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Jiansong Zhou and Ka-Kit Tung

Data Center (NCDC) or the Goddard Institute for Space Studies (GISS)]. Undoubtedly, short-term natural climate fluctuations play a role: The “super” El Niño in 1998 made that year either the warmest or close to the warmest on record, and the La Niña in 2008 contributed to that year being not as warm. It is understood that these, and possibly other, natural fluctuations should be filtered out to reveal the underlying anthropogenic warming. Multiple linear regression (MLR) analysis is often employed

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Edmund K. M. Chang

2038 JOURNAL OF THE ATMOSPHERIC SCIENCES VOL.$0, NO. 13Downstream Development of Baroclinic Waves As Inferred from Regression Analysis EDMUND K. M. CHANGProgram in Atmospheric and Oceanic Sciences, Princeton University, Princeton, New Jersey(Manuscript received 17 July 1992, in final form 12 October 1992) ABSTRACT The structure and evolution of transient disturbances in

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Paul E. Roundy

threshold applied by Roundy (2012a) , which limited the analysis to a small sample of events), and they are also robust when data in the easterly background wind environments opposite the equator from the westerly wind monsoon regions are also retained in the analysis (not shown). Although Roundy (2012a) showed no gap in the wavenumber–frequency spectrum of OLR signals over warm-pool regions between the segments of the spectrum characteristic of Kelvin waves and the MJO, the wavelet regression

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Harry R. Glahn

JANUARY 1968 H A R R Y R. G L A H N 23Canonical Correlation and Its Relationship to Discriminant Analysis and Multiple Regression HARRY R. GLAHN1Weather Bureau, ESSA, Silver Spring, Md.(Manuscript received 26 June 1967)ABSTRACT Canonical correlation analysis is concerned with the determination of a linear combination of each of twosets of variables such that the correlation

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Alain Lahellec and Jean-Louis Dufresne

analysis and the feedback gain approach is only valid at equilibrium. In other situations, the surface layer divergence does not equal the outgoing TOA budget. Care should thus be taken when dealing with nonsteady analysis and we will come back to this difficulty in the next paragraph. b. From PRP to the regression method Extending the PRP approach, Gregory et al. (2004) proposed an innovative method to determine the global climate sensitivity to forcing from regression between the amplitudes of time

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Gyu Ho Lim and John M. Wallace

1718 JOURNAL OF THE ATMOSPHERIC SCIENCES VOL. 48, No. 15Structure and Evolution of Baroclinic Waves as Inferred from Regression Analysis Gvu He Lnv~* AND JOHN M. WALLACEDepartmem of Atmospheric Sciences, University of Washington, Seattle, Washington(ManuScript received 2 May 1990, in final form 27 Februar~ 1991) The structure of transient disturbances with periods shorter than a week is documented on the basis of onepoint

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Paul E. Roundy and William M. Frank

. 3. Methodology a. Independent verification of regression model The companion paper ( RF ) analyzes interactions between ISOe and ISOw anomalies using the regression model described above. Their Fig. 1 shows their composite analysis of these interactions in the longitude– time lag domain. In the current paper we wish to demonstrate that the regression model of RF produces results that are representative of physical processes. We do this by comparing the results of the RF regression

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Samuel S. P. Shen, Nancy Tafolla, Thomas M. Smith, and Phillip A. Arkin

that contribute to the reconstruction skills. The rest of the paper is arranged as follows: section 2 shows the multivariate regression version of the Smith method, section 3 describes the data used in the analysis and the EOF results, section 4 includes results, and section 5 contains conclusions and discussion. 2. Multivariate regression of the Smith reconstruction method a. Smith reconstruction, regression, and error bounds Smith et al. (1996) introduced a reconstruction method for sea

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Peter Hitchcock, Theodore G. Shepherd, and Shigeo Yoden

year to year in this region and season ( Fig. 7a ), presumably as a result of the dynamical variability associated with the timing of the final warming. Although we have not demonstrated what role these nonlocal rates play in the break down of the vortex in this model, this result provides a caution against using a local, climatological radiative damping rate in mechanistic modeling studies of this region. 4. Shortwave relaxation rates A similar regression analysis can be performed on shortwave

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Renqiang Liu and Yanyan Fu

-stratospheric temperature changes, neither has been quantitatively verified. Through detailed correlation analysis, Newman et al. (2001) showed that the interannual variability of March polar stratospheric temperatures during the period 1979–2000 is principally related to the tropospheric to lower-stratospheric eddy heat flux observed in January–February. They further used a simple linear fitting to explain, over the averaged annual cycle, the wave-driven and “dynamics free” components of current-month stratospheric

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