Some of the services that we’ll leech the data from require annoying accounts. These have to be set-up first and are assumed to be working.
Basically, you just need to follow the instructions. You sign-up to the Climate Data Store, create an account, and then just follow the instructions.
For this, you need to create an EarthData Login account. Once you have this, you probably want to try to download a product with that account to activate it. You can do this by just clicking on this link and downloading it.
Once you have set-up the accounts above, you can easily download the data using command line tools, or developing your own codes. Bear in mind that the amount of data can be significant, so a large enough storage space is needed, as well as a reasonable Internet connection.
The ERA5 data is the new generation ECMWF reanalysis product. As a reanalysis product, it is geared towards the past (providing an optimal estimate of the state using all available observations), and thus its usage in NRT is actually supplemented by using data from other ECMWF archives. The variables selected are:
10m_u_component_of_wind
10m_v_component_of_wind
2m_dewpoint_temperature
2m_temperature
evaporation
potential_evaporation
surface_solar_radiation_downwards
total_precipitation
volumetric_soil_water_layer_1
volumetric_soil_water_layer_2
volumetric_soil_water_layer_3
volumetric_soil_water_layer_4
(other variables can be selected by changing the code).Once the the CDS API account has been created, you can just use the simple script data_downloaders/era_downloader.py. The instructions are basically
Usage
=====
SYNOPSIS
./era_downloader.py
DESCRIPTION
A program to download Copernicus data.
EXAMPLES
./era_downloader.py -v
EXIT STATUS
No exit status yet, can't be bothered.
AUTHOR
J Gomez-Dans <j.gomez-dans@ucl.ac.uk>
See also https://github.com/NCEO-ODA/ghana_data
Options
=======
--help, -h show this help message and exit
--verbose, -v verbose output
--data_folder=OUTPUT_FOLDER, -d OUTPUT_FOLDER
Output folder to save data
--region=REGION, -r REGION
Region name
--lat=LAT, -y LAT Minimum/maximum latitude in decimal degrees.
--lon=LON, -x LON Minimum/maximum longitude in decimal degrees.
The script will download all the data available since 2000, but will check for existing files and will only download new data. So, to download data for Ghana (extent from -4 to 5 degrees longitude, 1 to 12 degrees latitude), we may use
python ./era_downloader.py -v d era5_download/ -r Ghana -y 1,12 -x -4,5
Since this is likely to take a while, you may want to use nohup and log the output to a file:
nohup python ./era_downloader.py -v d era5_download/ -r Ghana -y 1,12 -x -4,5 &>era_dload.log&
This downloads all the files (with names like ERA5_Ghana.2002_12.nc, where Ghana is the region name option, and we have year 2002 and month 12). The files are stored under era5_download/netcdf, in the original NetCDF format.
The files contain hourly data at the native resolution for the variables listed above. We usually require daily data, and we move to GeoTIFF format (a more network friendly data format), by using the data_downloader/era_to_tif.py script. This script basically reuses the location from the previous one (era5_download) and works on an annual basis:
python ./era_to_tif.py era5_download 2004