Although range check based on month climatic extremes is one of the most commonly used data quality control methods for Automatic Weather Stations(AWS) data, if it is applied to quality control of hourly air temperature data, there exist two weaknesses: (1) The larger threshold range of climatic extremes can make some abnormal data undetected; (2) Large amount of newly built AWS has no climatic extremes. To improve these weaknesses, a range check method is developed based on hourly threshold, which is computed by day climatic extremes. In order to obtain the lower and upper limits of hourly air temperature threshold, firstly, the principles of time and spatial interpolation are applied to calculate the daily temperature extremes at any site based on the generalized extreme value distribution theory. Then, the computing method of hourly threshold at any site is designed by means of the daily change regularity of temperature and numerical interpolation technology. The daily maximum and minimum air temperature of total 730 AWS in China are applied to design and calculate the lower and upper limits of hourly air temperature threshold which can be used for nationwide. Meanwhile, the punctuality, maximum, minimum air temperature of hourly data produced by 2400 AWS located in the national scale in 2010 are used to demonstrate the effectiveness of our proposed control approach. The results show that the quality control method based on the range check of hourly threshold has a lower undetected rate compared with the daily or monthly climatic extremes check. Especially, it can be adopted by those stations without historical data. Its check results can be strengthened by combining with spatial consistency check to reduce the false detection rate greatly.
WANG Haijun
,
YAN Qiaoqiao
,
XIANG Fen
,
PAN Meng
. Algorithm Design of Quality Control for Hourly Air Temperature[J]. Plateau Meteorology, 2014
, 33(6)
: 1722
-1729
.
DOI: 10.7522/j.issn.1000-0534.2014.00028
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