Updated: 17-11-2023
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Accelerated Development of Precise Forecasting System
CMA has been improving its forecasting capacity, with a focus on the "five ones" (one hour lead time for local severe weather warnings, one day for hourly weather forecasting, one week for disastrous weather forecasting, one month for high impact weather process forecasting, and one year for abnormal global climate prediction) to lead towards sustained forecasting technique innovation, continuously optimized processes and well-established system. Seamless smart grid forecast steps towards more accurate and full-coverage forecasting, and forecast factors are extended to cover severe weather.
Since its establishment, CMA Center for Earth System Modeling and Prediction (CEMC) has built a relatively complete NWP operational system, which combines nowcasting, short-range, short- and medium-Range, sub-seasonal, seasonal to inter-annual forecasting, kilometer to hundred-meter resolution, global to regional, deterministic and ensemble forecasting, basically realizing the independent and controlled Numerical Weather Prediction (NWP) core techniques. The domestically developed Advanced Radiative Transfer Modeling System (ARMS) has been successfully connected to the global weather model. In this context, satellite data assimilation in NWP model has been boosted to 80%, and FengYun satellite data to 14%, the days of global weather model forecasts available for the northern hemisphere are up to 8.1, and that for East Asia to 8.5. It's capable of forecasting tropical cyclones over global oceans, with obvious advantages in forecasting the frequency and intensity of heavy rain or above from April to July. The application rate of weather radar data in regional model has increased to 54.13%. The global climate model has been useful in predicting key indicators such as Asian summer monsoon circulation, El Niño and tropical intra-seasonal oscillation.
The seamless smart grid forecasting product system has been preliminarily established, with 3-h/10-day and 10-km resolution at global scale, and hourly/24-hour and 5-km resolution in China. It releases guidance products of objective forecasting of strong convection weather at 3 hour intervals, and the forecasts for 11,621 foreign cities and 243 important cities including those of the Belt and Road countries. In addition, it also conducts monitoring and forecasting of global disasters such as typhoons, heat waves and cold spells.
In 2022, the accuracy of 24-hour rainfall, maximum and minimum air temperature forecasts nationwide stood at 86.5%, 83.3% and 84.5% respectively, and that of rainstorm at 91%, the warnings of strong convection were released 42 minutes earlier, hitting a historic high, while the error of 24-hour typhoon track forecast was 72 km. The accuracy (Ps score) of provincial-level monthly air temperature and precipitation prediction was 83.9 and 79.0 respectively, ranking at second and fifth since 2013, and that of precipitation forecast in flood prone period was 78.9, the highest since 2013.
Meteorological Information and Data Sharing
Nationwide operations of the meteorological big data cloud platform has been put into service. The platform gathers and manages the meteorological data universe and related industry data, with a data scale of 67PB and a daily increment of 41TB, and the average access time is 0.3 seconds. It provides flat support for nationwide meteorological services based on highly concurrent, reliable, timely and extensible real-time data, and computing power and algorithm services. It has preliminarily forged a new meteorological operational technology system by the support for 132 systems nationwide to complete cloud-based transformation and releasing 2139 shared algorithms.
Meteorological data sharing services have been further strengthened. In 2022, China Meteorological Data Network reported 690 million page views, with the annual data service volume of about 99.6TB, a total of over 459,000 registered users from 21 major social industries in 109 countries, benefiting several research and education institutions, government departments and sectors. Moreover, it has supported a total of 11,639 research projects under National Science and Technology Support Program, 863 Program, 973 Program and under the National Natural Science Foundation.