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Real-time Observation Monitoring and Analysis Network. Haihe LIANG, etc. TECO-2008. The quality guarantee of meteorological observation needs to establish effective management system. equipment installation compatibility sitting and exposure performance monitoring calibration
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Real-time Observation Monitoring and Analysis Network Haihe LIANG, etc. TECO-2008
The quality guarantee of meteorological observation needs to establish effective management system. • equipment installation • compatibility • sitting and exposure • performance monitoring • calibration • maintenance, metadata • real-time quality control
In China, there is a great observation network used in weather and climate observation. • 2456 national AWSs • 158 Doppler weather radars • 120 upper-air soundings • And others
Real-time Observation Monitoring and Analysis Network • Meteorological Observation Centre, CMA established monitoring and analysis system, began to monitor the observation on real-time, and outputted the analysis products. • In 2006, the system has began to develop. In 2007, the version 1.o was finished. • It includes equipment performance monitoring, data quality monitoring and maintenance information management • It is for automatic weather station, upper air sounding system and Doppler weather radar. • The operational experiment was done in 2007 and 2008, and improved the operation quality and achieved good benefits.
The system structure • The system structure has been designed as “2-level”, national and provincial system: • National system accepts data from provincial system. • The provincial system is responsible for collecting information. • 2-level system exchanges data based on request-service or real-time.
Software structure • C/S and B/S models are used • C/S is taken to data processing, and B/S is for users. • Data processing uses VC++ and ORACLE to establish C/S structure for data collecting, processing and evaluating. • User system adopts J2EE combined with WEBGIS and ORACLE.
(1) Performance and parameter monitoring • Performance and parameter monitoring • parameter, alarm and failure data • It forms a closed cycle from information collecting, processing, data statistic and feedback.
Status and parameter display Parameter checking Status in time series Failure parts analyzing
Radar status is displayed with weather forecast • Technician could pay more attention to severe weather areas
Before a typhoon arriving, the lower power is found at YANGJIAN radar, so the technician recover it in time. • It helps to check radar, a klystron was replaced in 2006
Data quality monitoring • Real-time data quality monitoring checks and analyzes: • File format • Extremum • Space-time consistency • Environment changes supervision • Reliability indexes • The data quality monitoring is used to • Guide the maintenance technicians to find failure in time • Offer evidences to hardware and software updating for decision-makers. • Evaluate data quality.
AWS data quality evaluation • The data has be displayed as 4 levels: • 0:normal • 1:usable • 2:alarm • 3:false • Based on statistic, it tell us the ground temperature has more problems
Guiding to maintenance Discontinuous Conflicting Data Invariable Data Inconstant varying
CINRAD Data Quality • Radar Data Quality Assistance Efforts • Hotline Technicians Monitor Continuously • Technical Assistance Group Monitors • Tools Used • Unedited National Mosaic • Radar Reflectivity Comparison • New algorithms will be developed for reducing technician watching, but there are difficulties in auto-check.
Upper air sounding data check • Upper air WTH are compared with threshold, the abnormal data is recorded and putted into database, then statistics can be displayed. • Technician can pay more attention to the larger number.
Observation information management • Instruments and parts have IDs number. • Observation information management includes • Log on duty • Repair record • Validity of calibration • Logistics • Station environment pictures and cameras
Observation environment protection • Station environment pictures and cameras • 8-azimuth pictures • Updated in half-year. • Video is based on WEB users. • It is also used to observe weather phenomena.
Evaluation indexes • There are 3 indexes : Reliability (R) = T1/T, Availability (A) = (T1+T2)/T Failure (F)= (T3+T4)/T • T is for all time, T1 normal time, T2 usable time,T3 alarm T4 for failure.
The radar availability are 89.49%, 95.3%, 96.2% from June to August in 2006-2008 • AWS alarms and error is going down
It is being done: • GPS/MET, lightning, Profiler, etc, will be monitored. • QC algorithm will be developed further, for example, Radar QC, AWS QC,etc. • Trainning technician. • After testing the system will be used in most provinces 2009. • Based on the statistics some problems are found, so the software and hardware are being updated.