The Gmao Hybrid 4d-Envar Observing System Simulation Experiment Framework

• Published in: Monthly weather review Vol. 151; no. 7; pp. 1717 - 1734
• Main Authors: Akkraoui, Amal El, Privé, Nikki C, Errico, Ronald M, Todling, Ricardo
• Format: Journal Article
• Language: English
• Published: Goddard Space Flight Center American Meteorological Society 01.07.2023
• Subjects: Earth Resources and Remote Sensing; Error Analysis; Variational Analysis; Data Assimilation
• ISSN: 0027-0644; 1520-0493
• DOI: 10.1175/MWR-D-22-0254.1

This work describes the extension of the Global Modeling and Assimilation Office (GMAO) Observing System Simulation Experiment (OSSE) framework to use a hybrid 4D-EnVar scheme instead of 3D-Var. The original 3D-Var and hybrid 4D-EnVar OSSEs use the same version of the data assimilation system (DAS) so that a direct comparison is possible in terms of the validation with respect to their corresponding real cases. Rather than quantifying the differences between the two data assimilation methodologies, a short inter-comparison of upgrading from a 3D- to a 4D-OSSE is provided to highlight aspects where this change matters to the OSSE community and to identify features of data assimilation that can only be explored in a four-dimensional OSSE framework. A short validation of the hybrid 4D-EnVar OSSE shows that conclusions from previous assessments of the 3D-Var OSSE in its ability to mimic the behavior of the real system still hold with the same caveats. Furthermore, some aspects of the ensemble configuration and behavior are discussed along with forecast sensitivity to observation impacts (FSOI). Estimates of error standard deviations are shown to be smaller in the hybrid 4D-EnVar OSSE but with little impact on the character of the error. A discussion on future work directions focuses on exploring the four-dimensional aspect such as the error distribution within the assimilation window or four-dimensional handling of high-temporal density observations.