Statistical climate downscaling in Python

A project on how to incorporate physics constraints into deep learning architectures for downscaling or other super--resolution tasks.

Scale down / "pause" Kubernetes workload (Deployments, StatefulSets, and/or HorizontalPodAutoscalers and CronJobs too !) during non-work hours.

Diffusion for climate downscaling

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.

TopoPyScale: a Python library to perform simplistic climate downscaling at the hillslope scale

Probabilistic Downscaling of Climate Variables Using Denoising Diffusion Probabilistic Models

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

A project on how to incorporate physics constraints into deep learning architectures for downscaling or other super--resolution tasks.

Code repository associated with "Statistical treatment of convolutional neural network super-resolution of inland surface wind for subgrid-scale variability quantification" (Getter, Bessac, Rudi, Feng).

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

Multicore! Faster!

Generative Adversarial Models for Extreme Geospatial Downscaling

Scale down Kubernetes deployments after work hours