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Tomislava Vukićević

: Sensitivity analysis using an adjoint of the PSU/NCAR mesoscale model. Mon. Wea. Rev., 120, 1644-1645.Farrell, B. F., 1990: Small error dynamics and the predictability of atmospheric flows. J. Atmos. Sci., 47, 2409-2416.Hoffman, R. N., and E. Kalnay, 1983: Lagged average forecasting: An alternative to Monte Carlo forecasting. Tellus, 35A, 100 118.Houtekamer, P. L., 1992: The quality of skill forecasts for a low order spectral model. Mort. Wea. Rev., 120, 2993-3002.Kalnay, E., and A. Dalcher

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Carl W. Kreitzberg and Donald J. Perkey

data are implied to the extent that these~results are plausible in view of observed convectiverainbands. More explicit comparison of forecasts usingreal data as input and verifying against observations'requires use of the three-dimensional version of themesoscale model. Preliminary results have been obtained from a forecast of the storm of 21 February 1971(Kreitzberg et al., 1974; Perkey, 1976). The mesoscale primitive equation model is docu mented in Section 2 including the equations and

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Jonathan Poterjoy and Fuqing Zhang

experiment description a. Forecast model and ensemble generation The fully compressible, nonhydrostatic, mesoscale WRF version 3.1 ( Skamarock et al. 2005 ) was used for this study with a coarse domain of 202 × 181 horizontal grid points at 40.5-km grid spacing and 2 two-way nested domains that automatically follow the storm using the WRF vortex-following algorithm. The innermost domain (D3), where all analysis is performed, has a 253 × 253 horizontal grid with 4.5-km spacing. All domains use 35 vertical

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Greg J. Holland and Mark Lander

tentatively conclude that these interactionswere important. 2) NUMERICAL MODELING EXPERIMENTS To test the potential for mesoscale vortices to causethe observed meanders of Typhoon Sarah, we conducted a series of experiments with a barotropic model.A full description of the system used is contained inHolland et al. (1991 ). It consists of a nondivergentbarotropic model with 70-km horizontal resolution ona mercator projection that was developed for researchand forecasting associated with the ONR Tropical

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Fuqing Zhang

. , 1986 : Gravity waves. Mesoscale Meteorology and Forecasting, P. S. Ray, Ed., Amer. Meteor. Soc., 272–288 . Hoskins , B. J. , M. E. McIntyre , and A. W. Robertson , 1985 : On the use and significance of isentropic potential vorticity maps. Quart. J. Roy. Meteor. Soc. , 111 , 877 – 946 . Kaplan , M. L. , and D. A. Paine , 1977 : The observed divergence of the horizontal velocity field and pressure gradient force at the mesoscale. Beitr. Phys. Atmos. , 50 , 321 – 330

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Boualem Khouider, Ying Han, and Joseph A. Biello

improved and the forecast track error of hurricanes is reduced when the Wu and Yanai (1994) CMT scheme is included into the National Centers for Environmental Prediction’s (NCEP’s) operational Global Forecast System (GFS) ( Han and Pan 2006 ). While the above cited CMT parameterizations achieved relative success in global and regional climate simulations, they do not systematically include CMT due to organized mesoscale systems, which is believed to play a significant role in the TOGA COARE data

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Jun Peng, Lifeng Zhang, and Jiping Guan

: 10.1002/qj.2025 . Skamarock , W. C. , 2004 : Evaluating mesoscale NWP models using kinetic energy spectra . Mon. Wea. Rev. , 132 , 3019 – 3032 , doi: 10.1175/MWR2830.1 . Skamarock , W. C. , and J. B. Klemp , 2008 : A time-split nonhydrostatic atmospheric model for weather research and forecasting applications . J. Comput. Phys. , 227 , 3465 – 3485 , doi: 10.1016/j.jcp.2007.01.037 . Skamarock , W. C. , and Coauthors , 2008 : A description of the Advanced Research WRF version 3

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Da-Lin Zhang and J. Michael Fritsch

-levelsupply of high-Os air; 4) the low-level jet weakened; and5) lOWC~ air from east of the Appalachians flowed intothe vortex.The results indicate that successful prediction of theevolution of mesoscale convective systems and significant improvement of quantitative precipitation forecasts not only hinge upon the model treatment of con15 SEPTEMBER 1987DA-LIN ZHANG AND J. MICHAEL FRITSCH2611vection, but also depend upon the physics of other mesoscale processes. In particular, the resolvable-scalephase changes

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Matthew F. Garvert, Brian A. Colle, and Clifford F. Mass

1. Introduction Over the past decade, marked improvements in the ability of high-resolution mesoscale models to simulate accurately the complex effects of terrain have been documented in various studies (e.g., Colle and Mass 1996 ; Bruintjes et al. 1994 ). Yet despite the increased accuracy of numerical models, there are still significant deficiencies in the precipitation forecasts over mountainous terrain ( Colle and Mass 2000 ; Colle et al. 1999 , 2000 ). These precipitation errors appear

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Jun Peng, Lifeng Zhang, Yu Luo, and Yun Zhang

system simulated by the Advanced Research Weather Research and Forecasting model (ARW). Section 2 describes the numerical model and simulation setup. Section 3 presents the results of the control simulation, which successfully reproduced characteristics analogous to that documented by the observations and previous studies. Section 4 presents the mesoscale KE spectra characteristic of the mei-yu front system, and discusses the sensitivity of the mesoscale KE spectra to latent heating. A

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