Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0 – Part 1: System description and preliminary experimental results

Abstract

We developed a strongly coupled aerosol–meteorology four-dimensional variational (4D-Var) assimilation system, CMA-GFS-AERO 4D-Var, for investigating the feedback of aerosol data assimilation on meteorological forecasts. This system was developed on the basis of the framework of the incremental analysis scheme of the China Meteorological Administration Global Forecasting System (CMA-GFS). CMA-GFS-AERO 4D-Var includes three component models: forward, tangent linear, and adjoint models. The CMA-GFS-AERO forward model was constructed by integrating an aerosol module containing the main physical processes of black carbon (BC) aerosol in the atmosphere into the CMA-GFS weather model. The tangent linear model and the adjoint model of the aerosol module were further developed and coupled online with the CMA-GFS tangent linear and adjoint models, respectively. In CMA-GFS-AERO 4D-Var, the BC mass concentration was used as the control variable and minimized together with atmospheric variables. The validation of this system includes the tangent linear approximation, the adjoint correctness test, the single-observation experiment, and the full-observation experiment. The results show that the CMA-GFS-AERO tangent linear model performs well in terms of tangent linear approximation for BC and that adjoint sensitivity agrees well with tangent linear sensitivity. Assimilating BC observations can generate analysis increments not only for BC but also for atmospheric variables, highlighting the capability of CMA-GFS-AERO 4D-Var in exploring the feedback of BC assimilation on atmospheric variables. The computational performance of CMA-GFS-AERO 4D-Var also indicates its potential in operational application. This study focuses on the theoretical architecture and practical implementation of the system; the detailed analysis of a series of cycling assimilation experiments will be described in part 2 of this set of companion papers.