xclim Official Documentation
xclim is an operational Python library for climate services, providing numerous climate-related indicator tools with an extensible framework for constructing custom climate indicators, statistical downscaling and bias adjustment of climate model simulations, as well as climate model ensemble analysis tools.
xclim is built using xarray and can seamlessly benefit from the parallelization handling provided by dask. Its objective is to make it as simple as possible for users to perform typical climate services data treatment workflows. Leveraging xarray and dask, users can easily bias-adjust climate simulations over large spatial domains or compute indices from large climate datasets.
- Why xclim?
- Basic Usage
- Workflow Examples
- Ensemble-Reduction Techniques
- Frequency analysis
- Customizing and controlling xclim
- Extending xclim
- Statistical Downscaling and Bias-Adjustment
- Statistical Downscaling and Bias-Adjustment - Advanced tools
- Frequency adaption with a rolling window
- Spatial Analogues examples
- Uncertainty partitioning
- Climate Indicators
- Climate Indices
- Health Checks
- Unit Handling
- Command Line Interface
- Bias Adjustment and Downscaling Algorithms
- Spatial Analogues