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1.
In order to estimate the impacts of buildings on air pollution dispersion, numerical simulations are performed over an idealized urban area, modelled as regular rows of large rectangular obstacles. The simulations are evaluated with the results of the Mock Urban Setting Test (MUST), which is a near full-scale experiment conducted in Utah’s West Desert area: it consists of releases of a neutral gas in a field of regularly spaced shipping containers. The numerical simulations are performed with the model Mercure_Saturne, which is a three-dimensional computational fluid dynamics code adapted to atmospheric flow and dispersion simulations. It resolves complex geometries and uses, in this study, a k–∈ closure for the turbulence model. Sensitivity studies focus on how to prescribe the inflow conditions for turbulent kinetic energy. Furthermore, different sets of coefficients available in the literature for the k–∈ closure model are tested. Twenty MUST trials with different meteorological conditions are simulated and detailed analyses are performed for both the dynamical variables and average concentration. Our results show overall good agreement according to statistical comparison parameters, with a fraction of predictions for average concentration within a factor of two of observations of 67.1%. The set of simulations offers several inflow wind directions and allows us to emphasize the impact of elongated buildings, which create a deflection of the plume centerline relative to the upstream wind direction.  相似文献   

2.
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3.
The Gaussian distribution is a good approximation for transient (instantaneously released) puff concentration distributions within a short period of time after release. Artificial neural network (ANN) models for puff dispersion coefficients were developed, based on observations from field experiments covering a wide range of meteorological conditions (in March, May, August and November). Their average predictions were in very good agreement with measurements, having high correlation coefficients (r > 0.99). A non-linear multi-variable regression model for dispersion coefficients was also developed, under the assumption that puff dispersion coefficients increase with time, and follow power laws. Both ANN-based and multi-regression non-linear models were able to use easily measured atmospheric parameters directly, without the necessity of predefining the Pasquill stability category. Predictions of ANN-based and multi-regression-based Gaussian puff models were compared with those of Gaussian puff models using Slade’s dispersion coefficients and COMBIC, a sophisticated model based on Gaussian distributions. Predictions from our two new models showed better agreement with concentration measurements than the other Gaussian puff models, by having a much higher fraction within a factor of two of measured values, and lower normalized mean square errors.  相似文献   

4.
A set of tracer experiments designed to compare two concentration fluctuation detectors and measure fluctuation statistics at high frequencies is described. A detector which has been used in several previous fluctuation experiments (the TIP photoionisation detector manufactured by Photovac of Canada) is compared with another with a much higher frequency response (the flame ionisation detector — FID — made by Cambustion of the UK). Good agreement is found and results show that the signal optimization system used in previous work with the TIP provides an accurate enhancement of the instrument output, thus improving confidence in the results of previous papers. They also confirm that the TIP detector is able to resolve most of the concentration variance in most situations of interest, but not at very short range. Measurements of the high frequency end of the fluctuation spectrum using the FID show inertial-convective subrange behaviour at frequencies not resolved by the TIP, supporting earlier work. Fluctuation spectra measured very close to the source are also shown to have a characteristic +2/3 power law behaviour (when nSc (n) is plotted against n) at lower frequencies, in agreement with theoretical predictions.  相似文献   

5.
A comprehensive model for the prediction of concentration fluctuations in plumes dispersing in the complex and highly disturbed wind flows in an urban environment is formulated. The mean flow and turbulence fields in the urban area are obtained using a Reynolds-averaged Navier-Stokes (RANS) flow model, while the standard k-ϵ turbulence model (k is the turbulence kinetic energy and ϵ is the viscous dissipation rate) is used to close the model. The RANS model provides a specification of the velocity statistics of the highly disturbed wind flow in the urban area, required for the solution of the transport equations for the mean concentration and concentration variance (both of which are formulated in the Eulerian framework). A physically-based formulation for the scalar dissipation time scale t d , required for the closure of the transport equation for , is presented. This formulation relates t d to an inner time scale corresponding to “internal” concentration fluctuation associated with relative dispersion, rather than an outer time scale associated with the entire portion of the fluctuation spectrum. The two lowest-order moments of concentration ( and ) are used to determine the parameters of a pre-chosen functional form for the concentration probability density function (clipped-gamma distribution). Results of detailed comparisons between a water-channel experiment of flow and dispersion in an idealized obstacle array and the model predictions for mean flow, turbulence kinetic energy, mean concentration, concentration variance, and concentration probability density function are presented.  相似文献   

