AMLCS-DA: A data assimilation package in Python for Atmospheric General Circulation Models

This paper introduces AMLCS-DA, a Python package designed to perform sequential Data Assimilation (DA) on Atmospheric General Circulation Models (AT-GCM). The provides implementations of well-known ensemble-based methods. default forecast step relies the AT-GCM SPEEDY. Users can define various configurations for assimilation steps, including density observational networks, background error correlation structures, and inflation factors. also allows analyzing errors in ways, such as time evolution statistics across pressure levels. Additionally, enables testing new methods realistic operational scenarios comparing their performance with DA formulations.