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v2.1.2

Getting Started

  • Overview: Why climpred?
  • Scope of climpred
  • Quick Start
  • Examples
    • Dask
      • Using dask with climpred
    • Pre-Processing
      • Setting up your own output
      • intake-esm for cmorized output
    • Subseasonal
      • Calculate the skill of a MJO Index as a function of lead time
      • Calculate the skill of a MJO Index as a function of lead time for Weekly Data
    • Monthly and Seasonal
      • Calculate ENSO Skill as a Function of Initial Month vs. Lead Time
      • Calculate Seasonal ENSO Skill
    • Decadal
      • Demo of Perfect Model Predictability Functions
      • Hindcast Predictions of Equatorial Pacific SSTs
      • Diagnosing Potential Predictability
      • Significance Testing

User Guide

  • Setting Up Your Dataset
  • PredictionEnsemble Objects
  • Verification Alignment
  • Metrics
  • Comparisons
  • Significance Testing
  • Bias Removal
  • Temporal and Spatial Smoothing
  • Prediction Terminology
  • Reference Forecasts

Help & Reference

  • API Reference
  • What’s New
  • Code of Conduct
  • Contribution Guide
  • Contributors
  • Helpful Links
  • Publications Using climpred
  • Related Packages
  • Release Procedure
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  • Examples
  • Edit on GitHub

Examples¶

Note

Please use the climpred-dev enviroment

$ conda env create -f ci/requirements/climpred-dev.yml

to ensure that all dependencies are installed to complete all example notebooks listed here.

Dask¶

  • Using dask with climpred

Pre-Processing¶

  • Setting up your own output
  • intake-esm for cmorized output

Subseasonal¶

  • Calculate the skill of a MJO Index as a function of lead time
  • Calculate the skill of a MJO Index as a function of lead time for Weekly Data

Monthly and Seasonal¶

  • Calculate ENSO Skill as a Function of Initial Month vs. Lead Time
  • Calculate Seasonal ENSO Skill

Decadal¶

  • Demo of Perfect Model Predictability Functions
  • Hindcast Predictions of Equatorial Pacific SSTs
  • Diagnosing Potential Predictability
  • Significance Testing
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