6.
Direct eddy-covariance measurements of aerosol number fluxes obtained during the 2007 CHATS field experiment in Dixon, California, USA are compared with relaxed eddy accumulation simulations using temperature and water vapour concentration as proxy scalars. After a brief discussion of the limited time response of the aerosol measurement, the applicability of temperature and water vapour concentration as proxy scalars for aerosol number concentration is investigated by evaluating scalar and spectral correlation coefficients as simple measures of scalar similarity. In addition, the proportionality factor b, which compensates for the use of a constant sampling flow in relaxed eddy accumulation, is derived from the time series of aerosol number, temperature and water vapour, and its variability is analyzed. The reduction of the b factor due to application of a deadband, i.e. the rejection of data when the vertical wind speed is close to zero, is evaluated for all three studied scalars, and compared with published functional relationships. In this study, using temperature or water vapour as proxy scalars for aerosol number shows no advantage over the use of a constant b factor. Thus, it is suggested to apply a deadband H REA  = w′/σ w  = 0.6 to 0.8 (where w′ is the vertical velocity fluctuation and σ w is its standard deviation), to use a theoretical b factor based on a parameterization that includes a stability dependence, and to calculate the deadband effect according to a derived relation for aerosol relaxed eddy accumulation.  相似文献   

7.
Observations of 1-s average concentration fluctuations during two trials of a U.S. Army diffusion experiment are presented and compared with model predictions based on an exponential probability density function (pdf). The source is near the surface and concentration monitors are on lines about 30 to 100 m downwind of the source. The observed ratio of the standard deviation to the mean of the concentration fluctuations is about 1.3 on the mean plume axis and 4 to 5 on the mean plume edges. Plume intermittency (fraction of non-zero readings) is about 50%; on the mean plume axis and 10%; on the mean plume edges. A meandering plume model is combined with an exponential pdf assumption to produce predictions of the intermittency and the standard deviation of the concentration fluctuations that are within 20%; of the observations.  相似文献   

8.
Eight short-range, open-terrain SF6 tracer tests in low wind speeds were conducted during Phase 2 of Project Sagebrush using continuous releases. Four tests were made during very unstable conditions in July and August 2016, and four during very stable conditions in October 2016. All tests featured 10-min averaging and 1-Hz sampling of tracer concentrations together with an extensive suite of meteorological measurements. We find that the uncertainty in well-mixed daytime measurements of tracer concentrations, using the absolute value of the relative percentage difference in collocated duplicate samplers, approaches a downwind limit of about 7–8%. Concentration variability in collocated sampling, due to stochastic factors and independent of measurement uncertainty, increases the total observational uncertainty closer to the source from about 20% (daytime) to 40% (very stable conditions). Longer averaging periods moderately reduce the concentration variability. The data indicate that the large increase in concentration variability is linked with the suppression of turbulent mixing, small eddy length scales, and meandering in very stable conditions. These results should be considered when comparing observations with model predictions in evaluations.  相似文献   

9.
We examine the performance of two steady-state models, a numerical solution of the advection-diffusion equation and the Gaussian plume-model-based AERMOD (the American Meteorological Society/Environmental Protection Agency Regulatory Model), to predict dispersion for surface releases under low wind-speed conditions. A comparison of model estimates with observations from two tracer studies, the Prairie Grass experiment and the Idaho Falls experiment indicates that about 50% of the concentration estimates are within a factor of two of the observations, but the scatter is large: the 95% confidence interval of the ratio of the observed to estimated concentrations is about 4. The model based on the numerical solution of the diffusion equation in combination with the model of Eckman (1994, Atmos Environ 28:265–272) for horizontal spread performs better than AERMOD in explaining the observations. Accounting for meandering of the wind reduces some of the overestimation of concentrations at low wind speeds. The results deteriorate when routine one-level observations are used to construct model inputs. An empirical modification to the similarity estimate of the surface friction velocity reduces the underestimation at low wind speeds.  相似文献   

