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Getting Started

  • Overview: Why climpred?
  • Scope of climpred
  • Quick Start
  • Examples
    • Calculate skill for NWP model GEFS for 6-hourly global forecasts
    • Skill from ECMWF downloaded with herbie
    • Calculate skill of a MJO Index of SubX model GEOS_V2p1 as function of daily lead time
    • Calculate skill of a MJO Index of S2S models as function of daily lead time
    • Calculate skill of a MJO Index of SubX model GEOS_V2p1 as function of weekly lead time
    • Calculate skill of S2S model ECMWF for daily global reforecasts
    • Calculate ENSO Skill of NMME model NCEP-CFSv2 as Function of Initial Month vs. Lead Time
    • Calculate Seasonal ENSO Skill of the NMME model NCEP-CFSv2
    • Demo of Perfect Model Predictability Functions
    • Hindcast Predictions of Equatorial Pacific SSTs
    • Diagnosing Potential Predictability
    • Significance Testing
    • Implications of verify(dim)
    • climpred on CPU vs GPU
    • Setting up your own output

User Guide

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

Help & Reference

  • API Reference
    • climpred.classes.PredictionEnsemble
    • climpred.classes.PredictionEnsemble.__init__
    • climpred.classes.PredictionEnsemble.__len__
    • climpred.classes.PredictionEnsemble.__iter__
    • climpred.classes.PredictionEnsemble.__delitem__
    • climpred.classes.PredictionEnsemble.__contains__
    • climpred.classes.PredictionEnsemble.__add__
    • climpred.classes.PredictionEnsemble.__sub__
    • climpred.classes.PredictionEnsemble.__mul__
    • climpred.classes.PredictionEnsemble.__truediv__
    • climpred.classes.PredictionEnsemble.__getitem__
    • climpred.classes.PredictionEnsemble.__getattr__
    • climpred.classes.PredictionEnsemble.coords
    • climpred.classes.PredictionEnsemble.nbytes
    • climpred.classes.PredictionEnsemble.sizes
    • climpred.classes.PredictionEnsemble.dims
    • climpred.classes.PredictionEnsemble.chunks
    • climpred.classes.PredictionEnsemble.chunksizes
    • climpred.classes.PredictionEnsemble.data_vars
    • climpred.classes.PredictionEnsemble.equals
    • climpred.classes.PredictionEnsemble.identical
    • climpred.classes.HindcastEnsemble
    • climpred.classes.HindcastEnsemble.__init__
    • climpred.classes.HindcastEnsemble.add_observations
    • climpred.classes.HindcastEnsemble.add_uninitialized
    • climpred.classes.HindcastEnsemble.get_initialized
    • climpred.classes.HindcastEnsemble.get_observations
    • climpred.classes.HindcastEnsemble.get_uninitialized
    • climpred.classes.HindcastEnsemble.verify
    • climpred.classes.HindcastEnsemble.bootstrap
    • climpred.classes.HindcastEnsemble.generate_uninitialized
    • climpred.classes.HindcastEnsemble.smooth
    • climpred.classes.HindcastEnsemble.remove_bias
    • climpred.classes.HindcastEnsemble.remove_seasonality
    • climpred.classes.HindcastEnsemble.plot
    • climpred.classes.HindcastEnsemble.plot_alignment
    • climpred.classes.PerfectModelEnsemble
    • climpred.classes.PerfectModelEnsemble.__init__
    • climpred.classes.PerfectModelEnsemble.add_control
    • climpred.classes.PerfectModelEnsemble.get_initialized
    • climpred.classes.PerfectModelEnsemble.get_control
    • climpred.classes.PerfectModelEnsemble.get_uninitialized
    • climpred.classes.PerfectModelEnsemble.verify
    • climpred.classes.PerfectModelEnsemble.bootstrap
    • climpred.classes.PerfectModelEnsemble.generate_uninitialized
    • climpred.classes.PerfectModelEnsemble.smooth
    • climpred.classes.PerfectModelEnsemble.remove_seasonality
    • climpred.classes.PerfectModelEnsemble.plot
    • climpred.bootstrap.bootstrap_uninit_pm_ensemble_from_control_cftime
    • climpred.bootstrap.bootstrap_uninitialized_ensemble
    • climpred.bootstrap.dpp_threshold
    • climpred.bootstrap.varweighted_mean_period_threshold
    • climpred.prediction.compute_perfect_model
    • climpred.reference.compute_persistence
    • climpred.reference.compute_persistence_from_first_lead
    • climpred.reference.compute_uninitialized
    • climpred.reference.compute_climatology
    • climpred.horizon.horizon
