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 library to perform simplistic climate downscaling at the hillslope scale

scikit-downscale

Statistical climate downscaling in Python

scalerack

Unified image upscaling and downscaling algorithms, from classical resampling to reconstruction and perceptual scaling methods.

dearprudence

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

rascal-ties

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

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

globsim

Using global reanalyses for permafrost simulation

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.

downscale

Downscaling & bias correction of CMIP6 tasmin, tasmax, and pr for the R/CIL GDPCIR project

pptx-downsizer

Python tool for downsizing Microsoft PowerPoint presentations (pptx) files.

dl4d

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