Introduction
European Climate Assessment & Dataset (ECA&D) offers datasets with daily gridded climate parameters, the E-OBS gridded dataset. This dataset is freely available for research and directly available for download without any registration or special scripting.
Prerequisite
There is no prerequisite for accessing and downloading the E-OBS data, but use is restricted. If you want to automate the download as described in this post you must have Karttur’s GeoImagine Framework installed.
E-OBS
E-OBS is a daily gridded observational dataset at 0.1 or 0.25 degrees spatial resolution over Europe derived from ECA&D information. the following thematic daily data is available:
| dataset | abbreviation |
| daily mean temperature | TG |
| daily minimum temperature | TN |
| daily maximum temperature | TX |
| daily precipitation sum | RR |
| daily mean sea level pressure | PP |
| daily mean wind speed | FG |
| daily mean relative humidity | HU |
| global radiation |
Access E-OBS data
E-OBS data access chunks offers downloading by just clicking the datasets you want. All data are offered at both 0.1 and 0.25 degrees spatial resolutions. The data is derived from an ensemble of models, and both the mean and the spread are available.
Using Karttur’s GeoImagine Framework
You can use Karttur’s GeoImagine to automate the download. Instead of clicking the individual files to download you create a list of the files you want to download and then save it as a simple text file (*.txt). The example below lists all the files with Daily precipitation sum (RR) at 0.1 degrees spatial resolution:
https://knmi-ecad-assets-prd.s3.amazonaws.com/ensembles/data/Grid_0.1deg_reg_ensemble/rr_ens_mean_0.1deg_reg_1950-1964_v26.0e.nc
https://knmi-ecad-assets-prd.s3.amazonaws.com/ensembles/data/Grid_0.1deg_reg_ensemble/rr_ens_mean_0.1deg_reg_1965-1979_v26.0e.nc
https://knmi-ecad-assets-prd.s3.amazonaws.com/ensembles/data/Grid_0.1deg_reg_ensemble/rr_ens_mean_0.1deg_reg_1980-1994_v26.0e.nc
https://knmi-ecad-assets-prd.s3.amazonaws.com/ensembles/data/Grid_0.1deg_reg_ensemble/rr_ens_mean_0.1deg_reg_1995-2010_v26.0e.nc
https://knmi-ecad-assets-prd.s3.amazonaws.com/ensembles/data/Grid_0.1deg_reg_ensemble/rr_ens_mean_0.1deg_reg_2011-2022_v26.0e.nc
To download the listed files, use the Framework process DownloadAncillary and define the download in a Json command file: 0115-download-E-OBS. You then have to link the Json command file to the list of executions to run:
## Download E-OBS Climate data ##
0115-download-E-OBS.json
Extract E-OBS data
The E-Obs data is delivered as Network Common Data Form version 4 NetCDF-4 (*.nc) files. To extract the 15 years worth of data from the file you need to define the connection between the bands in the NetCDF and the date they represent. To view the information of a NetCDF I use GDAL (see post on Install GDAL, QGIS and GRASS).
Using the naming of the downloaded files as defined in the Json command file: 0115-download-E-OBS:
gdalinfo path/to/rr_ens_mean_0.1deg_reg_1950-1964_v26.0e.nc
% gdalinfo /Volumes/sewetland/DOWNLOADS/E-OBS/RR/data/rr_ens_mean_0.1deg_reg_1950-1964_v26.0e.nc
Driver: netCDF/Network Common Data Format
Files: /Volumes/sewetland/DOWNLOADS/E-OBS/RR/data/rr_ens_mean_0.1deg_reg_1950-1964_v26.0e.nc
Size is 705, 465
Origin = (-25.000139508999698,71.499858543732898)
Pixel Size = (0.099999999599954,-0.099999995440814)
Metadata:
latitude#axis=Y
latitude#long_name=Latitude values
latitude#standard_name=latitude
latitude#units=degrees_north
longitude#axis=X
longitude#long_name=Longitude values
longitude#standard_name=longitude
longitude#units=degrees_east
NC_GLOBAL#Conventions=CF-1.4
NC_GLOBAL#E-OBS_version=26.0e
