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

-and-whiskers plots of predicted precipitation and the observed 4-day box average of 37 mm as a dashed line. This value is much smaller than the maximum values discussed in section 3 due to area averaging during the gridding process of the ENSEMBLES data (see details in Haylock et al. 2008 ) and large spatial inhomogeneities. Global models cannot be expected to capture this mesoscale spatial variability. Therefore, the forecasts are more useful as indicators of a potentially significant rain event than for

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Maxi Boettcher and Heini Wernli

) generalized the hypothesis that antecedent vorticity development should be relevant to subsequent explosive development by looking into a large sample of cyclone events. They established the concept of a “two-phase development” for cyclones showing a pronounced near-surface vorticity precursor. Simultaneously, theoretical studies using idealized two-dimensional models investigated the impact of diabatic processes on a baroclinic unstable environment ( Snyder and Lindzen 1991 ) and in mesoscale convective

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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

operational hurricane track forecast models. Bull. Amer. Meteor. Soc. , 77 , 925 – 933 . Chou , K.-H. , and C.-C. Wu , 2008 : Development of the typhoon initialization in a mesoscale model—Combination of the bogused vortex with the dropwindsonde data in DOTSTAR. Mon. Wea. Rev. , 136 , 865 – 879 . Fiorino , M. , 2008 : Record-setting performance of the ECMWF IFS in medium-range tropical cyclone track prediction. ECMWF Newsletter, No. 118, ECMWF, Reading, United Kingdom, 20–27 . Harnisch

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Paraskevi Giannakaki and Olivia Martius

. , and Bullock R. , 2006 : Object-based verification of precipitation forecasts. Part I: Methodology and application to mesoscale rain areas . Mon. Wea. Rev. , 134 , 1772 – 1784 , doi: 10.1175/MWR3145.1 . Davis, C. , Brown B. , Bullock R. , and Halley-Gotway J. , 2009 : The Method for Object-based Diagnostic Evaluation (MODE) applied to numerical forecasts from the 2005 NSSL/SPC Spring Program . Wea. Forecasting , 24 , 1252 – 1267 , doi: 10.1175/2009WAF2222241.1 . Dee, D. P. , and

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

evaluated in comparison to radar data. Groenemeijer and Craig (2012) showed that the stochastic scheme contributes significant variability in a mesoscale ensemble prediction system, but that the contribution varies strongly between different weather regimes. Here we investigated whether this additional variability produces a measurable improvement in various metrics of forecast quality. Two cases selected from the study of Groenemeijer and Craig (2012) were considered to illustrate the performance

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Tobias Selz and George C. Craig

convective-scale errors start to spin up balanced motions, which continue to grow at a slower rate through baroclinic instability (stage 3). This model describes how the intrinsic convective-scale uncertainty is able to grow upscale and contaminate the mesoscale and the large-scale forecast after a period of time. However, the relevance of this conceptual model is arguable because of the high level of idealization. The 10-km model resolution used in the main experiments of Zhang et al. (2007) was

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Julia H. Keller

. Atmos.–Ocean , 42 , 235 – 250 , doi: 10.3137/ao.420402 . 10.3137/ao.420402 Davis , C. , B. Brown , and R. Bullock , 2006 : Object-based verification of precipitation forecasts. Part I: Methodology and application to mesoscale rain areas . Mon. Wea. Rev. , 134 , 1772 – 1784 , doi: 10.1175/MWR3145.1 . 10.1175/MWR3145.1 ECMWF , 2008 : European Centre for Medium-Range Weather Forecasts Ensemble Prediction System—Operational archive Cycle35r3, Resolution T639L62, accessed April 2011

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Kirstin Kober and George C. Craig

physically based stochastic perturbations will be introduced as well as the mesoscale weather prediction model used in this study and the verifying observational data. In section 3 , the method will be applied in several case studies representing two different weather regimes to assess the structure of the perturbations, their impact on the precipitation fields, and the sensitivities in parameter settings of the perturbations scheme. Additionally, forecast quality of other variables will be assessed

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Andreas Schäfler, Andreas Dörnbrack, Christoph Kiemle, Stephan Rahm, and Martin Wirth

improvements in NWP, the quantitative precipitation forecast (QPF) skill has not changed significantly in recent years. Thus, improving the QPF is one of the main research interests in numerical weather prediction ( Fritsch and Carbone 2004 ; Rotunno and Houze 2007 ; Richard et al. 2007 ; Wulfmeyer et al. 2008 ). The interaction between various synoptic-scale and mesoscale processes, such as large-scale forcing ( Massacand et al. 2001 ; Hoinka and Davies 2007 ), orographic lifting ( Reeves and Rotunno

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