A Python tool for fitting the logistic curve to the forecast error growth data is available here.
It is using the standard package scipy.optimize. An example is included.

The paper with the new model for the error growth has been published in Tellus A.

Python tool is written by Martin Horvat and is available also from his github account: https://github.com/horvatm.