Second-Order Closure Integrated Puff Research Articles

Comparison of SCIPUFF predictions to SO2 measurements from instruments on the MetOp-A, MetOp-B, Aura and Suomi satellites from the 2016 fire at Al-Mishraq

On October 20th, 2016, Daesh (Islamic State) set fire to the sulfur production and storage site at Al-Mishraq, Iraq. The fire burned continuously for seven days resulting in the release of a buoyant dynamic sulfur dioxide (SO2) toxic plume extending geographically for over 300 km. This Al-Mishraq event provides an opportunity for scientists to address probabilistic atmospheric transport and dispersion (PATD) hazard model performance across multiple downwind scales over a large area. In using any PATD model, a fair evaluation of the model depends on the quality of the source term – especially for a very dynamic source term such as a burning sulfur stockpile. An innovative approach to derive such a source for Al-Mishraq was explored by the Swedish Defence Research Agency (in Swedish Totalförsvarets forskningsinstitut, or FOI). The experts from FOI characterized the SO2 source term based on satellite observations, which reflect vertically-integrated concentrations and are expressed in Dobson units (DU). The work throughout this paper is a novel approach and leverages the FOI analysis to evaluate a PATD, the Second Order Closure Integrated Puff (SCIPUFF) transport and dispersion code as adapted within the Hazard Prediction and Assessment Capability (HPAC). SCIPUFF predictions are compared to the satellite-based vertically-integrated SO2 measurements from the Moderate Resolution Imaging Spectro-radiometer (MODIS) instruments. Satellite measurements were available at 07Z and 11Z daily from 21 to 26 Oct 2016. A 1-DU background was assumed. SCIPUFF over predicts (factor of 2) column density (DU) peaks in the near field (40, 80, and 120 km) and under predicts in the far field (200, 280 and 320 km); best agreement is at the 160 km arc. Plume direction errors of 25–80° are found when comparing the azimuths of peak observed and predicted column densities. Performance metrics traditionally used for model evaluation included fractional bias (FB), normalized mean-square error (NMSE), and figure of merit in space (FMS). The FB at 07Z was −0.2 to +0.09 across the eight arcs, 40–320 km downwind. Upon analyses, SCIPUFF showed approximate equal over and under prediction for the 07Z; and the FB at 11Z under predicted seven of eight arcs, with values that ranged from −0.07 to +0.36. The NMSE was 3.11–5.06 with no identifiable trends on arc distance. The FMS, averaged over each arc, by day, was between 0.31 and 0.56. Higher values were found in the early and later stages of the fire 21–22 and 25–26 October. Lower averaged FMS values were calculated for 23–24 October which corresponds to a period where the fire burned hotter and SO2 mass was injected to higher altitudes of 1–4 km.

Single source impacts on secondary pollutants using a Lagrangian reactive puff model: Comparison with photochemical grid models

Abstract Recent updates to U.S. regulatory guidelines for modeling impacts of single sources to secondary pollutants, such as ozone (O3) and fine particulate matter (PM2.5), require the use of established photochemical models with a complete treatment of gas-phase and aerosol chemistry as the preferred method for a Tier 2 demonstration approach. Such models include photochemical grid models (PGMs), as well as Lagrangian puff models with the requisite treatment of processes governing the formation of secondary pollutants from their precursors. SCICHEM is an open source reactive puff model that includes treatments for gas, aerosol, and aqueous-phase chemistry that are comparable to those in PGMs. The dispersion component of SCICHEM is based on the state-of-the-science puff model, SCIPUFF (Second-order Closure Integrated Puff). The model is a valuable tool that requires fewer resources and setup cost to run than PGMs to calculate the impacts of a single source or a small number of sources on downwind ozone and PM2.5. This paper describes a model inter-comparison study of secondary pollutant impacts due to emissions from a hypothetical coal-fired power plant stack. The models compared in this study include SCICHEM and the two most commonly used PGMs, CMAQ and CAMx. Stacks are located in 4 separate regions of the U.S. with distinct differences in chemical environments and geographical features. The key inputs (hypothetical stack parameters and emission rates, meteorology) to the three models are based on a common dataset for consistency. The source impacts calculated by the PGMs are based on zero-out simulations (i.e., with and without the source of interest) as well as the source apportionment tools available in CAMx, while SCICHEM directly predicts source impacts in a single simulation. Annual simulations are conducted to determine the frequency distribution of source impacts over the 4 regions. The comparison of model results shows both similarities and differences in the frequencies and magnitudes of peak impacts predicted by the three models. There is good agreement among all models in their predictions of 98th and 99th percentile impacts.

