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GitHub / Dan-Boat / PyESD

Python Package for Empirical Statistical Downscaling. pyESD is under active development and all colaborators are welcomed. The purpose of the package is to downscale any climate variables e.g. precipitation and temperature using predictors from reanalysis datasets (eg. ERA5) to point scale. pyESD adopts many ML and AL as the transfer function.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Dan-Boat%2FPyESD

Stars: 36
Forks: 8
Open Issues: 0

License: mit
Language: Python
Repo Size: 68.4 MB
Dependencies: 407

Created: over 2 years ago
Updated: 2 months ago
Last pushed: 3 months ago
Last synced: about 1 month ago

Commit Stats

Commits: 163
Authors: 2
Mean commits per author: 81.5
Development Distribution Score: 0.067
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/Dan-Boat/PyESD

Topics: deep-learning, downscaling, ensemble-machine-learning, machine-learning, precipitation, sckit-learn, tensorflow2

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