scholarly journals Employing Spectral Analysis to Obtain Dispersion Parameters in an Atmospheric Environment Driven by a Mesoscale Downslope Windstorm

Author(s):  
Cinara Ewerling da Rosa ◽  
Michel Stefanello ◽  
Silvana Maldaner ◽  
Douglas Stefanello Facco ◽  
Débora Regina Roberti ◽  
...  

Considering the influence of the downslope windstorm called “Vento Norte” (VNOR; Portuguese for “North Wind”) in planetary boundary layer turbulent features, a new set of turbulent parameterizations, which are to be used in atmospheric dispersion models, has been derived. Taylor’s statistical diffusion theory, velocity spectra obtained at four levels (3, 6, 14, and 30 m) in a micrometeorological tower, and the energy-containing eddy scales are used to calculate neutral planetary boundary layer turbulent parameters. Vertical profile formulations of the wind velocity variances and Lagrangian decorrelation time scales are proposed, and to validate this new parameterization, it is applied in a Lagrangian Stochastic Particle Dispersion Model to simulate the Prairie Grass concentration experiments. The simulated concentration results were shown to agree with those observed.

2009 ◽  
Vol 9 (10) ◽  
pp. 3371-3383 ◽  
Author(s):  
J. Cui ◽  
M. Sprenger ◽  
J. Staehelin ◽  
A. Siegrist ◽  
M. Kunz ◽  
...  

Abstract. The particle dispersion model FLEXPART and the trajectory model LAGRANTO are Lagrangian models which are widely used to study synoptic-scale atmospheric air flows such as stratospheric intrusions (SI) and intercontinental transport (ICT). In this study, we focus on SI and ICT events particularly from the North American planetary boundary layer for the Jungfraujoch (JFJ) measurement site, Switzerland, in 2005. Two representative cases of SI and ICT are identified based on measurements recorded at Jungfraujoch and are compared with FLEXPART and LAGRANTO simulations, respectively. Both models well capture the events, showing good temporal agreement between models and measurements. In addition, we investigate the performance of FLEXPART and LAGRANTO on representing SI and ICT events over the entire year 2005 in a statistical way. We found that the air at JFJ is influenced by SI during 19% (FLEXPART) and 18% (LAGRANTO), and by ICT from the North American planetary boundary layer during 13% (FLEXPART) and 12% (LAGRANTO) of the entire year. Through intercomparsion with measurements, our findings suggest that both FLEXPART and LAGRANTO are well capable of representing SI and ICT events if they last for more than 12 h, whereas both have problems on representing short events. For comparison with in-situ observations we used O3 and relative humidity for SI events. As parameters to trace ICT events we used a combination of NOy/CO and CO, however these parameters are not specific enough to distinguish aged air masses by their source regions. Moreover, a sensitivity study indicates that the agreement between models and measurements depends significantly on the threshold values applied to the individual control parameters. Generally, the less strict the thresholds are, the better the agreement between models and measurements. Although the dependence of the agreement on the threshold values is appreciable, it nevertheless confirms the conclusion that both FLEXPART and LAGRANTO are well able to capture SI and ICT events with duration longer than 12 h.


2009 ◽  
Vol 9 (1) ◽  
pp. 1447-1487
Author(s):  
J. Cui ◽  
M. Sprenger ◽  
J. Staehelin ◽  
A. Siegrist ◽  
M. Kunz ◽  
...  

Abstract. The particle dispersion model FLEXPART and the trajectory model LAGRANTO are Lagrangian models which are widely used to study synoptic-scale atmospheric air flows such as stratospheric intrusions (SI) and intercontinental transport (ICT). In this study, we focus on SI and ICT events particularly from the North American planetary boundary layer for the Jungfraujoch (JFJ) measurement site, Switzerland, in 2005. Two representative cases of SI and ICT are identified based on measurements recorded at Jungfraujoch and are compared with FLEXPART and LAGRANTO simulations, respectively. Both models well capture the events, showing good temporal agreement between models and measurements. In addition, we investigate the performance of FLEXPART and LAGRANTO on representing SI and ICT events over the entire year 2005 in a statistical way. We found that the air at JFJ is influenced by SI during 19% (FLEXPART) and 18% (LAGRANTO), and by ICT from the North American planetary boundary layer during 13% (FLEXPART) and 12% (LAGRANTO) of the entire year. Through intercomparsion with measurements, our findings suggest that both FLEXPART and LAGRANTO are well capable of representing SI and ICT events if they last for more than 12 h, whereas both have problems on representing short events. It is also shown that although the long-range transported air is characterized by relatively low NOy/CO ratios and elevated CO concentrations, using a combination of NOy/CO and CO as control parameters still encounters difficulty in distinguishing aged air masses by their source regions. Moreover, a sensitivity study indicates that the agreement between models and measurements depends significantly on the threshold values applied to the individual control parameters. Generally, the less strict the thresholds are, the better the agreement between models and measurements. Although the dependence of the agreement on the threshold values is appreciable, it nevertheless confirms the conclusion that both FLEXPART and LAGRANTO are well able to capture SI and ICT events with sustaining time longer than 12 h.


Author(s):  
Yuanwei Ma ◽  
Dezhong Wang ◽  
Zhilong Ji ◽  
Nan Qian

In atmospheric dispersion models of nuclear accident, the empirical dispersion coefficients were obtained under certain experiment conditions, which is different from actual conditions. This deviation brought in the great model errors. A better estimation of the radioactive nuclide’s distribution could be done by correcting coefficients with real-time observed value. This reverse problem is nonlinear and sensitive to initial value. Genetic Algorithm (GA) is an appropriate method for this correction procedure. Fitness function is a particular type of objective function to achieving the set goals. To analysis the fitness functions’ influence on the correction procedure and the dispersion model’s forecast ability, four fitness functions were designed and tested by a numerical simulation. In the numerical simulation, GA, coupled with Lagrange dispersion model, try to estimate the coefficients with model errors taken into consideration. Result shows that the fitness functions, in which station is weighted by observed value and by distance far from release point, perform better when it exists significant model error. After performing the correcting procedure on the Kincaid experiment data, a significant boost was seen in the dispersion model’s forecast ability.