Application of the Approximate Bayesian Computation methods in the stochastic estimation of atmospheric contamination parameters for mobile sources

In this paper the Bayesian methodology, known as Approximate Bayesian Computation (ABC), is applied to the problem of the atmospheric contamination source identification. The algorithm input data are on-line arriving concentrations of the released substance registered by the distributed sensors network. This paper presents the Sequential ABC algorithm in detail and tests its efficiency in estimation of probabilistic distributions of atmospheric release parameters of a mobile contamination source. The developed algorithms are tested using the data from Over-Land Atmospheric Diffusion (OLAD) field tracer experiment. The paper demonstrates estimation of seven parameters characterizing the contamination source, i.e.: contamination source starting position (x,y), the direction of the motion of the source (d), its velocity (v), release rate (q), start time of release (ts) and its duration (td). The online-arriving new concentrations dynamically update the probability distributions of search parameters. The atmospheric dispersion Second-order Closure Integrated PUFF (SCIPUFF) Model is used as the forward model to predict the concentrations at the sensors locations.

Impact assessment of PM10 cement plants emissions on urban air quality using the SCIPUFF dispersion model.

The Second-order Closure Integrated Puff (SCIPUFF) model was used to study the impact on urban air quality caused by two cement plants emissions located near the city of Caserta, Italy, during the entire year of 2015. The simulated and observed PM10 concentrations were compared using three monitoring stations located in urban and sub-urban area of Caserta city. Both simulated and observed concentrations are shown to be highest in winter, lower in autumn and spring and lowest in summer. Model results generally follow the pattern of the observed concentrations but have a systematic under-prediction of the concentration values. Measures of the bias, NMSE and RMSE indicate a good correlation between observed and estimated values. The SCIPUFF model data analysis suggest that the cement plants are major sources for the measured PM10 values and are responsible for the deterioration of the urban air quality in the city of Caserta.

A Subkilometer-Gridlength Ensemble for Representing Stable Boundary Layer Forecast Uncertainty over Complex Terrain

Abstract An ensemble prediction system featuring subkilometer horizontal grid spacing and high vertical resolution is used to quantify forecast uncertainty in the stable boundary layer (SBL). Diversity in initial conditions and/or planetary boundary layer/surface layer physics within the WRF Model provides ensembles with up to 12 members. WRF explicit ensemble data drive trajectory calculations and the Second-Order Closure Integrated Puff (SCIPUFF) model for hazard prediction. Explicit ensemble SCIPUFF forecasts are compared to single-member SCIPUFF forecasts leveraging WRF ensemble wind field uncertainty statistics. The performance of 1.3- and 0.4-km horizontal-gridlength ensemble configurations is evaluated for two case studies of differing flow regimes with respect to the Nittany Valley in central Pennsylvania where uncertainty in atmospheric transport and dispersion (ATD) is dependent on drainage flows and circulations related to trapped lee-wave activity. Results demonstrate that a 12-member ensemble provides reasonable spread in ATD forecasts. Additionally, single-member SCIPUFF surface-dosage probability forecasts using the meteorological ensemble statistics generally reflect the pattern while encompassing the hazard area given by the explicit SCIPUFF ensemble, but at a reduced computational cost. Low-level wind and temperature forecasts given by the 12-member, 0.4-km ensemble are improved significantly over corresponding 1.3-km ensemble forecasts. In general, the 12-member, subkilometer-gridlength ensemble configuration reliably captures temperature and wind fluctuations related to drainage flows and trapped lee-wave activity that directly impact ATD. Localized data assimilation positively impacts overall probabilistic forecast skill when trapped lee waves are present, and drainage flow case results appear more dependent on model physics than initialization strategy.

