@misc{9776cb629d1349839c9b16f0f7b3802a,
title = "pySTEPS/pysteps",
abstract = "Pysteps is an open-source and community-driven Python library for probabilistic precipitation nowcasting, i.e. short-term ensemble prediction systems.The aim of pysteps is to serve two different needs. The first is to provide a modular and well-documented framework for researchers interested in developing new methods for nowcasting and stochastic space-time simulation of precipitation. The second aim is to offer a highly configurable and easily accessible platform for practitioners ranging from weather forecasters to hydrologists.The pysteps library supports standard input/output file formats and implements several optical flow methods as well as advanced stochastic generators to produce ensemble nowcasts. In addition, it includes tools for visualizing and post-processing the nowcasts and methods for deterministic, probabilistic, and neighbourhood forecast verification.",
author = "Daniele Nerini and Seppo Pulkkinen and {Perez Hortal}, Andre and Carlos Velasco and Loris Foresti and Ruben Imhoff and Petteri Karsisto and Codacy Badger and Thinker Hong and Jussi Tiira",
year = "2019",
month = apr,
day = "7",
doi = "10.5281/zenodo.2631910",
language = "English",
}