10.
Concentration fluctuation data from surface-layer released smokeplumes have been investigated with the purpose of finding suitable scaling parametersfor the corresponding two-particle, relative diffusion process.Dispersion properties have been measured at downwind ranges between 0.1 and 1 km from a continuous, neutrally buoyant ground level source. A combinationof SF6 and chemical smoke (aerosols) was used as tracer. Instantaneous crosswind concentration profiles of high temporal (up to 55 Hz) and spatialresolution (down to 0.375 m) were obtained from aerosol-backscatter Lidar detectionin combination with simultaneous gas chromatograph (SF6) reference measurements. The database includes detailed crosswind concentration fluctuation measurements. Each experiment, typically of 1/2-hour duration, containsplume mean and variance concentration profiles, intermittency profiles andexceedence and duration statistics. The diffusion experiments were accompanied by detailed in-situ micrometeorological mean and turbulence measurements. In this paper, a new distance-neighbour function for surface-released smoke plumes is proposed, accompanied by experimental evidence in its support. The new distance-neighbour function is found to scale with the surface-layer friction velocity,and not with the inertial subrange dissipation rate, over the range of distance-neighbour separations considered.  相似文献   

11.
Inverse-dispersion calculations can be used to infer atmospheric emission rates through a combination of downwind gas concentrations and dispersion model predictions. With multiple concentration sensors downwind of a compound source (whose component positions are known) it is possible to calculate the component emissions. With this in mind, a field experiment was conducted to examine the feasibility of such multi-source inferences, using four synthetic area sources and eight concentration sensors arranged in different configurations. Multi-source problems tend to be mathematically ill-conditioned, as expressed by the condition number κ. In our most successful configuration (average κ = 4.2) the total emissions from all sources were deduced to within 10% on average, while component emissions were deduced to within 50%. In our least successful configuration (average κ = 91) the total emissions were calculated to within only 50%, and component calculations were highly inaccurate. Our study indicates that the most accurate multi-source inferences will occur if each sensor is influenced by only a single source. A “progressive” layout is the next best: one sensor is positioned to “see” only one source, the next sensor is placed to see the first source and another, a third sensor is placed to see the previous two plus a third, and so on. When it is not possible to isolate any sources κ is large and the accuracy of a multi-source inference is doubtful.  相似文献   

12.
Adaptive observations for hurricane prediction   总被引：1，自引：1，他引：0  
Summary This study proposes a method that can be used to provide guidelines to aircraft reconnaissance for hurricane observations. The method combines numerical weather prediction (NWP) model with a statistical approach to target adaptive observations over areas where the hurricane predictions are very sensitive to the initial analysis for the NWP-model. A single model experiment is performed using regular initial analysis, while 50 other ensemble runs are performed from randomly perturbed initial states. Under the perfect model assumption, the single model experiment serves as a true state. The method first computes the forecast error variances at a certain verification time, e.g. hour 48, and then locates the maximum centers of variances. After the locations of the maximum forecast error variances are known, various correlations of different variables between these maximum variance points and the perturbation fields at the target time, e.g. hour 12, are calculated to identify those locations at the target time, over where the observational errors might be responsible for the growth of forecast error variances at the verification time. Statistically, these correlation fields indicate where the most sensitive areas are at the target time, i.e. where the need for additional observations is suggested. Hurricane Fran of 1996 is used to test the proposed method. The reason for choosing this case is that, during the first 48 hour forecast, the track forecast from NWP-model was very close to the best track. Two additional experiments were designed to examine the method. One experiment updates predicted variables at the target time (12 h) over the areas, to where the proposed method indicates the forecast would be sensitive. The updating combines observations (or truth) with the first guess (predicted) fields. Another experiment also modifies predicted variables at the target time (12 h), but over the areas where the method indicates the forecast errors are less correlated to. The results show that the modification has greatly reduced the forecast error variances at the verification time (48 h) in the first experiment, however it has a very little impact on the variance fields at the forecast hour (48 h) in the second experiment. It is very clear from our experiments, that the proposed method is able to identify sensitive areas, where additional observations can help to reduce hurricane forecast errors from an NWP-model. Received July 19, 1999 Revised November 28, 1999  相似文献   

