Application of the Weather Research and Forecasting Model for Air Quality Modeling in the San Francisco Bay Area

Rogers, Raphael E.; Deng, Aijun; Stauffer, D.; Gaudet, Brian; Jia, Yunfeng; Soong, Su-Tzai; Tanrikulu, Saffet

doi:10.1175/jamc-d-12-0280.1

Cited by 44 publications

(58 citation statements)

References 31 publications

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“…With WRF FDDA, observations are assimilated through the entire simulation to ensure the optimal model solutions that combine both the observation and the dynamic solution, a technique referred to as dynamic analysis. Data assimilation can be accomplished by nudging the model solutions toward gridded analyses based on observations (analysis nudging) or directly toward the individual observations (observation nudging), with a multiscale gridnesting assimilation framework, typically using a combination of these two approaches (Deng et al, 2009;Rogers et al, 2013).…”

Section: Transport Modelmentioning

confidence: 99%

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Quantifying methane emissions from natural gas production in north-eastern Pennsylvania

et al. 2017

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Abstract. Natural gas infrastructure releases methane (CH 4 ), a potent greenhouse gas, into the atmosphere. The estimated emission rate associated with the production and transportation of natural gas is uncertain, hindering our understanding of its greenhouse footprint. This study presents a new application of inverse methodology for estimating regional emission rates from natural gas production and gathering facilities in north-eastern Pennsylvania. An inventory of CH 4 emissions was compiled for major sources in Pennsylvania. This inventory served as input emission data for the Weather Research and Forecasting model with chemistry enabled (WRFChem), and atmospheric CH 4 mole fraction fields were generated at 3 km resolution. Simulated atmospheric CH 4 enhancements from WRF-Chem were compared to observations obtained from a 3-week flight campaign in May 2015. Modelled enhancements from sources not associated with upstream natural gas processes were assumed constant and known and therefore removed from the optimization procedure, creating a set of observed enhancements from natural gas only. Simulated emission rates from unconventional production were then adjusted to minimize the mismatch between aircraft observations and model-simulated mole fractions for 10 flights. To evaluate the method, an aircraft mass balance calculation was performed for four flights where conditions permitted its use. Using the model optimization approach, the weighted mean emission rate from unconventional natural gas production and gathering facilities in northeastern Pennsylvania approach is found to be 0.36 % of total gas production, with a 2σ confidence interval between 0.27 and 0.45 % of production. Similarly, the mean emission estimates using the aircraft mass balance approach are calculated to be 0.40 % of regional natural gas production, with a 2σ confidence interval between 0.08 and 0.72 % of production. These emission rates as a percent of production are lower than rates found in any other basin using a top-down methodology, and may be indicative of some characteristics of the basin that make sources from the north-eastern Marcellus region unique.

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Section: Transport Modelmentioning

confidence: 99%

“…FDDA (Deng et al, 2009) was used in this research with the same strategy as used in Rogers et al (2013). Both analysis nudging and observation nudging were applied on the 9 km grid, and only observation nudging was applied on the 3 km grid.…”

Section: Transport Modelmentioning

confidence: 99%

Quantifying methane emissions from natural gas production in north-eastern Pennsylvania

et al. 2017

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“…The assimilation improves the model performance significantly (Rogers et al, 2013;Deng et al, 2017) without interfering with mass conservation and the continuity of the airflow. Surface wind and temperature measurements, including from the Ontario (KONT) and Chino (KCNO) airport stations, and upper-air measurements were assimilated within the coarser grids using the WRF-FDDA system.…”

Section: In Situ Measurements: Picarromentioning

confidence: 99%

Methane emissions from dairies in the Los Angeles Basin

et al. 2017

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Abstract. We estimate the amount of methane (CH 4 ) emitted by the largest dairies in the southern California region by combining measurements from four mobile solar-viewing ground-based spectrometers (EM27/SUN), in situ isotopic 13/12 CH 4 measurements from a CRDS analyzer (Picarro), and a high-resolution atmospheric transport simulation with a Weather Research and Forecasting model in large-eddy simulation mode (WRF-LES).The remote sensing spectrometers measure the total column-averaged dry-air mole fractions of CH 4 and CO 2 (X CH 4 and X CO 2 ) in the near infrared region, providing information on total emissions of the dairies at Chino. Differences measured between the four EM27/SUN ranged from 0.2 to 22 ppb (part per billion) and from 0.7 to 3 ppm (part per million) for X CH 4 and X CO 2 , respectively. To assess the fluxes of the dairies, these differential measurements are used in conjunction with the local atmospheric dynamics from wind measurements at two local airports and from the WRF-LES simulations at 111 m resolution.Our top-down CH 4 emissions derived using the Fourier transform spectrometers (FTS) observations of 1.4 to 4.8 ppt s −1 are in the low end of previous top-down estimates, consistent with reductions of the dairy farms and urbanization in the domain. However, the wide range of inferred fluxes points to the challenges posed by the heterogeneity of the sources and meteorology. Inverse modeling from WRF-LES is utilized to resolve the spatial distribution of CH 4 emissions in the domain. Both the model and the measurements indicate heterogeneous emissions, with contributions from anthropogenic and biogenic sources at Chino. A Bayesian inversion and a Monte Carlo approach are used to provide the CH 4 emissions of 2.2 to 3.5 ppt s −1 at Chino.

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“…The benefit of applying nudging to improve meteorological simulations has been demonstrated by several studies (e.g., Deng et al, 2009;Gilliam and Pleim, 2010;Rogers et al, 2013). However, the impact of the improved fields on air quality simulations has been investigated by relatively fewer studies.…”

Section: LI Et Al: the Impact Of Observation Nudging On Simulatedmentioning

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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Application of the Weather Research and Forecasting Model for Air Quality Modeling in the San Francisco Bay Area

Cited by 44 publications

References 31 publications

Quantifying methane emissions from natural gas production in north-eastern Pennsylvania

Quantifying methane emissions from natural gas production in north-eastern Pennsylvania

Methane emissions from dairies in the Los Angeles Basin

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

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