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自动观测与人工观测差异的初步分析
Differences Between Automatic and Manual Observation
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摘要: 利用2001—2005年我国700个地面自动气象站与人工平行观测期间的数据, 对自动与人工观测的气温、气压、相对湿度、地表温度、风速风向、降水量进行了差异分析, 统计了两种观测之间的对比差值、百分误差和风向相符率。 对各要素观测差异在全国的分布特点进行了分析, 并检验了气温自动观测对气温资料连续性的可能影响。 结果表明:自动观测与人工观测各气象要素均存在一定的差异, 但大部分地区各要素的差异都在自动站误差允许范围之内; 造成差异的原因是多方面的, 包括仪器本身存在缺陷及观测方法不一致等。各要素自动观测与人工观测差异在全国的分布特点各不相同, 同一要素在不同的气候背景条件下差异大小不一致; 如果要将人工观测数据与自动观测数据连续使用, 还要检验自动观测与人工观测序列是否有显著性差异, 并进行均一性订正。 自动站的使用对年气温序列有一定影响, 总体差异不显著, 但当自动观测与人工观测气温合并使用时, 应进行均一性检验。Abstract: Manual observation is being replaced by automatic observation in China gradually. Till 2006, there are altogether 1904 automatic weather stations (AWS) in the country. Great changes have taken place in the observational rules and methods of AWS comparing with manual observations. Inhomogeneity of observational time series may be caused by many reasons and the change of observational instrument is an important one. The records of AWS and manual parallel observation in a certain period of time may be used in analyzing the observational differences between AWS and manual.Based on the data of automatic and manual parallel observations in 700 stations during 2001—2005, the differences of temperature, precipitation, pressure, relative humidity, wind speed, wind direction and ground surface temperature are calculated and the characteristic differences between automatic and manual observation in different areas are analyzed. Results show that certain differences exist in all the meteorological elements between automatic and manual observation, but in most areas the differences in temperature, precipitation, pressure, relative humidity, wind velocity and direction and ground surface temperature fall in the accepted error rang of AWS. In most stations in China the difference is of ±0.1℃ in the annual mean temperature. To be exact , the difference of annual mean maximum and minimum temperature is a little larger than annual mean temperature. More significant system error appears in the automatic observation of a few stations, and when the automatic observational data of temperature are used the instrument systematic error should be corrected. The difference of all elements between automatic and manual observation has different distribution features in China, and the same element may vary greatly in different climatic situations. In dry areas or in the seasons with little precipitation, there is a great differences between auto and manual precipitation observation. The areas with difference of 0.2—0.6 hPa in pressure are mainly distributed in the western areas with high sea level elevation. In the wet areas in the south of the Yangtze River, Tibetan Plateau, northeastern area and mountain stations of the northeast, big difference appears in the auto and manual observation of relative humidity. In the north during snowing period there is a significant difference between auto and manual observation of ground surface temperature. The use of automatic stations exerts certain influence on the continuity of annual mean temperature, so it is necessary to test whether the significant difference exists in the auto and manual observation time series if manual and auto observation data are used. Homogeneity correction is needed if the significant difference appears.The difference between auto and manual observation is unavoidable. Any instrument change in history will bring the data difference, especially the change from manual observation to automatic observation with quite different observational instrument and method. The time series of automatic observation are short in China and the replacement by automatic observation just starts, so with longer observational time series and more automatic stations further analysis is needed to know the causes for the difference between automatic and manual observation as well as correcting methods .
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Key words:
- automatic observation;
- manual observation;
- difference
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图 1 年平均、年平均最高、年平均最低气温差值频率分布图
Fig. 1 Frequency distribution of the difference of annual mean, annual mean maximum and annual mean minimum temperature
表 1 与长序列年平均气温有显著差异的自动站观测数据(单位:℃)
Table 1 AWS observations with significant difference to long time series in annual mean temperature(unit:℃)
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