河北保定气象站长序列气温资料缺测记录插补和非均一性订正

基于多源的气温月值资料，在数据整合和初步质量控制基础上，同时采用标准化序列法和多元线性回归法对河北保定气象站1913-2014 年月平均气温、最高气温和最低气温资料进行了插补。通过交叉检验法分析发现，标准化序列法插补得到的气温序列效果较好，并且气候统计特征与同区域周边站的研究结果更具一致性。利用惩罚最大F 检验（PMF）对插补后序列的均一性进行了检验，结果表明：通过插补得到的保定站百年气温月值序列的均一性相对较好，仅月平均最低气温序列存在2 个显著间断点，分别由同类型仪器的更换和台站迁移导致，研究中采用分位数匹配（QM）对其进行了订正，建立了保定站百年气温月值序列。通过与邻近单站及我国中东部区域均一化百年气温序列的综合对比显示，本文建立的保定站百年气温月值序列与邻近单站的相关性基本达到0.8 以上；从增暖趋势来看，保定站与中东部区域平均序列分别达0.121 ℃/10a、0.204 ℃/10a，基本在同一量级内：这一定程度上说明建立的保定站百年气温序列相对合理。

The Interpolation and Homogenization of Long-Term Temperature Time Series at Baoding Observation Station in Hebei Province

Using multi-source of monthly temperature and precipitation data on the basis of preliminary integration and quality control, monthly mean temperature, maximum temperature, minimum temperature, and precipitation time series covering 1913-2014 at observation Baoding are interpolated by both two approaches of standardized method and multivariate linear regression. The interpolation results analyzed by cross validation are that the standardized method is more right for temperature data, but for precipitation is the method of multivariate linear regression. Then, the better interpolated time series are homogenized by the penalized maximal F test (PMF), and results indicate that those monthly hundred-term temperature and precipitation data are relatively continuous, only two breakpoints have been detected in the mean minimum temperature series, respectively, by the same type of instrument replacement and station relocation, and also have been adjusted by Quantile-Matching (QM), in the interest of construction of the monthly hundred-term temperature and precipitation time series at observation Baoding. Moreover, we compare the data here with the homogenized monthly temperature and precipitation data during 1913-2014 at observations Beijing and Tianjin from some aspects of trend change and correlation analysis, which show that the data we constructed in this paper are relatively logical and errorless, thus can fill the blank of lack of a complete homogeneous hundred-term climate series for quantitative analysis of climate change in North China Plain.