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Jacob T. Radford, Gary M. Lackmann, and Martin A. Baxter

tough old bull: “Statistically significant” expires . Amer. Stat. , 73 , 352 – 357 , . 10.1080/00031305.2018.1543616 Koch , S. E. , B. Ferrier , M. T. Stoelinga , E. Szoke , S. J. Weiss , and J. S. Kain , 2005 : The use of simulated radar reflectivity fields in the diagnosis of mesoscale phenomena from high-resolution WRF model forecasts . 11th Conf. on Mesoscale Processes , Albuquerque, NM, Amer. Meteor. Soc., J4J.7 , https

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Astrid Suarez, Heather Dawn Reeves, Dustan Wheatley, and Michael Coniglio

uncertainty in synoptic-scale (200–1000 km) flows in the presence of moist convection (e.g., Zhang et al. 2003 ; Zhang 2005 ; Zhang et al. 2007 ). Ensemble-based four-dimensional data assimilation using the ensemble Kalman filter (EnKF; Evensen 1994 ) has been shown to improve forecasts and reduce uncertainty for large-scale geophysical prediction problems ( Houtekamer and Mitchell 1998 ; Anderson 2001 ; Whitaker and Hamill 2002 ) and for the analysis and short-term prediction of mesoscale and

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Rebecca D. Adams-Selin, Susan C. van den Heever, and Richard H. Johnson

4 discusses the sensitivity of the five operational parameters to microphysical changes, and section 5 provides the conclusions. 2. Methodology a. Model setup The Advanced Research core of the Weather Research and Forecasting (WRF-ARW) model, version 3.2.1 ( Skamarock et al. 2008 ), was used in this study to simulate an isolated bow echo case over Oklahoma on 13 March 2003. This model was chosen as its ability to simulate case studies of mesoscale phenomena is well known. It is widely used in

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Barry H. Lynn

contrast, Fig. 2 shows the number of grid elements (averaged) versus the number of observed strokes [4 × 4 km 2 (10 min) −1 ; hereafter only (10 min) −1 for brevity]. Both datasets (high and low) have very similar distributions of lightning, indicating that lightning intensity should not be used as a possible descriptor of the case study days. Fig . 2. Average number of grid elements binned against strokes [(10 min) −1 ]. North American Mesoscale Forecast System (NAM) initial and lateral boundary

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Matthew E. Gropp and Casey E. Davenport

fields for each supercell evolution category. Supercell location is indicated by the black dot. b. Mesoscale environments Common forecasting parameters were evaluated in the inflow region, including MUCAPE, MUCIN, and effective SRH; these parameters were selected as being the most likely to illustrate differences among the evolution types based on the findings of previous research (e.g., Nowotarski et al. 2011 ; Coffer and Parker 2015 ). Composite grids of these parameters were generated for each

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Sanjib Sharma, Ridwan Siddique, Nicholas Balderas, Jose D. Fuentes, Seann Reed, Peter Ahnert, Robert Shedd, Brian Astifan, Reggina Cabrera, Arlene Laing, Mark Klein, and Alfonso Mejia

-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 . Demargne, J. , Brown J. , Liu Y. , Seo D.-J. , Wu L. , Toth Z. , and Zhu Y. , 2010 : Diagnostic verification of hydrometeorological and hydrologic ensembles . Atmos. Sci. Lett. , 11 , 114 – 122 , doi: 10.1002/asl.261 . Demargne, J. , and Coauthors , 2014 : The science of NOAA’s Operational Hydrologic Ensemble Forecast

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Xu Zhang, Yuhua Yang, Baode Chen, and Wei Huang

(2004) reported that heavy rainfall over the Korean Peninsula is mainly organized by strong synoptic-scale forcing. In this weather regime, the mechanisms responsible for heavy precipitation are different from precipitation over the central United States, which is produced by mesoscale convective systems. Over the United States, the role of parameterized convection is crucial to simulations of mesoscale properties and precipitation forecasting. However, CPS plays an insignificant role in the

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Pengyuan Li, Gang Fu, Chungu Lu, Dan Fu, and Shuai Wang

energy (TKE). In the present study, a sea fog event that occurred in a stably stratified boundary layer and was accompanied with an LLJ at around 360 m above the sea level was investigated using the Advanced Research core of the Weather Research and Forecasting Model (WRF ARW; Skamarock et al. 2008 ). We analyzed the relationship between the formation mechanism of this fog episode and the low-level jet, and examined the role of each term in the TKE budget equation, such as shear and buoyancy

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Sabrina Bentzien and Petra Friederichs

convection. Because of their high resolution of 10 km or less and their nonhydrostatic dynamics, HR-NWP models are able to describe mesoscale processes in an explicit and more detailed way. Today, many meteorological services use HR-NWP models for operational forecasts ( Skamarock and Klemp 2008 ; Saito et al. 2006 ; Staniforth and Wood 2008 ; Baldauf et al. 2011 ; Seity et al. 2011 ). Although HR-NWP model forecasts lead to more realistic mesoscale structures ( Mass et al. 2002 ), QPF is still

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Miriam L. Apsley, Kelsey J. Mulder, and David M. Schultz

, the data and simulations in this article will be insufficient to address the issue of tornadogenesis in this case. Thus, we focus on the misocyclones, the locations of the tornadoes, and an approach to forecasting the occurrence of tornadoes along lines, as demonstrated for the case of Britain’s greatest tornado outbreak on 23 November 1981. 3. Observations: Synoptic and mesoscale overview At 1200 UTC 22 November 1981, archived Met Office charts identified a broad region of low pressure with two

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