Dataset Open Access

A Deep Learning-Based Hybrid Model of Global Terrestrial Evaporation

Koppa, Akash; Rains, Dominik; Hulsman, Petra; Poyatos, Rafael; Miralles, Diego G.

This repository contains the datasets used in the research article "A Deep Learning-Based Hybrid Model of Global Terrestrial Evaporation".

The repository contains the following files: 1) Input - contains all the processed input used for training the deep learning models and the datasets used for creating the figures in the article. 2) Output - contains the final deep learning models and the outputs (evaporation and transpiration stress factor) outputs from the hybrid model developed in the study.

Formats: All scripts are in the programming language Python. The datasets are in HDF5 and NetCDF file formats.

The codes related to the research article and deep learning model are available in the following repository: https://github.com/akashkoppa/StressNet

Files (29.1 GB)
Name Size
data_figures_hybrid_paper.zip
md5:2e3ce593336da4d6a02c4157aea8809b
1.5 GB Download
output_hybrid_model_output.zip
md5:5ae99fea254d871265699289443dc7cf
27.6 GB Download
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