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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.

Currently employed transformation systems require selectable marker genes encoding antibiotic or herbicide resistance, along with the gene of interest (GOI), to select transformed cells from among a large population of untransformed cells. The continued presence of these selectable markers, especially in food crops such as rice (Oryza sativa L.), is of increasing public concern. Techniques based on DNA recombination and Agrobacterium-mediated co-transformation with two binary vectors in a single or two different Agrobacterium strains, or with super-binary vectors carrying two sets of T-DNA border sequences (twin T-DNA vectors), have been employed by researchers to produce selectable marker-free (SMF) transgenic progeny. We have developed a double right-border (DRB) binary vector carrying two copies of T-DNA right-border (RB) sequences flanking a selectable marker gene, followed by a GOI and one copy of the left border sequence. Two types of T-DNA inserts, one initiated from the first RB containing both the selectable gene and the GOI, and the other from the second RB containing only the GOI, were expected to be produced and integrated into the genome. In the subsequent generation, these inserts could segregate away from each other, allowing the selection of the progeny with only the GOI. We tested this vector using two selectable marker genes and successfully obtained progeny plants in which the second selectable marker gene segregated away from the first. Using the DRB binary vector system, we recovered SMF transgenic lines containing a rice ragged stunt virus (RRSV)-derived synthetic resistance gene in the rice cultivars Jarrah and Xiu Shui. Approximately 36–64% of the primary transformants of these cultivars yielded SMF progeny. Among SMF Jarrah transgenic progeny <50% of plants contained the RRSV transgene. Thus, we have developed an efficient vector for producing SMF plants that allows straightforward cloning of any GOIs in comparison with the published ‘twin T-DNA’ vectors.

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