Lessons
Detailed breakdown of all hands-on labs and resources throughout the workshop.
📓 Jupyter Notebooks
Interactive notebooks for hands-on learning. Launch them in Binder or run locally.

Python Fundamentals
| Notebook | Description | Launch |
| Python Setup | Environment setup and configuration |  |
| Python Basics | Variables, data types, control flow |  |
| NumPy | Array operations and numerical computing |  |
| Pandas | DataFrames and tabular data |  |
| Matplotlib | Data visualization and plotting |  |
Geospatial & Climate Data
VECTRI Modeling
📜 Download Scripts
Python scripts for automated data downloading. All scripts are in the docs/scripts/ folder.
Rainfall Data
| Script | Dataset | Description |
download_chirps.py | CHIRPS | Daily rainfall (0.05°, 1981-present) |
download_arc2.py | ARC2 | Africa rainfall (0.1°, 1983-present) |
download_tamsat.py | TAMSAT | Africa rainfall (0.0375°, 1983-present) |
download_gfs_precip_forecast.py | NCEP GFS | Precipitation forecast (0.25°, 0-16 days) |
download_ecmwf-hres_precip.py | ECMWF HRES | Precipitation forecast (0.25°, 0-10 days) |
download_ecmwf-s2s-precip.py | ECMWF S2S | Sub-seasonal precipitation (1.5°, 0-46 days) |
download_ecmwf_s2s_precip_daily_ensemble.py | ECMWF S2S Ensemble | Ensemble precipitation forecasts |
download_c3s_seasonal_precip_ensmean_daily.py | C3S SEAS5 | Seasonal precipitation (0-7 months) |
download_chc_cmip6_precip_daily.py | CHC-CMIP6 | Climate projections (2015-2100) |
Temperature Data
| Script | Dataset | Description |
download_chirts.py | CHIRTS | Daily temperature (0.05°, 1983-2016) |
download_era5-land-temp.py | ERA5-Land | Reanalysis temperature (0.1°, 1950-present) |
download_era5-temp.py | ERA5 | Reanalysis temperature (0.25°, 1940-present) |
download_gfs_temp_forecast.py | NCEP GFS | Temperature forecast (0.25°, 0-16 days) |
download_ecmwf-hres_temp.py | ECMWF HRES | Temperature forecast (0.25°, 0-10 days) |
download_ecmwf-s2s-temp.py | ECMWF S2S | Sub-seasonal temperature (1.5°, 0-46 days) |
download_ecmwf_s2s_temp_daily_ensemble.py | ECMWF S2S Ensemble | Ensemble temperature forecasts |
download_c3s_seasonal_temp_ensmean_daily.py | C3S SEAS5 | Seasonal temperature (0-7 months) |
download_chc_cmip6_temp_daily.py | CHC-CMIP6 | Temperature projections (2015-2100) |
Population & Soil Data
| Script | Dataset | Description |
download_afripop_worldpop.py | AfriPop/WorldPop | Population density (100m-1km) |
download_worldpop_projections.py | WorldPop Projections | Population projections (2015-2030) |
download_harmonized_world_soil_database.py | HWSD | Soil texture fractions (~1km) |
📊 Sample Data
Pre-processed sample datasets for testing and learning (available in /data/samples/):
| File | Description | Size |
sample_chirps.nc | CHIRPS rainfall for Ethiopia | ~10 MB |
sample_era5.nc | ERA5 temperature for Ethiopia | ~15 MB |
ethiopia_admin.shp | Administrative boundaries | ~2 MB |
example_sys5.nc | VECTRI system configuration | ~1 MB |
example_data.nc | VECTRI input data | ~5 MB |
🚀 Quick Start
Run Notebooks Locally
# Clone the repository
git clone https://github.com/YonSci/vectri-mkdocs.git
cd vectri-mkdocs
# Create environment
conda create -n vectri python=3.11 -y
conda activate vectri
# Install dependencies
pip install -r requirements.txt
# Launch Jupyter
jupyter lab
Run Download Scripts
# Example: Download CHIRPS data for Ethiopia
python docs/scripts/download_chirps.py \
--start-date 2020-01-01 \
--end-date 2020-12-31 \
--lat-min 3 --lat-max 15 \
--lon-min 33 --lon-max 48 \
--output data/chirps_ethiopia_2020.nc
Need Help?
- Check the Resources page for documentation
- Review the Setup guide for installation issues
- Ask instructors during workshop sessions
- Collaborate with teammates!