Reactive puff model SCICHEM: Model enhancements and performance studies

The SCICHEM model incorporates complete gas phase, aqueous and aerosol phase chemistry within a state-of-the-science Gaussian puff model SCIPUFF (Second-order Closure Integrated Puff). The model is a valuable tool that can be used to calculate the impacts of a single source or a small number of sources on downwind ozone and PM2.5. The model has flexible data requirements: it can be run with routine surface and upper air observations or with prognostic meteorological model outputs and source emissions are specified in a simple text format. This paper describes significant advances to the dispersion and chemistry components of the model in the latest release, SCICHEM 3.0. Some of the major advancements include modeling of skewed turbulence for convective boundary layer and updated chemistry schemes (CB05 gas phase chemical mechanism; AERO5 aerosol and aqueous modules). The results from SCICHEM 3.0 are compared with observations from a tracer study as well as aircraft measurements of reactive species in power plant plumes from two field studies. The results with the tracer experiment (Copenhagen study) show that the incorporation of skewed turbulence improves the calculation of tracer dispersion and transport. The comparisons with the Cumberland and Dolet Hills power plume measurements show good correlation between the observed and predicted concentrations of reactive gaseous species at most downwind distances from the source.

Using soil records with atmospheric dispersion modeling to investigate the effects of clean air regulations on 60 years of manganese deposition in Marietta, Ohio (USA)

Atmospheric emissions of metals from anthropogenic activities have led to deposition and contamination of soils worldwide. We quantified addition of manganese (Mn) to soils around the largest emitter of Mn in the United States (U.S.) using chemical analyses and atmospheric dispersion modeling (Second-Order Closure Integrated Puff (SCIPUFF)). Concentrations of soil-surface Mn were enriched by 9-fold relative to that of the parent material within 1km of the facility. Elevated concentrations of Mn and chromium (Cr), another potentially toxic element that was emitted, document contamination only within 1m of the soil surface. Total mass of Mn added per unit land area integrated over 1m, mMn, equals ~80mgMncm−2 near the facility. Values of mMn remained above background up to tens of kilometers from the source. Air concentrations of Mn particles of 7.5-micron diameter simulated with SCIPUFF using available data for the emission rate and local meteorological conditions for 2006 were consistent with measured air concentrations. However, the Mn deposition calculated for 2006 with SCIPUFF yielded a cumulative value over the lifetime of the refinery (60years) that is a factor of 15 lower than the Mn observed to have been added to the soils. This discrepancy can be easily explained if Mn deposition rates before 1988 were more than an order of magnitude greater than today. Such higher emissions are probable, given the changes in metal production with time and the installation of emission controls after the Clean Air Act (1970). This work shows that atmospheric dispersion models can be used with soil profiles to understand the changes in metal emissions over decadal timescales. In addition, the calculations are consistent with the Clean Air Act accounting for a 15-fold decrease in the Mn deposition to soils around the refinery per metric ton of Mn alloy produced.

A hybrid nudging‐ensemble Kalman filter approach to data assimilation in WRF/DART

AbstractA hybrid nudging‐ensemble Kalman filter (HNEnKF), previously tested in the Lorenz three‐variable model and a two‐dimensional shallow‐water model, is now explored in WRF/DART with real observations using a Cross Appalachian Tracer Experiment case from September 1983 (CAPTEX‐83). The HNEnKF, effectively combining observation nudging and the ensemble Kalman filter (EnKF), achieves a more gradual data assimilation and greatly reduces the insertion noise compared to the EnKF.Three‐hourly surface observations and 12‐hourly rawinsonde observations from the World Meteorological Organization (WMO) are assimilated. These assimilated meteorological observations are used to verify the priors of the experiments. It is found that the HNEnKF generally obtains better priors than the EnKF. To independently verify the HNEnKF approach, the hourly WRF experiment results are also used to drive the Second‐Order Closure Integrated Puff (SCIPUFF) model to predict surface tracer concentrations that are verified against the observed surface concentration data. The HNEnKF analyses driving SCIPUFF produce better statistics of the independent tracer data than the EnKF. Thus there appear to be some advantages in the hourly dynamic analyses produced by the continuous HNEnKF compared to the intermittent EnKF. The analyses of surface pressure tendency demonstrate that the HNEnKF is able to provide better temporal smoothness and dynamic consistency in the hourly analyses than the EnKF. Copyright © 2012 Royal Meteorological Society

