Wildfire
Published September 26, 2024 | Version 0.4
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SeasFire Cube: A Global Dataset for Seasonal Fire Modeling in the Earth System

Creators

  • 1. Max Planck Institut of Biochemistry
  • 2. National Observatory of Athens
  • 3. Harokopio University of Athens

Description

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 <at> 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 <at> noa.gr) has led the efforts to collect and process them.

Notes

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

Files

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