自动站与人工站相对湿度观测结果的差异及原因分析

Research on the Cause of Difference between AWS-and MAN-Relative Humidity Observations

相对湿度是大气探测中最重要的变量之一。只有正确的空气湿度记录序列才能揭示水汽在长期气候趋势监测方面所起的作用。自2000年以来,使用了几十年的相对湿度等常规气象要素的人工观测逐渐被自动观测所取代,为了了解两种观测仪器所测结果的差异,选取了全国17个具有代表性站点的观测数据并对其年平均差、标准差、日变化规律等进行了统计分析,然后根据自动观测与人工观测各自的优点和缺陷,将相对湿度数据按照气温和相对湿度大小分成了9类进行对比分析。研究发现,大多数站点的自动站与人工站相比较,两者之间有一定的"系统偏差",并且相对湿度的自动观测存在偏干的现象,年平均在3.5%左右,在相对湿润的地区,这一现象更明显;在相同的气温条件或相同的相对湿度条件下,高湿或高温情况下的对比差值均偏大。

Relative humidity is one of the most important variables. So the list register with correct humidity observations can dispose the effect to trend of long climate observations. From 2000 on, the man-made observation which was used in past several decades was replaced by auto weather station （AWS）. About 17 observation stations were selected and analyzed by means of computing the annual average difference, standard deviation and the difference of diurnal variaticn. According to each disadvantage of auto weather station and man-made observation systems, relative humidity was sorted to 9 species in terms of the diversity with temperature and relative humidity, and compared and analyzed. It is indicated that there is systemic bias between man-made and auto weather observation in most stations. The magnitude of man-made observation is usually about 3.5 % larger than auto weather station. This phenomenon is more obvious in humid area. The bias is comparatively large in humid area in the same temperature, and there is similar result when the high temperature in the same relative humidity.