Scope of climpred#

climpred aims to be the primary package used to analyze output from initialized dynamical forecast models, ranging from short-term weather forecasts to decadal climate forecasts. The code base is driven by the geoscientific prediction community through open source development. It leverages xarray to keep track of core prediction ensemble dimensions (e.g., ensemble member, initialization date, and lead time) and dask to perform out-of-memory computations on large datasets.

The primary goal of climpred is to offer a comprehensive set of analysis tools for assessing the forecasts relative to a validation product (e.g., observations, reanalysis products, control simulations, baseline forecasts). This ranges from simple deterministic and probabilistic verification metrics — such as, e.g. mean absolute error or rank histogram — to more advanced contingency table-derived metrics. climpred expects users to handle their domain-specific post-processing of model output, so that the package can focus on the actual analysis of forecasts.

Finally, the climpred documentation will serve as a repository of unified analysis methods through jupyter notebook examples, and collects relevant references and literature.