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The Impact of Hail Size on Simulated Supercell Storms

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The Impact of Hail Size on Simulated Supercell Storms 1596 JOURNAL OF THE ATMOSPHERIC SCIENCES VOLUME 61 The Impact of Hail Size on Simulated Supercell Storms SUSAN C. VAN DEN HEEVER AND WILLIAM R. COTTON Colorado State University, Fort Collins, Colorado (Manuscript received 14 November 2002, in ®nal form 15 January 2004) ABSTRACT Variations in storm microstructure due to updraft strength, liquid water content, and the presence of dry layers, wind shear, and cloud nucleating aerosol concentrations are likely to lead to changes in hail sizes within deep convective storms. The focus of this paper is to determine how the overall dynamics and microphysical structure of deep convective storms are affected if hail sizes are somehow altered in a storm environment that is otherwise the same. The sensitivity of simulated supercell storms to hail size distributions is investigated by systematically varying the mean hail diameter from 3 mm to 1 cm using the Regional Atmospheric Modeling System (RAMS) model. Increasing the mean hail diameter results in a hail size distribution in which the number concentration of smaller hailstones is decreased, while that of the larger hailstones is increased. This shift in the hail size distribution as a result of increasing the mean hail diameter leads to an increase in the mean terminal fall speed of the hail species and to reduced melting and evaporation rates. The sensitivity simulations demonstrate that the low-level downdrafts are stronger, the cold pools are deeper and more intense, the left-moving updraft is shorter-lived, the right-moving storm is stronger but not as steady, and the low-level vertical vorticity is greater in the cases with smaller hail stones. The maximum hail mixing ratios are greater in the larger hail simulations, but they are located higher in the storm and farther away from the updraft core in the smaller hail runs. Changes in the hail size distribution also appear to in¯uence the type of supercell that develops. 1. Introduction to how the way in which the ice phase is parameterized affects the characteristics of simulated deep convective It may be expected that variations in storm micro- storms, with the possible exception of Meyers et al. structure due to updraft strength, liquid water content, (1997) and Gilmore et al. (2004). the presence of dry layers, wind shear, and cloud nu- Selecting which hydrometeor species to represent and cleating aerosol concentrations [cloud condensation nu- determining an appropriate size distribution for each clei (CCN), giant CCN (GCCN), and ice-forming nuclei (IFN)] will lead to changes in hail sizes within deep species are examples of some of the options that need convective storms. Changes in hail sizes may in turn to be considered when using a single-moment bulk mi- in¯uence the dynamical and microphysical character- crophysical parameterization scheme, a type of micro- istics of these storms. The focus of this paper is to physical scheme often used in mesoscale and cloud determine how the overall dynamics and microphysical models. Ice parameters also need to be set for a broad structure of deep convective storms are affected if the range of storm systems if the model is to be used op- hail sizes are somehow altered in a storm environment erationally where ``tweaking'' of the parameters is not that is otherwise the same. an option. Determining suitable values for microphys- Experiments designed to investigate the sensitivity to ical parameters is made dif®cult by the lack of in situ including the ice phase in mesoscale models have dem- cloud data and the fact that the values can vary signif- onstrated signi®cant impacts on both the dynamic and icantly from one storm system to another. As a result precipitation characteristics of simulated deep convec- of these dif®culties, microphysical parameter values are tive storms (e.g., Chen and Cotton 1988; Jewett et al. often chosen somewhat arbitrarily. 1990; Johnson et al. 1993; Tartaglione et al. 1996; The use of a single-moment microphysical scheme Schlesinger 1999; Gilmore et al. 2004). While the im- necessarily results in certain characteristics of the hy- pacts of including the ice phase have been investigated drometeor size distribution having to be ®xed through- to some degree, very little attention has been given as out the model domain for the duration of the simulation. The mean hydrometeor diameter may be held ®xed while the number concentration intercept is diagnosed, Corresponding author address: Susan C. van den Heever, Dept. or the intercept parameter may be speci®ed and the mean of Atmospheric Sciences, Colorado State University, Fort Collins, CO 80523-1371. hydrometeor diameter is then diagnosed. However, the E-mail: [email protected] use of a single-moment scheme, unlike the more so- q 2004 American Meteorological Society 1JULY 2004 VAN DEN HEEVER AND COTTON 1597 