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Tools to detect and track deformation features (leads and pressure ridges) in sea-ice deformation data.

License: GNU General Public License v3.0

Python 13.31% Jupyter Notebook 86.69%

lkf_tools's Introduction

lkf_tools

Tools to detect and track deformation features (leads and pressure ridges) in sea-ice deformation data.

Getting Started

Download/clone this repository.

Installing python

First you need to install conda to install the python environment needed for this package. This can easily be done using a miniforge.

After installing conda with a miniforge you can install the python environment using:

conda env create -f environment.yml

and activate the environment:

conda activate lkf_tools

To install as python package run the following command with the repository directory:

$ python setup.py develop

Generate LKF data-set

There is a tutorial notebook that illustrates how to generate a LKF data-set from a netcdf file. This tutorial uses model output from the SIREx model output repository and also uses the SIREx sampling strategies that are described in detail in this Hutter et al. 2022. The tutorial shows you how to:

  • download and read in the netcdf file
  • detect LKFs in the netcdf file
  • run the tracking algorithm on the detected LKFs
  • some basic plotting routines of the extracted LKFs

Algorithm description

An in-depth description of the algorithm can be found here:

Hutter, N., Zampieri, L., and Losch, M.: Leads and ridges in Arctic sea ice from RGPS data and a new tracking algorithm, The Cryosphere Discuss., https://doi.org/10.5194/tc-2018-207, accepted for publication, 2018. 

Author

Nils Hutter [email protected]

DOI

DOI

License

GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007

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