Analysis of a two-layer cloud system with RAMS model and comparison to airborne observations

A three-dimensional numerical model (Regional Atmospheric Modeling System—-RAMS) was used to study the formation and evolution of water forms in a two-layer cloud structure observed during a field campaign over Brest (France). The model performance in regular operations, using conventional meteorological data as initial and lateral boundary conditions, was also examined. Remote sensing observations of the cloud system and in-situ aircraft data, selected during the campaign, were used to validate the model outputs. The model simulations showed that the lower cloud formation was characterized by high number concentration of pristine ice and snow, while the concentration of aggregates, graupel and hail were considerably lower. Hydrometeors in liquid phase appeared demonstrating high number concentration and water content on the top of this layer. The upper cloud layer consisted only of frozen water substances in lower amounts. The qualitative and quantitative comparison of the model-calculated meteorological and microphysical fields to the available observational data revealed that the model reflected fairly well the cloud structure (e.g., the spatio-temporal variability of the cloud parameters, the geometry of the cloud system). However, there were deviations as far as the model underestimating the ice water content (IWC) and number concentration (N_t) fields is concerned, especially at the atmospheric layer between 2.5 and 4 km of altitude. These deviations of the model simulated quantities from the measured ones may be attributed either to the performance of the model’s microphysics scheme, to instrument inaccuracies and to the local disturbance caused by the aircraft.     

Turbulence closure models and their application in RAMS

Turbulence closures are fundamental for modelling the atmospheric diffusion in numerical codes and the resulting eddy diffusivities are key parameters in describing the transport and dispersion in the boundary layer. In this work, four turbulence closure schemes have been applied for reproducing a neutral flow over schematic complex terrain using the meteorological model RAMS. Two of the closures, a one-equation (E-l) and a two-equations (E-) model, have been implemented in RAMS in alternative to the ones originally available. In these cases, an analytical method based on the similarity theory for the atmospheric surface layer and boundary layer is adopted to calculate the empirical constants of the turbulence closures. Some examples of numerical studies performed to simulate the flow and turbulence over a 3-D hill in wind-tunnel experiment in neutral stratification are presented and discussed. An intercomparison of simulations related to different closures is considered by analysing the main features of the flow over the hill and by comparing calculated vertical profiles of turbulent kinetic energy with measured ones.     

Numerical Investigation of the Effects of Boundary-Layer Evolution on the Predictions of Ozone and the Efficacy of Emission Control Options in the Northeastern United States

This paper examines the effects of two different planetary boundary-layer (PBL) parameterization schemes – Blackadar and Gayno–Seaman – on the predicted ozone (O₃) concentration fields using the MM5 (Version 3.3) meteorological model and the MODELS-3 photochemical model. The meteorological fields obtained from the two boundary-layer schemes have been used to drive the photochemical model to simulate O₃ concentrations in the northeastern United States for a three-day O₃ episodic period. In addition to large differences in the predicted O₃ levels at individual grid cells, the simulated daily maximum 1-h O₃ concentrations appear at different regions of the modeling domain in these simulations, due to the differences in the vertical exchange formulations in these two PBL schemes. Using process analysis, we compared the differences between the different simulations in terms of the relative importance of chemical and physical processes to O₃ formation and destruction over the diurnal cycle. Finally, examination of the photochemical model's response to reductions in emissions reveals that the choice of equally valid boundary-layer parameterizations can significantly influence the efficacy of emission control strategies.     

Three-Dimensional Modelling of Concentration Fluctuations in Complicated Geometry

The strong fluctuating component in the measured concentration time series of a dispersing gaseous pollutant in the atmospheric boundary layer, and the hazard level associated to short-term concentration levels, demonstrate the necessity of calculating the magnitude of turbulent fluctuations of concentration using computational simulation models. Moreover the computation of concentration fluctuations in cases of dispersion in realistic situations, such as built-up areas or street canyons, is of special practical interest for hazard assessment purposes. In this paper, the formulation and evaluation of a model for concentration fluctuations, based on a transport equation, are presented. The model is applicable in cases of complex geometry. It is included in the framework of a computational code, developed for simulating the dispersion of buoyant pollutants over complex geometries. The experimental data used for the model evaluation concerned the dispersion of a passive gas in a street canyon between 4 identical rectangular buildings performed in a wind tunnel. The experimental concentration fluctuations data have been derived from measured high frequency concentrations. The concentration fluctuations model is evaluated by comparing the model's predictions with the observations in the form of scatter plots, quantile-quantile plots, contour plots and statistical indices as the fractional bias, the geometrical mean variance and the factor-of-two percentage. From the above comparisons it is concluded that the overall model performance in the present complex geometry case is satisfactory. The discrepancies between model predictions and observations are attributed to inaccuracies in prescribing the actual wind tunnel boundary conditions to the computational code.     

