Lake Ice Forecasting with Deep Learning - Archived Data

This data archive accompanies the article “A Deep Learning Approach to Lake Ice Forecasting”. It contains the harmonized lake datasets and the current version of the Lake Ice Forecasting – Deep Learning (LIF-DL) model required to reproduce the results presented in the publication.

The archive is organized as follows:

LIF_DL_Best/ — Contains the trained model checkpoint file (.ckpt), along with required supplementary data and metadata necessary for model deployment and inference.

nc/ — Contains harmonized lake datasets for five study sites: Great Bear Lake, Great Slave Lake, Lake Athabasca, Reindeer Lake, and Lake Winnipeg.Each dataset is provided as a NetCDF file containing daily variables from the Interactive Multisensor Snow and Ice Mapping System (IMS), ERA5, and the Global Lake Database (GLDB).The datasets span 2004-02-25 to 2021-12-31, at 4 km spatial resolution, in EPSG:3411 projection.

These data are intended for use with the corresponding code repository available on GitHub: 

https://github.com/h2o-geomatics/lif-dl

Together, the code and dataset enable full reproduction of the experiments, figures, and results described in the article.