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Downscaling Python Packages

Python packages with the GitHub topic downscaling. Sorted by relevance, with stars and monthly downloads.
NREL
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.

2K 131 34
jhamman
scikit-downscale

Statistical climate downscaling in Python

2K 195 43
ArcticSnow
topopyscale

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

1K 60 17
NatLabRockies
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.

454 131 34
brews
dearprudence

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

287 4 0
carlgogo
dl4ds

Deep Learning for empirical DownScaling

158 102 28
geocryology
globsim

Using global reanalyses for permafrost simulation

151 21 6
alvaro-gc95
rascal-ties

Open-source tool for climatological time series reconstruction and extension

141 10 2
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.

120 60 11
ClimateImpactLab
downscale

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

93 152 36
scholer
pptx-downsizer

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

90 24 2
carlgogo
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

76 102 28
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