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Georgios Fragkoulidis and Volkmar Wirth

.1002/qj.2139 . 10.1002/qj.2139 Glatt , I. , A. Dörnbrack , S. Jones , J. Keller , O. Martius , A. Müller , D. H. Peters , and V. Wirth , 2011 : Utility of Hovmöller diagrams to diagnose Rossby wave trains . Tellus , 63A , 991 – 1006 , https://doi.org/10.1111/j.1600-0870.2011.00541.x . 10.1111/j.1600-0870.2011.00541.x Grazzini , F. , and F. Vitart , 2015 : Atmospheric predictability and Rossby wave packets . Quart. J. Roy. Meteor. Soc. , 141 , 2793 – 2802 , https

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Andreas Schlueter, Andreas H. Fink, Peter Knippertz, and Peter Vogel

National Oceanic and Atmospheric Administration (NOAA) OLR dataset ( Liebmann and Smith 1996 ) was used to filter the waves in the period from 1981 to 2013. The spatial resolution of this dataset is 2.5° × 2.5°. To demonstrate the effect of orography, we used the 5-min gridded ETOPO5 elevation dataset ( NGDC 1988 ). c. Wave filtering Six different wave types were analyzed in this study, sorted according to their scale: MJO, ER, MRG, Kelvin, TD, and EIG ( n = 0, hereafter simply called EIG) waves. WIG

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Andreas Schlueter, Andreas H. Fink, and Peter Knippertz

computed from the surface to the top of the model domain (0.1 hPa) and were provided by the ECMWF. The daily interpolated National Oceanic and Atmospheric Administration (NOAA) OLR dataset ( Liebmann and Smith 1996 ) was used to filter the waves following the methods applied in Part I . OLR has the advantage that it is available for a relatively long period. Consistent with Part I , the time period spans from 1981 to 2013. The precipitation patterns associated with each wave band are discussed in

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