An open-source solution which leverages machine learning to improve numerical weather prediction
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Powerful Neural Networks
Fast and accurate, AMSIMP’s neural networks provide high quality weather forecasts and predictions.

Operational Model
AMSIMP offers a pretrained operational model architecture. It is trained on a dataset from the past decade, ranging from the year 2009 to the year 2016.

Near Real-Time NWP
AMSIMP offers near real-time numerical weather prediction through initialisation conditions provided by the Global Data Assimilation System.

The core of AMSIMP is well-optimized Python code. A performance increase of 6.18 times can be expected in comparison against a physics-based model of a similar resolution.

Easy to use
AMSIMP’s high level and intuitive syntax makes it accessible for programmers and atmospheric scientists of any experience level.

Open source
Distributed under the GNU General Public License v3.0, AMSIMP is developed publicly on GitHub.

A quick look at the software's high level and intuitive syntax