ECMWFCode4Earth/ml_drought
Machine learning to better predict and understand drought. Moving github.com/ml-clim
Implements an end-to-end pipeline for standardizing climate data into unified formats suitable for ML model training and evaluation, with modular task classes handling data preprocessing, feature engineering, and intercomparison workflows. Integrates with ECMWF/Copernicus Climate Data Store APIs and supports both Conda and Docker containerization for reproducible execution across heterogeneous environments.
No commits in the last 6 months.
Stars
93
Forks
18
Language
Jupyter Notebook
License
—
Category
Last pushed
May 18, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ECMWFCode4Earth/ml_drought"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
confidence-duku/bakaano-hydro
A distributed hydrology-guided neural network model for streamflow prediction
OuyangWenyu/torchhydro
TorchHydro: datasets, and models for watershed hydrological modeling
mhpi/hydrodl2
Repository for MHPI differentiable hydrological models.
WaterFutures/water-futures-battle
Part of the Battle of Water Networks competition series | WDSA/CCWI 2026, May 18-21, Paphos,...
JohnNay/forecastVeg
A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python