carlos-gg / 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
☆83Updated last month
Related projects: ⓘ
- Deep learning approaches for statistical downscaling in climate☆63Updated 2 years ago
- (Semi-official) repository of "Deep-Learning-Based Gridded Downscaling of Surface Meteorological Variables in Complex Terrain".☆11Updated 3 years ago
- ☆109Updated 3 years ago
- ☆36Updated 2 years ago
- ☆28Updated last year
- Python Package for Empirical Statistical Downscaling. pyESD is under active development and all colaborators are welcomed. The purpose of…☆44Updated last month
- Clean, easier to use version of the downscaling cGAN☆22Updated 6 months ago
- Jupyter notebooks for WRF-Hydro trainings☆50Updated last month
- post-processing experiments with neural networks☆59Updated 2 years ago
- Stochastic, Recurrent Super-resolution GAN For Downscaling Time-evolving Fields☆66Updated 3 years ago
- Maximum Covariance Analysis in xarray for Climate Science☆67Updated last year
- pyEOF: Empirical Orthogonal Function (EOF) analysis and Rotated EOF analysis in Python☆42Updated 3 years ago
- A Python Package for Statistical Analysis of Climate☆55Updated last month
- ☆28Updated 3 weeks ago
- Python code to assist in familiarizing meteorologists with machine learning☆54Updated last year
- A collection of Python scripts for running WRF with the DART data assimilation system☆29Updated last year
- A collection aiming to bring all the amazing work of Deep Learning for Climate Super-res together.☆82Updated 8 months ago
- climetlab plugin to access subseasonal to seasonal (S2S) forecasts for the s2s-ai-challenge☆35Updated last year
- Beta for Pangeo Postprocessing☆15Updated 4 years ago
- Python scripts during my PhD studies (2020 - 2022)☆24Updated last year
- A line of code to analyze climate☆27Updated last week
- Tool using python and cdo to apply daily climate downscaling with BCSD.☆30Updated 2 years ago
- A project on how to incorporate physics constraints into deep learning architectures for downscaling or other super--resolution tasks.☆67Updated last year
- Deep Learning for Post-Processing Ensemble Weather Forecasts☆86Updated last year
- AI Challenges based on the SEVIR weather dataset☆37Updated 3 years ago
- RDA apps clients. Subdirectories will be organized by language, e.g. python, perl, c++, bash☆31Updated 7 months ago
- A commandline utility for converting GeoTIFF files for use in WRF☆47Updated last year
- ☆26Updated last month
- Uses machine learning to predict convective initiation and decay from satellite data.☆22Updated last year
- Python code for MWR paper 'Using Artificial Neural Networks for Generating Probabilistic Subseasonal Precipitation Forecasts over Califor…☆12Updated 4 years ago