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Michael L. Kaplan and Douglas A. Paine

been developed in an effort to simulate the interaction bet~veen quasi-geostrophicand mesoscale forcing. Initializations performed at 127 km with either a diagnostic omega equation orbarotropic forecast are followed by a prediction with a moist nine-level primitive equation model at 32 km.Several integrations are performed utilizing both real and artificial data for the problem of the waterinduced heat island in the cold season. The results of these integrations indicate important variations inboth

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F. Zhang, Chris Snyder, and Richard Rotunno

known about the mechanisms by which small-scale errors grow and influence larger scales. In this paper, we investigate through integrations of a high-resolution regional NWP model the hypotheses that moist convection is a primary mechanism for forecast-error growth at sufficiently small scales, and that convective-scale errors contaminate the mesoscale within lead times of interest to NWP, thus effectively limiting the predictability of the mesoscale. Existing demonstrations of the limit of

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Pierre Augier and Erik Lindborg

circulation models (GCMs) (e.g., Koshyk and Hamilton 2001 ; Hamilton et al. 2008 ) and mesoscale numerical weather prediction (NWP) models ( Skamarock 2004) reproduce quite realistic mesoscale spectra. Other GCMs, as for example the European Centre for Medium-Range Weather Forecasts (ECMWF)'s weather prediction model Integrated Forecast System, produce mesoscale spectra significantly steeper and with smaller magnitude than the measured ones, even with relatively high-resolution versions (e.g., Shutts

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Fuqing Zhang and Jason A. Sippel

development in their tropical weather outlooks. SZ08 studied the disturbance with short-range ensemble forecasts from a mesoscale model at low resolution with parameterized moist convection and at high resolution with explicit convection. Taking advantage of discrepancies between ensemble members, they used statistical correlation to elucidate why some ensemble members strengthened the disturbance into a tropical cyclone and others did not. They found that the combination of deep moisture and high CAPE

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Dale R. Durran and Mark Gingrich

m and 1 km may destroy the predictability of motions with scales on the order of 10 km in just a few hours. Yet mesoscale numerical weather prediction models are now routinely used to generate 48-h forecasts that include features on scales O (10) km. The justification for these attempts to forecast small-scale features at such long lead times is largely based on the proposition of Anthes et al. (1985) that phenomena generated by the interaction of the large-scale flow with known small

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Steven E. Koch, Brian D. Jamison, Chungu Lu, Tracy L. Smith, Edward I. Tollerud, Cecilia Girz, Ning Wang, Todd P. Lane, Melvyn A. Shapiro, David D. Parrish, and Owen R. Cooper

encounters. J. Atmos. Sci. , 43 , 2838 – 2844 . Benjamin , S. G. , G. A. Grell , J. M. Brown , and T. G. Smirnova , 2004a : Mesoscale weather prediction with the RUC hybrid isentropic–terrain-following coordinate model. Mon. Wea. Rev. , 132 , 473 – 494 . Benjamin , S. G. Coauthors 2004b : An hourly assimilation forecast cycle: The RUC. Mon. Wea. Rev. , 132 , 495 – 518 . Bennetts , D. A. , and J. C. Sharp , 1982 : The relevance of conditional symmetric instability to the

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Justin R. Minder and David E. Kingsmill

about 100 m ( Lundquist et al. 2008 ). The several hundred meters of mesoscale snow line lowering implied by these case studies and multiyear observations is of large enough scale to have important implications for both hydrometeorological forecasting (e.g., White et al. 2002 ) and climate impacts associated with snowpack accumulation (e.g., Minder 2010 ). The ability of numerical models to capture and predict this mesoscale structure of the snow line is largely uncharacterized. A range of studies

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Hua Chen and Sundararaman G. Gopalakrishnan

as wind shear (e.g., Gray 1968 ; Merrill 1988 ; DeMaria and Kaplan 1994 ), moisture in the low to mid troposphere (e.g., Gray 1968 ), and inner-core processes ranging from convective to mesoscale (e.g., Schubert and Hack 1982 ; Willoughby et al. 1982 ; Kossin and Schubert 2001 ; Eastin et al. 2005a , b ) all have been known to influence the RI of TCs. All these factors interact in a nonlinear fashion, making the RI problem a complex forecast issue. Although there is currently much less

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James A. Ridout

1996 ; Lucas and Zipser 1996 ). In order to obtain insight into the potential for this type of control, in section 2 of the present study the impact on cloud growth of moisture variations of the nature of those associated with dry tongue episodes in the tropical Pacific is investigated by means of a series of quasi-cloud-resolving-scale numerical forecast experiments. These forecasts are carried out using a version of the Naval Research Laboratory's Coupled Ocean–Atmosphere Mesoscale Prediction

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Yuan Wang, Lifeng Zhang, Jun Peng, and Saisai Liu

different scales. These components can be systematically analyzed in spectral space through energy spectrum analysis and spectral energy budget diagnosis, thus providing a better understanding of the internal dynamics and energetics of TCs and the atmospheric mesoscale energy spectrum. In the study presented here, the issues discussed above are preliminarily explored by examining the mesoscale HKE spectra of an idealized TC simulated by the Weather Research and Forecasting (WRF) Model. The available

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