.. THUNER homepage THUNER - Thunderstorm Event Reconnaissance ------------------------------------------------------- .. figure:: ./images/mcs_gridrad_20100804.gif :alt: GridRad Demo Welcome to THUNER's documentation! ========================================= The Thunderstorm Event Reconnaissance (THUNER) package is a flexible toolkit for multi-feature detection, tracking, tagging and analysis of events in meteorological datasets. THUNER's intended application is to the tracking and analysis of convective weather events. If you use this package in your work, consider citing the following papers; - `Leese et al. (1971) 2.0.CO;2>`__ - `Dixon and Wiener (1993) 2.0.CO;2>`__ - `Whitehall et al. (2015) `__ - `Fridlind et al (2019) `__ - `Raut et al (2021) `__ - `Short et al. (2023) `__ Note many excellent alternatives to THUNER exist, including `PyFLEXTRKR `__, `GTG `__, `TAMS `__, `tobac `__ and `MOAAP `__. When designing a tracking based research project involving THUNER, consider performing sensitivity tests using these alternatives. Check out the :doc:`installation` section for instructions on installing and running THUNER Contents -------- .. toctree:: :maxdepth: 2 :numbered: introduction installation tutorials api for_developers Acknowledgements ------------------ THUNER was developed by `Ewan Short `__ while supported by Australian Research Council grants `CE170100023 `__. and `DP200102516 `__. Computational resources during development were provided by the Australian `National Computational Infrastructure (NCI) `__. THUNER's documentation is hosted on Read the Docs. .. figure:: ./images/logo_black.svg :alt: THUNER logo :align: center