    • climpred.stats.decorrelation_time
    • climpred.stats.dpp
    • climpred.stats.varweighted_mean_period
    • climpred.stats.rm_poly
    • climpred.stats.rm_trend
    • climpred.tutorial.load_dataset
    • climpred.preprocessing.shared.load_hindcast
    • climpred.preprocessing.shared.rename_to_climpred_dims
    • climpred.preprocessing.shared.rename_SLM_to_climpred_dims
    • climpred.preprocessing.shared.set_integer_time_axis
    • climpred.preprocessing.mpi.get_path
    • climpred.smoothing.temporal_smoothing
    • climpred.smoothing.spatial_smoothing_xesmf
    • climpred.graphics.plot_bootstrapped_skill_over_leadyear
    • climpred.graphics.plot_ensemble_perfect_model
    • climpred.graphics.plot_lead_timeseries_hindcast
    • climpred.utils.convert_init_lead_to_valid_time_lead
    • climpred.utils.convert_valid_time_lead_to_init_lead
    • climpred.metrics.Metric
    • climpred.metrics.Metric.__init__
    • climpred.metrics.Metric.__repr__
    • climpred.metrics._get_norm_factor
    • climpred.metrics._pearson_r
    • climpred.metrics._pearson_r_p_value
    • climpred.metrics._effective_sample_size
    • climpred.metrics._pearson_r_eff_p_value
    • climpred.metrics._spearman_r
    • climpred.metrics._spearman_r_p_value
    • climpred.metrics._spearman_r_eff_p_value
    • climpred.metrics._mse
    • climpred.metrics._rmse
    • climpred.metrics._mae
    • climpred.metrics._median_absolute_error
    • climpred.metrics._nmse
    • climpred.metrics._nmae
    • climpred.metrics._nrmse
    • climpred.metrics._msess
    • climpred.metrics._mape
    • climpred.metrics._smape
    • climpred.metrics._uacc
    • climpred.metrics._std_ratio
    • climpred.metrics._conditional_bias
    • climpred.metrics._unconditional_bias
    • climpred.metrics._bias_slope
    • climpred.metrics._msess_murphy
    • climpred.metrics._crps
    • climpred.metrics._crpss
    • climpred.metrics._crpss_es
    • climpred.metrics._brier_score
    • climpred.metrics._threshold_brier_score
    • climpred.metrics._rps
    • climpred.metrics._discrimination
    • climpred.metrics._reliability
    • climpred.metrics._rank_histogram
    • climpred.metrics._contingency
    • climpred.metrics._roc
    • climpred.metrics._spread
    • climpred.metrics._mul_bias
    • climpred.metrics._less
    • climpred.comparisons.Comparison
    • climpred.comparisons.Comparison.__init__
    • climpred.comparisons.Comparison.__repr__
    • climpred.comparisons._e2o
    • climpred.comparisons._m2o
    • climpred.comparisons._m2m
    • climpred.comparisons._m2e
    • climpred.comparisons._m2c
    • climpred.comparisons._e2c
    • climpred.options.set_options
  • What’s New
  • Code of Conduct
  • Contribution Guide
  • Contributors
  • Helpful Links
  • Literature
  • Publications Using climpred
  • Related Packages
  • Release Procedure
  • Repository
  • Suggest edit
  • Open issue
  • .rst

Related Packages

Related Packages#

We’re big fans of open-source software at climpred and want to support and collaborate with any other forecasting-related packages. Below is a list of packages that have some place in the Earth System forecasting world. Please reach out to us if you are aware of any open-source packages in this domain that are not on the list.

  • Microsoft forecasting: A collection of best practices for time series forecasting.

  • MurCSS: A tool for standardized evaluation of decadal hindcast systems. See also this and this page for additional resources on scoring from MurCSS.

  • properscoring: Probabilistic forecast metrics in python. (We’ve since wrapped these functions in xskillscore.)

  • pySTEPS: Framework for short-term ensemble forecasting of precipitation.

  • S2D Verification: An R package for a common set of tools for forecast verification.

  • SwirlsPy: Analysis and prediction of nowcasts for precipitation and weather phenomena.

  • xskillscore: Metrics for verifying forecasts (a key dependency to climpred).

  • doppyo with many metrics transferred to xskillscore

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© Copyright 2019-2023, climpred development team.

Last updated on 2023-04-05.