Local volume solvers for Earth system data assimilation: implementation in the framework for Joint Effort for Data Assimilation Integration
Journal Article
The Joint Effort for Data assimilation Integration (JEDI) is an; international collaboration aimed at developing an open software; ecosystem for model agnostic data assimilation. This paper considers; implementation of the model-agnostic family of the local volume solvers; in the JEDI framework. The implemented solvers include the Local; Ensemble Transform Kalman Filter (LETKF), the Gain form Ensemble; Transform Kalman Filter (GETKF), and the optimal interpolation variant; of the LETKF filter (LETKF-OI). This paper documents the implementation; choices and strategies that allow model agnostic implementation. We also; document an expansive set of localization approaches that includes; generic distance-based localization, localization based on modulated; ensemble products, but also localizations specific to ocean (based on; the Rossby radius of deformation), and land (based on the terrain; difference between observation and model grid point). Finally, we apply; the developed solvers in a limited set of experiments, including; single-observation experiments in atmosphere and ocean, and cycling; experiments for the ocean, land, and aerosol assimilation. We also; provide a proof of concept that illustrates how JEDI Ensemble Kalman; Filter solvers can be used in a strongly coupled framework providing; increments to the ocean based on the combined observations from the; ocean and the atmosphere.
