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Franklin R. Robertson, Michael G. Bosilovich, Junye Chen, and Timothy L. Miller

increments and relate these forcings to the stepwise evolution in passive microwave sensing associated with the AMSU-A and Special Sensor Microwave Imager (SSM/I) ( section 3 ). Section 4 provides some diagnostics on what aspects of climate variability within the 30-yr period survive or are distorted by these artifacts. We then use principal component analysis to characterize space–time variability of the increment terms. In section 5 we show how applying a statistical regression methodology to

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Nili Harnik, Judith Perlwitz, and Tiffany A. Shaw

surface in the stratosphere and upon reflection, back down into the troposphere. The goal of this paper is to investigate the impact of the observed changes in the extratropical Southern Hemisphere on downward wave coupling between the stratosphere and troposphere. We show that downward wave coupling from September to December has increased significantly over the last three decades because of changes in the wave geometry. The datasets and the analysis approach are described in section 2 , the results

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Siegfried Schubert, Hailan Wang, and Max Suarez

determine the 5% significance levels. For the regressions, the iid variates are scaled to have the same variance as the leading REOFs, and these are then used as the predictors for either precipitation or surface temperature at each grid point. This is carried out 1000 times (for every grid point) and the values are sorted from smallest to largest. The 950th (900th) value is the 5% (10%) significance value for each surface temperature (precipitation) regression. 3. Diagnostic analysis based on MERRA In

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Michael A. Brunke, Zhuo Wang, Xubin Zeng, Michael Bosilovich, and Chung-Lin Shie

-derived products, but this was only done for latent heat flux using buoy data in the North Pacific and Atlantic. Futhermore, with the recent availability of a new generation of several ocean surface turbulent flux products, we should now ask the question, Is the new generation of reanalyses [e.g., the Modern-Era Retrospective Analysis for Research and Applications (MERRA), the Climate Forecast System Reanalysis (CFSR), and the ECMWF interim reanalysis (ERA-Interim)] better than the previous generation [e

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Tiffany A. Shaw, Judith Perlwitz, Nili Harnik, Paul A. Newman, and Steven Pawson

1. Introduction In a recent study Shaw et al. (2010) investigated the nature of downward wave coupling between the stratosphere and troposphere using the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) dataset. Downward wave coupling occurs when planetary waves reflected in the stratosphere impact the troposphere and is distinct from zonal-mean coupling, which results from wave dissipation and its subsequent impact on the zonal-mean flow ( Perlwitz and

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David H. Bromwich, Julien P. Nicolas, and Andrew J. Monaghan

a numerical weather prediction model anchored with a variety of meteorological observations. Importantly, these observations do not include precipitation rates. Three new global reanalyses have been produced since 2008: the European Centre for Medium-Range Weather Forecasts “Interim” reanalysis (ERA-Interim) ( Simmons et al. 2006 ; Uppala et al. 2008 ); the National Aeronautics and Space Administration Modern Era Retrospective-Analysis for Research and Applications (MERRA) ( Bosilovich et al

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