STILT footprints data set 3

This repository contains the third batch of training data sets of measurement footprints. The footprints are used to train the deep learning model presented in our paper titled "FootNet v1.0: Development of a machine learning emulator of atmospheric transport". Preprint of the manuscript could be accessed at https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1526/. The footprints are provided in Numpy compressed array format, which could be decompressed with Python 3.10.6 and NumPy 1.23.4.