湖北省气温资料非均一性的订正及影响分析OA

Using homogeneous long-term data for climate assessment is crucial for enhancing the accuracy of evaluation results and provides important guidance for improving the adaptive capacity of human society and eco-system to respond to climate warming.Employed RHtests V4 software and combined with the meteorological sta-tion metadata,the reference stations were selected by the methods of adjacent station selection and Pearson corre-lation analysis,then inhomogeneity test and correction were conducted on the maximum and minimum tempera-ture series of 74 national meteorological stations in Hubei Province during 1961-2024,by defining inhomogene-ity bias and its contribution rate,the effects of inhomogeneity on annual and seasonal average maximum and min-imum temperatures series were analyzed.The results showed that,from 1961 to 2024,43.2%of the stations in Hubei Province exhibited inhomogeneity in the maximum temperature series,while 60.8%showed inhomogene-ity in the minimum temperature series;Minimum temperature was more sensitive to station relocation than maxi-mum temperature,while the inhomogeneity effect on temperature series caused by automated observation was weak.The trend bias in the annual and seasonal temperature series was generally small caused by data inhomoge-neity in Hubei Province,the warming rate of the annual average maximum was overestimated by 0.002℃·(10a)-1,while the annual average minimum temperature was underestimated by 0.001℃·(10a)-1,with inhomogeneity contribution rates of 0.84%and-0.37%separately,meanwhile more stations overestimated than underestimated;Among the stations with significant breakpoints in maximum temperature,56.3%showed an overestimation and 43.7%showed an underestimation on the variation rates of annual average maximum tem-perature,with average inhomogeneity contribution rates of 1.15%and-0.54%,respectively;Among the sta-tions with significant breakpoints in minimum temperature,51.1%had an overestimation and 48.9%had an un-derestimation on the variation rates of annual average minimum temperature,with average inhomogeneity contri-bution rates of 0.45%and-1.24%;In four seasons,the inhomogeneity effect was weakest in spring;While av-erage maximum temperature in winter,and average minimum temperature in autumn showed the most signifi-cant inhomogeneity effects,with contribution rates of-1.97%and 0.50%.In all stations,the degree of signifi-cant underestimation on the variation rate of average maximum temperature,and the degree of significant overes-timation and underestimation on the variation rate of average minimum temperature in autumn were markedly higher than in other seasons;Zigui was the station with the most significant inhomogeneity effect,primarily due to station relocation,and the variation rate of its autumn average minimum temperature was underestimated by 0.034℃·(10a)-1,with inhomogeneity contribution rate of-23.42%.