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Jason C. Knievel
and
Richard H. Johnson

Abstract

The authors present a unique, scale-discriminating study of the environment-relative circulations within a mesoscale convective system (MCS) and mesoscale convective vortex (MCV). The MCS, a leading convective line and trailing stratiform region that became asymmetric, passed through the National Oceanic and Atmospheric Administration (NOAA) Profiler Network (NPN) in Kansas and Oklahoma on 1 August 1996. The MCV appeared in the MCS's stratiform region just prior to the system's mature stage and grew to a depth of over 12 km as the MCS dissipated. The MCV did not apparently survive to the next day.

A spatial bandpass filter was used to divide observed wind into a component that was predominantly synoptic background wind and a component that was predominantly a mesoscale perturbation on that background wind.

A mesoscale updraft, mesoscale downdraft, and divergent outflows in the lower and upper troposphere were evident after the synoptic background wind was removed, so these four circulations were internal and fundamental to the MCS.

The mesoscale perturbation in wind in the middle troposphere extended farther behind the MCS than ahead of it, consistent with analytic studies and numerical simulations of gravity waves generated by heat sources characteristic of MCSs with leading convective lines and trailing stratiform regions.

Deepening of the MCV appeared to be reflected in the vertical wind shear at the vortex's center: as the MCV strengthened, the mesoscale shear through its lower part decreased, perhaps as wind became more vortical at increasing altitudes. Mesoscale and synoptic vertical shears were of similar magnitude, so an average of environmental soundings outside an MCS probably does not accurately represent the shear that affects an MCV. This suggests the need to reevaluate how the kinematical settings of MCVs are diagnosed.

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Jason C. Knievel
and
Richard H. Johnson

Abstract

By animating enhanced coarse surface pressure observations of 12 1985 Preliminary Regional Experiment for Storm-Scale Operational Research Meteorology (PRE-STORM) mesoscale convective systems (MCSs) the authors exposed 92 transitory highs and lows living within virtually all of the systems’ mesohighs and wake lows. A quasi-Lagrangian (feature following, not material following) analysis of the pressure fields produced five primary results.

First, these transients, with magnitudes of a few millibars, horizontal dimensions of order 100 km, and average lifetimes of about 2 h, collectively composed spatial and temporal envelopes that contributed at least part of the total pressure field within mesohighs and wake lows. Transients did not apparently favor formation or dissipation in any location of the envelopes. Second, as the MCSs matured, the difference between each complex’s transitory highs’ mean pressure and transitory lows’ mean pressure increased in 78% of the conclusive cases. Apparently, one frequent role of MCSs is locally to magnify storm-scale pressure gradients. Third, transient paths reflect the frequent symmetric-to-asymmetric metamorphoses of the MCSs. Fourth, the temporal fluctuations of the numbers and apparent sizes of transients within a composite MCS partially support theories of MCS upscale evolution. Finally, the composite’s transient numbers and apparent sizes varied almost identically with time in a pattern that closely resembles the fluctuation of stratiform and convective volumetric rain rates of MCSs.

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Jason C. Knievel
and
Richard H. Johnson

Abstract

The authors employ data from the NOAA Wind Profiler Network to present a scale-discriminating vorticity budget for a mesoscale convective vortex (MCV) that was generated by a mesoscale convective system (MCS) in Oklahoma and Kansas on 1 August 1996.

A spatial bandpass filter was used to divide observed wind into mesoscale and synoptic components. Then the authors sought sources and sinks of vorticity in those two components over 9 h of the MCV's lifetime.

The vorticity budget reveals that both the mesoscale and synoptic winds supplied significant vorticity to the MCV. The vortex's origin could not be proved, but data weakly suggest that tilting may have been mostly responsible. Convergence of absolute vorticity by the mesoscale wind was the reason the MCV grew deeper and stronger as the MCS weakened. Finally, tilting of synoptic and mesoscale vorticity by gradients in mesoscale vertical motion was responsible for a secondary deepening of the MCV as the MCS dissipated.

The budget suggests that, if the MCV of 1 August 1996 is representative, completely realistic simulations of MCVs should include planetary vorticity and a plausible, three-dimensionally heterogeneous synoptic wind.

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Todd P. Lane
and
Jason C. Knievel

Abstract

Over the past decade, numerous numerical modeling studies have shown that deep convective clouds can produce gravity waves that induce a significant vertical flux of horizontal momentum. Such studies used models with horizontal grid spacings of O(1 km) and produced strong gravity waves with horizontal wavelengths greater than about 20 km. This paper is an examination of how simulated gravity waves and their momentum flux are sensitive to model resolution. It is shown that increases in horizontal resolution produce more power in waves with shorter horizontal wavelengths. This change in the gravity waves’ spectra influences their vertical propagation. In some cases, gravity waves that were vertically propagating in coarse simulations become vertically trapped in fine simulations, which strongly influences the vertical flux of horizontal momentum.

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Matthew D. Parker
and
Jason C. Knievel

Meteorologists and other weather enthusiasts sometimes lament that they live in weather holes—places that receive less exciting weather than do their surroundings . This belief seems to stem from countless hours spent gazing at thunderstorms on displays of radar reflectivity. To test objectively whether radar observations truly bear out this belief, the authors analyzed 6 yr of composite reflectivity from the Weather Surveillance Radar-1988 Doppler (WSR-88D) network. Statistics for 28 target cities, selected for their prominent meteorological communities, are compared with statistics for random points in the conterminous United States to see whether any of the targets is truly a weather hole or, perhaps, a hot spot—the counterpart to a hole. Holes and hot spots are defined by the frequency of convective echoes at a target relative to echoes in the surrounding region, and by the probability that convective echoes near a target were followed shortly by a convective echo at that target.

