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Maxi Boettcher and Heini Wernli

DRWs occur and how often they intensify explosively. This study is a first approach to address these questions and to quantify the occurrence, the geographical distribution, and the intensification of DRWs in the Northern Hemisphere (i.e., over the North Atlantic and the North Pacific Oceans). A sophisticated tracking algorithm that is described in section 2 is applied to 10 yr of operational European Centre for Medium-Range Weather Forecasts (ECMWF) analyses. Section 3 addresses the frequency

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Volkmar Wirth, Michael Riemer, Edmund K. M. Chang, and Olivia Martius

latitude band, with the weighting function being proportional to the zonal variance of the meridional wind. This algorithm self-adjusts to the optimum range of latitudes and avoids the need to predetermine a fixed latitude band. Another algorithm makes the latitudinal band depend even on longitude with the aim to follow the main waveguide ( Martius et al. 2006 ). A systematic comparison between different types of Hovmöller diagrams shows that the refinements are beneficial in situations where otherwise

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Jana Čampa and Heini Wernli

-dimensional variational data assimilation (4D-Var) with a 12-h window versus 3D-Var]. The data are available every 6 h. The original fields were interpolated onto a 1° × 1° regular grid and the PV field was calculated from the wind and temperature fields on the model levels and then interpolated on a stack of pressure levels (every 25 hPa between 1000 and 100 hPa). The cyclones were identified and tracked using the algorithm introduced by Wernli and Schwierz (2006) . The algorithm searches for minima in the SLP

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Gabriel Wolf and Volkmar Wirth

packet and smoothly decays to smaller values at the boundaries of the wave packet. The carrier wave C oscillates between positive and negative values and varies on a much shorter spatial scale than A . The amplitude A will also be referred to as envelope in the following. The task of envelope reconstruction is tantamount as to find an algorithm that allows one to compute A ( λ ) when υ ( λ ) is given. In the past, meteorologists have used essentially two methods in order to reach this goal

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Maxi Boettcher and Heini Wernli

. Therefore the QG low-level forcing for ascent is too weak in amplitude, but it correctly pinpoints the regions where the slantwise circulation associated with the low-level DRW leads to ascent and descent. For investigating and comparing the DRW evolution in the analyses and forecasts, the tracking algorithm for DRWs developed by Kenzelmann (2005) has been refined. The algorithm searches in a smoothed version of the vertically averaged low-level PV field for grid points with PV maxima that exceed 0

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Gabriel Wolf and Volkmar Wirth

; Grazzini and Vitart 2015 ). Despite some obvious advantages in comparison with Hovmöller diagrams, diagnosing and tracking of RWPs is far from straightforward and may occasionally yield misleading results. In particular, diagnosing RWP objects on a longitude–latitude map requires a number of choices, like for instance choosing an algorithm to compute the envelope of a wave packet and picking a threshold. Neither Hovmöller diagrams nor RWP tracking inherently provides information about the propagation

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Kirstin Kober, Annette M. Foerster, and George C. Craig

forecasts. An ensemble of 100 members is generated that consists of 10 groups, each containing 10 members. The 10 groups represent different initial and boundary conditions and are defined by the selection of 10 representative members out of the 51-member global European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble with a clustering algorithm ( Molteni et al. 2001 ). Within each group, these members represent different large-scale forcing conditions that translate into different initial

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Paraskevi Giannakaki and Olivia Martius

have complex structures, and there are cases in which reanalysis objects and forecast objects do not overlap. MODE is an ideal method for these cases, as a fuzzy logic algorithm is used to match the objects. If the objects do not overlap, a total interest value is calculated for the two objects by taking into account the area ratio and the centroid distance based on the following equation: [simplified Eq. (1) from Davis et al. (2009) ], where is the total interest value ( ) for the j th

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Martin Weissmann, Florian Harnisch, Chun-Chieh Wu, Po-Hsiung Lin, Yoichiro Ohta, Koji Yamashita, Yeon-Hee Kim, Eun-Hee Jeon, Tetsuo Nakazawa, and Sim Aberson

) and one that assimilates dropsondes (DROP). Special TEMP and SYNOP were not denied. All other observations from the NCEP archive were ingested into the assimilation system for both runs. The experiments were conducted in a cycled mode for the whole T-PARC period. Dropsondes in the Atlantic were also removed in the NODROP run. The NCEP Global Data Assimilation System (GDAS) consists of a quality control algorithm, a TC vortex initialization procedure, data assimilation, and the global spectral

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Franziska Teubler and Michael Riemer

denote PV anomalies on the 325-K isentrope. The dashed line denotes the ridge axis. Our algorithm to identify the PV anomalies associated with troughs and ridges works as follows: trough and ridge axes are identified as the lines at which the meridional wind anomaly vanishes ( υ ′ = 0) in data smoothed over 7° × 7°. For our purpose, these lines provide a reliable estimate of the trough (ridge) axes poleward (equatorward) of the 2 potential vorticity unit (PVU; 1 PVU = 10 −6 K kg −1 m 2 s −1

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