Version 2.0.0 Release¶
We now support sub-annual (e.g., seasonal, monthly, weekly, daily) forecasts.
We provide a host of deterministic and probabilistic metrics. We support both
perfect-model and hindcast-based prediction ensembles, and provide
PerfectModelEnsemble
and
HindcastEnsemble
classes to make analysis easier.
See quick start and our examples to get started.
Installation¶
You can install the latest release of climpred
using pip
or conda
:
pip install climpred
conda install -c conda-forge climpred
You can also install the bleeding edge (pre-release versions) by cloning this
repository and running pip install . --upgrade
in the main directory
Getting Started
User Guide
- Setting Up Your Dataset
- PredictionEnsemble Objects
- Verification Alignment
- Metrics
- Comparisons
- Significance Testing
- Prediction Terminology
- Reference Forecasts
Help & Reference
- API Reference
- What’s New
- Helpful Links
- Publications Using climpred
- Contribution Guide
- Code of Conduct
- Release Procedure
- Contributors