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Eric P. Grimit and Clifford F. Mass

Pennsylvania State University–National Center for Atmospheric Research fifth-generation Mesoscale Model (PSU–NCAR MM5; Grell et al. 1994 ) suggest diminishing returns as grid spacing drops below 12 km, when evaluated using standard measures of forecast skill ( Mass et al. 2002 ). Furthermore, numerical model forecasts can be very sensitive to slight changes in the larger-scale initial conditions ( Brooks et al. 1992 ). Recognition of such predictability issues has led to increased interest in developing

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William H. Raymond and Roland B. Stull

DECEMBER 1990 RAYMOND AND STULL 2471Application of Transilient Turbulence Theory to Mesoscale Numerical Weather Forecasting WILLIAM H. RAYMOND*Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin, Madison, Wisconsin ROLAND B. STULL*Department of Meteorology, University of Wisconsin, Madison, Wisconsin(Manuscript received 20 Mamh 1989, in

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Morten Køltzow, Barbara Casati, Eric Bazile, Thomas Haiden, and Teresa Valkonen

forecast accuracy by the use of optimized physics for the targeted area and finer horizontal and vertical resolution ( Jung et al. 2016 ). However, operational convection permitting resolution models have just recently started to appear for the Arctic domain. Müller et al. (2017) and Yang et al. (2018) describe added value from operational high-resolution HIRLAM–ALADIN Research on Mesoscale Operational NWP in Euromed (HARMONIE)–Applications of Research to Operations at Mesoscale (AROME) runs in the

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Craig S. Schwartz, Glen S. Romine, Morris L. Weisman, Ryan A. Sobash, Kathryn R. Fossell, Kevin W. Manning, and Stanley B. Trier

storm-scale EnKF DA of radar observations for individual cases [e.g., Snyder and Zhang 2003 ; Zhang et al. 2004 ; Dowell at al. 2004 ; Putnam et al. (2014) , and references therein], only more recently have mesoscale EnKF DA systems been employed to initialize convection-allowing ensemble forecasts over meso- α - to synoptic-scale regions. For example, several case studies (e.g., Jones and Stensrud 2012 ; Melhauser and Zhang 2012 ; Jones et al. 2013 , 2015 ; Schumacher and Clark 2014 ) and

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Donald C. Norquist

standard meteorological variables (temperature, wind, humidity, pressure) as produced by the theater numerical weather prediction (NWP) model. Cloud forecasts are required out to 36 h beyond the current (most recent observation) time, with a stated degree of accuracy. This paper describes the methods developed to provide the required cloud predictions and presents an assessment of their predictive skill. Because the cloud variables required are not explicitly predicted by any known mesoscale NWP

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Lisa S. Alexander, David M. L. Sills, and Peter A. Taylor

products when detecting/analyzing convective development along mesoscale boundaries. In other words, cell initiations are often first and better detected using data above the CAPPI 1-km level. Finally, it is important that boundary information be used to detect and nowcast the initiation of convective storms. A semiobjective, manual approach was used in this study for boundary identification, though it is recognized that this is too labor intensive for operational use by forecasters. High

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Mika Peace, Trent Mattner, Graham Mills, Jeffrey Kepert, and Lachlan McCaw

mesoscale environment. Several of these (e.g., Mills 2005 , 2008a ; Charney and Keyser 2010 ; Zimet et al. 2007 ) describe dynamical mixing of dry and high-momentum air from the mid–upper troposphere to above a fire site. In each of the events above, extreme fire behavior occurred in an environment where dry, high-momentum air was present in the midtroposphere. Each study proposed meteorological mechanisms by which the surface fire activity could be enhanced by mixing of the air mass from the mid

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Shengjun Zhang, Tim Li, Xuyang Ge, Melinda Peng, and Ning Pan

code. Thus, even though the observed TC structure is given, there is an observation error associated with the observed data. We did include some level of reasonable observation noise. b. Application of the TCDI–3DVAR scheme to an operational forecast system The aforementioned dynamic initialization scheme has been implemented in the Coupled Ocean–Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC; Hendricks et al. 2011 ). Figure 11 is a flowchart describing how the TCDI

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Donna F. Tucker and Kristine S. Zentmire

well. Acknowledgments We are grateful to Dr. Edward Tollerud of the Forecast Systems Laboratory for providing the dataset with MCC times and locations. REFERENCES Anderson, C. J., and R. W. Arritt, 1998: Mesoscale convective complexes and persistent elongated convective systems over the United States during 1992 and 1993. Mon. Wea. Rev., 126, 578–599. 10.1175/1520-0493(1998)126<0578:MCCAPE>2.0.CO;2 Augustine, J. A., and K. W. Howard, 1988: Mesoscale convective complexes over the United States

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Dustan M. Wheatley and David J. Stensrud

high-resolution numerical weather prediction (NWP) products can serve as a proxy for the real atmosphere, but the initial conditions of NWP models are often devoid of important mesoscale features, a potential source of forecast error. Mesoscale surface data assimilation is one approach for improving model initialization/spinup and subsequently derived products. The present study emphasizes the potential role of including surface pressure observations in mesoscale ensemble data assimilation. To meld

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