire project, the datacube can be used for several other tasks. For example, it can be used to model teleconnections and memory effects in the earth system. Additionally, it can be used to model emissions from wildfires and the evolution of wildfire regimes. It has been created in the context of the SeasFire project, which deals with "Earth System Deep Learning for Seasonal Fire Forecasting" and is funded by the European Space Agency (ESA) in the context of ESA Future EO-1 Science for Society Call. It contains 21 years of data (2001-2021) in an 8-days time resolution and 0.25 degrees grid resolution. It has a diverse range of seasonal fire drivers. It expands from atmospheric and climatological ones to vegetation variables, socioeconomic and the target variables related to wildfires such as burned areas, fire radiative power, and wildfire-related CO2 emissions. Datacube properties Feature Value Spatial Coverage Global Temporal Coverage 2001 to 2021 Spatial Resolution 0.25 deg x 0.25 deg Temporal Resolution 8 days Number of Variables 54 Tutorial Link https://github.com/SeasFire/seasfire-datacube Full name DataArray name Unit Contact * Dataset: ERA5 Meteo Reanalysis Data Mean sea level pressure mslp Pa NOA Total precipitation tp m MPI Relative humidity rel_hum % MPI Vapor Pressure Deficit vpd hPa MPI Sea Surface Temperature sst K MPI Skin temperature skt K MPI Wind speed at 10 meters ws10 m*s-2 MPI Temperature at 2 meters - Mean t2m_mean K MPI Temperature at 2 meters - Min t2m_min K MPI Temperature at 2 meters - Max t2m_max K MPI Surface net solar radiation ssr MJ m-2 MPI Surface solar radiation downwards ssrd MJ m-2 MPI Volumetric soil water level 1 swvl1 m3/m3 MPI Volumetric soil water level 2 swvl2 m3/m3 MPI Volumetric soil water level 3 swvl3 m3/m3 MPI Volumetric soil water level 4 swvl4 m3/m3 MPI Land-Sea mask lsm 0-1 NOA Dataset: Copernicus CEMS Drought Code Maximum drought_code_max unitless NOA Drought Code Average drought_code_mean unitless NOA Fire Weather Index Maximum fwi_max unitless NOA Fire Weather Index Average fwi_mean unitless NOA Dataset: CAMS: Global Fire Assimilation System (GFAS) Carbon dioxide emissions from wildfires cams_co2fire kg/m² NOA Fire radiative power cams_frpfire W/m² NOA Dataset: FireCCI - European Space Agency’s Climate Change Initiative Burned Areas from Fire Climate Change Initiative (FCCI) fcci_ba ha NOA Valid mask of FCCI burned areas fcci_ba_valid_mask 0-1 NOA Fraction of burnable area fcci_fraction_of_burnable_area % NOA Number of patches fcci_number_of_patches N NOA Fraction of observed area fcci_fraction_of_observed_area % NOA Dataset: Nasa MODIS MOD11C1, MOD13C1, MCD15A2 Land Surface temperature at day lst_day K MPI Leaf Area Index lai m²/m² MPI Normalized Difference Vegetation Index ndvi unitless MPI Dataset: Nasa SEDAC Gridded Population of the World (GPW), v4 Population density pop_dens persons per square kilometers NOA Dataset: Global Fire Emissions Database (GFED) Burned Areas from GFED (large fires only) gfed_ba hectares (ha) MPI Valid mask of GFED burned areas gfed_ba_valid_mask 0-1 NOA GFED basis regions gfed_region N NOA Dataset: Global Wildfire Information System (GWIS) Burned Areas from GWIS gwis_ba ha NOA Valid mask of GWIS burned areas gwis_ba_valid_mask 0-1 NOA Dataset: NOAA Climate Indices Arctic Oscillation Index oci_ao unitless NOA Western Pacific Index oci_wp unitless NOA Pacific North American Index oci_pna unitless NOA North Atlantic Oscillation oci_nao unitless NOA Southern Oscillation Index oci_soi unitless NOA Global Mean Land/Ocean Temperature oci_gmsst unitless NOA Pacific Decadal Oscillation oci_pdo unitless NOA Eastern Asia/Western Russia oci_ea unitless NOA East Pacific/North Pacific Oscillation oci_epo unitless NOA Nino 3.4 Anomaly oci_nino_34_anom unitless NOA Bivariate ENSO Timeseries oci_censo unitless NOA Dataset: ESA CCI Land Cover Class 0 - No data lccs_class_0 % NOA Land Cover Class 1 - Agriculture lccs_class_1 % NOA Land Cover Class 2 - Forest lccs_class_2 % NOA Land Cover Class 3 - Grassland lccs_class_3 % NOA Land Cover Class 4 - Wetlands lccs_class_4 % NOA Land Cover Class 5 - Settlement lccs_class_5 % NOA Land Cover Class 6 - Shrubland lccs_class_6 % NOA Land Cover Class 7 - Sparse vegetation, bare areas, permanent snow and ice lccs_class_7 % NOA Land Cover Class 8 - Water Bodies lccs_class_8 % NOA Dataset: Biomes Dataset: Calculated Grid Area in square meters area m² NOA *The datacube specifications (temporal, spatial resolution, chunk size) have been set up by the Max Planck Institut (MPI) team. For the variables that the contact is MPI, Lazaro Alonso (lalonso bgc-jena.mpg.de) has led the efforts to collect and process them. For the variables that the contact is NOA, Ilektra Karasante (ile.karasante noa.gr) has led the efforts to collect and process them.

The creation of this cube has been funded by the European Space Agency (ESA), in the context of ESA Future EO-1 Science for Society Call