An Experimental Field Dataset with Buoyant, Neutral, and Dense Gas Atmospheric Releases and Model Comparisons in Low–Wind Speed (Diffusion) Conditions

Abstract A unique field dataset from a series of low–wind speed experiments, modeling efforts using three commonly used models to replicate these releases, and statistical analysis of how well these models were able to predict the plume concentrations is presented. The experiment was designed to generate a dataset to describe the behavior of gaseous plumes under low-wind conditions and the ability of current, commonly used models to predict these movements. The dataset documents the release and transport of three gases: ammonia (buoyant), ethylene (neutral), and propylene (dense) in low–wind speed (diffusion) conditions. Release rates ranged from 1 to 20 kg h−1. Ammonia and ethylene had five 5-min releases each to represent puff releases and five 20-min releases each to represent plume releases. Propylene had five 5-min puffs, six 20-min plumes, and a single 30-min plume. Thirty-two separate releases ranging from 6 to 47 min were conducted, of which only 30 releases generated useful data. The data collected included release rates, atmospheric concentrations to 100 m from the release point, and local meteorological conditions. The diagnostics included nine meteorological stations on 100-m centers and 36 photoionization detectors in a radial pattern. Three current state-of-the-practice models, Aerial Locations of Hazardous Atmospheres (ALOHA), Emergency Prediction Information code (EPIcode), and Second-Order Closure Integrated Puff (SCIPUFF), were used to try to duplicate the measured field results. Low wind speeds are difficult to model, and all of the models had difficulty replicating the field measurements. However, the work does show that these models, if used correctly, are conservative (overpredict concentrations) and can be used for safety and emergency planning.

Comparison of Observed, MM5 and WRF-NMM Model-Simulated, and HPAC-Assumed Boundary-Layer Meteorological Variables for 3 Days During the IHOP Field Experiment

The objective of the study is to evaluate operational mesoscale meteorological model atmospheric boundary-layer (ABL) outputs for use in the Hazard Prediction Assessment Capability (HPAC)/Second-Order Closure Integrated Puff (SCIPUFF) transport and dispersion model. HPAC uses the meteorological models’ routine simulations of surface buoyancy flux, winds, and mixing depth to derive the profiles of ABL turbulence. The Fifth-Generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5) and the Weather Research and Forecast-Nonhydrostatic Mesoscale Model (WRF-NMM) ABL outputs and the HPAC ABL parameterisations are compared with observations during the International H2O Project (IHOP). The meteorological models’ configurations are not specially designed research versions for this study but rather are intended to be representative of what may be used operationally and thus have relatively coarse lowest vertical layer thicknesses of 59 and 36 m, respectively. The meteorological models’ simulations of mixing depth are in good agreement (±20%) with observations on most afternoons. Wind speed errors of 1 or 2 ms−1 are found, typical of those found in other studies, with larger errors occurring when the simulated centre of a low-pressure system is misplaced in time or space. The hourly variation of turbulent kinetic energy (TKE) is well-simulated during the daytime, although there is a meteorological model underprediction bias of about 20–40%. At night, WRF-NMM shows fair agreement with observations, and MM5 sometimes produces a very small default TKE value because of the stable boundary-layer parameterisation that is used. The HPAC TKE parameterisation is usually a factor of 5–10 high at night, primarily due to the fact that the meteorological model wind-speed output is at a height of 30 m for MM5 and 18 m for WRF-NMM, which is often well above the stable mixing depth. It is concluded that, before meteorological model TKE fields can be confidently used by HPAC, it would help to improve vertical resolution near the surface, say to 10 m or less, and it would be good to improve the ABL parameterisations for shallow stable conditions.

