The operational global four-dimensional variational data assimilation system at the China Meteorological Administration

Since 1 July 2018, the GRAPES (Global/Regional Assimilation and PrEdiction System) global 4-dimensional variational (4D-Var) data assimilation system has been in operation at the China Meteorological Administration (CMA). In this study, the GRAPES global 4D-Var data assimilation system is comprehensively introduced. This system applies the non-hydrostatic global tangent-linear model (TLM) and the adjoint model (ADM) for the first time. The use of a digital filter as a weak constraint is achieved. A series of linear physical processes is developed, including vertical diffusion, subgrid-scale orographic parametrization, large-scale condensation, and cumulus convection parametrization. The vertical diffusion and subgrid-scale orographic schemes are used in the operational suite and the linear convection parametrization and large-scale condensation scheme remain under assessment. The Lanczos and conjugate gradient (Lanczos-CG) algorithm and the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm are also developed. In terms of computational optimization, the total computational time of the GRAPES global TLM and ADM is approximately threefold that of the GRAPES global nonlinear model (NLM). Before it became operational, a one-year retrospective trial was performed on the GRAPES global 4D-Var data assimilation system. The entire system was stable, and the analysis and forecasting performances were significantly better than those of the 3D-Var data assimilation system, especially in the Southern Hemisphere.