Performance analysis of WRF and LES in describing the evolution and structure of the planetary boundary layer

We implemented the Weather Research and Forecast (WRF) model and WRF Large-Eddy Simulation (WRF–LES), focusing on calculations for the planetary boundary layer (PBL), and compared the results against a data set of a well-documented campaign, in the Houston–Galveston area, Texas, in summer 2006. A methodology using WRF in a mesoscale and LES was implemented to assess the performance of the model in simulating the evolution and structure of the PBL over Houston during the Vertical Mixing Experiment. Also, the WRF model in a real case mode was examined to explore potential differences between the results of each simulation approach. We analyzed both WRF results for key meteorological parameters like wind speed, wind direction and potential temperature, and compared the model results against the observations. The reasonably good agreement of LES results forced with observed surface fluxes provides confidence that LES describes turbulence quantities such as turbulent kinetic energy correctly and warrants further turbulence structure analysis. The LES results indicate a weak but noticeable nighttime turbulent kinetic energy which was produced by wind shear in Houston’s planetary boundary layer and which may likely be related to intermittent turbulence. This is supported by observations made at the University of Houston Moody Tower air quality station when intermittent peaks of carbon monoxide occurred in the evening, although the variability in wind conditions was very little.     

POD characterisation of extreme wake patterns of turbulent wind fields past rectangular buildings

Environmental Fluid Mechanics - The turbulent wind fields around three different rectangular building models in two types of simulated atmospheric boundary layer are measured using particle image...     

The performance of RAMS in representing the convective boundary layer structure in a very steep valley

Data from a comprehensive field study in the Riviera Valley of Southern Switzerland are used to investigate convective boundary layer structure in a steep valley and to evaluate wind and temperature fields, convective boundary layer height, and surface sensible heat fluxes as predicted by the mesoscale model RAMS. Current parameterizations of surface and boundary layer processes in RAMS, as well as in other mesoscale models, are based on scaling laws strictly valid only for flat topography and uniform land cover. Model evaluation is required to investigate whether this limits the applicability of RAMS in steep, inhomogeneous terrain. One clear-sky day with light synoptic winds is selected from the field study. Observed temperature structure across and along the valley is nearly homogeneous while wind structure is complex with a wind speed maximum on one side of the valley. Upvalley flows are not purely thermally driven and mechanical effects near the valley entrance also affect the wind structure. RAMS captured many of the observed boundary layer characteristics within the steep valley. The wind field, temperature structure, and convective boundary layer height in the valley are qualitatively simulated by RAMS, but the horizontal temperature structure across and along the valley is less homogeneous in the model than in the observations. The model reproduced the observed net radiation, except around sunset and sunrise when RAMS does not take into account the shadows cast by the surrounding topography. The observed sensible heat fluxes fall within the range of simulated values at grid points surrounding the measurement sites. Some of the scatter between observed and simulated turbulent sensible heat fluxes are due to sub-grid scale effects related to local topography.     

