Downscaling Python Packages

nrel-sup3r

The Super-Resolution for Renewable Resource Data (sup3r) software uses generative adversarial networks to create synthetic high-resolution wind and solar spatiotemporal data from coarse low-resolution inputs.

topopyscale

TopoPyScale, a Python package to perform simplistic climate downscaling at the hillslope scale.

scikit-downscale

Statistical climate downscaling in Python

dearprudence

Internal Python library filled with sugar for swallowing downscalingCMIP6 parameter files.

globsim

Using global reanalyses for permafrost simulation

nlr-sup3r

The Super-Resolution for Renewable Resource Data (sup3r) software uses generative adversarial networks to create synthetic high-resolution wind and solar spatiotemporal data from coarse low-resolution inputs.

dl4ds

Deep Learning for empirical DownScaling. Python package with state-of-the-art and novel deep learning algorithms for empirical/statistical downscaling of gridded data

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.

rascal-ties

Python package to reconstruct and extend observational climate series through empricial downscaling of large-scale models

downscale

Tools for downscaling gridded data in xarray

dl4d

Deep Learning for empirical DownScaling

pptx-downsizer

Tool for downsizing Microsoft PowerPoint pptx presentations.