Additional Products
Copernicus Global 30 meter Digital Elevation Model dataset in COG format
The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters. The Copernicus DEM GLO-30 is distributed by OpenTopography and corresponds to the DGED 2023_1 release of the Copernicus DEM.
| Property | Value |
|---|---|
| Spatial extent | [-180.0, -90.0, 180.0, 90.0] |
| Temporal extent | 2010/12/12 - 2012/11/20 |
| DOI | 10.71570/84mw-cg74 |
Copernicus Global 90 meter Digital Elevation Model dataset in COG format
The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. GLO-90 provides worldwide coverage at 90 meters (refers to 30 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters. The Copernicus DEM GLO-90 is distributed by OpenTopography and corresponds to the DGED 2023_1 release of the Copernicus DEM.
| Property | Value |
|---|---|
| Spatial extent | [-180.0, -90.0, 180.0, 90.0] |
| Temporal extent | 2010/12/12 - 2012/11/20 |
| DOI | 10.71570/9eac-fa33 |
High-resolution 3D NO2 (DACNO2) over Western Europe, Daily - V1
Daily 3-D NO2 concentrations (µg m-3) over Western Europe, on a 2 km × 2 km grid at 8 height levels from the surface to 5000 m. Produced by DACNO2, a deep learning model driven by meteorology, emission proxies, and geographic predictors, and trained against CAMS European air quality reanalysis and EEA surface observations.
| Property | Value |
|---|---|
| Spatial extent | [-5, 42, 9, 54] |
| Temporal extent | 2023/01/01 - Current |
| DOI | 10.71570/411j-8063 |
High-resolution 3D NO2 (DACNO2) over Western Europe, Monthly - V1
Monthly mean 3-D NO2 concentrations (µg m-3) over Western Europe, on a 2 km × 2 km grid at 8 height levels from the surface to 5000 m. Derived from daily fields produced by DACNO2, a deep learning model driven by meteorology, emission proxies, and geographic predictors, and trained against CAMS European air quality reanalysis and EEA surface observations.
| Property | Value |
|---|---|
| Spatial extent | [-5, 42, 9, 54] |
| Temporal extent | 2023/01/01 - Current |
| DOI | 10.71570/1ck8-pb92 |
High-resolution 3D NO2 (DACNO2) over Western Europe, Yearly - V1
Yearly mean 3-D NO2 concentrations (µg m-3) over Western Europe, on a 2 km × 2 km grid at 8 height levels from the surface to 5000 m. Derived from daily fields produced by DACNO2, a deep learning model driven by meteorology, emission proxies, and geographic predictors, and trained against CAMS European air quality reanalysis and EEA surface observations.
| Property | Value |
|---|---|
| Spatial extent | [-5, 42, 9, 54] |
| Temporal extent | 2023/01/01 - Current |
| DOI | 10.71570/hhy2-t149 |
Agrometeorological indicators from 2000 to present derived from reanalysis (AgERA5)
This dataset provides daily surface meteorological data as input for agriculture and agro-ecological studies. This dataset is based on the hourly ECMWF ERA5 data at surface level and is referred to as AgERA5. Acquisition and pre-processing of the original ERA5 data is a complex and specialized job. By providing the AgERA5 dataset, users are freed from this work and can directly start with meaningful input for their analyses and modelling. To this end, the variables provided in this dataset match the input needs of most agriculture and agro-ecological models.
Data were aggregated to daily time steps at the local time zone and corrected towards a finer topography at a 0.1° spatial resolution. The correction to the 0.1° grid was realized by applying grid and variable-specific regression equations to the ERA5 dataset interpolated at 0.1° grid. The equations were trained on ECMWF’s operational high-resolution atmospheric model (HRES) at a 0.1° resolution. This way the data is tuned to the finer topography, finer land use pattern and finer land-sea delineation of the ECMWF HRES model.
The data was produced on behalf of the Copernicus Climate Change Service.
This collection holds a selection of the AgERA5 version 2.0 variables, downloaded from the Copernicus Climate Data Store and converted to Cloud Optimized GeoTIFF. Each item bundles the variables available for a single day.
| Property | Value |
|---|---|
| Spatial extent | [-180.0, -90.0, 180.0, 90.0] |
| Temporal extent | 2000/01/01 - Current |
| DOI | 10.71570/8e7x-an80 |