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I. G. Watterson

HLM can be deduced, however. Regressing the entire PC1 ( x ) against the U anomalies ( y ) reproduces the EOF1 as the regression coefficient b (in the linear regression equation y = a + bx + ε). Performed with partition by month, regression produces a node that varies as shown in Fig. 2b . Given this, it is worth comparing with results from EOF analysis performed individually for each month. The resulting nodes are similar. This is because the new PCs are highly correlated with the

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Francis Codron

latitude, a is the radius of the earth, and the star denotes the wind departure from its zonal mean. Daily time series of the EF of the SAM were constructed by projecting the zonal-mean EF on the latitudinal structure of the SAM 300-hPa zonal wind anomalies. 3. Description of the SAM structure a. Hemispheric analysis The regressions of the 850-hPa geopotential height onto the SAM time series are shown on the top panels of Fig. 2 for the three different climatologies of Fig. 1 : DJ, MA and JJA. The

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Robert X. Black and Brent A. McDaniel

circulation variability. A recent observational analysis of the Northern Hemisphere circulation indicates that, in fact, Northern Hemisphere SFW events accelerate the seasonal weakening of high-latitude circumpolar westerlies (in contrast to the climatological trend) simultaneously in the stratosphere and troposphere ( Black et al. 2006 , hereafter BMR ). The time evolution of the SFW events consists of a bidirectional dynamical coupling in which tropospheric planetary waves weaken the stratospheric

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John Marshall, David Ferreira, J-M. Campin, and Daniel Enderton

the nature of the variability, we performed an empirical orthogonal function (EOF) analysis of the zonally and yearly averaged fields of the coupled simulation. The analysis was carried out poleward of 20°S using 1000 yr of data. Figure 9 shows the first EOFs of the zonal wind/current and meridional circulation of the ocean and atmosphere. The principal components (PC) have been normalized to unit variance so that their EOFs are in physical units and correspond to one standard deviation of the

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Thomas Jung and Peter B. Rhines

. Brown , A. R. , 2004 : Resolution dependence of orographic torques. Quart. J. Roy. Meteor. Soc. , 130 , 3029 – 3046 . Chang , E. K. M. , 1993 : Downstream development of baroclinic waves as inferred from regression analysis. J. Atmos. Sci. , 50 , 2038 – 2053 . Chang , E. K. M. , S. Lee , and K. L. Swanson , 2002 : Storm track dynamics. J. Climate , 15 , 2163 – 2183 . Dickson , R. R. , 2003 : Stirring times in the Atlantic. Nature , 424 , 141 – 142 . Doyle , J. D

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