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.
|
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 |
| 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 |
| Land-Sea mask | lsm | 0-1 | NOA |
| Dataset: Copernicus | |||
| 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 | |||
| 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: 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
Files
CHANGELOG.pdf
Files
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