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R. J. Hung, T. Phan, D. C. Lin, R. E. Smith, R. R. Jayroe, and S. West

Abstract

Enhanced convection-initiated gravity waves associated with an isolated tornado in the absence of a squall line are investigated. Ray-tracing computations based on data observed on 29 May 1977 indicated that the wave sources were located in north-central Oklahoma. Comparison with a radar echo map during the time period when the waves were excited showed that the waves were generated by an isolated cloud with enhanced convection. GOES infrared digital data during the time period from wave excitation to tornado touchdown were analyzed. Results showed that the cloud where the gravity waves were excited was characterized by both a very low temperature at the cloud top and a very high expansion rate of the cold cloud-top area. The lead time between the excitation of the gravity waves and the tornado touchdown is discussed in conjunction with the growth rate of the clouds associated with the tornado.

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A. S. Dennis, Paul L. Smith, and James R. Miller Jr.

Abstract

No abstract available.

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S. Clark Rowland, Richard G. Layton, and David R. Smith

Abstract

Clean, single crystals of silver iodide have been found to serve as a very poor nucleating agent for ice. The controlled introduction of impurities on the crystal surface by means of photolytic decomposition has been shown to greatly increase its nucleating ability.

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S. R. Diehl, D. T. Smith, and M. Sydor

Abstract

A numerical solution to the three-dimensional advection-diffusion equation is developed and applied to the dispersion of power plant stack contaminants throughout the boundary layer. The method employs Lagrangian marker particles undergoing variable random-walk displacements to simulate a gradient-transfer process. The size of the particle displacements is directly related to the magnitude of the vertical and horizontal diffusivities which can be any functions of space and time. Using recent atmospheric turbulence data, empirical expressions for the eddy diffusivities are derived for the entire boundary layer in terms of common meteorologic parameters. Reasonable agreement is found between the numerical predictions and actual fly-ash data collected in the vicinity of a 500 MW coal-fired power station.

The random-walk technique has a number of distinct advantages over both finite-difference and particle-in-a-cell methods. It is mathematically simple, computationally fast, and requires only modest amounts of computer memory. The accuracy of the method is evaluated by comparison with a series solution of the two-dimensional diffusion equation appropriate to the surface layer.

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S. P. Ballard, B. W. Golding, and R. N. B. Smith

Abstract

A mesoscale model is used to simulate the diurnal evolution of sea fog off the northeast Scottish coast observed on 27 April 1984. It is shown that the accuracy of the early part of the forecast is very dependent on the specification of the initial conditions. If the initial description of the fog is sufficiently good the model can accurately erode it during the day and reform it in the following evening. The dependence of the accuracy of the forecasts on vertical resolution is also discussed.

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H. E. Ngodock, S. R. Smith, and G. A. Jacobs

Abstract

Realistic dynamic systems are often strongly nonlinear, particularly those for the ocean and atmosphere. Applying variational data assimilation to these systems requires a tangent linearization of the nonlinear dynamics about a background state for the cost function minimization. The tangent linearization may be accurate for limited time scales. Here it is proposed that linearized assimilation systems may be accurate if the assimilation time period is less than the tangent linear accuracy time limit. In this paper, the cycling representer method is used to test this assumption with the Lorenz attractor. The outer loops usually required to accommodate the linear assimilation for a nonlinear problem may be dropped beyond the early cycles once the solution (and forecast used as the background in the tangent linearization) is sufficiently accurate. The combination of cycling the representer method and limiting the number of outer loops significantly lowers the cost of the overall assimilation problem. In addition, this study shows that weak constraint assimilation corrects tangent linear model inaccuracies and allows extension of the limited assimilation period. Hence, the weak constraint outperforms the strong constraint method. Assimilated solution accuracy at the first cycle end is computed as a function of the initial condition error, model parameter perturbation magnitude, and outer loops. Results indicate that at least five outer loops are needed to achieve solution accuracy in the first cycle for the selected error range. In addition, this study clearly shows that one outer loop in the first cycle does not preclude accuracy convergence in future cycles.

