Abstract:

Based on the high frequency observation data obtained from the automatic weather station, a threshold check algorithm developed using the percentile threshold method (PTM) was used to conduct a detection test to seconds temperature and pressure data.Specifically, six coefficient combination schemes for PTM and two standard deviation methods were adopted to conduct the detection test.Results show that the developed method has higher efficiency and lower misjudgment rate.In these tests, three schemes indicate better test results with a lower flagging percentage relative to the given statistical expected value.The number of "flagging" data for three schemes are 33, 3, and 0, the flagging percentage are 0.076 %、0.007 %, and 0.000 %, respectively.Among three schemes, the scheme combining 1-minute sliding window with a 30-minute time interval is optimal with the features of the least "flagging" data, the lowest misjudgment rate, and a small computation burden for the computer.The continuous 30-day seconds' temperature and pressure data were tested with this method, and the results are satisfying.Besides, this method is also able to test artificially constructed incorrect data.This algorithm could be applied to check those meteorological data at stations that had a short history, are newly constructed or outlying, and have bad conditions and therefore is helpful to identify the emergent problems in the data collection phase and to improve the automation level of data quality check.

Key words: Threshold check, Quality control, Seconds data, Percentile threshold method