scholarly journals Modelo euleriano semi-analítico para a dispersão de contaminantes na Camada Limite Planetária

2000 ◽  
pp. 113
Author(s):  
Davidson M. Moreira ◽  
Angela B. D. Moura ◽  
Marco T. de Vilhena ◽  
Gervásio Annes Degrazia
Keyword(s):  
Wind Speed ◽  
Dispersion Model ◽  
Model Performance ◽  
Eddy Diffusivity ◽  
Advection Equation ◽  
Average Value ◽  
Prairie Grass ◽  
The Laplace Transform ◽  
Quality Dispersion ◽  
Semi Empirical

An analytical air quality dispersion model based on a discretization of the planetary boundary layer in N sub-layers is presented. In each sub-layer the diffusion-advection equation is solved by the Laplace Transform techniques, considering an average value for the vertical exchange coefficient and the wind speed. As a consequence, the present approach allows to employ realistic semi-empirical profiles for the eddy diffusivity and wind speed, in such manner that the inhomogeneous turbulence can be handle. The model performance have been evaluated using the well-known Copenhagen and Prairie Grass datasets. Then, the application of the statistical evalution procedure (Hanna, 1989) over the out coming results has show that the proposed analytical dispersion model produces a good fitting of the observational data.

Highly accurate analytical footprint model for general stratification of the atmosphere

2020 ◽  
Author(s):  
Jean-Claude Krapez ◽  
Gregoire Ky ◽  
Claire Sarrat
Keyword(s):  
Wind Speed ◽  
Power Law ◽  
Dispersion Model ◽  
Source Area ◽  
Eddy Diffusivity ◽  
Particle Dispersion ◽  
Accurate Estimation ◽  
Remotely Sensed Data ◽  
Footprint Model ◽  
Advection Term

<p>The flux footprint (or so-called source area) is the zone of the surface that contributes to a measured vertical flux (e.g. of water vapor or carbon dioxide) between the ground and the atmosphere: Footprint models are then used to derive location and size of the source area and for interpretation of flux-tower measurements, in particular to estimate the contribution of passive scalar sources to these measured fluxes, and to combine measured fluxes with remotely sensed data.</p><p>Existing footprint models are of two types: either they derive from the solution of an advection-diffusion differential equation or they result from a parameterization based on numerical simulations performed with a Lagrangian stochastic particle dispersion model. Models of the first type are essentially based on the hypothesis of power-law profiles of the mean wind speed u(z) and eddy diffusivity K(z). Our objective was to suppress this constraint and to build a footprint model for any type of profile, in particular Monin-Obukhov surface-layer profiles.</p><p>The model was developed in the frame of the K-theory. Homogeneous conditions were assumed in the horizontal plane and the alongwind diffusion term was neglected with respect to the advection term. A semi-analytical tool has been developed to cope with any type of atmosphere stratification. Applying a dedicated quadrupole method, the boundary layer is divided into a series of sublayers and an extended power law model is applied in each of them (10 to 15 sublayers are enough to reach an error of less than 0.1%, whatever the atmosphere stability).</p><p>In the end, a highly accurate estimation of the footprint can be obtained very quickly for any profile of wind speed and eddy diffusivity.</p>

scholarly journals A quasi-experimental coastal region eddy diffusivity applied in the APUGRID model

2020 ◽  
Vol 38 (3) ◽  
pp. 603-610
Author(s):  
Silvana Maldaner ◽  
Michel Stefanello ◽  
Luis Gustavo N. Martins ◽  
Gervásio Annes Degrazia ◽  
Umberto Rizza ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Sonic Anemometer ◽  
Coastal Region ◽  
Eddy Diffusivity ◽  
Turbulent Dispersion ◽  
Southeastern Brazil ◽  
Advection Equation ◽  
Concentration Data ◽  
Eddy Diffusivities ◽  
Quasi Experimental

Abstract. In this study, Taylor statistical diffusion theory and sonic anemometer measurements collected at 11 levels on a 140 m high tower located in a coastal region in southeastern Brazil have been employed to obtain quasi-empirical convective eddy diffusivity parameterizations in a planetary boundary layer (PBL). The derived algebraic formulations expressing the eddy diffusivities were introduced into an Eulerian dispersion model and validated with Copenhagen tracer experiments. The employed Eulerian model is based on the numerical solution of the diffusion–advection equation by the fractional step/locally one-dimensional (LOD) methods. Moreover, the semi-Lagrangian cubic-spline technique and Crank–Nicolson implicit scheme are considered to solve the advection and diffusive terms. The numerical simulation results indicate that the new approach, based on these quasi-experimental eddy diffusivities, is able to reproduce the Copenhagen concentration data. Therefore, the new turbulent dispersion parameterization can be applied in air pollution models.