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Thomas M. Smith, Samuel S. P. Shen, and Ralph R. Ferraro

Abstract

Extended precipitation forecasts, with leads of weeks to seasons, are valuable for planning water use and are produced by the U.S. National Weather Service. Forecast skill tends to be low and any skill improvement could be valuable. Here, methods are discussed for improving statistical precipitation forecasting over the contiguous United States. Monthly precipitation is forecast using predictors from the previous month. Testing shows that improvements are obtained from both improved statistical methods and from the use of satellite-based ocean-area precipitation predictors. The statistical superensemble method gives higher skill compared to traditional statistical forecasting. Ensemble statistical forecasting combines individual forecasts. The proposed superensemble is a weighted mean of many forecasts or of forecasts from different prediction systems and uses the forecast reliability estimate to define weights. The method is tested with different predictors to show its skill and how skill can be improved using additional predictors. Cross validation is used to evaluate the skill. Although predictions are strongly influenced by ENSO, in the superensemble other regions contribute more to the forecast skill. The superensemble optimally combines forecasts based on different predictor regions and predictor types. The contribution from multiple predictor regions improves skill and reduces the ENSO spring barrier. Adding satellite-based ocean-area precipitation predictors noticeably increases forecast skill. The resulting skill is comparable to that from dynamic-model forecasts, but the regions with best forecast skill may be different. This paper shows that the statistical superensemble forecasts may be complementary to dynamic forecasts and that combining them may further increase forecast skill.

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S. Pond, S. D. Smith, P. F. Hamblin, and R. W. Burling

Abstract

Measurements of the spectra of fluctuations in wind velocity over the sea sensed by three basically different instruments are described. One comparison shows good agreement between spectra from a thrust anemometer and cup anemometers. Another shows that greatly improved precision of spectra derived from a hot wire anemometer can be gained by calibrating the low frequency response against spectra from cup anemometers. The measurements confirm Kolmogoroff's prediction of the existence of a universal form of the spectrum at high wave numbers. The shape of a spectrum of temperature fluctuations agrees with that found by earlier workers.

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Craig S. Schwartz, Glen S. Romine, Kathryn R. Smith, and Morris L. Weisman

Abstract

Convection-permitting Weather Research and Forecasting (WRF) Model forecasts with 3-km horizontal grid spacing were produced for a 50-member ensemble over a domain spanning three-quarters of the contiguous United States between 25 May and 25 June 2012. Initial conditions for the 3-km forecasts were provided by a continuously cycling ensemble Kalman filter (EnKF) analysis–forecast system with 15-km horizontal grid length. The 3-km forecasts were evaluated using both probabilistic and deterministic techniques with a focus on hourly precipitation. All 3-km ensemble members overpredicted rainfall and there was insufficient forecast precipitation spread. However, the ensemble demonstrated skill at discriminating between both light and heavy rainfall events, as measured by the area under the relative operating characteristic curve. Subensembles composed of 20–30 members usually demonstrated comparable resolution, reliability, and skill as the full 50-member ensemble. On average, deterministic forecasts initialized from mean EnKF analyses were at least as or more skillful than forecasts initialized from individual ensemble members “closest” to the mean EnKF analyses, and “patched together” forecasts composed of members closest to the ensemble mean during each forecast interval were skillful but came with caveats. The collective results underscore the need to improve convection-permitting ensemble spread and have important implications for optimizing EnKF-initialized forecasts.

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V. E. Suomi, R. Fox, S. S. Limaye, and W. L. Smith

Abstract

A powerful facility for meteorological analysis called the Man Computer Interactive Data Access System (McIDAS) was designed and implemented in the early 1970's at the Space Science and Engineering Center of the University of Wisconsin-Madison. Hardware and software experience gained via extensive use of that facility and its derivatives have led to a newer implementation of McIDAS on a larger computer with significant enhancements to the supporting McIDAS software. McIDAS allows remote and local access to a wide range of data from satellites and conventional observations, time lapse displays of imagery data, overlaid graphics. and current and past meteorological data. Available software allows one to perform analysis of a wide range of digital images as well as temperature and moisture sounding data obtained from satellites. McIDAS can generate multicolor composites of conventional and satellite weather data, radar and forecast data in a wide variety of two- and three-dimensional displays as well as time lapse movies of these analyses. These and other capabilities are described in this paper.

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