TINT (TINT is not TITAN) is an easy-to-use storm cell tracking package based on the TITAN methodology by Dixon and Wiener. This code is in early alpha stage, so documentation and testing are still being built. If you have any suggestions or wish to contribute, please open an issue. Feel free to email me at mhpicel@gmail.com if you need assistance.
To install TINT, first install the dependencies listed above. NOTE: Py-ART needs to be installed from source because TINT requires updates that are ahead of the current conda and pypi release.
Then clone:
git clone https://github.com/openradar/TINT.git
then:
cd TINT python setup.py install
Thanks to Bhupendra Raut for creating the original protoype for this tracking method in R.
The development of this software is supported by the Climate Model Development and Validation (CMDV) activity funded by the Office of Biological and Environmental Research in the US Department of Energy Office of Science.
Dixon, M. and G. Wiener, 1993: TITAN: Thunderstorm Identification, Tracking, Analysis, and Nowcasting—A Radar-based Methodology. J. Atmos. Oceanic Technol., 10, 785–797, doi: 10.1175/1520-0426(1993)010<0785:TTITAA>2.0.CO;2.
Leese, J.A., C.S. Novak, and B.B. Clark, 1971: An Automated Technique for Obtaining Cloud Motion from Geosynchronous Satellite Data Using Cross Correlation. J. Appl. Meteor., 10, 118–132, doi: 10.1175/1520-0450(1971)010<0118:AATFOC>2.0.CO;2.