xclim: xarray-based climate data analytics

Abstract

xclim is a Python library that enables computation of climate indicators over large, heterogeneous data sets. It is built using xarray objects and operations, can seamlessly benefit from the parallelization handling provided by dask, and relies on community conventions for data formatting and metadata attributes. xclim is meant as a tool to facilitate both climate science research and the delivery of operational climate services and products. In addition to climate indicator calculations, xclim also includes utilities for bias correction and statistical adjustment, ensemble analytics, model diagnostics, data quality assurance, and metadata standards compliance. Statement of need Researchers and climate service providers analyse data from large ensembles of Earth System Model (ESM) simulations. These analyses typically include model comparisons with observations , bias-correction and statistical adjustment, computation of various climate indicators and diagnostics, and ensemble statistics. As the number of models contributing to these ensembles grows, so does the complexity of the code required to deal with model idiosyncrasies, outlier detection, unit conversion, etc. In addition, growing ensemble sizes and advancements in the spatiotemporal resolution of ESMs further raises the computational costs of running those analyses. xclim is designed to meet the operational needs of climate service providers by offering algorithms for over 150 climate indicators, multiple downscaling algorithms, ensemble statistics, and other associated utilities.