Change Log

Version 0.4 (Alpha) - April 29, 2015

• Tidy up code
• Improve installation procedure
• Work on reproducibility (through virtualenv)
• Get all tests working

Version MSc_Dissertation (Alpha) - August 28, 2014

• Implementing SGD training/matching against IBTrACS data
• Look into different classifiers: SGD/QDC/cutoff etc.
• Plot all figures for dissertation

Version 0.3 (Alpha) - August 15, 2014

• Implementing SGD training/matching against IBTrACS data
• Improve worker crash handling in pyro_cluster
• Improve documentation
• Run for 20 years worth of analysis on UCL computers
• Fix bugs with Pyro code
• Fix up tests

Version 0.2 (Alpha) - July 18, 2014

• Abstract out tracking code and have first shot at implementing a Kalman filter based tracker
• Implement StormtracksResultsManager that can be used for saving/loading results to disk
• Improve pyro_cluster code to the point where it is usable (speedups of 10x using 15 UCL computers)
• Add logging to pyro_cluster code to aid debugging
• Handle lons/lats consistently - always use -180 to 180 in code
• Add some functional/bug tests
• PEP8 test all code in tests
• Document most classes/functions (and add a coverage check in documentation)
• Make names more consistent in code
• Fix some bugs

Version 0.1 (Alpha) - July 10, 2014

• Download and load of IBTrACS and C20 Reanalysis data
• Vorticity tracking (nearest neighbour) in place
• Matching of vorticity to best tracks
• Plotting of output on world maps
• pyro_cluster proof of concept working
• Make installable through PyPI
• Add structure for documentation
• Proper settings file that is easy to modify and stored in ~/.stormtracks

Version 0.0.X

• Experimented with a range of ways of tracking tropical cyclone:

  • Adapting Qinling Wu’s eddy detection algorithm

    • Used a modified voronoi segmentation scheme to partition up ocean
    • Then used a region shirinking technique to localise and detect eddy centres
    • Made sure that the Okubu-Weiss paramater was satisfied for the eddy centres
    • It wasn’t overly suitable for tracking hurricanes:
    • There are typically ~1000s of eddies in the ocean, whereas there will only be ~ 100s of pressure minima

  • Through min pressure:

    • Found to be hard to track pressure minima from one timestep to the other
    • After talking to Kevin Hodges (Reading University) this approach was abandoned for tracking
    • However lot of the code developed (e.g. finding Radius of Outermost Closed Isobar - ROCI) may still be useful
    • Code is located in cyclone.py

  • Settled on tracking vorticity maxima

• Look at Kevin Walsh’s Fortran algorithm for cyclone tracking and take some ideas (and an implementation of a 4th order vorticity algorithm)

  • Ran algorithm against C20 data and found Katrina/Wilma in 2005 data

• Get Kevin Hodges TRACK code building (but don’t manage to get it running against data)

• Downloaded C20 u9950/v9950, prmsl fields for vorticity/pressure

  • Full data sets used, i.e. that contain each ensemble member separately
  • This is better than the mean for tracking features (according to Chris Brierley and Kevin Hodges)
  • Kevin Hodges recommended using an average of wind fields

• Plot a variety of different data fields to get a feel for data:

  • e.g. vorticity with best track overlayed

• Speed up some of the analysis:

  • c functions for vorticity calculations

• Basic analysis:

  • pressure min, vorticity max etc.

• Look into parallelising analysis:

  • Settled on Pyro4 library for remote python execution
  • Set up a basic manager/worker system and tested on UCL computers

• Experiment with Support Vector Machine (SVM) implementation in sckikit-learn

• Implement a basic Kalman filter and check that it is producing reasonable data

• Smoothing and upscaling of vorticity/pressure data