Research on the application of maximum entropy production modelin operational numerical weather forecast system

Accurately calculating land surface heat fluxes have great scientific significance and practical value for understanding land-atmosphere interaction and improving capability of weather forecast. The methods commonly used for calculating land surface heat fluxes in current weather forecast numerical models are based on Monin-Obukhov Similarity Theory (MOST). They have some limitations and are difficult to make further improvement. Meanwhile, a method based on maximum entropy production (MEP) model is proposed to calculate land surface heat fluxes in recent years. It has advantages and achieves good results, and is increasingly being applied in the study of land-atmosphere exchange. This article introduces the MEP model into operational weather forecast numerical model (CMA-BJ model) in Beijing Meteorological Service to calculate land surface sensible heat flux, latent heat flux and ground heat flux, replacing the existing MOST-based methods in the model. Simulation experiments on period from June to August 2022 are conducted to evaluate the performance of the operational numerical model system with MEP model on predicting land surface and atmospheric meteorological elements and precipitation. The results show that the use of MEP model in CMA-BJ model can significantly improve the simulation of surface energy balance and thermodynamic processes of land surface and boundary layer. Also enhance the ability of the model to simulate air temperature, humidity and wind in boundary layer. And ultimately increase the accuracy of precipitation prediction, especially for heavy rainfall. The TS scores of rainstorms in North China and Yangtze River basin have increased by 20% and 10% respectively. The predicted diurnal precipitation variations are also more consistent with observation, along with higher correlation coefficient. Therefore, these results show that it is feasible to use MEP model in numerical weather forecast models and operational systems.