山东省气温资料的均一性检验及订正OA
Homogeneity Test and Revision of Temperature Data in Shandong Province
利用山东省 123个国家基本气象台站建站至 2023 年逐月气温数据,采用惩罚最大 F检验(PMF)、惩罚最大 T 检验(PMT)和标准正态同质性检验(SNHT)的方法,结合台站元数据信息,开展气温序列的均一性检验与订正,以提升山东省气温资料的可靠性.结果表明:(1)山东省气温序列普遍存在非均一性,其中月尺度平均、最高和最低气温序列分别检测到 63 个、71 个和 114 个显著断点,台站迁移是导致序列不连续性的主要因素;(2)经一元线性回归订正处理后,全省年平均最高气温和年平均最低气温的上升趋势分别由 0.230℃·10a-1 和0.330℃·10a-1 增至0.260℃·10a-1和 0.400℃·10a-1;(3)均一化处理有效提升了部分台站数据的连续性和均一性,但并未改变全省气温显著上升趋势的整体格局,仅在区域分布上存在局部差异,其中鲁东南部因台站迁移导致的增温趋势被低估的现象尤为明显.本研究构建的均一化气温数据集,可为科学评估山东省农业气候资源变化、气候变化影响及农业气象灾害风险提供可靠的数据支撑.
The homogeneity of the temperature series is fundamental to the accuracy of climate change assessments.To enhance the reliability of temperature records in Shandong province,monthly mean,maximum and minimum temperature data from 123 national basic meteorological stations up to 2023 were compiled.A combined detection framework that integrates the Penalized maximum F-test(PMF),Penalized maximum T-test(PMT)and Standard normal homogeneity test(SNHT),supplemented by comprehensive metadata,was applied to perform systematic homogeneity testing and adjustment.The results showed that:(1)inhomogeneity proved spatially ubiquitous with 63,71 and 114 statistically significant breakpoints were identified in the monthly mean,maximum and minimum temperature series,respectively.Station relocation was the dominant driver of these discontinuities.(2)After applying a one-segment linear regression adjustment,the warming trend for annual mean maximum temperature increased from 0.230℃·10y-1 to 0.260℃·10y-1,while the trend for annual mean minimum temperature rose from 0.330℃·10y-1 to 0.400℃·10y-1.(3)Homogenization markedly improved the continuity and homogeneity of individual station records,yet it did not alter the overall warming pattern across Shandong,only subtle spatial differences emerged,most notably an intensifying warming trend in the southeast of Shandong,which was attributed to station relocation.The homogenized dataset developed in this study provides a robust scientific basis for more precise evaluation of climate change risks and impacts in Shandong province.
刘思宇;高静;张平;赵煜飞;郭庆燕;冯腾琦
山东省气象防灾减灾重点实验室/山东省气象数据中心,济南 250031国家气象信息中心,北京 100081山东省气象防灾减灾重点实验室/山东省气象数据中心,济南 250031国家气象信息中心,北京 100081山东省气象防灾减灾重点实验室/山东省气象数据中心,济南 250031山东省气象防灾减灾重点实验室/山东省气象数据中心,济南 250031
山东气温序列均一性检验趋势分析订正RHtest软件
ShandongTemperature seriesHomogeneity testTrend analysisCorrectionRHtest software
《中国农业气象》 2026 (6)
827-840,14
山东气象局科研项目(2022SDYD042024sdxm05)新一轮农业气候资源普查和区划项目(2026101010YE064)
评论