NCAR / GeoCATLinks
GeoCAT website
☆16Updated 10 months ago
Alternatives and similar repositories for GeoCAT
Users that are interested in GeoCAT are comparing it to the libraries listed below
Sorting:
- ☆20Updated 3 years ago
- A lightweight interface for working with the Weather Research and Forecasting (WRF) model output in Xarray.☆64Updated last week
- Numerical & Scientific Computing with Python Tutorial☆68Updated 5 years ago
- GeoCAT-viz contains tools to help plot geoscience data, including convenience and plotting functions that are used to facilitate plotting…☆58Updated 2 weeks ago
- A package for converting NetCDF files from time-slice (history) format to time-series (single-variable) format.☆41Updated 5 months ago
- python code for dynamic tropopause calculations☆36Updated 5 years ago
- Python code for calculating 'offline' trajectories using u, v, and w wind components from NWP model output☆24Updated 6 years ago
- A set of GrADS functions in Python (hdivg, hcurl...)☆11Updated 4 years ago
- Python package to label and track unique geospatial features from gridded datasets☆44Updated 2 weeks ago
- The Model and ObservatioN Evaluation Toolkit (MONET)☆47Updated 2 weeks ago
- Python GUI of Earth Observations and Model Evaluation Toolkit☆12Updated 6 years ago
- Materials for the Machine Learning in Python for Environmental Science Problems AMS 2020 Short Course☆29Updated 5 years ago
- A super lightweight Lagrangian model for calculating millions of trajectories using ERA5 data☆41Updated 2 months ago
- Earth System Model Lab (esmlab). ⚠️⚠️ ESMLab functionality has been moved into <https://github.com/NCAR/geocat-comp>. ⚠️⚠️☆24Updated 4 years ago
- oocgcm is a python library for the analysis of large gridded geophysical dataset.☆40Updated 7 years ago
- code for simple models of the atmosphere and ocean☆32Updated 3 years ago
- Python for ocean - atmosphere science and engineering☆29Updated 10 years ago
- Basic tutorial for ESMPy Python package☆36Updated 3 years ago
- ☆16Updated last year
- Tutorial on building and using effective colormaps in climate science