A MODEL FOR THE SIMULATION OF CROSSWIND INTEGRATED CONCENTRATIONS IN THE SURFACE-BASED INVERSION LAYER

2012 ◽  
Vol 03 (04) ◽  
pp. 1250017
Author(s):  
MANISH MODANI ◽  
MAITHILI SHARAN
Keyword(s):  
Wind Speed ◽  
Numerical Models ◽  
Dispersion Model ◽  
Inversion Layer ◽  
Delta Function ◽  
Eddy Diffusivity ◽  
Analytical Models ◽  
Dirac Delta ◽  
Proposed Model ◽  
Functional Forms

A dispersion model for the estimation of crosswind integrated concentrations in the surface-based inversion is proposed. The generalized forms of eddy diffusivity with spatial dependence in both horizontal and vertical directions and vertical height-dependent wind speed are considered. In view of the computational limitation associated with numerical models for Dirac-delta function, the source term is expressed as a limiting case of normal distribution. The accuracy of the employed numerical scheme to solve the resulting partial differential equation with appropriate physically relevant boundary conditions is checked with those obtained from the respective analytical solutions available in literature for the particular forms of eddy diffusivity and wind speed. Concentrations computed from the proposed model are found close to those obtained from analytical models. The concentrations obtained from the proposed model are evaluated for the generalized functional forms of eddy diffusivity (Degrazia and Moraes, 1992; Degrazia et al., 2001) and diabatic logarithmic profile as well as power-law profile of wind speed with the observations from Hanford (Doran et al., 1984) and Copenhagen (Gryning and Lyck, 1984) diffusion experiments in stable and unstable conditions, respectively. Majority of the cases i.e., 64% and 96% are predicted in factor of two to observations in both stable and unstable conditions, respectively.

scholarly journals TURBULENT EDDY DIFFUSIVITIES FOR A PLANETARY BOUNDARY LAYER GENERATED BY THERMAL AND MECHANICAL EFFECTS

2013 ◽  
Vol 31 (4) ◽  
pp. 609 ◽  
Author(s):  
André Becker Nunes ◽  
Gervásio Annes Degrazia ◽  
Cláudia Rejane Jacondino De Campos ◽  
Davidson Martins Moreira
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Mean Squared Error ◽  
Dispersion Model ◽  
Eddy Diffusivity ◽  
Advection Equation ◽  
Turbulent Eddy ◽  
Mechanical Effects ◽  
Boundary Layer Turbulence ◽  
Eddy Diffusivities

ABSTRACT. To estimate the superficial concentration of contaminants an eulerian model of dispersion was used, where the main scheme is the diffusion-advection equation that employs turbulent eddy diffusivity. The aim of this work is a comparison between different eddy diffusivity derivations for a planetary boundary layer turbulence generated by thermal and mechanical effects. The accuracy of eddy diffusivity derivations was evaluated by comparing the data simulated in the eulerian dispersion model and the observed concentrations of the Copenhagen and Praire Grass experiments. Three convective eddy diffusivity derivations were compared among themselves: 1) proposed by Degrazia et al., 2) proposed Hostlag & Moeng and 3) the derivation gotten by the parameters of Hanna. Two neutral eddy diffusivity derivations were also compared: 1) proposed by Degrazia et al. and 2) gotten by the parameters of Hanna. In order to improve the comparisons some adjustments and increments were made in Hostlag & Moeng derivation and in that gotten by the parameters of Hanna. We can observe that despite the eddy diffusivities having been formulated by different ways, the results were similar and sufficiently satisfactory. In the convective case, the best simulations of each derivation showed a Normalized Mean Squared Error between 0.04 and 0.05 when compared with Copenhagen dataset.Keywords: dispersion model, Taylor theory, lagrangean timescale. RESUMO. Na estimativa da concentração superficial de contaminantes foi usado um modelo de dispersão euleriano, tendo como esquema principal a equação de difusão-advecção que emprega coeficiente de difusão turbulento. O objetivo deste trabalho é a comparação entre diferentes derivações de coeficientes de difusão para uma camada limite planetária cuja turbulência é gerada por fatores térmicos e mecânicos. A precisão das derivações foi calculada por meio da comparação entre os dados simulados pelo modelo euleriano de dispersão e os dados de concentração observados nos experimentos de Copenhagen e Praire Grass. Três derivações de coeficientes de difusão convectivos foram comparadas: 1) a proposta por Degrazia et al., 2) a proposta por Hostlag & Moeng, e 3) a derivação obtida através dos parâmetros de Hanna. Também foram comparadas duas derivações de coeficientes de difusão neutros: 1) uma proposta por Degrazia et al. e 2) a obtida por meio dos parâmetros de Hanna. Para uma melhor comparação, foram feitos alguns ajustes nas derivações de Hostlag e Moeng e na obtida através dos parâmetros de Hanna. Pode-se observar que apesar das derivações serem obtidas por diferentes metodologias, os resultados foram similares e suficientemente satisfatórios. Para o caso convectivo, as melhores simulações de cada derivação apresentaram Erro Quadrático Médio Normalizado entre 0,04 e 0,05 quando comparados com os dados do experimento de Copenhagen.Palavras-chave: modelo de dispersão, teoria de Taylor, escala de tempo lagrangeana.

