西安观测站长序列气温资料缺测记录插补和非均一性检验  

Interpolation and Inhomogeneity Test of Missing Measurement Records in Long-term Temperature Series at Xi'an Observation Station

作　　者：张高健 高山 惠英 金丽娜 ZHANG Gaojian;GAO Shan;HUI Ying;JIN Lina(Xi'an Meteorological Bureau,Xi'an 710016,China;Shaanxi Institute of Meteorological Sciences,Xi'an 710016,China)

机构地区：[1]西安市气象局,陕西西安710016 [2]陕西省气象科学研究所,陕西西安710016

出　　处：《沙漠与绿洲气象》2024年第1期149-155,共7页Desert and Oasis Meteorology

基　　金：陕西省气象局秦岭和黄土高原生态环境气象重点实验室2020年开放研究基金课题(2020Y-10)。

摘　　要：以西安观测站1971-2013年日平均气温、最高气温和最低气温序列为研究对象,利用标准序列法和多元线性回归法进行插补实验,计算插补值与实测值的平均误差、平均绝对误差、均方根误差和插补值与实测值误差在0.5℃以内的样本比例,对比分析两种插值方法的相对优劣。结果表明:多元线性回归法插补得到的气温序列效果好于标准序列法,并且气候趋势特征与实际观测值序列更具一致性。采用t检验法、惩罚最大T检验(PMTT)、惩罚最大F检验(PMFT)对西安站1951-2020年平均气温序列的均一性进行检验。依据台站历史沿革数据进行的t检验,在6次台站历史沿革变化中,只有2次造成了年平均气温和年平均最高气温序列间断,分别由观测时次增加和仪器换型导致;年平均最低气温有4次出现间断,分别由台站站址迁移、观测时次增加、仪器换型、缺测值插补造成。PMTT和PMFT检测中发现的4次间断点因无元数据支持,认为属于合理间断点,这2种方法均未检测出因缺测值插补引起的间断点,一定程度上说明采用多元线性回归法对缺测值插补得到的西安站1951-2020年气温序列相对合理,气温序列的均一性较好。Based on the series of daily mean temperature,maximum temperature and minimum temperature in Xi'an observation station from 1971 to 2013,the interpolation experiments are carried out by using standard series method and multiple linear regression method,calculating the average error,average absolute error,root mean square error and the proportion of samples with the error between the interpolation value and the measured value within 0.5℃.The relative advantages and disadvantages of the two interpolation methods are compared and analyzed The experimental results show that the daily temperature series which obtained by the multiple linear regression method is better than the standard series method,and the characteristics of climate trend are more consistent with the actual observed data series.The t-test,the penalized maximal T test(PMTT)and the penalized maximal F test(PMFT)are used to test the homogeneity of the annual mean temperature series in Xi'an observation station from 1951 to 2020.The test results show that according to the t-test conducted on the historical evolution data of the station,only 2 of 6 times changes caused the discontinuity of the annual mean temperature and annual mean maximum temperature series,which were respectively caused by the increase of observation time and the change the instrument type.There were four discontinuities in the annual mean minimum temperature,which were caused by the relocation of stations,the increase of observation time,the replacement of instruments and the interpolation of missing measurement values.The four discontinuity points found in PMTT and PMFT detection are considered to be reasonable discontinuity points because there is no metadata support,and none of the two methods detected discontinuities caused by interpolation of missing measurement values,which indicates to a certain extent that the temperature series of Xi'an observation station from 1951 to 2020 obtained by the interpolation of missing measurement values with multiple linear regression method is

关 键 词：气温 缺测数据插补 均一化检验 

分 类 号：P413[天文地球—大气科学及气象学]