Intercomparison of planetary boundary layer parameterization and its impacts on surface ozone concentration in the WRF/Chem model for a case study in Houston/Texas

Cuchiara, G. C.; Li, X.; Carvalho, Jonas C.; Rappenglück, Bernhard

doi:10.1016/j.atmosenv.2014.07.013

Cited by 84 publications

(65 citation statements)

References 34 publications

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“…Our past modeling experiences indicated that employing the Yonsei University (YSU) for the PBL scheme and the Kain-Fritsch (K-F) for the cumulous scheme gave the best results for the Houston area. The YSU scheme was also one of the two PBL schemes recommended by Cuchiara et al (2014). The K-F scheme is "drier" than others and produces a smaller number of "false" convectional thunderstorms.…”

Section: Physics and Fdda Optionsmentioning

confidence: 99%

The impact of observation nudging on simulated meteorology and ozone concentrations during DISCOVER-AQ 2013 Texas campaign

Choi

Czader

et al. 2016

Atmos. Chem. Phys.

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Abstract. Accurate meteorological fields are imperative for correct chemical transport modeling. Observation nudging, along with objective analysis, is generally considered a lowcost and effective technique to improve meteorological simulations. However, the meteorological impact of observation nudging on chemistry has not been well characterized. This study involved two simulations to analyze the impact of observation nudging on simulated meteorology and ozone concentrations during the 2013 Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Texas campaign period, using the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models. The results showed improved correlations between observed and simulated parameters. For example, the index of agreement (IOA) improved by about 9 % for surface temperature and 6-11 % for surface zonal (U-WIND) and meridional (V-WIND) winds when observation nudging was employed. Analysis of a cold front event indicated that nudging improved the timing of wind transition during the front passage. Observation nudging also reduced the model biases for the planetary boundary layer height predictions. Additionally, the IOA for CMAQ simulated surface ozone improved by 6 % during the simulation period. The high-ozone episode on 25 September was a post-front ozone event in Houston. The small-scale morning wind shifts near the Houston Ship Channel combined with higher aloft ozone early morning likely caused the day's ozone exceedance. While observation nudging did not recreate the wind shifts on that day and failed to reproduce the observed high ozone, analyses of surface and aircraft data found that observation nudging helped the model yield improved ozone predictions. In a 2 h period during the event, substantially better winds in the sensitivity case noticeably improved the ozone. The average IOA for ozone in the period increased from just over 0.4 to near 0.7. Further work on improving the capability of nudging to reproduce local meteorological events such as stagnations and wind reversals could enhance a chemical transport model's skill for predicting high-ozone events.

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Section: Physics and Fdda Optionsmentioning

confidence: 99%

The impact of observation nudging on simulated meteorology and ozone concentrations during DISCOVER-AQ 2013 Texas campaign

Choi

Czader

et al. 2016

Atmos. Chem. Phys.

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“…The land surface data from the United States Geological Survey (USGS) were used. In past air quality studies in Houston we used YSU and found promising results (Czader et al, 2013), and recent intercomparisons with other PBL schemes for the same area showed that YSU simulates vertical meteorological profiles as satisfactorily as the Asymmetric Convective Model version 2 (ACM2); the Mellor-Yamada-Janjic (MYJ) and quasi-normal scale elimination (QNSE), but may be the best to replicate vertical mixing of ozone precursors (Cuchiara et al, 2014). The cumulus scheme is set to be identical to the MM5 one, which is described below.…”

Section: Wrf Modelmentioning

confidence: 99%

MM5 v3.6.1 and WRF v3.5.1 model comparison of standard and surface energy variables in the development of the planetary boundary layer

Wilmot

Rappenglück

et al. 2014

Geosci. Model Dev.

