pysteps v1.5.0

Pysteps v1.5.0 is now available with some exciting new features! We would like to thank everyone who contributed to this release.

Key updates

• Add new ensemble nowcast model: Lagrangian INtegro-Difference equation model with Autoregression (LINDA) by Pulkkinen et al. (2021). [#221, gallery]
• Implement the local Lagrangian approach for probabilistic nowcasting by Germann and Zawadzki (2004). [#207, gallery]
• Refactor the utils.interpolate module. The rbfinterp2d method now wraps the scipy's Rbf class, while the old version is renamed to idwinterp2d (inverse distance interpolation). [#210]
• Implement the max_num_features keyword argument for all methods in the pysteps.feature module. With this argument, the user can specify the maximum number of detected features. [#225]

Bug fixes

• Fix a bug in utils.spectral.rapsd function causing negative frequency for evenly-sized images. [#211]
• Fix coordinates of the bounding box in io.importers.import_mrms_grib. [#222]

Installation

You can upgrade to the latest release using pip install pysteps --upgrade or conda update pysteps -c conda-forge. It is also possible to build from source following these instructions.

Important note

This release represents our last feature release for pysteps v1, while our efforts will now focus on the upcoming v2! See #216 to learn more about this.

Contributors

Thanks to the following developers for their contributions in this release (alphabetical order):
@aperezhortal, @dnerini, @loforest, @pulkkins, @RubenImhoff