A stochastic Lagrangian micromixing model for the dispersion of reactive scalars in turbulent flows: role of concentration fluctuations and improvements to the conserved scalar theory under non-homogeneous conditions

Several reaction schemes, based on the conserved scalar theory, are implemented within a stochastic Lagrangian micromixing model to simulate the dispersion of reactive scalars in turbulent flows. In particular, the formulation of the reaction-dominated limit (RDL) reaction scheme is here extended to improve the model performance under non-homogeneous conditions (NHRDL scheme). The validation of the stochastic model is obtained by comparison with the available measurements of reactive pollutant concentrations in a grid-generated turbulent flow. This test case describes the dispersion of two atmospheric reactant species (NO and O₃) and their reaction product (NO₂) in an unbounded turbulent flow. Model inter-comparisons are also assessed, by considering the results of state-of-the-art models for pollutant dispersion. The present validation shows that RDL reaction scheme provides a systematic overestimation (relative error of ca. 85% around the centreline) in computing the local reactant consumption/production rate, whereas the NHRDL scheme drastically reduces this gap (relative error lower than 5% around the centreline). In terms of NO₂ production (or reactant consumption), neglecting concentration fluctuations determines overestimations of the product mean of around 100% and a NO₂ local production of one order of magnitude higher than the reference simulation. In terms of standard deviations, the concentration fluctuations of both the passive and reactive scalars are generally of the same order of magnitude or up to 1 or 2 orders of magnitudes higher than the corresponding ensemble mean values, except for the background reactant close to the plume edges. The study highlights the importance of modelling pollutant reactions depending on the instantaneous instead of the mean concentrations of the reactants, thus quantifying the role of the turbulent fluctuations of concentration, in terms of scalar statistics (mean, standard deviation, intensity of fluctuations, skewness and kurtosis of concentration, segregation coefficient, simulated reaction rate). This stochastic particle method represents an efficient numerical technique to solve the convection–diffusion equation for reactive scalars and involves several application fields: micro-scale air quality (urban and street-canyon scales), accidental releases, impact of odours, water quality and fluid flow industrial processes (e.g. combustion).     

复杂地形城市SO2扩散特征的模拟研究

利用中尺度气象模式RAMS和大气扩散模式HYPACT,结合甘肃省-中科院科技合作项目"兰州市大气污染及对策研究"于2000年12月在兰州市城区进行的大气污染物监测资料,通过资料分析与模拟计算,研究了兰州市冬季SO2的扩散特点。研究结果表明:大气扩散模式较好地模拟出了SO2时空分布特征,与同期监测资料的分析结果比较一致,模式模拟的SO2浓度分布的日变化与环流场的日变化紧密相关;模拟的SO2浓度的空间分布与污染源的排放方式有关,污染源的排放高度不同,造成污染的高度也不同,高架源对地面的影响比较小,而中、低架源对地面的影响比较大。     

Nitrogen source apportionment—a comparison between a dynamic and a statistical model

A dynamic model, HBV-N, and a statistical model, MESAW, for nitrogen source apportionment were compared regarding model performance, model uncertainty and user applicability. The HBV-N model simulates continuous series of nitrogen concentrations with meteorological data and sub-basin characteristics as input. Diffuse nitrogen emissions are defined as regional model parameters which are calibrated by comparison of observed and simulated nitrogen data. The MESAW model uses nitrogen loads for a fixed time interval at each monitoring site as response variable and sub-basin characteristics as explanatory variables to estimate diffuse nitrogen emissions through non-linear regression analysis. The two models were applied in the Matsalu Bay watershed (3640 km²) in Estonia and the same land use and point sources data were used as input. Both models gave similar levels of diffuse total nitrogen emissions and retention rates, which also fit well with previous estimates made in Estonia and Scandinavia. A sensitivity analysis of the model parameters also showed similar uncertainty levels, which indicated that the model uncertainty was more dependent on the availability of nitrogen data and land cover distribution than the choice of model. Furthermore, the sensitivity analysis showed a parameter interdependency in both models, which implied the risk of compensation between estimated diffuse emissions and retention. In conclusion, however, the study showed that both models were capable of estimating nitrogen leakage from the dominating land classes and giving reliable source apportionment from the available input data. The study indicated that the HBV-N model has its advantage in assessments where detailed outputs are needed and when run-off data are limited, while the statistical MESAW model has its advantage in extensive studies since it is easily applied to large watersheds that have dense monitoring networks.     

