Research on the homogeneity of air temperature series over Tibetan Plateau
Meteorological observation data is the basis of climate change research.Detection and correction ofhomogeneity of meteorological data can improve the precision and accuracy of the climate change research.Based on the monthly mean temperature data from 65 meteorological stations over the Tibetan Plateau and the surrounding areas from 1961-2010,detection and correction of homogeneity of temperature series were carried out by using the PMFT method.The results show that condition of homogeneity of mean air temperature data over the Tibetan Plateau is poor.There are 32 detected stations,accounting for 49％ of the total,at least having one breakpoint.The adjusted temperature data is homogeneity.Analyzing the data found that the annual mean temperature had risen with a rate of 0.32 ℃ · (10a)-1 in the Tibetan Plateau from 1961-2010;the seasonal warming rates over the Tibetan Plateau had been 0.24,0.26,0.32 and 0.48 ℃ · (10a)-1 for spring,summer,autumn and winter,respectively,slightly smaller than the results obtained by using the original data.The study also found that the data homogeneity or not has little effect on the analysis result of climate change for the plateau as a whole,but has much effect on the result for part of the plateau.Spatially,climate change in the Tibetan Plateau is very different from one area to another area.Therefore,for researching the difference of the climate change over the Tibetan Plateau in the future,detection and correction of homogeneity of meteorological data is particularly necessary.The metadata from meteorological station plays an important role in the process of the climate data homogeneity test and correction,which may provide basical information that affect climate sequence homogeneity,such as the changing site,observation time,method and instrument,and provides reference for analysis,inspection and correction of climate data sequence.In order to improve the accuracy of data homogeneity test,it is necessary to strengthen the study of climate data homogeneity test technique in the future and as far as possible to collect more detail metadata.
NETL
NSTL
万方数据
维普
