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A New Method of Significance Testing for Correlation-Coefficient Fields and Its Application
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作者 Xiaojuan SUN Siyan LI +2 位作者 Julian XL WANG Panxing WANG Dong GUO 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2022年第3期529-535,共7页
Correlation-coefficient fields are widely used in short-term climate prediction research. The most frequently used significance test method for the correlation-coefficient field was proposed by Livezey, in which the n... Correlation-coefficient fields are widely used in short-term climate prediction research. The most frequently used significance test method for the correlation-coefficient field was proposed by Livezey, in which the number of significantcorrelation lattice(station) points on the correlation coherence map is used as the statistic. However, the method is based on two assumptions:(1) the spatial distribution of the lattice(station) points is uniform;and(2) there is no correlation between the physical quantities in the correlation-coefficient field. However, in reality, the above two assumptions are not valid.Therefore, we designed a more reasonable method for significance testing of the correlation-coefficient field. Specifically, a new statistic, the significant-correlation area, is introduced to eliminate the inhomogeneity of the grid(station)-point distribution, and an empirical Monte Carlo method is employed to eliminate the spatial correlation of the matrix.Subsequently, the new significance test was used for simultaneous correlation-coefficient fields between intensities of the atmospheric activity center in the Northern Hemisphere and temperature/precipitation in China. The results show that the new method is more reasonable than the Livezey method. 展开更多
关键词 correlation-coefficient field significant-correlation area empirical monte carlo method significance test
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