13.
A study of the neutrally-stratified flow within and over an array of three-dimensional buildings (cubes) was undertaken using simple Reynolds-averaged Navier—Stokes (RANS) flow models. These models consist of a general solution of the ensemble-averaged, steady-state, three-dimensional Navier—Stokes equations, where the k-ε turbulence model (k is turbulence kinetic energy and ε is viscous dissipation rate) has been used to close the system of equations. Two turbulence closure models were tested, namely, the standard and Kato—Launder k-ε models. The latter model is a modified k-ε model designed specifically to overcome the stagnation point anomaly in flows past a bluff body where the standard k-ε model overpredicts the production of turbulence kinetic energy near the stagnation point. Results of a detailed comparison between a wind-tunnel experiment and the RANS flow model predictions are presented. More specifically, vertical profiles of the predicted mean streamwise velocity, mean vertical velocity, and turbulence kinetic energy at a number of streamwise locations that extend from the impingement zone upstream of the array, through the array interior, to the exit region downstream of the array are presented and compared to those measured in the wind-tunnel experiment. Generally, the numerical predictions show good agreement for the mean flow velocities. The turbulence kinetic energy was underestimated by the two different closure models. After validation, the results of the high-resolution RANS flow model predictions were used to diagnose the dispersive stress, within and above the building array. The importance of dispersive stresses, which arise from point-to-point variations in the mean flow field, relative to the spatially-averaged Reynolds stresses are assessed for the building array.  相似文献   

14.
Local Scales of Turbulence in the Stable Boundary Layer   总被引：1，自引：1，他引：0  
Local, gradient-based scales, which contain the vertical velocity and temperature variances, as well as the potential temperature gradient, but do not include fluxes, are tested using data collected during the CASES-99 experiment. The observations show that the scaling based on the temperature variance produces relatively smaller scatter of empirical points. The resulting dimensionless statistical moments approach constant values for sufficiently large values of the Richardson number Ri. This allows one to derive predictions for the Monin–Obukhov similarity functions φ m and φ h , the Prandtl number Pr and the flux Richardson number Rf in weak turbulence regime.  相似文献   

15.
Intraseasonal variability in the eastern Pacific warm pool in summer is studied, using a regional ocean?Catmosphere model, a linear baroclinic model (LBM), and satellite observations. The atmospheric component of the model is forced by lateral boundary conditions from reanalysis data. The aim is to quantify the importance to atmospheric deep convection of local air?Csea coupling. In particular, the effect of sea surface temperature (SST) anomalies on surface heat fluxes is examined. Intraseasonal (20?C90?day) east Pacific warm-pool zonal wind and outgoing longwave radiation (OLR) variability in the regional coupled model are correlated at 0.8 and 0.6 with observations, respectively, significant at the 99% confidence level. The strength of the intraseasonal variability in the coupled model, as measured by the variance of outgoing longwave radiation, is close in magnitude to that observed, but with a maximum located about 10° further west. East Pacific warm pool intraseasonal convection and winds agree in phase with those from observations, suggesting that remote forcing at the boundaries associated with the Madden?CJulian oscillation determines the phase of intraseasonal convection in the east Pacific warm pool. When the ocean model component is replaced by weekly reanalysis SST in an atmosphere-only experiment, there is a slight improvement in the location of the highest OLR variance. Further sensitivity experiments with the regional atmosphere-only model in which intraseasonal SST variability is removed indicate that convective variability has only a weak dependence on the SST variability, but a stronger dependence on the climatological mean SST distribution. A scaling analysis confirms that wind speed anomalies give a much larger contribution to the intraseasonal evaporation signal than SST anomalies, in both model and observations. A LBM is used to show that local feedbacks would serve to amplify intraseasonal convection and the large-scale circulation. Further, Hovm?ller diagrams reveal that whereas a significant dynamic intraseasonal signal enters the model domain from the west, the strong deep convection mostly arises within the domain. Taken together, the regional and linear model results suggest that in this region remote forcing and local convection?Ccirculation feedbacks are both important to the intraseasonal variability, but ocean?Catmosphere coupling has only a small effect. Possible mechanisms of remote forcing are discussed.  相似文献   

16.
An algorithm for the estimation of root zone soil moisture is presented. Global fields of the soil moisture within the uppermost metre of soil are derived with a temporal resolution of 10 days. For calibration, long-term soil moisture observations from the former Soviet Union are used. The variance of the measurements is largely dominated by the spatial variability of the long-term mean soil moisture, while the temporal variability gives comparatively small contribution. Consequently, the algorithm is organised into two steps. The first step concentrates on the retrieval of the spatial variance of the long-term means, which comprises more than 85% of the total soil moisture variability. A major part of the spatial variance can be explained by four easily available fields: the climatological precipitation, land use, soil texture, and terrain slope. The second step of the algorithm is dedicated to the local temporal variability. This part of variability is recovered by using passive microwave data from scanning multichannel microwave radiometre (SMMR) supported by monthly averaged fields of air temperature and precipitation. The 6-GHz channel of SMMR is shown to be severely disturbed by radio frequency interference, so that information from the 10-GHz channel is used instead. The algorithm provides reasonable soil moisture fields which is confirmed by a comparison with independent measurements from Illinois.  相似文献   

