climpred: analysis of ensemble forecast models for climate prediction

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

• Overview: Why climpred?
• Scope of climpred
• Quick Start
• Examples

User Guide

• Setting Up Your Dataset
• PredictionEnsemble Objects
• Comparisons
• Metrics
• Prediction Terminology
• Baseline Forecasts

Help & Reference

• API Reference
• What’s New
• Helpful Links
• Publications Using climpred
• Contribution Guide
• Release Procedure
• Contributors