The water vapor-related microphysical processes (WVRMPs) in cloud microphysics schemes are crucial to the formation and dissipation of clouds, which have a significant impact on the quantitative precipitation forecasting of numerical weather prediction models. In this study, a well physics-based parallel-split transition approach (PSTA) to compute the WVRMPs from the same temperature and humidity state is developed and compared with the original sequential-update transition approach (SUTA) in a double-moment cloud microphysics scheme. Case study and batch experiments were carried out to investigate their different impacts on the clouds and precipitation simulated by the Global/Regional Assimilation and Prediction System (GRAPES) regional 3 km high-resolution model of the China Meteorological Administration (CMA), named CMA-MESO. The results show that the PSTA experiment tends to simulate a narrower and more concentrated precipitation area with a higher-intensity center compared to those of the SUTA experiment, which is more consistent with the observations. In the cold region, the net transition rates of WVRMPs from the PSTA experiment with more ice-phase hydrometeors are higher than those from the SUTA experiment. While in the warm region, the condensation and evaporation rates with violent fluctuation simulated by the SUTA are significantly larger than those from the PSTA experiment, resulting in less precipitation. The batch experiments indicate that the equitable threat scores (ETSs) of 24-h precipitation simulated by the PSTA are just slightly better than those of the SUTA, yet its ETSs of 48-h precipitation have been systematically improved for all magnitude levels against the SUTA. It is demonstrated that more attention should be paid to the reasonable treatments of the WVRMPs in developing cloud microphysics schemes.

Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas, there is a deficiency of relevant research, operational techniques, and experience. This made providing meteorological services for this event particularly challenging. The China Meteorological Administration (CMA) Earth System Modeling and Prediction Centre, achieved breakthroughs in research on short- and medium-term deterministic and ensemble numerical predictions. Several key technologies crucial for precise winter weather services during the Winter Olympics were developed. A comprehensive framework, known as the Operational System for High-Precision Weather Forecasting for the Winter Olympics, was established. Some of these advancements represent the highest level of capabilities currently available in China. The meteorological service provided to the Beijing 2022 Games also exceeded previous Winter Olympic Games in both variety and quality. This included achievements such as the “100-meter level, minute level” downscaled spatiotemporal resolution and forecasts spanning 1 to 15 days. Around 30 new technologies and over 60 kinds of products that align with the requirements of the Winter Olympics Organizing Committee were developed, and many of these techniques have since been integrated into the CMA’s operational national forecasting systems. These accomplishments were facilitated by a dedicated weather forecasting and research initiative, in conjunction with the preexisting real-time operational forecasting systems of the CMA. This program represents one of the five subprograms of the WMO’s high-impact weather forecasting demonstration project (SMART2022), and is also a part of their Regional Association (RA) II Research Development Project (Hangzhou RDP). Therefore, the research accomplishments and meteorological service experiences from this program will be carried forward into forthcoming high-impact weather forecasting activities. This article provides an overview and assessment of this program and the operational national forecasting systems.