The information in this GitHub page is intended for the training activities developed and organized through time by the H SAF consortium. Some material may refer to discontinued H SAF products and the scripts may use superseded versions of the required Python packages. The information and the material are provided on a “as is” basis and will be not updated/maintained in the future, hence it may not work as expected. The user is referred to the new updated material provided by the consortium. For any further inquiries, contact the H SAF user support at us_hsaf@meteoam.it
ECMWF is hosting the H SAF and HEPEX joint workshop on “Satellite inspired hydrology in an uncertain future” from 25-28 November 2019.
Part of the workshop will be a demonstration sessions on Thursday afternoon (28 Nov). Please find below the description and instruction of the demo sessions.
Demonstrations (from download to visualization) of surface soil moisture (SSM), root-zone soil moisture (RZSM) and a drought monitoring application of the products can be found in the soil moisture cluster folder. To run the jupyter notebook exercises, you will first need to install the relevant python libraries, which can be done by running the miniconda scripts provided. The miniconda scripts will install the libraries on a local environment on either linux or MacOS systems. Note that recent operating systems are required (e.g. MacOs Mojave or Ubuntu 16).
Access to the H SAF ftp is also important in order to download the products (new users can register here for a username and password http://hsaf.meteoam.it/user-registration.php)
Instructions to run soil moisture demo in terminal:
- Download Exercises and environment setup from Cluster Folder
- Download SSM test data from Dropbox Repository
- Run miniconda script: ./conda_env_setup_linux.sh or ./conda_env_setup_macOS.sh
- Activate local environment: source activate work_env
- Run jupyter notebook demo: jupyter-notebook workshop_demo_XXXX.ipynb
Instructions to run soil moisture applications in terminal:
- Download Exercises and environment setup from Cluster Folder
- Download Data from Dropbox Repository
- Run miniconda script: ./conda_env_setup_linux.sh or ./conda_env_setup_macOS.sh
- Activate local environment: source activate work_env
- Enter to exercise folder: cd /ex_XXXX/
- Run jupyter notebook application: jupyter-notebook ex_XXXX.ipynb