scholarly journals Toward reduced transport errors in a high resolution urban CO2 inversion system

Elem Sci Anth ◽  
2017 ◽  
Vol 5 ◽  
Author(s):  
Aijun Deng ◽  
Thomas Lauvaux ◽  
Kenneth J. Davis ◽  
Brian J. Gaudet ◽  
Natasha Miles ◽  
...  
Keyword(s):  
High Resolution ◽  
Wind Speed ◽  
Dispersion Model ◽  
Model Performance ◽  
Absolute Error ◽  
Particle Dispersion ◽  
Bias Reduction ◽  
Meteorological Observation ◽  
Inverse Results ◽  
The Impact

We present a high-resolution atmospheric inversion system combining a Lagrangian Particle Dispersion Model (LPDM) and the Weather Research and Forecasting model (WRF), and test the impact of assimilating meteorological observation on transport accuracy. A Four Dimensional Data Assimilation (FDDA) technique continuously assimilates meteorological observations from various observing systems into the transport modeling system, and is coupled to the high resolution CO2 emission product Hestia to simulate the atmospheric mole fractions of CO2. For the Indianapolis Flux Experiment (INFLUX) project, we evaluated the impact of assimilating different meteorological observation systems on the linearized adjoint solutions and the CO2 inverse fluxes estimated using observed CO2 mole fractions from 11 out of 12 communications towers over Indianapolis for the Sep.-Nov. 2013 period. While assimilating WMO surface measurements improved the simulated wind speed and direction, their impact on the planetary boundary layer (PBL) was limited. Simulated PBL wind statistics improved significantly when assimilating upper-air observations from the commercial airline program Aircraft Communications Addressing and Reporting System (ACARS) and continuous ground-based Doppler lidar wind observations. Wind direction mean absolute error (MAE) decreased from 26 to 14 degrees and the wind speed MAE decreased from 2.0 to 1.2 m s–1, while the bias remains small in all configurations (< 6 degrees and 0.2 m s–1). Wind speed MAE and ME are larger in daytime than in nighttime. PBL depth MAE is reduced by ~10%, with little bias reduction. The inverse results indicate that the spatial distribution of CO2 inverse fluxes were affected by the model performance while the overall flux estimates changed little across WRF simulations when aggregated over the entire domain. Our results show that PBL wind observations are a potent tool for increasing the precision of urban meteorological reanalyses, but that the impact on inverse flux estimates is dependent on the specific urban environment.

scholarly journals A quasi-experimental coastal region eddy diffusivity applied in the APUGRID model

2019 ◽  
Author(s):  
Silvana Maldaner ◽  
Michel Stefanello ◽  
Luis Gustavo N. Martins ◽  
Gervásio Annes Degrazia ◽  
Umberto Rizza ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Sonic Anemometer ◽  
Coastal Region ◽  
Eddy Diffusivity ◽  
Turbulent Dispersion ◽  
Southeastern Brazil ◽  
Advection Equation ◽  
Concentration Data ◽  
Eddy Diffusivities ◽  
Quasi Experimental

Abstract. In this study, Taylor statistical diffusion theory and sonic anemometer measurements collected at 11 levels on a 140-m high tower located at a coastal region in southeastern Brazil have been employed to obtain quasi-empirical convective eddy diffusivity parameterizations in a planetary boundary layer (PBL). The derived algebraic formulations expressing the eddy diffusivities were introduced into an Eulerian dispersion model and validated with Copenhagen tracer experiments. The employed Eulerian model is based on the numerical solution of the diffusion-advection equation by the Fractional Step/Locally One-Dimensional (LOD) methods. Moreover, the semi-Lagrangian cubic-spline technique and Crank-Nicholson implicit scheme are considered to solve the advection and diffusive terms. The numerical simulation results indicate that the new approach, based on these quasi-experimental eddy diffusivities, is able to reproduce the Copenhagen concentration data. Therefore, the new turbulent dispersion parameterization can be applied in air pollution models.