Improving SCIPUFF Dispersion Forecasts with NWP Ensembles

Abstract The relationships between atmospheric transport and dispersion (AT&D) plume uncertainty and uncertainties in the transporting wind fields are investigated using the Second-Order Closure, Integrated Puff (SCIPUFF) AT&D model driven by numerical weather prediction (NWP) meteorological fields. Modeled contaminant concentrations for episode 1 of the 1983 Cross-Appalachian Tracer Experiment (CAPTEX-83) are compared with recorded ground-level concentrations of the inert tracer gas C7F14. This study evaluates a Taylor-diffusion-based parameterization of dispersion uncertainty for SCIPUFF that uses Eulerian meteorological ensemble velocity statistics and a Lagrangian integral time scale as input. These values are diagnosed from NWP ensemble data. Individual simulations of the tracer release fail to reproduce some of the monitored surface concentrations of the tracer. The plumes that are predicted using the uncertainty model in SCIPUFF are broader, improving the overlap between the predicted and observed results. Augmenting the meteorological input to SCIPUFF with meteorological ensemble-uncertainty parameters therefore provides both a better estimate of the expected plume location and the relative uncertainties in the predicted concentrations than single deterministic forecasts. These results suggest that this new parameterization of NWP wind field uncertainty for dispersion may provide more sophisticated information that may benefit emergency response and decision making.

Ensemble Variance Calibration for Representing Meteorological Uncertainty for Atmospheric Transport and Dispersion Modeling

Abstract In the event of the release of a dangerous atmospheric contaminant, an atmospheric transport and dispersion (ATD) model is often used to provide forecasts of the resulting contaminant dispersion affecting the population. These forecasts should also be accompanied by accurate estimates of the forecast uncertainty to allow for more informed decisions about the potential hazardous area. This study examines the calculation of uncertainty in the meteorological data as derived from an ensemble, and its effects when used as additional input to drive an ATD model. The first part of the study examines the capability of a linear function to relate ensemble spread to error variance of the ensemble mean given ensemble spread from 24 days of forecasts from the National Centers for Environmental Prediction (NCEP) Short-Range Ensemble Forecast (SREF). This linear function can then be used to calibrate the ensemble spread to produce a more accurate estimate of the meteorological uncertainty. Results for the linear relationship of wind variance are very good, with values of the coefficient of determination R2 generally exceeding 0.94 for forecast lengths of 12 h and greater. The calibration is shown to be more sensitive to forecast hour than vertical level within the lower troposphere. The second part presents a 24-h case study to assess the impact of meteorological uncertainty calculations on Second-Order Closure Integrated Puff (SCIPUFF) ATD model predictions. Both uncalibrated ensemble wind variances and wind variances calibrated based on the results of the first part show improvement in mean concentration forecasts relative to a control experiment using the default hazard mode uncertainty when compared with a baseline SCIPUFF integration based on a high-resolution dynamic analysis of the meteorological conditions. The SCIPUFF experiments that use a wind variance calibration show both qualitative and quantitative improvement in most of the mean concentrations and patterns over the control experiment and the SCIPUFF experiment using uncalibrated wind variances. The SCIPUFF experiments using meteorological ensemble uncertainty information also produce mean concentrations and patterns that compare favorably to those of an explicit SCIPUFF ensemble based on each SREF member. Use of the uncalibrated variance information within a single ATD prediction produces mean ATD predictions most similar to those of the explicit ATD ensemble, and use of calibrated ensemble variance is shown to have some advantages over the explicit ATD ensemble.