2021 ◽  
Vol 14 (4) ◽  
pp. 2205-2220
Author(s):  
Matthias Faust ◽  
Ralf Wolke ◽  
Steffen Münch ◽  
Roger Funk ◽  
Kerstin Schepanski

Abstract. Trajectory models are intuitive tools for airflow studies. But in general, they are limited to non-turbulent, i.e. laminar flow, conditions. Therefore, trajectory models are not particularly suitable for investigating airflow within the turbulent atmospheric boundary layer. To overcome this, a common approach is handling the turbulent uncertainty as a random deviation from a mean path in order to create a statistic of possible solutions which envelops the mean path. This is well known as the Lagrangian particle dispersion model (LPDM). However, the decisive factor is the representation of turbulence in the model, for which widely used models such as FLEXPART and HYSPLIT use an approximation. A conceivable improvement could be the use of a turbulence parameterisation approach based on the turbulent kinetic energy (TKE) at high temporal resolution. Here, we elaborated this approach and developed the LPDM Itpas, which is coupled online to the German Weather Service's mesoscale weather forecast model COSMO. It benefits from the prognostically calculated TKE as well as from the high-frequency wind information. We demonstrate the model's applicability for a case study on agricultural particle emission in eastern Germany. The results obtained are discussed with regard to the model's ability to describe particle transport within a turbulent boundary layer. Ultimately, the simulations performed suggest that the newly introduced method based on prognostic TKE sufficiently represents the particle transport.


2018 ◽  
Vol 57 (1) ◽  
pp. 185-192 ◽  
Author(s):  
Davidson Moreira ◽  
Marcelo Moret

AbstractIn this study, an analytical solution for the steady-state fractional advection–diffusion equation was obtained to simulate the atmospheric dispersion of pollutants in a vertically inhomogeneous planetary boundary layer. The authors propose a method that uses the modified generalized integral Laplace transform technique to solve the transformed problem with a fractional derivative, resulting in a more general solution. The model results were compared with the fractional Gaussian model and demonstrate that, when considering an experimental dataset under moderately unstable conditions, fractional-derivative models perform better than traditional integer-order models.


2004 ◽  
Vol 61 (23) ◽  
pp. 2877-2887 ◽  
Author(s):  
Jeffrey C. Weil ◽  
Peter P. Sullivan ◽  
Chin-Hoh Moeng

Abstract A Lagrangian dispersion model driven by velocity fields from large-eddy simulations (LESs) is presented for passive particle dispersion in the planetary boundary layer (PBL). In this combined LES–Lagrangian stochastic model (LSM), the total velocity is divided into resolved or filtered and unresolved or subfilter-scale (SFS) velocities. The random SFS velocity is modeled using an adaptation of Thomson's LSM in which the ensemble-mean velocity and velocity variances are replaced by the resolved velocity and SFS variances, respectively. The random SFS velocity forcing has an amplitude determined by the SFS fraction of the total turbulent kinetic energy (TKE); the fraction is about 0.15 in the bulk of the simulated convective boundary layer (CBL) used here and reaches values as large as 0.31 and 0.37 in the surface layer and entrainment layer, respectively. For the proposed LES–LSM, the modeled crosswind-integrated concentration (CWIC) fields are in good agreement with the 1) surface-layer similarity (SLS) theory for a surface source in the CBL and 2) convection tank measurements of the CWIC for an elevated release in the CBL surface layer. The second comparison includes the modeled evolution of the vertical profile shape with downstream distance, which shows the attainment of an elevated CWIC maximum and a vertically well-mixed CWIC far downstream, in agreement with the tank data. For the proposed model, the agreement with the tank data and SLS theory is better than that obtained with an earlier model in which the SFS fraction of the TKE is assumed to be 1, and significantly better than a model that neglects the SFS velocities altogether.


2020 ◽  
Author(s):  
Matthias Faust ◽  
Ralf Wolke ◽  
Steffen Münch ◽  
Roger Funk ◽  
Kerstin Schepanski

Abstract. Trajectory models are intuitive tools for airflow studies. But in general, they are limited to non-turbulent, i.e. laminar flow conditions. Therefore, trajectory models are not particularly suitable for investigating airflow within the turbulent atmospheric boundary layer. To overcome this, a common approach is handling the turbulent uncertainty as a random deviation from a mean path in order to create a statistic of possible solutions which envelops the mean path. This is well known as Lagrangian particle dispersion model (LPDM). However, the decisive factor is the representation of turbulence in the model, for which widely used models such as FLEXPART and HYSPLIT use an approximation. A conceivable improvement can be using a turbulence parameterisation approach based on the turbulent kinetic energy (TKE) on high temporal resolution. Here, we elaborated this approach and developed the LPDM Itpas, which is online coupled to the German Weather Service's mesoscale weather forecast model COSMO. It allows for benefiting from the prognostically calculated TKE as well as from the high-frequent wind information. We exemplary demonstrate the model's applicability for a case study on agricultural particle emission in Eastern Germany. The results obtained are discussed with regard to the model's ability to describe particle transport within a turbulent boundary layer. Ultimately, the simulations performed suggest that the newly introduced method based on prognostic TKE sufficiently represents the particle transport.


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