Large-Eddy Simulations of the Atmospheric Boundary Layer Using a New Subgrid-Scale Model – I. Slightly unstable and neutral cases

Subgrid-scale (SGS) modeling is a long-standing problem and a critical component in the large-eddy simulation (LES) of atmospheric boundary layer. A variety of SGS models with different levels of sophistication have been proposed for different needs, such as Smagorinsky's (1963) eddy viscosity model, Mason and Thomson's (1992) stochastic backscattering model, and Sullivan et al.'s (1994) near surface model. A modified Smagorinsky SGS model has been used in the LES version of Terminal Area Simulation System (TASS-LES). It has successfully simulated the buoyancy-dominated, convective atmospheric boundary layer flows, while simulations of the shear-dominated, slightly unstable, neutral, and stably stratified boundary layer flows are not so good. For the later, we used a simpler version of Sullivan et al.'s subgrid-scale model in which turbulent kinetic energy equation is not included and the model is still the first-order closure. A momentum profile matching approach is adopted in the proposed model. A series of simulations for shear-dominated, slightly unstable and neutral boundary layers are performed using different subgrid-scale models and different grid resolutions. The results are compared with those of Sullivan et al. (1994) and with empirical similarity relations for the surface layer. The simulations with the new SGS model appear to be far more satisfactory than those with the modified Smagorinsky model.     

Sensitivity of ecological models to their climate drivers: statistical ensembles for forcing.

Global and regional numerical models for terrestrial ecosystem dynamics require fine spatial resolution and temporally complete historical climate fields as input variables. However, because climate observations are unevenly spaced and have incomplete records, such fields need to be estimated. In addition, uncertainty in these fields associated with their estimation are rarely assessed. Ecological models are usually driven with a geostatistical model's mean estimate (kriging) of these fields without accounting for this uncertainty, much less evaluating such errors in terms of their propagation in ecological simulations. We introduce a Bayesian statistical framework to model climate observations to create spatially uniform and temporally complete fields, taking into account correlation in time and space, spatial heterogeneity, lack of normality, and uncertainty about all these factors. A key benefit of the Bayesian model is that it generates uncertainty measures for the generated fields. To demonstrate this method, we reconstruct historical monthly precipitation fields (a driver for ecological models) on a fine resolution grid for a climatically heterogeneous region in the western United States. The main goal of this work is to evaluate the sensitivity of ecological models to the uncertainty associated with prediction of their climate drivers. To assess their numerical sensitivity to predicted input variables, we generate a set of ecological model simulations run using an ensemble of different versions of the reconstructed fields. We construct such an ensemble by sampling from the posterior predictive distribution of the climate field. We demonstrate that the estimated prediction error of the climate field can be very high. We evaluate the importance of such errors in ecological model experiments using an ensemble of historical precipitation time series in simulations of grassland biogeochemical dynamics with an ecological numerical model, Century. We show how uncertainty in predicted precipitation fields is propagated into ecological model results and that this propagation had different modes. Depending on output variable, the response of model dynamics to uncertainty in inputs ranged from uncertainty in outputs that matched that of inputs to those that were muted or that were biased, as well as uncertainty that was persistent in time after input errors dropped.     

A simple model for simulation of insect pheromone dispersion within forest canopies

Synthetic pheromones and other behavioral chemicals are used by land managers to prevent insect-caused tree mortality or crop failure in forest and agricultural systems. Currently, no method exists to continuously measure pheromone concentration or movement in real-time. To improve our understanding of pheromone fate and transport under different forest canopies, results from a set of surrogate pheromone (sulfur hexafluoride tracer) experimental trials were used to evaluate a simple, instantaneous, three-dimensional Lagrangian dispersion model. The model was designed to predict both instantaneous and time-averaged pheromone concentrations. Overall, the results from the model show simulated time-averaged arc maximum concentrations within a factor of two of the observed data. The model correctly matched the sharp peaks and narrow widths of the meandering plumes observed in the instantaneous data, however the magnitude of the instantaneous peaks was often under-estimated. This model and evaluation provide the basis for a tool that can be used to guide deployment of synthetic pheromones or other semiochemicals for monitoring, mass trapping, or disruption of mating or aggregation.     

Risk,Risk Aversion,and On-Farm Soil Depletion

This paper studies the production and attendant soil depletion choices of a risk-averse farmer in two related models. The first is a two-date model with uncertainty in both production and end-of-period land price. The second is a three-date model in which production and consumption choices are made in both periods, but there is uncertainty only in the second period. In both models, the paper identifies plausible conditions under which a higher level of initial farmer wealth and/or a lower level of production and land risk lead to a lower level of output and, as a result, a lower level of output-induced soil depletion.     

