The Preliminary Analysis and Optimization of Meteorological Data Delivery Operation Flow

Radar products, AWS data, T213 model products and the satellite product data are taken as cases, and the operation process flows for them are drawn using standard flow analysis method. Several critical time points are defined (for instance, data zero time, time of data arrival in provincial meteorological bureau, time of data sent to National Meteorological Information Center, time of data broadcast and so on), then several KPIs (key performance indicators) are identified. During the process of experiments, critical time points are recorded, then quantitative analysis and statistics are performed for time consumed in each leg of data delivery. On this basis, the critical factor that influences timeliness of data delivery is analyzed. Analysis suggest that the critical factors that influences timeliness of radar product data and AWS data are T₁(the internal of data zero time and time of data arrival in provincial meteorological bureau) and T₂(the time internal of data arrival in provincial meteorological bureau and data sent to National Meteorological Information Center); the cause is that there is no standard data delivery service flow in the two leg of data delivery. The critical factor that influences timeliness of T213 is the DVB-S broadcast, which consumes 5852s, taking 99% of the end to end data delivery time. The amount of T213 files is so large that the bandwidth of broadcast is overloading. In addition, during the experiments it's also found that some log data of delivery is absent. So standard data delivery service flow for the whole operation system should be established. Then the optimization solution is proposed and implemented. The result of optimization shows that the timeliness of data delivery is increased significantly and better operation effect is obtained. The optimization has practical significance in establishing standard data delivery service flow and increasing the timeliness of data delivery.