Evaluating wind fields from a diagnostic model over complex terrain in the Phoenix region and implications to dispersion calculations for regional emergency response

AbstractThis paper compares the wind field from a diagnostic model (CALMET) over complex terrain in the Phoenix region in the USA with observations that are gridded by a state‐of‐the‐art Four‐Dimensional Data Assimilation (FDDA) system. The wind difference between the CALMET and FDDA wind fields is larger at night than in the day. The magnitude of the wind difference can be smaller than 5% of the mean wind speed at low levels in areas with dense observational stations, while it can be larger than 80% in areas without observational stations or at high altitudes. The vector‐mean wind direction difference over the domain is 15° on the surface level and 25° between 10 and 1500 m. To evaluate the effects of the wind difference on dispersion calculations, dispersion of a hypothetical passive tracer released from surface point sources is simulated by the second‐order closure integrated puff (SCIPUFF) model driven by the CALMET and FDDA wind fields, respectively. Differences in the two simulated tracer concentration fields increase with time due to accumulation of effects of the wind differences both near the surface and at higher altitudes. Even for release in the area with the densest distribution of surface stations, the relative difference in the peak surface concentration from CALMET‐SCIPUFF and from FDDA‐SCIPUFF is less than 10% only within 0.5 h after the release in the afternoon, and increases to 70% at 1.5 h; this is because of large differences in wind above the surface. For release in the area with few stations, the difference can be larger than 100% or even larger after 1.5 h from the release. To improve dispersion simulations driven by the CALMET wind in the region, observations at upper‐air stations are needed and the current surface observation network needs to be reorganized or more stations are needed to account for the influence of terrain. Copyright © 2009 Royal Meteorological Society

Source Characterization with a Genetic Algorithm–Coupled Dispersion–Backward Model Incorporating SCIPUFF

Abstract This paper extends the approach of coupling a forward-looking dispersion model with a backward model using a genetic algorithm (GA) by incorporating a more sophisticated dispersion model [the Second-Order Closure Integrated Puff (SCIPUFF) model] into a GA-coupled system. This coupled system is validated with synthetic and field experiment data to demonstrate the potential applicability of the coupled model to emission source characterization. The coupled model incorporating SCIPUFF is first validated with synthetic data produced by SCIPUFF to isolate issues related directly to SCIPUFF’s use in the coupled model. The coupled model is successful in characterizing sources even with a moderate amount of white noise introduced into the data. The similarity to corresponding results from previous studies using a more basic model suggests that the GA’s performance is not sensitive to the dispersion model used. The coupled model is then tested using data from the Dipole Pride 26 field tests to determine its ability to characterize actual pollutant measurements despite the stochastic scatter inherent in turbulent dispersion. Sensitivity studies are run on various input parameters to gain insight used to produce a multistage process capable of a higher-quality source characterization than that produced by a single pass. Overall, the coupled model performed well in identifying approximate locations, times, and amounts of pollutant emissions. These model runs demonstrate the coupled model’s potential application to source characterization for real-world problems.

An evaluation of three diagnostic wind models (CALMET, MCSCIPUF, and SWIFT) with wind data from the Dipole Pride 26 field experiments

AbstractThis paper describes the evaluation of three diagnostic wind models by direct comparison with wind field data. The models are the California Meteorological Model (CALMET), the Mass Consistent model (MCSCIPUF) associated with the Second Order Closure Integrated Puff (SCIPUFF) transport/dispersion model, and the Stationary Wind Field and Turbulence (SWIFT) model. The evaluation follows previous works by Chang, Franzese & Hanna, who compared the same three models, and by Bradley & Mazzola who evaluated SWIFT coupled with SCIPUFF. As with SWIFT, MCSCIPUF is incorporated in the Hazard Prediction and Assessment Capability (HPAC), while CALMET is linked with the California Puff model (CALPUFF), another transport and dispersion model. The Dipole Pride 26 (DP26) experiments, performed at the US Department of Energy (DOE) Nevada Test Site, are used as the source of the wind data. They provide a comprehensive set of meteorological data with wide‐ranging atmospheric stability conditions over a complex terrain. Model calculations were compared with measured data in two phases. The first phase uses complete sets of data from eight locations (the 8M phase) as model inputs, and thus tests the ability of the models to reproduce input conditions. In the second phase, five of the measured wind sites are withheld from input, and instead used for validation of model calculations (the 3M phase). In the first phase, the errors were found (with some exceptions) to be quite small. In the second phase, mean absolute errors were found to be of the order of 1ms−1 and 30°, with only small differences among models in terms of performance. Copyright © 2005 Royal Meteorological Society

