StevePny/DataAssimBench
Benchmarking tools for applying AI/ML to data assimilation
This project helps operational weather forecasters and climate scientists integrate real-time observations with complex numerical models. You input observational data from various sources and a chosen Earth system model, and it outputs a more accurate 'best guess' of current atmospheric or oceanic conditions, which then improves predictions and quantifies uncertainties. It is designed for researchers and practitioners in Earth system modeling and data assimilation.
No commits in the last 6 months.
Use this if you need to benchmark and develop new methods for data assimilation, especially when combining AI/ML techniques with numerical Earth system models.
Not ideal if you are looking for a pre-built, production-ready data assimilation system for general operational use without custom development or research.
Stars
26
Forks
2
Language
Python
License
Apache-2.0
Category
Last pushed
Jun 06, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/StevePny/DataAssimBench"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
NVIDIA/earth2studio
Open-source deep-learning framework for exploring, building and deploying AI weather/climate workflows.
mllam/neural-lam
Research Software for Neural Weather Prediction for Limited Area Modeling
chengtan9907/OpenSTL
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
NVIDIA/earth2mip
Earth-2 Model Intercomparison Project (MIP) is a python framework that enables climate...
aditya-grover/climate-learn
Source code for ClimateLearn