Structure of an Information and Computing System for Solving the Problem of Data Assimilation in Environmental Modeling

Abstract

The article presents the development and implementation of an information-computational system (ICS) specifically designed for assessing greenhouse gas fluxes from the Earth’s surface using data assimilation methods. This system effectively interfaces with the MOZART-4 chemical transport model and utilizes satellite data from AIRS, ensuring accurate and reliable estimations of gas fluxes. At the core of this system lies the application of the ensemble Kalman filter algorithm, LETKF, for methane flux estimation, enabling the consideration of uncertainties in both data and model representations. The paper extensively discusses the architectural and technical solutions employed, emphasizing the necessity of adapting the system to the intricacies of the utilized model, thereby enhancing result accuracy. Furthermore, it elaborates on the mathematical foundations of the methodology and includes a practical demonstration of the algorithm’s application within the information-computational system framework. The findings of this research hold significant value as they pave the way for further advancements in utilizing such systems for environmental modeling and data assimilation endeavors, contributing to our understanding and management of the Earth’s environment.