Application of the Correction Algorithm to Mass Conservation in GRAPES_GFS

The conservation of mass is very important for the dynamic core of numerical model, especially for climate simulation or medium and long term prediction. For the traditional semi-Lagrangian dynamic core, it is difficult to satisfy the mass conservation theoretically, the finite volume method can be used in the semi-Lagrangian continuous equation to satisfy the mass conservation in theory, but the practical application is more complex, and no operational center adopt the method at this time. On the other hand, the traditional semi-Lagrangian method combined with a simple and easy mass correction algorithm is also a good choice.The GRAPES_GFS (Global-Regional Assimilation and PrEdiction System, Global Forecast System) of Numerical Prediction Center of CMA (China Meteorological Administration) faces a problem that the mass loss is obviously in the process of long term integration. The global mean sea level pressure drops about 1 hPa in 10-day run, due to the choice of the continuity equation and the calculation accuracy of the dynamical core. In the early times of development, there is a very simple mass correction algorithm in GRAPES_GFS, however, in the process of batch testing of the system in 2013, it is found that this algorithm will lead to the increase of the height bias at the top level of the model, so the algorithm is closed.Ideas of C-CAM (Climate-Community Atmosphere Model) model are drawn on, to achieve mass conservation through the correction of surface pressure. A method is developed adjusting mass in each grid box according to different weight coefficient, with the basic idea of modifying more in the grid boxes which have larger changes in mass while less in those with smaller changes. The feasibility of this method is verified by a series of experiments, including ideal test, real case prediction and a batch of cycle prediction, illustrating that the method can effectively reduce the bias of height field under the premise of ensuring the mass conservation, and alleviate the problem of underestimating weather systems. It shows that this method has a certain application value in actual operational forecast, and be further studied in calculating the weight coefficient of each point. It can reduce the bias of the height field at the top level of the model, as well as the high latitude in the Southern Hemisphere.