Alek Petty
Python scripts used to produce the skillful seasonal forecasts of Arctic (and Alaskan) sea ice extent. Results from this analysis were recently published in JGR Earth's Future.
Citation: Petty, A. A., D. Schroder, J. C. Stroeve, T. Markus, J. Miller, N. T. Kurtz, D. L. Feltham, D. Flocco (2017), Skillful spring forecasts of September Arctic sea-ice extent using passive microwave sea ice observations, Earth’s Future, 4 , doi:10.1002/2016EF000495.
Individual descriptions should be included at the top of each script. Not all processing/plotting scripts have been included yet.
Python 2.7 was used for all processing. I have not tested these scripts in Python 3.
I use Conda to intall/manage the various Python packages. Check out the file 'packages.txt' for a list of the Python package versions I used to run these Scripts. I should probably do this in a conda environment and output that information at some point.
Information about installing Conda/Python, and a brief introduction to using Python can be found on my NASA Cryospheric Sciences meetup repo: https://github.com/akpetty/cryoscripts.
The gridded forecast datasets were generated from the following, pubclically available datasets:
Sea ice concentration data (final): http://nsidc.org/data/nsidc-0051
Sea ice concentration data (near real-time): https://nsidc.org/data/nsidc-0081
Melt onset data: http://neptune.gsfc.nasa.gov/csb/index.php?section=54
(note that the melt onset data are not made avilable each year near real-time, so contact me if required).
Simulated melt pond data were provided by CPOM-Reading, with the detrended forecast data included in this repo.
Contact me if you any any questions!
Alek