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Downloaded 10/01/21 08:47 AM UTC 2062 JOURNAL of the ATMOSPHERIC SCIENCES VOLUME 57 Et Al 1JULY 2000 BRYAN AND FRITSCH 2061 Diabatically Driven Discrete Propagation of Surface Fronts: A Numerical Analysis GEORGE H. BRYAN AND J. MICHAEL FRITSCH Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania (Manuscript received 2 July 1998, in ®nal form 30 August 1999) ABSTRACT Discrete frontal propagation has been identi®ed as a process whereby a surface front discontinuously moves forward, without evidence of frontal passage across a mesoscale region. Numerical simulations are employed to examine the upper-level evolution of a discrete frontal propagation event and to explore the processes that were responsible for the discrete movement. Model results indicate that a frontal pressure trough was not able to penetrate through a deep surface-based layer of cool air created by a precipitating convective system several hundred kilometers in advance of the front. Meanwhile, a new low-level baroclinic zone formed well ahead of the front along the southern side of the cool layer. As the midlevel front moved continuously over the cool layer, a new low-level front developed in the new baroclinic zone and the original low-level front dissipated. At the surface, the simulated front did not pass through the cool layer. Frontogenesis terms reveal that the prefrontal circulation that becomes the new frontal circulation initially forms directly from diabatic frontogenesis. Daytime heating in the prefrontal boundary layer and cooling from thunderstorms combine to create a thermal gradient and a mesoscale pressure perturbation. Winds turn in response to the altered pressure ®eld and form a convergent boundary, resulting in kinematic frontogenesis. The boundary subsequently undergoes rapid intensi®cation. Sensitivity studies were conducted in which latent heating due to precipitation was withheld and the in¯uence of clouds on the radiation scheme was ignored. In a simulation with both of these effects withheld, the original front passes continuously through the region, that is, there is no discrete propagation. Thus, diabatic processes associated with a large complex of thunderstorms were necessary to induce the discrete frontal propagation in this case. This conclusion contrasts with previous studies, where fronts were observed to propagate discretely in dry environments. 1. Introduction disrupted by the deep, stable cold dome created by the convection, the midlevel front propagated continuously. Discrete surface frontal propagation is de®ned as dis- This paper presents a numerical simulation of the case continuous movement of a front at the surface. Bryan studied by Bryan and Fritsch (2000, hereafter referred and Fritsch (2000) examined a case of discrete frontal to as BF). A number of aspects of this case warrant propagation in a convective environment. In their case, further study. In particular, calculations of surface fron- a prefrontal convective system generated a large, deep togenetical tendencies in BF suggest that diabatic pro- cold dome just ahead of an approaching cold front. The cesses played an important role in initiating the pre- low-level cold front was observed to stall and undergo frontal trough. Output from a numerical simulation can frontolysis as it encountered the cold dome. Meanwhile, be used to con®rm or refute this suggestion. Further- a trough formed on the downstream side of the cold more, it remains to be seen whether the diabatic pro- dome and underwent rapid frontogenesis. Eventually, cesses were completely necessary in inducing the dis- the original surface frontal trough disappeared, the me- crete frontal movement in this case. In a study of discrete soscale wind ®eld adjusted to the new pressure pattern, frontal propagation in stable winter conditions, Charney and the prefrontal trough replaced the original front as and Fritsch (1999) found that cold fronts can propagate the dominant frontal feature. Their analysis suggests discretely without the need for precipitation processes. that, although the low-level frontal properties (e.g., pres- On the other hand, there is evidence that diabatic pro- sure trough, wind shift, and temperature gradient) were cesses may be important in initiating frontogenesis by creating mass ®eld changes and, eventually, wind ®eld changes as the system adjusts toward geostrophic bal- ance. The mesoscale wind shift lines and troughs may Corresponding author address: George H. Bryan, 503 Walker Building, University Park, PA 16802. then undergo frontogenesis. For example, several stud- E-mail: [email protected] ies (e.g., Purdom 1982; Pielke and Segal 1986; Segal q 2000 American Meteorological Society Unauthenticated | Downloaded 10/01/21 08:47 AM UTC 2062 JOURNAL OF THE ATMOSPHERIC SCIENCES VOLUME 57 et al. 