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. In section 3 , we elucidate the horizontal structure of CCWs and their associated convection on the basis of a linear regression analysis. The governing thermodynamics for all disturbances are examined in section 5 . In section 6 , an MSE budget analysis is performed for each wave type. Finally, the major findings of the study are summarized in section 7. 2. Data and methods a. CLAUS brightness temperature dataset Satellite-observed brightness temperature T b data are used as a proxy
. In section 3 , we elucidate the horizontal structure of CCWs and their associated convection on the basis of a linear regression analysis. The governing thermodynamics for all disturbances are examined in section 5 . In section 6 , an MSE budget analysis is performed for each wave type. Finally, the major findings of the study are summarized in section 7. 2. Data and methods a. CLAUS brightness temperature dataset Satellite-observed brightness temperature T b data are used as a proxy
the standard deviation for synoptic temperature from December to the following February, representing winter STV. All data used in this study have been detrended. The Student’s t test is applied to examine the significance of the correlation coefficients, regression coefficients, and composite analysis. To estimate the intensification of extratropical eddies, we employ the maximum Eady growth rate to measure atmospheric baroclinicity instability ( Eady 1949 ; Lindzen and Farrell 1980
the standard deviation for synoptic temperature from December to the following February, representing winter STV. All data used in this study have been detrended. The Student’s t test is applied to examine the significance of the correlation coefficients, regression coefficients, and composite analysis. To estimate the intensification of extratropical eddies, we employ the maximum Eady growth rate to measure atmospheric baroclinicity instability ( Eady 1949 ; Lindzen and Farrell 1980
