climpred: verification of weather and climate forecasts¶
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Note
We are actively looking for new contributors for climpred! Riley moved to McKinsey’s Climate Analytics team. Aaron is finishing his PhD in Hamberg, Germany, but will stay in academia. We especially hope for python enthusiasts from seasonal, subseasonal or weather prediction community. In our past coding journey, collaborative coding, feedbacking issues and pull requests advanced our code and thinking about forecast verification more than we could have ever expected. Aaron can provide guidance on implementing new features into climpred. Feel free to implement your own new feature or take a look at the good first issue tag in the issues. Please reach out to us via gitter.
Version 2.1.3 Release¶
March 23th, 2021
After our JOSS
paper is published, the climatology reference forecast was introduced and persistence
forecasts are extended for all metrics (before probabilistic persistence skill was not
calculated) (GH#566).
Furthermore, any errors in PredictionEnsemble.map(func)
or
PredictionEnsemble.call()
does not call silently anymore, but raises warnings
instead (GH#552).
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 or
pip install git+https://github.com/pangeo-data/climpred.git
Getting Started
User Guide
Help & Reference