黑河综合遥感联合试验自动气象站数据质量控制与产品生成

“黑河综合遥感联合试验”自动气象站(AWS)数据的质量控制(QC)分两个阶段进行：计算机自动控制阶段(QC1)和人机交互判断阶段(QC2)。QC1利用气候学界限值检查、台站极值检查、基本气象公式检查、内部一致性检查、时间一致性检查、综合决策算法,对自动气象站资料进行了自动质量控制；QC2中质量控制人员在QC1质量控制的基础上,对判断为可疑和错误的数据进行人工判断、分析错误原因、订正逻辑性错误,并给出数据的最终质量评价。上述质量控制后的自动气象站资料分两级发布,以供科研使用。最终结果表明:QC1中的质量检查可以有效地识别出观测资料中存在的明显错误；经过QC2数据逻辑错误订正后,“黑河综合遥感联合试验”AWS(Automatic Weather Station)数据总体质量较高,达到了预期的试验目标。

Data Quality Control and Products of Automatic Weather Stations for Watershed Allied Telemetry Experimental Research

Data quality control procedures of Automatic Weather Stations (AWS) from Watershed Allied Telemetry Experimental Research (WATER) are divided into two stages,computer automatic control stage (QC1) and human|computer interaction judging stage (QC2).In the QC1,many quality control techniques are integrated to achieve a better automatic check scheme,including the climate extreme value check,the basic meteorological formula check,the interior consistency check,the temporal consistency check,and the decision|making algorithm.In the following QC2,all questionable and error data judged by the QC1 stage will be artificially checked again.The error origins are explored,logical errors are corrected,and final data quality is determined.Products from the above quality control procedures are divided into two levels to distribute.The results indicate that the quality check of QC1 can effectively indentify most errors in the AWS data and by the errors correcting in QC2 the AWS data quality of WATER is very good and comes up to the advance experimental expectation.