Train and evaluate weather/climate model emulators
Project description
FME: Weather/Climate Model Emulation
This package contains code to train and evaluate weather/climate model emulators as seen in "ACE: A fast, skillful learned global atmospheric model for climate prediction" (arxiv:2310.02074) and "Application of the Ai2 Climate Emulator to E3SMv2's global atmosphere model, with a focus on precipitation fidelity" (JGR-ML).
Installation
The package can be installed via PyPI using:
pip install fme
Quickstart
A quickstart guide may be found here.
Documentation
See complete documentation here.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
fme-2024.9.0.tar.gz
(224.6 kB
view details)
Built Distribution
fme-2024.9.0-py3-none-any.whl
(296.6 kB
view details)
File details
Details for the file fme-2024.9.0.tar.gz
.
File metadata
- Download URL: fme-2024.9.0.tar.gz
- Upload date:
- Size: 224.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.8.19
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c5afd2bbcdbdde38f895f09bbbd43ac48b0f45ee6ea04341bd2b40b614a8577c |
|
MD5 | eec73e8029e408d84c58121f189c85b1 |
|
BLAKE2b-256 | 3796454fb5faaf6879ce1206aa87e436b74922f30852654f462981de55bca3c4 |
File details
Details for the file fme-2024.9.0-py3-none-any.whl
.
File metadata
- Download URL: fme-2024.9.0-py3-none-any.whl
- Upload date:
- Size: 296.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.8.19
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2afac67a410860ec50aa0a2e1d9c355b45f247e06d3eecd0a9b3b0052aceecf5 |
|
MD5 | b782c06967fd9901d9e4527f2e59d1d7 |
|
BLAKE2b-256 | ccd07c40682377d15286a3d1ff178f32c1906c23c3c4803d8ed09611d3dbfe39 |