Welcome to the AIESDA Wiki
AIESDA (Artificial Intelligence based Earth System Data Assimilation) is a next-generation framework designed to integrate AI Foundation Models into traditional Numerical Weather Prediction (NWP) and Data Assimilation (DA) workflows. The goal of this project is to provide Data Assimilation engine based on JEDI and to bridge it seamlessly with Dynamical Forecast Systems (Bharat, Mithuna) as well as cutting-edge AI Foundation Models (GraphCast, Pangu-Weather, etc.).
Modular and Object Oriented Design
Seperation of concern
Entry Level Data Identity Verification
git clone https://github.com/NCMRWF/aiesda.git
cd aiesda
./install.sh
import xarray
from aidaconf import ModelPassport
# Load a raw forecast file
ds = xarray.open_dataset("pangu_forecast.nc")
# Identify and Verify via Passport
interface = ModelPassport.identify(ds)
# Standardize for JEDI
standard_ds = interface.prepare_state(ds)To register a new model, update the MODEL_REGISTRY in aidadic.py:
"new_model_name": {
"interface_class": "ailib.NewModelInterface",
"required_vars": ["t", "q", "u", "v"],
"horizontal_res": 0.1,
"vertical_levels": "standard_grid_key",
"allow_nans": False,
"mapping": {"air_temperature": "t", ...}
}