Evaluation of Interregional Transport Using the MM5–SCIPUFF System

Abstract Improved understanding of transport issues and source–receptor relationships on the interregional scale is dependent on reducing the uncertainties in the ability to define complex three-dimensional wind fields evolving in time. The numerical models used for this purpose have been upgraded substantially in recent years by introducing finer grid resolution, better representation of subgrid-scale physics, and practical four-dimensional data assimilation (FDDA) techniques that reduce the accumulation of errors over time. The impact of these improvements for interregional transport is investigated in this paper using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) and the Second-Order Closure Integrated Puff (SCIPUFF) dispersion model to simulate the 1983 Cross-Appalachian Tracer Experiment (CAPTEX-83) episode 1 of 18–19 September 1983. Combining MM5 and SCIPUFF makes it possible to verify predicted tracer concentrations against observed surface concentrations collected during the CAPTEX-83 study. Conclusions from this study are as follows. 1) Not surprisingly, a baseline model configuration reflecting typical capabilities of the late 1980s (70-km horizontal grid, 15 vertical layers, older subgrid physics, and no FDDA) produced large meteorological errors that severely degraded the accuracy of the surface tracer concentrations predicted by SCIPUFF. 2) Improving the horizontal and vertical resolution of the MM5 to 12 km (typical for current operational model) and 32 layers led to some improvements in the statistical skill, but the further addition of more advanced physics produced much greater reductions of simulation errors. 3) The use of FDDA, along with 12-km resolution and improved physics, produced the overall best performance. 4) Further reduction of the horizontal grid size to 4 km had a detrimental effect on meteorological and plume-dispersion solutions in this case because of misrepresentation of convection associated with a cold front by the MM5's explicit moist physics.

Comparison of atmospheric transport calculations over complex terrain using a mobile profiling system and rawinsondes

AbstractA comparison of atmospheric transport and dispersion calculations over complex terrain was investigated using a mobile profiling system (MPS) versus standard meteorological balloons. Meteorological and sulfur hexafluoride (SF6) concentration data were collected and used to evaluate the performance of a transport and diffusion model coupled with a mass consistency wind field model. Meteorological data were collected throughout April 1995, and parts of August 1995. Both meteorological and concentration data were measured in December 1995. Once the models were validated, the comparison of performance with different upper‐air data were accomplished. The models used included the SCIPUFF (Second‐order Closure Integrated Puff) transport and diffusion model and the MINERVE mass consistency wind model. Evaluation of the models was focused primarily on their effectiveness as a short‐term (one to four hours) predictive tool. These studies showed how the combination of weather and transport models could be used to help direct emergency response following a hazardous material release. The models were used in tandem to direct the deployment of mobile sensors intended to intercept and measure tracer clouds. The MINERVE model was validated for the specific terrain of interest using April 1995 data. The capability of SCIPUFF driven by realistic three‐dimensional wind fields generated by MINERVE is demonstrated using data collected in December 1995. Copyright © 2000 Royal Meteorological Society

Wind and Diffusion Modeling for Complex Terrain

Abstract Atmospheric transport and dispersion over complex terrain were investigated. Meteorological and sulfur hexafluoride (SF6) concentration data were collected and used to evaluate the performance of a transport and diffusion model coupled with a mass consistency wind field model. Meteorological data were collected throughout April 1995. Both meteorological and plume location and concentration data were measured in December 1995. The meteorological data included measurements taken at 11–15 surface stations, one to three upper-air stations, and one mobile profiler. A range of conditions was encountered, including inversion and postinversion breakup, light to strong winds, and a broad distribution of wind directions. The models used were the MINERVE mass consistency wind model and the SCIPUFF (Second-Order Closure Integrated Puff) transport and diffusion model. These models were expected to provide and use high-resolution three-dimensional wind fields. An objective of the experiment was to determine if...