The data do, indeed, reveal mesoscale variability in occurrences of thunderstorms, as well as distinct signatures of storms' motion and the footprints of stormy regions at each target. However, although the data support the basic concept of convective weather holes and hot spots, only one of the meteorological targets fully met the authors' criteria for a hole and only one fully met their criteria for a hot spot. During the 6 yr studied, nearly all of the selected targets experienced convective storms about as often as their immediate surroundings did.

These results suggest that meteorologists are unnecessarily cranky about the frequency of storms in their hometowns. Meteorologists' belief that they live in weather holes may reveal the need to explore more deeply the statistical behavior of moist convection. The authors comment on some of the strengths and weaknesses of using composite reflectivity alone for that exploration and for determining weather holes and hot spots. Finally, the authors speculate that, with the proper quality control, statistics might serve in the near future as very powerful tools for probabilistic forecast guidance.

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Patrick Hawbecker
and
Jason C. Knievel

Abstract

Simulations of Chesapeake Bay breezes are performed with varying water surface temperature (WST) datasets and formulations for the diurnal cycle of WST to determine whether more accurate depictions of water surface temperature improve prediction of bay breezes. The accuracy of simulations is measured against observed WST, inland wind speed and temperature, and in simulations’ ability to detect bay breezes via a detection algorithm developed for numerical model output. Missing WST data are found to be problematic within the Weather Research and Forecasting (WRF) Model framework, especially when activating the prognostic equation for skin temperature, sst_skin. This is alleviated when filling all missing WST values with skin temperature values within the initial and boundary conditions. Performance of bay-breeze prediction is shown to be somewhat associated with the resolution of the WST dataset. Further, model performance in simulating WST as well as in simulating the Chesapeake Bay breeze is improved when diurnal fluctuations of WST are considered via the sst skin option. Prior to running simulations, model performance in simulating the bay breeze can be accurately predicted through the use of a simple formulation.

Open access
Patrick Hawbecker
and
Jason C. Knievel

Abstract

A novel algorithm is developed for detecting and classifying the Chesapeake Bay breeze and similar water-body breezes in output from mesoscale numerical weather prediction (NWP) models. To assess the generality of the new model-based detection algorithm (MBDA), it is tested on simulations from the Weather Research and Forecasting (WRF) Model and on analyses and forecasts from the High-Resolution Rapid Refresh (HRRR) model. The MBDA outperforms three observation-based detection algorithms (OBDAs) when applied to the same model output. In addition, by defining the onshore wind directions on the basis of model land-use data and not on the actual geography of the region of interest, performance of the OBDAs with model output can be improved. Although simulations by the WRF Model were used to develop the new MBDA, it performed best when applied to HRRR analyses. The generality of the MBDA is promising, and additional tuning of its parameters might improve it further.

Open access
Jason C. Knievel
,
George H. Bryan
, and
Joshua P. Hacker

Abstract

Diffusion that is implicit in the odd-ordered advection schemes in early versions of the Advanced Research core of the Weather Research and Forecasting (WRF) model is sometimes insufficient to remove noise from kinematical fields. The problem is worst when grid-relative wind speeds are low and when stratification is nearly neutral or unstable, such as in weakly forced daytime boundary layers, where noise can grow until it competes with the physical phenomena being simulated. One solution to this problem is an explicit, sixth-order numerical diffusion scheme that preserves the WRF model’s high effective resolution and uses a flux limiter to ensure monotonicity. The scheme, and how it was added to the WRF model, are explained. The scheme is then demonstrated in an idealized framework and in simulations of salt breezes and lake breezes in northwestern Utah.

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George H. Bryan
,
Jason C. Knievel
, and
Matthew D. Parker

Abstract

The authors evaluate whether the structure and intensity of simulated squall lines can be explained by “RKW theory,” which most specifically addresses how density currents evolve in sheared environments. In contrast to earlier studies, this study compares output from four numerical models, rather than from just one. All of the authors’ simulations support the qualitative application of RKW theory, whereby squall-line structure is primarily governed by two effects: the intensity of the squall line’s surface-based cold pool, and the low- to midlevel environmental vertical wind shear. The simulations using newly developed models generally support the theory’s quantitative application, whereby an optimal state for system structure also optimizes system intensity. However, there are significant systematic differences between the newer numerical models and the older model that was originally used to develop RKW theory. Two systematic differences are analyzed in detail, and causes for these differences are proposed.

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Jason C. Knievel
,
David A. Ahijevych
, and
Kevin W. Manning

Abstract

The authors demonstrate that much can be learned about the performance of a numerical weather prediction (NWP) model by examining the temporal modes of its simulated rainfall. Observations from the Weather Surveillance Radar-1988 Doppler (WSR-88D) network are used to evaluate the rainfall frequency, and its diurnal and semidiurnal modes, in simulations made by a preliminary version of the Weather Research and Forecasting (WRF) model for the conterminous United States during the summer of 2003.

Simulations and observations were broadly similar in the normalized amplitudes of their diurnal and semidiurnal modes, but not in the modes' phases, and not in overall frequency of rain. Simulated rain fell too early, and light rain was too frequent. The model also did not produce the distinct, nocturnal maximum in rainfall frequency that is integral to the hydrologic cycle of the Great Plains. The authors provide evidence that there were regional and phenomenological dependencies to the WRF model's performance.

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