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Abstract. Air quality forecasting requires atmospheric weather models to generate accurate meteorological conditions, one of which is the development of the planetary boundary layer (PBL). An important contributor to the development of the PBL is the land-air exchange captured in the energy budget as well as turbulence parameters. Standard and surface energy variables were modeled using the fifth-generation Penn State/National Center for Atmospheric Research mesoscale model (MM5), version 3.6.1, and the Weather Research and Forecasting (WRF) model, version 3.5.1, and compared to measurements for a southeastern Texas coastal region. The study period was 28 August-1 September 2006. It also included a frontal passage.The results of the study are ambiguous. Although WRF does not perform as well as MM5 in predicting PBL heights, it better simulates energy budget and most of the general variables. Both models overestimate incoming solar radiation, which implies a surplus of energy that could be redistributed in either the partitioning of the surface energy variables or in some other aspect of the meteorological modeling not examined here. The MM5 model consistently had much drier conditions than the WRF model, which could lead to more energy available to other parts of the meteorological system. On the clearest day of the study period, MM5 had increased latent heat flux, which could lead to higher evaporation rates and lower moisture in the model. However, this latent heat disparity between the two models is not visible during any other part of the study. The observed frontal passage affected the performance of most of the variables, including the radiation, flux, and turbulence variables, at times creating dramatic differences in the r 2 values.

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“…However, systematic bias was eliminated using multi-linear regression post-processing because short-term peaks of several days were not captured by the model (Ritter et al, 2013). Different PBL schemes did not show any preference for all meteorological parameters but for O 3 concentration, YSU scheme gave better comparison than WRF-Chem with observed data (Cuchiara et al, 2014). Two new chemistry aerosol options in WRF-Chem viz.…”

Section: Summary Of Wrf-chem Studiesmentioning

confidence: 99%

“…WRF-Chem was also implemented to estimate surface ozone concentration with different planetary boundary layer schemes over Houston/Texas region (Cuchiara et al, 2014). Here, also similar set was used except PBL schemes.…”

Section: Application Of Wrf-chemmentioning

confidence: 99%

Application of WRF Model for Air Quality Modelling and AERMOD - A Survey

Kumar

Patil

Dikshit

et al. 2017

Aerosol Air Qual. Res.

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Meteorology plays a crucial role in air quality. The presence of uncertainties of a significant nature in the meteorological profile used during air quality model simulation has the potential to affect negatively the results of the simulations. This paper describes a most recent version of the meteorological model called Weather Research and Forecasting (WRF) model and its importance in air quality. The performance of WRF depends upon the intended application and parameterization scheme of physics options. WRF model is also applied to investigate the simulation results with various land surface models (LSMs) and Planetary Boundary Layer (PBL) parameterizations and various set of microphysics options. It predicts various meteorological spatial parameters like mixing layer height, temperature, humidity, rain fall, cloud cover and wind. The WRF results are integrated with air quality model (AQM) and the AQM depends upon the performance of WRF. It has been applied for evaluation of national pollution control policy, behaviour of plume rise, property of aerosols, prediction of Ozone, SO 2 , NO x , PM 10 , PM 2.5 etc. using AQM for various sources. The effect of topography and different seasons on the concentration of pollutants in the atmosphere has also been studied using AQM. AQM AERMOD has also been reviewed with various other AQM models such as ADMS-Urban and CALPUFF. AERMOD has been used for different time scales, health risk assessment, evaluation of various control strategies, Environmental Impact Assessment (EIA) studies and emission factor estimation. This paper presents the importance of meteorological model to AQM as well as many applications of AQM to demonstrate various scientific questions and policies.

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Intercomparison of planetary boundary layer parameterization and its impacts on surface ozone concentration in the WRF/Chem model for a case study in Houston/Texas

Cited by 84 publications

References 34 publications

The impact of observation nudging on simulated meteorology and ozone concentrations during DISCOVER-AQ 2013 Texas campaign

The impact of observation nudging on simulated meteorology and ozone concentrations during DISCOVER-AQ 2013 Texas campaign

MM5 v3.6.1 and WRF v3.5.1 model comparison of standard and surface energy variables in the development of the planetary boundary layer

Application of WRF Model for Air Quality Modelling and AERMOD - A Survey

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