气象因素对环境空气质量达标的影响分析

以天津市为例,分析地面风场、大气层结及天气形势等主要污染气象参量的特征及其与环境空气质量的相关关系;估算高、低污染潜势的天气背景对大气污染物浓度的影响幅度;提出在天气气候分类的基础上,建立气象条件标准化分级,评估气象条件对环境空气质量影响水平的方法。研究表明:天津市采暖季高污染的天气形势出现的频率约为34%,而非采暖季高污染的天气形势出现的频率约为16%,ISCLT3模型模拟结果显示相应于相同的污染源排放数据库由于采暖季和非采暖季气象条件不同引起的SO2全市平均浓度的差异约在10%以上。污染源源强相对稳定的条件下,高污染潜势的天气背景对空气污染的加剧作用大于低污染潜势的天气背景对空气污染的减轻作用。     

Impact of consistent boundary layer mixing approaches between NAM and CMAQ

Discrepancies in grid structure, dynamics and physics packages in the offline coupled NWS/NCEP NAM meteorological model with the U.S. Environmental Protection Agency Community Multiscale Air Quality (CMAQ) model can give rise to inconsistencies. This study investigates the use of three vertical mixing schemes to drive chemistry tracers in the National Air Quality Forecast Capability (NAQFC). The three schemes evaluated in this study represent various degrees of coupling to improve the commonality in turbulence parameterization between the meteorological and chemistry models. The methods tested include: (1) using NAM predicted TKE-based planetary boundary height, h, as the prime parameter to derive CMAQ vertical diffusivity; (2) using the NAM mixed layer depth to determine h and then proceeding as in (1); and (3) using NAM predicted vertical diffusivity directly to parameterize turbulence mixing within CMAQ. A two week period with elevated surface O₃ concentrations during the summer 2006 has been selected to test these schemes in a sensitivity study. The study results are verified and evaluated using the EPA AIRNow monitoring network and other ozonesonde data. The third method is preferred a priori as it represents the tightest coupling option studied in this work for turbulent mixing processes between the meteorological and air quality models. It was found to accurately reproduce the upper bounds of turbulent mixing and provide the best agreement between predicted h and ozonesonde observed relative humidity profile inferred h for sites investigated in this study. However, this did not translate into the best agreement in surface O₃ concentrations. Overall verification results during the test period of two weeks in August 2006, did not show superiority of this method over the other 2 methods in all regions of the continental U.S. Further efforts in model improvement for the parameterizations of turbulent mixing and other surface O₃ forecast related processes are warranted.     

Development of a rotorcraft dust-emission parameterization using a CFD model

Flights of rotorcraft over the desert floor can result in significant entrainment of particulate matter into the atmospheric boundary layer. Continuous or widespread operation can lead to local and regional impacts on visibility and air quality. To account for this pollutant source in air quality models, a parameterization scheme is needed that addresses the complex vertical distribution of dust ejected from the rotorcraft wake into the atmospheric surface layer. A method to parameterize the wind and turbulence fields and shear stress at the ground is proposed here utilizing computational fluid dynamics and a parameterized rotor model. Measurements taken from a full scale experiment of rotorcraft flight near the surface are compared to the simulation results in a qualitative manner. The simulation is shown to adequately predict the forward detachment length of the induced ground jet compared to the measured detachment lengths. However, the simulated ground vortex widths and vorticity deviate substantially from the measured values under a range of flight speeds. Results show that the method may be applicable for air quality modeling assuming slow airspeeds of the rotorcraft, with advance ratios of 0.005–0.02.     