scholarly journals Eddy diffusivity derived from drifter data for dispersion model applications

2012 ◽  
Vol 62 (9) ◽  
pp. 1381-1398 ◽  
Author(s):  
Michela De Dominicis ◽  
Giovanni Leuzzi ◽  
Paolo Monti ◽  
Nadia Pinardi ◽  
Pierre-Marie Poulain
Keyword(s):  
Dispersion Model ◽  
Eddy Diffusivity

scholarly journals Wind turbine wake models' evaluation for different downstream locations

2021 ◽  
Vol 6 ◽  
pp. 40
Author(s):  
Panagiotis Triantafyllou ◽  
John K. Kaldellis
Keyword(s):  
Wind Speed ◽  
Research Work ◽  
Past Research ◽  
Wake Flow ◽  
Wake Effect ◽  
Calculation Results ◽  
Wind Park ◽  
Semi Empirical ◽  
Turbine Wake ◽  
Streamwise Distance

The land use limitations, especially for onshore applications, have led modern Wind Turbines (WTs) to be aggregated in wind parks under the scope of minimizing the necessary area required. Within this framework, the trustworthy prediction of the wind speed deficiency downstream the WTs' hub (known also as the “wake effect”) and the meticulous wind park micrositing are of uppermost importance for the optimized WTs siting across the available land area. In this context, substantial effort has been made by the academic and research community, contributing to the deployment of several analytical, numerical and semi-empirical wake models, attempting to estimate the wind speed values at different locations downstream a WT. The accuracy of several semi-empirical and analytical wake models, serving also as the basis for pertinent commercial software development, is investigated in the present work, by comparing their outcome with experimental data from a past research work that concerns the wake flow. The dimensionless streamwise distance (known also with the term “downstream distance”) from the WT's hub is used as benchmark in order to categorize and evaluate the calculation results. A dedicated comparison between the wind speed cases investigated is conducted, striving to properly assess the wake models' prediction accuracy. The notable findings obtained for the wake models examined designate the requirement for subsequent research to enlighten the wake effect dynamic behavior.

scholarly journals Generating wind power scenarios for probabilistic ramp event prediction using multivariate statistical post-processing

2018 ◽  
Author(s):  
Rochelle P. Worsnop ◽  
Michael Scheuerer ◽  
Thomas M. Hamill ◽  
Julie K. Lundquist
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Farm ◽  
Weather Prediction ◽  
Model Performance ◽  
The United States ◽  
Numerical Weather Prediction Model ◽  
Post Processing ◽  
Skill Scores ◽  
Ramp Events

Abstract. Wind power forecasting is gaining international significance as more regions promote policies to increase the use of renewable energy. Wind ramps, large variations in wind power production during a period of minutes to hours, challenge utilities and electrical balancing authorities. A sudden decrease in wind energy production must be balanced by other power generators to meet energy demands, while a sharp increase in unexpected production results in excess power that may not be used in the power grid, leading to a loss of potential profits. In this study, we compare different methods to generate probabilistic ramp forecasts from the High Resolution Rapid Refresh (HRRR) numerical weather prediction model with up to twelve hours of lead time at two tall-tower locations in the United States. We validate model performance using 21 months of 80-m wind speed observations from towers in Boulder, Colorado and near the Columbia River Gorge in eastern Oregon. We employ four statistical post-processing methods, three of which are not currently used in the literature for wind forecasting. These procedures correct biases in the model and generate short-term wind speed scenarios which are then converted to power scenarios. This probabilistic enhancement of HRRR point forecasts provides valuable uncertainty information of ramp events and improves the skill of predicting ramp events over the raw forecasts. We compute Brier skill scores for each method at predicting up- and down-ramps to determine which method provides the best prediction. We find that the Standard Schaake Shuffle method yields the highest skill at predicting ramp events for these data sets, especially for up-ramp events at the Oregon site. Increased skill for ramp prediction is limited at the Boulder, CO site using any of the multivariate methods, because of the poor initial forecasts in this area of complex terrain. These statistical methods can be implemented by wind farm operators to generate a range of possible wind speed and power scenarios to aid and optimize decisions before ramp events occur.

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