phisticated two-moment bulk microphysical schemes, TABLE 1. RAMS model con®guration and options. does allow for the direct control of the hail size, and Model aspect Setting hence for the investigation of the sensitivity of storm Grid Arakawa C grid dynamics to these hail size variations. Single grid Given the importance of understanding how changes Horizontal grid: Dx 5Dy 5 1km in hailstone size and the microphysical structure of 140 points 3 170 clouds may alter hailstorm dynamics, the apparent sig- points ni®cance of including the ice phase in numerical sim- Vertical grid: Dz variable 35 vertical levels ulations of deep convective storms, and the dif®culty Model top: ;23 km in determining appropriate values of various ice param- Nine levels below 1 km AGL eters, it is essential that we understand the sensitivity Initialization Horizontally homogeneous of simulated storm characteristics to variations in hail- Time step 5s Simulation duration 2h stone size distribution characteristics. The purpose of Microphysics scheme Single-moment bulk microphysics the research presented in this paper is therefore to de- Water species: vapor, cloud water, termine the impact that changes in the hail size distri- rain, pristine ice, snow, aggre- bution may have on simulated deep convective storms. gates, graupel, and hail all acti- In particular, the following two questions will be ad- vated Convective initiation Warm, moist bubble dressed. Boundary conditions Radiative lateral boundary (Klemp and Wilhelmson 1978a) 1) Does varying the mean hail diameter have an impact Rigid lid at model top with Ray- on the basic dynamic, thermodynamic, and precip- leigh friction layer itation characteristics of simulated supercell storms? Free-slip lower boundary 2) If so, what are the impacts and why do they occur? Turbulence scheme Smagorinsky (1963) deformation K To address these questions, the mean hail diameter was systematically varied, and the spectrum of simulated supercell storm characteristics that developed was in- applied at the lateral boundaries (Klemp and Wilhelm- vestigated. It will be shown in this paper that storm son 1978a), a Rayleigh friction layer was extended from longevity, the cold pool dynamics, the amount and type approximately 17.5 km AGL to the model top to absorb of precipitation, the distribution of precipitation with gravity waves, and the lower boundary was free slip. A respect to the updraft, the low-level vertical vorticity, single-moment bulk microphysical scheme (Walko et al. and the type of storm that develops are all sensitive to 1995) was used, and all the water species were activated. variations in the mean hail diameter. The details of the model con®guration are summarized The mesoscale model used to conduct the sensitivity in Table 1. experiments, several microphysical parameterization as- The model domain was initialized horizontally ho- pects, and the experiment design are described in section mogeneously using a sounding that is typical of severe 2. The results of varying the mean hail diameter will storm days over Oklahoma (Fig. 1). A similar sounding be presented in section 3. A discussion of the impli- was used by Grasso (2000). The sounding is character- cations of these results is included in section 4. ized by 3130 J of convective available potential energy (CAPE) and veering winds from the surface to 2 km AGL. The lifting condensation level occurs at approx- 2. Model and experiment setup imately 840 mb. Convection was initiated using a warm (3-K temperature perturbation), moist (20% moisture a. Model con®guration perturbation) rectangular bubble that was 10 km by 10 The Regional Atmospheric Modeling System km (x 5 30 to 40, y 5 30 to 40) in the horizontal (the (RAMS; Pielke et al. 1992; Cotton et al. 2003) devel- position of which is indicated on Fig. 3), and which oped at Colorado State University (CSU) was used to extended from the surface to approximately 2.5 km achieve our stated goal. A single model grid (140 3 AGL. All the simulations were run for at least 2 h. 170 3 35) with grid spacing of 1 km in the horizontal and variable spacing in the vertical was employed. The b. Microphysical parameterization considerations and lowest vertical grid spacing was 100 m, and this was experiment design stretched using a stretch ratio of 1.1 until the vertical grid spacing reached 2000 m, above which it was kept All the available hydrometeor species (cloud water, constant. The model top extended beyond 23 km above rain, pristine ice, snow, aggregates, graupel, and hail) ground level (AGL), and there were nine model levels of the single-moment bulk microphysical scheme in within the ®rst kilometer AGL. These grid spacings are RAMS were activated for the sensitivity tests conducted suf®cient to resolve storm-scale features and processes, here (Walko et al. 1995). The Marshall±Palmer (expo- but are insuf®cient to simulate tornadogenesis. The long nential) size distribution was used for all species (Mar- time step was 5 s.
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