NREL / PhIRE
☆60Updated last year
Related projects ⓘ
Alternatives and complementary repositories for PhIRE
- Stochastic, Recurrent Super-resolution GAN For Downscaling Time-evolving Fields☆66Updated 3 years ago
- post-processing experiments with neural networks☆59Updated 2 years ago
- ☆28Updated last year
- ☆88Updated 6 months ago
- A plugin for climetlab to retrieve the Eumetnet postprocessing benchmark dataset.☆31Updated 3 weeks ago
- ☆33Updated this week
- Easy emulating of geophysical models including (but not limited to!) Earth System Models.☆54Updated last year
- A lower-level API for Machine Learning inference in operations☆36Updated 4 months ago
- climetlab plugin to access subseasonal to seasonal (S2S) forecasts for the s2s-ai-challenge☆35Updated last year
- Python code for "Applications of Deep Learning to Ocean Data Inference and Sub-Grid Parameterisation" (https://doi.org/10.1029/2018MS0014…☆48Updated 5 years ago
- TECA, theToolkit for Extreme Climate Analysis, contains a collection of climate anlysis algorithms targetted at extreme event detection a…☆57Updated last week
- Deep Learning for Post-Processing Ensemble Weather Forecasts☆87Updated last year
- Brian's python workshop, where he keeps his tools, paint, and anything else useful.☆36Updated 2 weeks ago
- Beta for Pangeo Postprocessing☆15Updated 4 years ago
- Deep learning approaches for statistical downscaling in climate☆68Updated 2 years ago
- Spatio-Temporal Downscaling of Climate Data using Convolutional and Error-Predicting Neural Networks☆20Updated 3 years ago
- Metrics for the verification, evaluation and optimisation of forecasts, predictions or models.☆65Updated this week
- Climate analysis toolbox to investigate teleconnections, test for causality, and make forecasts.☆30Updated last year
- Code for neural network parameterization project☆70Updated 4 years ago
- Uncertainty quantification for machine learning at Cooperative Institute for Research in the Atmosphere☆15Updated last year
- ☆38Updated 3 years ago
- Invert geophysical fluid dynamic problems (elliptic partial differential equations) using SOR iteration method.☆43Updated 7 months ago
- Python codes for studying predictability and data assimlation with a surface quasi-geostrophic turbulence model☆26Updated 8 months ago
- A collection aiming to bring all the amazing work of Deep Learning for Climate Super-res together.☆86Updated 9 months ago
- Lorenz 1996 two time-scale model for learning machine learning☆36Updated this week
- ☆32Updated this week
- Diffusion for climate downscaling☆36Updated 4 months ago
- Clean, easier to use version of the downscaling cGAN☆22Updated 8 months ago
- Tool using python and cdo to apply daily climate downscaling with BCSD.☆33Updated 2 years ago
- A 2-layer quasi-geostrophic atmospheric model in Python. Can be coupled to a simple land or shallow-water ocean component.☆35Updated 3 weeks ago