NC_GLOBAL#history=Fri Sep 30 08:24:40 2022: ncks --no-abc -d time,0,5478 /data2/Else/EOBSv26.0e/Grid_0.1deg/rr//rr_ensmean_master_rectime.nc /data2/Else/EOBSv26.0e/Grid_0.1deg/rr//rr_ens_mean_0.1deg_reg_1950-1964_v26.0e.nc
Fri Sep 30 08:22:30 2022: ncks --no-abc --mk_rec_dmn time /data2/Else/EOBSv26.0e/Grid_0.1deg/rr//rr_ensmean_master.nc /data2/Else/EOBSv26.0e/Grid_0.1deg/rr//rr_ensmean_master_rectime.nc
Fri Sep 30 07:11:36 2022: ncks -O -d time,0,26478 /data2/Else/EOBSv26.0e/Grid_0.1deg/rr/rr_ensmean_master_untilJul2022.nc /data2/Else/EOBSv26.0e/Grid_0.1deg/rr/rr_ensmean_master.nc
NC_GLOBAL#NCO=netCDF Operators version 4.7.5 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)
NC_GLOBAL#References=http://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php
NETCDF_DIM_EXTRA={time}
NETCDF_DIM_time_DEF={5479,4}
NETCDF_DIM_time_VALUES={0,1,2 ... 5478}
rr#add_offset=0
rr#cell_methods=time: mean
rr#long_name=rainfall
rr#scale_factor=0.1
rr#standard_name=thickness_of_rainfall_amount
rr#units=mm
rr#_FillValue=-9999
time#calendar=standard
time#cell_methods=time: mean
time#long_name=Time in days
time#standard_name=time
time#units=days since 1950-01-01 00:00
Corner Coordinates:
Upper Left ( -25.0001395, 71.4998585)
Lower Left ( -25.0001395, 24.9998607)
Upper Right ( 45.4998602, 71.4998585)
Lower Right ( 45.4998602, 24.9998607)
Center ( 10.2498603, 48.2498596)
Band 1 Block=705x465 Type=Int16, ColorInterp=Undefined
NoData Value=-9999
Unit Type: mm
Offset: 0, Scale:0.100000001490116
Metadata:
add_offset=0
cell_methods=time: mean
long_name=rainfall
NETCDF_DIM_time=0
NETCDF_VARNAME=rr
scale_factor=0.1
standard_name=thickness_of_rainfall_amount
units=mm
_FillValue=-9999
Band 2 Block=705x465 Type=Int16, ColorInterp=Undefined
NoData Value=-9999
Unit Type: mm
Offset: 0, Scale:0.100000001490116
Metadata:
add_offset=0
cell_methods=time: mean
long_name=rainfall
NETCDF_DIM_time=1
NETCDF_VARNAME=rr
scale_factor=0.1
standard_name=thickness_of_rainfall_amount
units=mm
_FillValue=-9999
...
...
Band 5479 Block=705x465 Type=Int16, ColorInterp=Undefined
NoData Value=-9999
Unit Type: mm
Offset: 0, Scale:0.100000001490116
Metadata:
add_offset=0
cell_methods=time: mean
long_name=rainfall
NETCDF_DIM_time=5478
NETCDF_VARNAME=rr
scale_factor=0.1
standard_name=thickness_of_rainfall_amount
units=mm
_FillValue=-9999
With 15 years worth of daily data, each NetCDF file contains approximately 5479 bands (dependent on how the leap years fall). You can not extract these individually; an automated process is needed. For this tutorial we will use Karttur’s GeoImagine Framework and the process OrganizeNetCDFetGRIB In the background the process calls gdal_translate.
Extract NetCDF using Karttur’s GeoImagine Framework
If you installed Karttur’s GeoImagine Framework, you can use the process OrganizeNetCDFetGRIB for extracting all bands in a NetCDF file automatically. They will then be extracted into the default system of the Framework and also registered in the Framework database.
gdal_translate -of GTiff -b 10 file.nc test.tiff
daily mean temperature (0.1):
https://knmi-ecad-assets-prd.s3.amazonaws.com/ensembles/data/Grid_0.1deg_reg_ensemble/tg_ens_mean_0.1deg_reg_1950-1964_v26.0e.nc
https://knmi-ecad-assets-prd.s3.amazonaws.com/ensembles/data/Grid_0.1deg_reg_ensemble/tg_ens_mean_0.1deg_reg_1965-1979_v26.0e.nc
https://knmi-ecad-assets-prd.s3.amazonaws.com/ensembles/data/Grid_0.1deg_reg_ensemble/tg_ens_mean_0.1deg_reg_1980-1994_v26.0e.nc
https://knmi-ecad-assets-prd.s3.amazonaws.com/ensembles/data/Grid_0.1deg_reg_ensemble/tg_ens_mean_0.1deg_reg_1995-2010_v26.0e.nc
https://knmi-ecad-assets-prd.s3.amazonaws.com/ensembles/data/Grid_0.1deg_reg_ensemble/tg_ens_mean_0.1deg_reg_2011-2022_v26.0e.nc