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Florian Harnisch and Martin Weissmann

1. Introduction Tropical cyclones (TCs) usually develop over data-sparse regions of the tropical oceans. The limited number of observations and the rapid development of TCs increases uncertainties of the model analysis in these regions, which can lead to significant forecast errors ( Langland 2005 ). Surveillance programs deploying dropsonde observations in and around TCs have been operated for the Atlantic ( Burpee et al. 1996 ; Aberson 2002 ) and the western North Pacific basin ( Wu et al

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Marlene Baumgart, Michael Riemer, Volkmar Wirth, Franziska Teubler, and Simon T. K. Lang

1. Introduction Numerical weather prediction has improved remarkably over the last decades (e.g., Bauer et al. 2015 ). Occasionally, however, very poor medium-range forecasts do still occur ( Rodwell et al. 2013 ). Forecast errors arise due to errors in the initial conditions and due to model deficiencies (e.g., Palmer and Hagedorn 2006 ). After 1–2 forecast days, localized errors may form that start to affect the synoptic-scale flow (e.g., Davies and Didone 2013 ; Martínez-Alvarado et al

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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

1. Introduction Tropical cyclone (TC) track forecasts have improved significantly over the past decades. The U.S. National Hurricane Center reported a reduction of its official 24–72-h mean track forecast error of nearly 50% in the time frame 1980–2008 for the Atlantic and eastern North Pacific ( NOAA/NWS/NHC 2009 ). Similar improvements were reported for Japan Meteorological Agency (JMA) official typhoon forecasts in the time period 1982–2007 (see the annual report for 2007 online at http

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Paraskevi Giannakaki and Olivia Martius

on the medium-range time scale ( Cressman 1948 ; Lee and Held 1993 ; Grazzini and Vitart 2015 ), provided that their representation in numerical weather prediction (NWP) models is accurate. However, Gray et al. (2014) found that both the meridional extent of upper-level Rossby waves and the tropopause sharpness in ridges decrease with forecast lead time. Errors in Rossby waves can be associated with errors in the forecasting of warm conveyor belts ( Martínez-Alvarado et al. 2015 ) and

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Lisa-Ann Quandt, Julia H. Keller, Olivia Martius, and Sarah C. Jones

1. Introduction As atmospheric blocking may cause high-impact weather like heat waves and flooding (e.g., Matsueda 2009 ), there is a special interest in its predictability and the physical processes that limit forecast quality. Blocking is a large-scale flow pattern that decelerates arriving eddies, as well as the background flow, and forces them to follow a more meridional direction (e.g., Rex 1950 ; Arakawa 1952 ; Sumner 1954 ). Atmospheric blocking is persistent and self-sustaining (e

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Lars Wiegand, Arwen Twitchett, Cornelia Schwierz, and Peter Knippertz

PV anomalies arising “naturally” during the cyclonic wave-breaking process. PV streamers west of the Alps extending into Africa can initiate dust emissions and the transport and deposition on Alpine glaciers ( Sodemann et al. 2006 ). Forecasts of PV streamers, as weather forecasts in general, are limited by deficiencies in numerical weather prediction models and uncertainties in the initial conditions. Ensemble forecasts provide probability information and are therefore of more value for

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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

transitioning cyclone (encircled during extratropical stage) and the “L” the position of the downstream cyclone. Together with Part I , this review describes developments in our understanding of ET since the first ET review by Jones et al. (2003 , hereafter J2003 ). The review by J2003 was motivated by the challenges that ET typically poses to forecasters in terms of predicting the structural evolution of the transitioning cyclone itself, and the high-impact weather that might be associated with it

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Julia H. Keller, Sarah C. Jones, and Patrick A. Harr

preexisting midlatitude wave pattern poses a challenge for numerical weather prediction (NWP) systems. Using various ensemble forecast systems, Harr et al. (2008) and Anwender et al. (2008) showed that ET events often coincide with increased forecast uncertainty in downstream regions. By conducting numerical experiments for the ET of Hurricane Helene (1996), Pantillon et al. (2012) further showed how forecast errors associated with the ET event propagate toward downstream regions and lead to

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Maxi Boettcher and Heini Wernli

realistic model setting. And finally, it is unclear how well operational forecast models predict the generation, propagation, and intensification of a DRW. A first study dealing with this issue has been performed for the storm Lothar by Kenzelmann (2005) . They analyzed the 50 simulations of the ECMWF ensemble prediction system and identified a strong sensitivity of the track and intensity of the mature storm to its structure and position relative to the jet axis during the DRW propagation phase

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Kirstin Kober and George C. Craig

1. Introduction Forecasting convective initiation more than a few hours in advance is an ongoing challenge in atmospheric research. The exact timing and location will probably not be forecast by numerical weather prediction (NWP) models in the near future, but forecasts of the probability of precipitation can show useful skill. Probabilistic forecasts aim to represent uncertainty that results from several sources of varying importance. The intrinsic uncertainty of a chaotic system like the

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