Data Assimilation Lorenz 96
The DALo96 platform, based on the Lorenz model, serves as a benchmark for testing data assimilation algorithms. This tool simplifies the evaluation of data assimilation techniques across different algorithms, particularly when the forcing parameter is perturbed.
Offering a wide range of data assimilation features, DALo96 is a suitable platform for students implementing software applications. The aim of DALo96 is to illuminate the core principles of various Data Assimilation (DA) methods using the Lorenz 96 model, by adjusting model parameters or assimilation technique parameters. Some of the notable DA techniques available include EnKF, EnKF Schur product covariance localization, EnKF modified Cholesky, EnKS, and EnKS modified Cholesky.
In several configurations, the forcing parameter is subject to additive noise, producing an ensemble space that provides flexibility for multiple model propagations. This parameter can be easily adjusted with a slider and perturbed using a knob. The platform also permits the selection of different data assimilation methods and the calculation of error metrics between the analysis step and the true state.