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Tobias Kremer, Elmar Schömer, Christian Euler, and Michael Riemer

; Joos and Forbes 2016 ). For example, a rather simple set of variables and appropriate thresholds can be used to identify warm conveyor belts as ensembles of trajectories that behave very similarly and that densely populate a compact region in 3D physical space (sometimes referred to as coherent bundles of trajectories; Wernli and Davies 1997 ). Clustering techniques have been employed more recently in an attempt to identify conveyor-belt trajectories more objectively (e.g., Hart et al. 2015 ). If

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Stephan Rasp and Sebastian Lerch

the mean value and standard deviation of the 2-m temperature forecasts. 3. Benchmark postprocessing techniques a. Ensemble model output statistics Within the general EMOS framework proposed by Gneiting et al. (2005) , the conditional distribution of the weather variable of interest, , given ensemble predictions , is modeled by a single parametric forecast distribution with parameters : The parameters vary over space and time, and depend on the ensemble predictions through suitable link

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Michael Maier-Gerber, Michael Riemer, Andreas H. Fink, Peter Knippertz, Enrico Di Muzio, and Ron McTaggart-Cowan

this study is split into “cyclone” and “no-cyclone” groups to elucidate dynamic causes limiting predictability of the pre-Chris cyclone’s formation. The group memberships are determined based on similarity between forecast tracks and the analysis track using a dynamic time warping technique (see section 2c for details). This track-based approach for the identification of equivalent cyclones in the forecast members ensures that those are excluded that are of substantially different origin from the

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Kevin Bachmann, Christian Keil, George C. Craig, Martin Weissmann, and Christian A. Welzbacher

Palmer 2011 ). Second, those ensembles require refined initial conditions, which can only be obtained by data assimilation (DA) of spatially dense observations on kilometer scales ( Johnson and Wang 2016 ). And third, novel techniques are necessary to verify the forecasts and assess their skill with observations of high spatial and temporal resolution ( Cintineo and Stensrud 2013 ). Estimates of the forecast horizon of storm-scale features remain rather pessimistic, being on the order of only a few

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Julia H. Keller, Christian M. Grams, Michael Riemer, Heather M. Archambault, Lance Bosart, James D. Doyle, Jenni L. Evans, Thomas J. Galarneau Jr., Kyle Griffin, Patrick A. Harr, Naoko Kitabatake, Ron McTaggart-Cowan, Florian Pantillon, Julian F. Quinting, Carolyn A. Reynolds, Elizabeth A. Ritchie, Ryan D. Torn, and Fuqing Zhang

research on the representation of model errors arising from diabatic processes using techniques such as stochastic physics. The research summarized in this review primarily focused on assessing the impact of ET on the short-to-medium-range forecast horizon. Preliminary results reveal a statistically significant correlation between monthly mean values of selected teleconnection indices and ET event counts, as well as significant departures from climatology on the subseasonal to seasonal time scale in

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

to surface weather that falls into the tail(s) of the respective local distribution (e.g., precipitation exceeding the 95th percentile). To the extent that weather events inherit predictability from larger-scale dynamical features such as RWPs ( Anthes et al. 1985 ), a better understanding of the RWPs may help to improve the weather forecast, and this is particularly relevant in case of extreme weather. An example is the episode in August 2002, when a quasi-stationary low pressure system over

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Hilke S. Lentink, Christian M. Grams, Michael Riemer, and Sarah C. Jones

, and R. L. Elsberry , 2000 : Extratropical transition of western North Pacific tropical cyclones: An overview and conceptual model of the transformation stage . Wea. Forecasting , 15 , 373 – 395 ,<0373:ETOWNP>2.0.CO;2 . 10.1175/1520-0434(2000)015<0373:ETOWNP>2.0.CO;2 Kossin , J. P. , and C. S. Velden , 2004 : A pronounced bias in tropical cyclone minimum sea level pressure estimation based on the Dvorak technique . Mon. Wea. Rev. , 132

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Mirjam Hirt, Stephan Rasp, Ulrich Blahak, and George C. Craig

.1175/1520-0493(1997)125<0527:TRDOEM>2.0.CO;2 . 10.1175/1520-0493(1997)125<0527:TRDOEM>2.0.CO;2 Wernli , H. , M. Paulat , M. Hagen , and C. Frei , 2008 : SAL—A novel quality measure for the verification of quantitative precipitation forecasts . Mon. Wea. Rev. , 136 , 4470 – 4487 , . 10.1175/2008MWR2415.1 Wernli , H. , C. Hofmann , and M. Zimmer , 2009 : Spatial forecast verification methods intercomparison project: Application of the SAL technique . Wea. Forecasting

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Paolo Ghinassi, Georgios Fragkoulidis, and Volkmar Wirth

; Fragkoulidis et al. 2018 ). Furthermore, it has been argued that the existence of RWPs has implications for predictability ( Lee and Held 1993 ; Grazzini and Vitart 2015 ), which is particularly relevant in the case of high-impact weather. The importance of RWPs has motivated the development of various techniques for their identification and analysis. These techniques include the famous Hovmöller diagram ( Hovmöller 1949 ), the analysis of eddy kinetic energy (short EKE; Chang and Orlanski 1993 ), the

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Gabriel Wolf and Volkmar Wirth

wave breaking toward the end of the life cycle resulted in the formation of a cutoff cyclone over Europe, which led to the heavy precipitation event. The rain was poorly forecast by the operational centers even on the relatively short time scale of a few days ( Grazzini and van der Grijn 2002 ). Assuming that large-scale and long-lived dynamical features should generally be predictable on a time scale longer than just a few days, this suggest that there may be room for improvements concerning the

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