Sensitivity of air quality model prediction to parameterization of vertical eddy diffusivity

Han, Zhiwei; Zhang, Meigen; An, Junling

doi:10.1007/s10652-008-9088-1

Cited by 6 publications

(3 citation statements)

References 25 publications

(32 reference statements)

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“…Lee et al [32] studied the importance of h, K z and its parameterization approach on the surface concentration of ozone. Their study reiterated the findings of many other recent investigations [33,34], described in detail later, that the entire diurnal evolution of the PBL, from its nocturnal shallowness to its increase to a maximum late-afternoon depth, are contributing factors to the surface concentrations of airborne pollutants. In Section 2, we will discuss the PBL modeling approaches of the selected five AQ models.…”

Section: Introductionsupporting

confidence: 59%

Coupling of Important Physical Processes in the Planetary Boundary Layer between Meteorological and Chemistry Models for Regional to Continental Scale Air Quality Forecasting: An Overview

Lee

Ngan

2011

Atmosphere

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A consensus among many Air Quality (AQ) modelers is that planetary boundary layer processes are the most influential processes for surface concentrations of air pollutants. Due to the many uncertainties intrinsically embedded in the parameterization of these processes, parameter optimization is often employed to determine an optimal set or range of values of the sensitive parameters. In this review study, we focus on the two of the most important physical processes: turbulent mixing and dry deposition. An emphasis was put on surveying AQ models that have been proven to resolve meso-scale features and cover a large geographical area, such as large regional, continental, or trans-continental boundary extents. Five AQ models were selected. Four of the models were run in real-time operational forecasting settings for continental scale AQ. The models use various forms of level 2.5 closure algorithms to calculate turbulent mixing. Tuning and parameter optimization has been used to tailor these algorithms to better suit their AQ models which are typically comprised of a coupled chemistry and meteorology model. Longer forecasts and long lead-times are inevitably under increasing demand for these models. Land Surface Models that have the capability for soil moisture and temperature data assimilation will have an advantage to constrain the key variables that govern the partitioning of surface sensible and latent heat fluxes and thus attain the potential to perform better in longer forecasts than those models that do not have this capability. Dry deposition velocity is a OPEN ACCESSAtmosphere 2011, 2 465 very significant model parameter that governs a major surface exchange activity. An exploratory study has been conducted to see the upper bound of roughness length in the similarity equation for aerodynamic resistance.

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Section: Introductionsupporting

confidence: 59%

Coupling of Important Physical Processes in the Planetary Boundary Layer between Meteorological and Chemistry Models for Regional to Continental Scale Air Quality Forecasting: An Overview

Lee

Ngan

2011

Atmosphere

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“…gradient Richardson number or Obukhov length, see Delage and Girard (1992), Delage (1997), Mahrt and Vickers (2003), Han et al (2009)]. 1.5-order models formulate diffusivity as a function of turbulent kinetic energy (e = 1 2 (u 2 + v 2 + w 2 )) and/or other variances of turbulent fluctuating components in addition to mixing length and stability (Mellor and Yamada 1974;Bougeault and Lacarrere 1989;Bélair et al 1999;Cuxart et al 2006).…”

Section: Downgradient Transportmentioning

confidence: 99%

Characterization and Parametrization of Reynolds Stress and Turbulent Heat Flux in the Stably-Stratified Lower Arctic Troposphere Using Aircraft Measurements

Aliabadi

Staebler

Liu

et al. 2016

Boundary-Layer Meteorol

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Aircraft measurements are used to characterize properties of clear-air turbulence in the lower Arctic troposphere. For typical vertical resolutions in general circulation models, there is evidence for both downgradient and countergradient vertical turbulent transport of momentum and heat in the mostly statically stable conditions within both the boundary layer and the free troposphere. Countergradient transport is enhanced in the free troposphere compared to the boundary layer. Three parametrizations are suggested to formulate the turbulent heat flux and are evaluated using the observations. The parametrization that accounts for the anisotropic nature of turbulence and buoyancy flux predicts both observed downgradient and countergradient transport of heat more accurately than those that do not. The inverse turbulent Prandtl number is found to only weakly decrease with increasing gradient Richardson number in a statistically significant way, but with large scatter in the data. The suggested parametrizations can potentially improve the performance of regional and global atmospheric models.

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“…The planetary boundary layer (PBL) is close to the surface underlying the troposphere, and strongly interacts with the atmosphere through turbulent exchanges of mass, energy and momentum in the PBL [1]. PBL parameterizations affect the model performance greatly with respect to vertical eddy diffusivities, surface energy budget, tracer concentrations (e.g., water vapor) and the transport of air pollutants [2][3][4][5][6]. Due to the complexity of the thermodynamic processes associated with radiation, cloud physics, air dynamics, surface friction and anthropogenic sources for water vapor and heat, it is both critical and challenging to reproduce PBL wind structure and predict urban air quality [7].…”

Section: Introductionmentioning

confidence: 99%

Understanding the Major Impact of Planetary Boundary Layer Schemes on Simulation of Vertical Wind Structure

et al. 2021

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The structure and evolution of the atmospheric planetary boundary layer (PBL) plays an important role in the physical and chemical processes of cloud–radiation interaction, vertical mixing and pollutant transport in the atmosphere. The PBL parameterization scheme describes the vertical transport of atmospheric momentum, heat, water vapor and other physical quantities in the boundary layer. The accuracy of wind field simulation and prediction is one of the most significant parameters in the field of atmospheric science and wind energy. Limited by the observation data, there are few studies on wind energy development. A 3D Doppler wind LiDAR (DWL) providing the high-vertical-resolution wind data over the urban complex underlying surface in February 2018 was employed to systematically evaluate the accuracy of vertical wind field simulation for the first time. 11 PBL schemes of the Weather Research and Forecasting Model (WRF) were employed in simulation. The model results were evaluated in groups separated by weather (sunny days, hazy days and windy days), observation height layers of wind field, and various observation wind speeds. Among these factors, the simulation accuracy is most closely related to the observation height layers of wind field. The simulation is fairly accurate at a height of 1000–2000 m, as most of the relative mean biases for wind speed and wind direction are less than 20% and 6% respectively. Below 1000 m, the wind speed and direction biases are about 30–150% m·s−1 and 6–30%, respectively. Moreover, when the observed wind speed was lower than 5 m·s−1, the biases were usually large, and the wind speed relative mean bias reaches up to 50–300%. In addition, the accuracy of the simulated wind profile is better in the range of 10–15 m·s−1 than other speed ranges, and is better above 1000 m than below 1000 m in the boundary layer. We see that the WRF boundary layer schemes have different applicabilities to different weather conditions. The WRF boundary layer schemes have significant differences in wind field simulations, with larger error under the complex topographies. A PBL scheme is not likely to maintain its advantages in the long term under different conditions including altitude and weather conditions.

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Sensitivity of air quality model prediction to parameterization of vertical eddy diffusivity

Cited by 6 publications

References 25 publications

Coupling of Important Physical Processes in the Planetary Boundary Layer between Meteorological and Chemistry Models for Regional to Continental Scale Air Quality Forecasting: An Overview

Coupling of Important Physical Processes in the Planetary Boundary Layer between Meteorological and Chemistry Models for Regional to Continental Scale Air Quality Forecasting: An Overview

Characterization and Parametrization of Reynolds Stress and Turbulent Heat Flux in the Stably-Stratified Lower Arctic Troposphere Using Aircraft Measurements

Understanding the Major Impact of Planetary Boundary Layer Schemes on Simulation of Vertical Wind Structure

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