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Jonathan A. Weyn and Dale R. Durran

1. Introduction The problem of mesoscale predictability in numerical weather forecasts is becoming increasingly important as computational resources allow the simulation of progressively finer-scale atmospheric features. It is also of societal importance, as the accurate prediction and localization of severe weather, including flash flooding and tornadoes, is vital to saving lives and property. Nearly 50 years ago, Edward Lorenz proposed the idea that certain deterministic fluid systems with

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Jonathan Poterjoy and Fuqing Zhang

500 hPa along with positive values of unfiltered 950-hPa ζ . The 950-hPa circulation in the EnKF-MADIS forecast remains weak after initialization ( Fig. 5c ) and lags behind the midlevel circulation in the days leading up to the genesis time. Likewise, the 950-hPa circulation in the EnKF-PREDICT simulation moves closer to the 500-hPa cyclone and intensifies with time. The forecast from this analysis also contains a noticeably higher number of mesoscale vorticity anomalies 24 h into the simulation

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Y. Qiang Sun and Fuqing Zhang

1. Introduction Current-generation numerical weather prediction (NWP) models now are capable of routinely capturing the evolution of large-scale synoptic weather systems but remain challenged in forecasting meso- and convective-scale weather phenomena such as squall lines and tornadic thunderstorms. It is of great interest to assess the predictability of these mesoscale severe weather systems, what their predictability limits are, and how to improve our forecasts, particularly with respect to

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Tomislava Vukicevic, Eric Uhlhorn, Paul Reasor, and Bradley Klotz

accuracy of track forecasting has been attributed primarily to improved prediction of synoptic- to planetary-scale circulation using global numerical prediction models ( Rappaport et al. 2009 ; McAdie and Lawrence 2000 ). In contrast, the lack of systematic improvement for the intensity forecast is not well understood. It has been hypothesized that progress has been limited by outstanding challenges of numerical prediction of mesoscale processes and multiscale interactions, in particular regarding the

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Hua Leighton, Sundararaman Gopalakrishnan, Jun A. Zhang, Robert F. Rogers, Zhan Zhang, and Vijay Tallapragada

Prediction Scheme (SHIPS) for the Atlantic basin . Wea. Forecasting , 9 , 209 – 220 , https://doi.org/10.1175/1520-0434(1994)009<0209:ASHIPS>2.0.CO;2 . 10.1175/1520-0434(1994)009<0209:ASHIPS>2.0.CO;2 Ek , M. B. , K. E. Mitchell , Y. Lin , E. Rogers , P. Grunmann , V. Koren , G. Gayno , and J. D. Tarpley , 2003 : Implementation of Noah land surface model advancements in the National Centers for Environmental Prediction operational mesoscale Eta model . J. Geophys. Res. , 108

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Jonathan A. Weyn and Dale R. Durran

that these may be a more important source of uncertainty than perturbations on the smallest resolved scales in very-high-resolution mesoscale models. In particular, recent work ( Durran and Gingrich 2014 ; Durran and Weyn 2016 ; WD17 ) has highlighted a little-known result in Lorenz (1969) suggesting that initial large-scale errors can be as detrimental to forecasts as initial small-scale errors of the same absolute amplitude. Morss et al. (2009) used a similar strategy of imposing initial

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Falko Judt

, which results in the loss of mesoscale predictability within hours ( Zhang et al. 2003 , 2007 ; Selz and Craig 2015 ; Durran and Weyn 2016 ; Weyn and Durran 2017 ). The practical consequence of this behavior is the well-known difficulty to forecast convective phenomena, such as tropical cyclones ( Sippel and Zhang 2008 ; Judt et al. 2016 ) and severe convective storms (e.g., Hawblitzel et al. 2007 ; Zhang et al. 2015 ). Because of their restricted domains, however, regional models cannot

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Mario Marcello Miglietta and Richard Rotunno

: Quantitative precipitation forecasting in the Alps: The advances achieved by the Mesoscale Alpine Programme . Quart. J. Roy. Meteor. Soc. , 133 , 831 – 846 , doi:10.1002/qj.65 . Romero , R. , C. A. Doswell III , and C. Ramis , 2000 : Mesoscale numerical study of two cases of long-lived quasi-stationary convective systems over eastern Spain . Mon. Wea. Rev. , 128 , 3731 – 3751 , doi:10.1175/1520-0493(2001)129<3731:MNSOTC>2.0.CO;2 . Rotach , M. W. , and Coauthors , 2009 : MAP D

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Hyeyum Hailey Shin and Song-You Hong

each grid size (Δ) describe how the resolved and parameterized turbulence should be represented at each grid size. This section provides brief descriptions of the LES model [the Weather Research and Forecasting Model (WRF)], the experimental setup and characteristics of the benchmark simulations, and the reference data obtained from the simulations. a. Model description WRF is used as an LES model. WRF calculates the fully compressible and nonhydrostatic governing equations that are formulated

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Shawn S. Murdzek, Paul M. Markowski, Yvette P. Richardson, and Matthew R. Kumjian

1. Introduction To forecast hazards associated with a convective storm, it is useful to know the properties of air parcels being ingested by the storm. For example, to predict whether a storm will produce a tornado, forecasters often examine inflow soundings for characteristics known to be favorable for tornadic storms, such as low lifted condensation levels (LCL), large amounts of low-level storm-relative helicity (SRH), and large vertical wind shear, which is typically assessed in terms of

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