1986) note that gradients in cloud cover can induce mesoscale circulations similar to sea and land breezes. Another diabatic process that can generate mesoscale boundaries is precipitation. Doswell (1982) showed that thunderstorm complexes can form intense out¯ow boundaries with properties similar to cold fronts. Ryan et al. (1989) presented a case where precipitation gen- erated a new baroclinic zone several hundred kilometers in advance of an approaching cold front. This paper examines the 5±6 September 1994 discrete frontal propagation event using a mesoscale-resolution simulation. The model output complements the obser- vational analysis and adds insight that cannot be drawn from standard analyses. The role of physical processes are explored by examining output from the various mod- el equations. Section 2 describes the numerical model con®guration. Section 3 examines the simulated evo- FIG. 1. Con®guration of model domains. lution of the event, and compares the results with ob- servations. Section 4 presents the vertical structure and evolution of discrete frontal propagation. Analysis of the scheme developed by Kain and Fritsch (1990). Of frontogenesis terms and quanti®cation of diabatic pro- particular value to this study, the Kain±Fritsch scheme cesses are presented in section 5. The results of several includes parameterized downdrafts necessary for sim- sensitivity experiments using the numerical model are ulating the convectively modi®ed low levels. included in section 6. A conceptual model for discrete The model initial conditions are derived from ®rst- frontal propagation is presented in section 7, followed guess ®elds supplied by the National Centers for En- by conclusions in section 8. vironmental Prediction that are then objectively en- hanced with observed surface and upper-air data (Man- ning and Haagenson 1992). At the beginning of the 2. Model design forecast, the four-dimensional data assimilation tech- The ®fth-generation Pennsylvania State University± nique of Stauffer and Seaman (1994) is utilized to bring National Center for Atmospheric Research Mesoscale the dynamic and thermodynamic ®elds into closer agree- Model (MM5) is utilized for this investigation (Dudhia ment with the observations while still satisfying the gov- 1993; Grell et al. 1994). MM5 is a nonhydrostatic model erning hydrodynamical system. with prognostic equations for temperature, horizontal, The numerical simulation of the 5±6 September 1994 and vertical components of motion, pressure, water va- discrete frontal propagation event was initialized at 0000 por mixing ratio, cloud water mixing ratio, and rain- UTC 5 September 1994 (0000/5) and run for 36 h, end- water mixing ratio. Twenty-®ve sigma (s) levels are ing at 1200/6. For the ®rst 12 h, four-dimensional data used in this study with 11 levels below 700 hPa where assimilation was applied. This simulation is hereafter boundary layer processes are important. Two model do- referred to as the control simulation (CTL). mains are used: a coarse mesh of 61 3 73 grid points For cross-section analyses of model output, averages with 60-km grid spacing, and a two-way interactive of several cross sections oriented perpendicular to the nested ®ne mesh domain of 64 3 76 grid points with fronts are constructed. The averages eliminate high-fre- 20 km grid spacing (Fig. 1). The location of the nested quency perturbations (such as those associated with ®ne mesh domain was chosen such that information moist parameterized convection at individual grid ele- from the outer boundaries of domain 1 would not be ments) but still retain the mesoscale structure and ver- advected into domain 2 during the model simulation. tical circulations associated with the fronts. The meth- This is important for dry run experiments since the odology of the cross section averaging is described in boundary conditions for domain 1 are observed con- the appendix. ditions that include precipitation processes. Model physics used in these simulations include the 3. Surface and upper-air evolution explicit bulk precipitation scheme with simple ice phys- ics based on the studies of Lin et al. (1983), Rutledge Despite minor differences in the timing and magni- and Hobbs (1983), Hsie et al. (1984), and Dudhia tude of features, the model is able to capture the basic (1989). The planetary boundary layer (PBL) parame- sequence of events in this case (Fig. 2). At the surface, terization is based on the work of Blackadar (1976, a prefrontal mesohigh and trough form at about the cor- 1979) and adapted for MM5 by Zhang and Anthes rect time and location. Over time, the surface trough (1982) and Zhang and Fritsch (1986). The subgrid-scale intensi®es and moves southward while the original front convective parameterization used in the simulation is slows,
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