类型变更的相邻气象观测站的日气温资料整合

Merge on daily temperature data by adjusting two series of adjacent meteorological stations with observation type alternation

利用日气温资料,分析了因气象观测站类型变更而致的气候资料连续性和均一性问题及其影响,提出了订正相邻观测站日气温并将因观测站类型变更而致的相邻站不连续日气温资料整合的方法。主要结论有:(1)气象观测站类型变更而致的气候数据不连续既影响资料的均一性,也影响气候变化研究的结果。在考虑或不考虑测站类型变更(仅1980年以后)时,对我国过去60年1月气温趋势变化的估计结果差别达6.0%。(2)虽然海拔差异明显影响相邻站气温,但城乡差别等下垫面及其周边环境差异因素的作用极为显著;可导致两个地理位置相近的测站最大月气温差别超过0.50℃。(3)利用相邻测站的月气温差异进行各月的日气温订正可以消除海拔、台站下垫面及其周边环境差异对观测资料的均一性影响;使订正后的序列能更好地反映出气候的年际变化特征;从而可为我国正在开展的气候区划新方案、气候变化对区划影响及冷暖期环境格局变化等研究工作提供更均一的气候观测基础资料。

Based on the daily temperature records from adjacent meteorological observation stations with observation type alternation from the period 1951-2010,we analyzed the discontinuity and inhomogeneity of their observed meteorological data,and presented an approach to merge these discontinuous meteorological data from these stations.The results could be concluded as follows.（1） The discontinuity of meteorological records caused by the alternation of observation stations would lead to the inhomogeneity of meteorological data and misunderstandings in climate change study.The estimated difference of variation trends in the mean air temperature in January during the past 60 years can reach as high as 6% whether we take into consideration temperature data of stations whose type changed after 1980.（2） Although elevation gradient has significant effects on the daily temperature between adjacent stations,differences in circumjacent environments and underlying surfaces such as rural and urban regions show greater impacts which could lead to an error of over 0.50℃ in monthly mean air temperature between two stations located closely to each other.（3） The adjustment of daily temperature based on difference analysis of observed monthly mean air temperature between adjacent stations can eliminate the inhomogeneity caused by the differences in circumjacent environments,underlying surfaces and elevation gradient.Adjusted temperature series could reflect the actual interannual variability of climate and serve as a set of reliable basic data for the ongoing studies on climate regionalization in China,the impact on climate regionalization from recent climate changes,and the variation of environmental patterns during the cold and warm periods.