珠江三角洲土地利用变化对特征大气污染物扩散的影响

在珠江三角洲两种下垫面条件下,应用CALPUFF大气污染扩散模式,对特征污染物SO2、SO42-的扩散进行数值模拟,探讨大规模土地利用变化,尤其是城镇建设用地增加,对珠江三角洲地区大气污染物扩散的影响,并通过对4个典型区污染物月均质量浓度变化特征分析,揭示土地利用变化对不同地区的污染物分布的影响机制。模拟结果表明：土地利用变化,尤其是城镇建设用地增加,不利于污染物扩散,污染源下风方向地区受影响较大,污染物质量浓度明显升高,SO2和 SO42-年均质量浓度分别增加14.07%和3.31%;受影响范围、变化幅度与污染源排污强度呈正相关,变化幅度亦与污染源距离远近呈负相关。土地利用变化后,尤其是城镇建设用地增加,四个典型区 SO2月均质量浓度都表现为升高趋势,且冬季 SO2质量浓度升高幅度最大,夏季升高幅度最小,临近污染源密集区的两个典型区SO2月均质量浓度分别增加33.6%和26.3%。土地利用变化不仅改变局地的污染扩散,也会对区域的污染扩散有一定影响,尤其对污染源分布密集区的大气污染物扩散影响强度最大。因此,建议人类在城市化建设过程中尽可能保留自然斑块,消除人工下垫面对污染物扩散的负面影响。     

Effects of experimental protocol on global vegetation model accuracy: A comparison of simulated and observed vegetation patterns for Asia

Prognostic vegetation models have been widely used to study the interactions between environmental change and biological systems. This study examines the sensitivity of vegetation model simulations to: (i) the selection of input climatologies representing different time periods and their associated atmospheric CO₂ concentrations, (ii) the choice of observed vegetation data for evaluating the model results, and (iii) the methods used to compare simulated and observed vegetation. We use vegetation simulated for Asia by the equilibrium vegetation model BIOME4 as a typical example of vegetation model output. BIOME4 was run using 19 different climatologies and their associated atmospheric CO₂ concentrations. The Kappa statistic, Fuzzy Kappa statistic and a newly developed map-comparison method, the Nomad index, were used to quantify the agreement between the biomes simulated under each scenario and the observed vegetation from three different global land- and tree-cover data sets: the global Potential Natural Vegetation data set (PNV), the Global Land Cover Characteristics data set (GLCC), and the Global Land Cover Facility data set (GLCF). The results indicate that the 30-year mean climatology (and its associated atmospheric CO₂ concentration) for the time period immediately preceding the collection date of the observed vegetation data produce the most accurate vegetation simulations when compared with all three observed vegetation data sets. The study also indicates that the BIOME4-simulated vegetation for Asia more closely matches the PNV data than the other two observed vegetation data sets. Given the same observed data, the accuracy assessments of the BIOME4 simulations made using the Kappa, Fuzzy Kappa and Nomad index map-comparison methods agree well when the compared vegetation types consist of a large number of spatially continuous grid cells. The results of this analysis can assist model users in designing experimental protocols for simulating vegetation.     

Performance and validation of a coupled parallel ADCIRC–SWAN model for THANE cyclone in the Bay of Bengal

An accurate prediction of near-shore sea-state is imperative during extreme events such as cyclones required in an operational centre. The mutual interaction between physical processes such as tides, waves and currents determine the physical environment for any coastal region, and hence the need of a parallelized coupled wave and hydrodynamic model. The present study is an application of various state-of-art models such as WRF, WAM, SWAN and ADCIRC used to couple and simulate a severe cyclonic storm Thane that developed in the Bay of Bengal during December 2011. The coupled model (ADCIRC–SWAN) was run in a parallel mode on a flexible unstructured mesh. Thane had its landfall on 30 December, 2011 between Cuddalore and Pondicherry where in-situ observations were available to validate model performance. Comprehensive experiment on the impact of meteorological forcing parameters with two forecasted tracks derived from WRF model, and JTWC best track on the overall performance of coupled model was assessed. Further an extensive validation experiment was performed for significant wave heights and surface currents during Thane event. The significant wave heights measured along satellite tracks by three satellites viz; ENVISAT, JASON-1 and JASON-2, as well in-situ near-shore buoy observation off Pondicherry was used for comparison with model results. In addition, qualitative validation was performed for model computed currents with HF Radar Observation off Cuddalore during Thane event. The importance of WRF atmospheric model during cyclones and its robustness in the coupled model performance is highlighted. This study signifies the importance of coupled parallel ADCIRC–SWAN model for operational needs during extreme events in the North Indian Ocean.