Quasi-Monte Carlo, Monte Carlo, and regularized gradient optimization methods for source characterization of atmospheric releases

An inversion technique based on MC/QMC search and regularized gradient optimization was developed to solve the atmospheric source characterization problem. The Gaussian Plume Model was adopted as the forward operator and QMC/MC search was implemented in order to find good starting points for the gradient optimization. This approach was validated on the Copenhagen Tracer Experiments. The QMC approach with the utilization of clasical and scrambled Halton, Hammersley and Sobol points was shown to be 10-100 times more efficient than the Mersenne Twister Monte Carlo generator. Further experiments are needed for different data sets. Computational complexity analysis needs to be carried out

Investigation of Reynolds Stresses in a 3D Idealized Urban Area Using Large Eddy Simulation

High resolution, large eddy simulation (LES) of neutral flow through an array of cubes has been conducted with periodic boundary conditions in lateral and longitudinal directions. In this paper, we first describe the model formulation and validate the simulation by comparing the mean flow and turbulence statistics with wind-tunnel experimental data from a cube array of buildings. The LES model is then used to investigate the physical mechanisms that lead to the low turbulent stresses that have been reported in the lower half of the urban canopy layer. To do this, the urban boundary layer is conceptually broken down into three distinct regions: (a) the urban roughness sub-layer, (b) street channels (roads with axis aligned with mean wind direction aloft) and (c) street canyons (roads with axis normal to the mean wind direction aloft). The distribution of the Reynolds stresses differ significantly amongst these regions and we hypothesize that the low stresses in the lower half of the canopy can been attributed to the temporary unstable of the above mentioned regions at different periods of time. In a complex urban area, these regions can be observed intermittently at the same physical location, thus, stresses with opposite signs have the potential to cancel each other and on average yield a low magnitude. In this paper, mean turbulence statistics and spectra from high resolution LES have been analyzed for these scenarios and the results have been interpreted within the context of the proposed idealized flow regions

Surface representation impacts on turbulent heat fluxes in the Weather Research and Forecasting (WRF) model (v.4.1.3)

The water and energy transfers at the interface between the Earth's surface and the atmosphere should be correctly simulated in numerical weather and climate models. This implies the need for a realistic and accurate representation of land cover (LC), including appropriate parameters for each vegetation type. In some cases, the lack of information and crude representation of the surface lead to errors in the simulation of soil and atmospheric variables. This work investigates the ability of the Weather Research and Forecasting (WRF) model to simulate surface heat fluxes in a heterogeneous area of southern France using several possibilities for the surface representation. In the control experiments, we used the default LC database in WRF, which differed significantly from the actual LC. In addition, sub-grid variability was not taken into account since the model uses, by default, only the surface information from the dominant LC category in each pixel (dominant approach). To improve this surface simplification, we designed three new interconnected numerical experiments with three widely used land surface models (LSMs) in WRF. The first one consisted of using a more realistic and higher-resolution LC dataset over the area of analysis. The second experiment aimed at investigating the effect of using a mosaic approach; 30 m sub-grid surface information was used to calculate the final grid fluxes based on weighted averages from values obtained for each LC category. Finally, in the third experiment, we increased the model stomatal conductance for conifer forests due to the large flux errors associated with this vegetation type in some LSMs. The simulations were evaluated with gridded area-averaged fluxes calculated from five tower measurements obtained during the Boundary-Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign. The results from the experiments differed depending on the LSM and displayed a high dependency of the simulated fluxes on the specific LC definition within the grid cell, an effect that was enhanced with the dominant approach. The simulation of the fluxes improved using the more realistic LC dataset except for the LSMs that included extreme surface parameters for coniferous forest. The mosaic approach produced fluxes more similar to reality and served to particularly improve the latent heat flux simulation of each grid cell. Therefore, our findings stress the need to include an accurate surface representation in the model, including soil and vegetation sub-grid information with updated surface parameters for some vegetation types, as well as seasonal and man-made changes. This will improve the modelled heat fluxes and ultimately yield more realistic atmospheric processes in the model

