The Statistic of Automatic Weather Station's Efficiency

Over 2100 state automatic weather stations (AWS) can be monitored by the Atmospheric Observing System Operations and Monitoring (ASOM) platform of CMA Meteorological Observation Center at present. They are divided into six groups by areas, which are north, northeast, east, south central, southwest, northwest China. The efficiencies of the AWS are statically analyzed in the respect of data arrival rate, equipment availability and reliability. Influencing factors on the data format errors of datagram and the qualities of data element errors are also analyzed. The results indicate that the data arrival rate, equipment availability and the reliability of all the 2100 state AWS maintain over 80%, with a generally consistent trend. The AWS operation efficiencies of the northeast region are the highest and those of the southwest are the lowest. The data arrival rate is the precondition of the equipment availability and reliability. With the data arrival rate fixed, the format error of datagram has more influence on the equipment availability and reliability comparing to the data elements errors. The 1st line data format errors have more influence on AWS operation efficiencies than the 2nd line data format errors. The ground temperature is the main elements affecting AWS operation efficiencies. Among the ground temperature factors, the different levels of ground temperature have different impacts on AWS efficiencies; 320 cm ground temperature has the most significant influence, while the 5 cm ground temperature's influence is relatively lower. It shows a trend that deeper layers of the geothermal elements have greater influences on AWS efficiencies.