17.
Based on gradient transport theory or K-theory, turbulent transport in the atmosphere has long been parameterized using the eddy diffusivity. Due to its simplicity, this approach has often been applied in many numerical models but rarely tested with observations. Here, the widely used O’Brien cubic polynomial approach has been validated together with an exponential approach against eddy diffusivity profiles determined from measurements and from large-eddy simulation data in stable conditions. Verification is completed by analyzing the variability effects on pollutant concentrations of two different vertical diffusion (K(z)) schemes incorporated in an atmospheric chemical model. It is shown that the analytical, exponential solution agrees better with observations than the O’Brien profile and should be used henceforth in practical applications.  相似文献   

18.
The reduction in variance of concentration fluctuations due to line averaging is estimated assuming that the process is influenced by the integral distance scale, y I , of ambient turbulence and the scaling width, W, of the time-averaged plume. An analytical formula is derived for the line-averaged variance for situations where the autocorrelogram is exponential and the point variance decreases exponentially with distance from plume centerline. Predictions of concentration fluctuation variance are compared with water tank and field data, with the result that the decrease of variance with averaging distance is well-simulated if the model parameters y I and W are carefully chosen.  相似文献   

19.
Arctic climate change in the Twenty-first century is simulated by the Community Climate System Model version 3.0 (CCSM3). The simulations from three emission scenarios (A2, A1B and B1) are analyzed using eight (A1B and B1) or five (A2) ensemble members. The model simulates a reasonable present-day climate and historical climate trend. The model projects a decline of sea-ice extent in the range of 1.4–3.9% per decade and 4.8–22.2% per decade in winter and summer, respectively, corresponding to the range of forcings that span the scenarios. At the end of the Twenty-first century, the winter and summer Arctic mean surface air temperature increases in a range of 4–14°C (B1 and A2) and 0.7–5°C (B1 and A2) relative to the end of the Twentieth century. The Arctic becomes ice-free during summer at the end of the Twenty-first century in the A2 scenario. Similar to the observations, the Arctic Oscillation (AO) is the dominant factor in explaining the variability of the atmosphere and sea ice in the 1870–1999 historical runs. The AO shifts to the positive phase in response to greenhouse gas forcings in the Twenty-first century. But the simulated trends in both Arctic mean sea-level pressure and the AO index are smaller than what has been observed. The Twenty-first century Arctic warming mainly results from the radiative forcing of greenhouse gases. The 1st empirical orthogonal function (explains 72.2–51.7% of the total variance) of the wintertime surface air temperature during 1870–2099 is characterized by a strong warming trend and a “polar amplification”-type of spatial pattern. The AO, which plays a secondary role, contributes to less than 10% of the total variance in both surface temperature and sea-ice concentration.  相似文献   

20.
The SF6 gas tracer observations for puffs released near the ground during the Joint Urban 2003 (JU2003) urban dispersion experiment in Oklahoma City have been analysed. The JU2003 observations, at distances of about 100–1,100 m from the source, show that, at small times, when the puff is still within the built-up downtown domain, the standard deviation of the concentration time series, σt, is influenced by the initial puff spread due to buildings near the source and by hold-up in the wakes of large buildings at the sampler locations. This effect is parameterised by assuming an initial σto of about 42 s, leading to a comprehensive similarity formula: σt = 42 + 0.1t. The second term, 0.1t, is consistent with an earlier similarity relation, σt = 0.1t, derived from puff observations in many experiments over rural terrain. The along-wind dispersion coefficient, σx, is assumed to equal σt u, in which u is the puff speed calculated as the distance from the source to the sampler, x, divided by the time after the release that the maximum concentration is observed at the sampler. σx can be expressed as σx = σxo + 0.14x, with the initial σxo of 45 m. This initial σxo agrees with the suggestion of an initial plume spread of about 40 m, made by McElroy and Pooler from analysis of the 1960s’ St. Louis urban dispersion experiment. The puff speeds, u, are initially only about 20% of the observed wind speed, averaged over about 80 street-level and rooftop anemometers in the city, but approach the mean observed wind speed as the puffs grow vertically. The scatter in the σt data is about ± a factor of two or three at any given travel time. The maximum σt is about 250 s, and the maximum duration of the puff over the sampler, Dt, sometimes called the retention time, is about 1,100 s or 18 min for these puffs and distances.  相似文献   

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