THE MATERHORN: Unraveling the Intricacies of Mountain Weather

Emerging application areas such as air pollution in megacities, wind energy, urban security, and operation of unmanned aerial vehicles have intensified scientific and societal interest in mountain meteorology. To address scientific needs and help improve the prediction of mountain weather, the U.S. Department of Defense has funded a research effort—the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program—that draws the expertise of a multidisciplinary, multi-institutional, and multinational group of researchers. The program has four principal thrusts, encompassing modeling, experimental, technology, and parameterization components, directed at diagnosing model deficiencies and critical knowledge gaps, conducting experimental studies, and developing tools for model improvements. The access to the Granite Mountain Atmospheric Sciences Testbed of the U.S. Army Dugway Proving Ground, as well as to a suite of conventional and novel high-end airborne and surface measurement platforms, has provided an unprecedented opportunity to investigate phenomena of time scales from a few seconds to a few days, covering spatial extents of tens of kilometers down to millimeters. This article provides an overview of the MATERHORN and a glimpse at its initial findings. Orographic forcing creates a multitude of time-dependent submesoscale phenomena that contribute to the variability of mountain weather at mesoscale. The nexus of predictions by mesoscale model ensembles and observations are described, identifying opportunities for further improvements in mountain weather forecasting

TEMPERATURE MEASUREMENTS COLLECTED FROM AN INSTRUMENTED VAN IN SALT LAKE CITY, UTAH AS PART OF URBAN 2000

Measurements of temperature and position were collected during the night from an instrumented van on routes through Salt Lake City and the rural outskirts. The measurements were taken as part of the Department of Energy Chemical and Biological National Security Program URBAN 2 Field Experiment conducted in October 2000 (Shinn et al., 2000 and Allwine et al., 2001a). The instrumented van was driven over three primary routes, two including downtown, residential, and ''rural'' areas and a third that went by a line of permanently fixed temperature probes (Allwine et al., 2001b) for cross-checking purposes. Each route took from 45 to 60 minutes to complete. Based on four nights of data, initial analyses indicate that there was a temperature difference of 2-5 C between the urban core and nearby ''rural'' areas. Analyses also suggest that there were significant fine scale temperature differences over distances of tens of meters within the city and in the nearby rural areas. The temperature measurements that were collected are intended to supplement the meteorological measurements taken during the URBAN2000 Field Experiment, to assess the importance of the urban heat island phenomenon in Salt Lake City, and to test the urban canopy parameterizations that have been developed for regional scale meteorological codes as part of the DOE CBNP program

Evaluation of a Fast-Response Urban Wind Model - Comparison to Single-Building Wind Tunnel Data

Prediction of the 3-dimensional flow field around buildings and other obstacles is important for a number of applications, including urban air quality studies, the tracking of plumes from accidental releases of toxic air contaminants, indoor/outdoor air pollution problems, and thermal comfort assessments. Various types of computational fluid dynamics (CFD) models have been used for determining the flow fields around buildings (e.g., Reisner et al., 1998; Eichhorn et al., 1988). Comparisons to measurements show that these models work reasonably well for the most part (e.g., Ehrhard et al., 2 ; Johnson and Hunter, 1998; Murakami, 1997). However, CFD models are computationally intensive and for some applications turn-around time is of the essence. For example, planning and assessment studies in which hundreds of cases must be analyzed or emergency response scenarios in which plume transport must be computed quickly. Several fast-response dispersion models of varying levels of fidelity have been developed to explicitly account for the effects of a single building or groups of buildings (e.g., UDM - Hall et al. (2000), NRC-Ramsdell and Fosmire (1995), CBP-3 - Yamartino and Wiegand (1986), APRAC - Daerdt et al. (1973)). Although a few of these models include the Hotchkiss and Harlow (1973) analytical solution for potential flow in a notch to describe the velocity field within an urban canyon, in general, these models do not explicitly compute the velocity field around groups of buildings. The EPA PRIME model (Schulman et al., 2000) has been empirically derived to provide streamlines around a single isolated building

Flux Richardson number measurements in stable atmospheric shear flows

The flux Richardson number R, (also known as the mixing efficiency) for the stably stratified atmospheric boundary layer is investigated as a function of the gradient Richardson number Ri(g), using data taken during two field studies: the Vertical Transport and Mixing Experiment (VTMX) in Salt Lake City, Utah (October 2000), and a long-term rural field data set from Technical Area 6 (TA-6) at Los Alamos National Laboratory, New Mexico. The results show the existence of a maximum R(f) (0.4-0.5) at a gradient Richardson number of approximately unity. These large-Reynolds-number results agree well with recent laboratory stratified shear layer measurements, but are at odds with some commonly used R(f) parameterizations, particularly under high-Ri(g) conditions. The observed variations in buoyancy flux and turbulent kinetic energy production are consistent with the concept of global intermittency of the atmospheric stable boundary layer