Application of aerosol speciation data as an in situ dust proxy for validation of the Dust Regional Atmospheric Model (DREAM)

Shaw, Patrick

doi:10.1016/j.atmosenv.2008.06.018

Cited by 19 publications

(32 citation statements)

References 21 publications

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“…Wet deposition for aerosol In-and below-cloud wet removal of particulates (Easter et al, 2004) In-cloud scavenging parameterization of Roselle and Binkowski (1999) Aerosol activation Abdul-Razzak and Ghan (A-R&G) (Abdul-Razzak and Ghan, 2002) Particles are activated if they exceed a critical diameter of 0.7 m (Strader et al, 1998) Aerosol direct effect Goddard shortwave radiative transfer model of Chou et al (1998) Shaw (2008) online module that generates emissions from soil surfaces (note that road dust emissions are not simulated) as described in Zhang et al (2012c). The land types that can generate dust include grassland, shrubland, mixed shrubland/grassland, savanna, and barren or sparsely vegetated land.…”

Section: Simulation Designmentioning

confidence: 99%

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe – Part 1: Model description, evaluation of meteorological predictions, and aerosol–meteorology interactions

Zhang

Sartelet

Wu³

et al. 2013

Atmos. Chem. Phys.

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Abstract. Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e., the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID)) are conducted over Western Europe. Part 1 describes the background information for the model comparison and simulation design, the application of WRF for January and July 2001 over triple-nested domains in Western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°, and the effect of aerosol/meteorology interactions on meteorological predictions. Nine simulated meteorological variables (i.e., downward shortwave and longwave radiation fluxes (SWDOWN and LWDOWN), outgoing longwave radiation flux (OLR), temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. The vertical profiles of temperature, dew points, and wind speed/direction are also evaluated using sounding data. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients and vertical profiles of major meteorological variables. While the domainwide performance of LWDOWN, OLR, T2, Q2, and RH2 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in SWDOWN, WS10, and Precip even at 0.125° or 0.025° in both months and in WD10 in January. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g., lack of soil temperature and moisture nudging), limitations in the physical parameterizations (e.g., shortwave radiation, cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g., snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvements for WS10, WD10, Precip, and some mesoscale events (e.g., strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. The WRF/Chem simulations with and without aerosols show that aerosols lead to reduced net shortwave radiation fluxes, 2 m temperature, 10 m wind speed, planetary boundary layer (PBL) height, and precipitation and increase aerosol optical depth, cloud condensation nuclei, cloud optical depth, and cloud droplet number concentrations over most of the domain. These results indicate a need to further improve the model representations of the above parameterizations as well as aerosol–meteorology interactions at all scales.

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Section: Simulation Designmentioning

confidence: 99%

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe – Part 1: Model description, evaluation of meteorological predictions, and aerosol–meteorology interactions

Zhang

Sartelet

Wu³

et al. 2013

Atmos. Chem. Phys.

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“…During Mar. [19][20][21][22][23]2010, the severe dust storm occurred in China. Figure 2 shows the evolution of the API at 86 stations during the event.…”

Section: Api and Pm10mentioning

confidence: 99%

“…[17][18][19][20][21][22][23][24]2010. API is a number to describe daily air quality, which is calculated by the observed surface concentrations of three air pollutants (SO 2 , NO 2 , PM 10 ) based on Chinese Air Quality Standard.…”

Section: Surface Datamentioning

confidence: 99%

“…Surface observation of PM 10 In WRF-Chem version 3.2, two dust production schemes are implemented in the model so that it can be applied on dust simulations. Shaw (2008) used a dust generating module and the land cover data sets to describe how particles will be emitted with winds, which are included in the Dust Regional Atmospheric Model (DREAM) [21].…”

Section: Introductionmentioning

confidence: 99%

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Numerical Studies on a Severe Dust Storm in East Asia Using WRF-Chem

Yu¹,

Wang²,

Liu³

et al. 2017

ACS

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Dust storm is one of the important natural disasters, which can have significant impact on terrestrial ecosystem, global climate, air quality and human health. In Mar. 19-23, 2010, a serious dust storm occurred over East Asia. It started from Mongolia, initially extending to the east, turning to the South of China, then back to the Northeast Asia. About 20% of the areas in China suffered from this severe dust event and the air was heavily polluted with massive airborne particulates. The Air Pollution Index (API) in many cities exceeded 500 when dust storm passed by, while the maximum surface PM 10 concentration reached 1900 µg/m 3 in east area. The coarse particles were dominated in PM 10 , with fine particles named as PM 2.5 only accounting for 5% -20% at cities along the dust moving track in South and East China. MODIS and CALIPSO satellite data were used to investigate the horizontal and vertical patterns of optical parameters of dust aerosol. The average AOD reached 2 -2.5 on dust days in most southeast regions. The dust can be transported up to 5 Km with maximum aerosol extinction coefficient of 0.35 -0.4 at 1 -3 Km in vertical. Synoptic weather was analyzed to understand the meteorological conditions and the backward trajectories were calculated to investigate the movements of air mass. The WRFChem model (Version 3.2) was applied to simulate the transport and deposition of the dust aerosols. The performance of Shaw (2008) and Chin (2002)

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“…27 vertical layers stretch unequally from the ground to 100 hPa. Asian emission inventory in 2006 (Zhang et al, 2009) Shaw, 2008Shaw, 2010, and vehicle emission estimated by COPERT IV Model (Kouridis et al, 2000) in Yangtze River Delta region were in use. Progress without considering the erosion of soil was also simulated for comparison.…”

Section: Wrf/chem Modelmentioning

confidence: 99%

Studies on a Severe Dust Storm in East Asia and Its Impact on the Air Quality of Nanjing, China

Huang

Wang

Jiang

et al. 2013

Aerosol Air Qual. Res.

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Long-range transport of dust aerosol has severe impact on the atmospheric environment over vast areas. In this study, the features of a severe dust storm and its transport characteristics were investigated during the period from 28 April to 5 May 2011 in East Asia. The combined impact on Nanjing was studied with the observational PM 10 , PM 2.5 , visibility and meteorological data, and the numerical models of HYSPLIT and WRF/Chem. This dust storm was caused by a cyclone on 28 April over arid and semiarid areas in Mongolia and China, and then transported to broad downwind areas including northern, central, and eastern parts of China, the Korean Peninsula, and Japan. Among the available data, the highest hourly PM 10 concentration reached 3.916 mg/m 3 at Jinchang site near the source area. In East China, the coastal cities had poorer air quality than inland ones for two days. Dust aerosol arrived at Nanjing from the northwest, and then north, owing to the movement of synoptic system, mixed with local anthropogenic emissions, resulting in the highest PM 10 concentration of 0.767 mg/m 3 with PM 2.5 level reaching 0.222 mg/m 3 . As the dust storm gradually turned eastward, the dust aerosol went over the seas in the east of the continent and then flowed back to Nanjing. Numerical simulations showed that dust aerosol affecting East China was mainly transported below the altitude of 2.5 km. The vertical profiles of PM 10 and PM 2.5 concentrations showed maxima at the altitude between 0.2 km and 1.3 km.

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Application of aerosol speciation data as an in situ dust proxy for validation of the Dust Regional Atmospheric Model (DREAM)

Cited by 19 publications

References 21 publications

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe – Part 1: Model description, evaluation of meteorological predictions, and aerosol–meteorology interactions

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe – Part 1: Model description, evaluation of meteorological predictions, and aerosol–meteorology interactions

Numerical Studies on a Severe Dust Storm in East Asia Using WRF-Chem

Studies on a Severe Dust Storm in East Asia and Its Impact on the Air Quality of Nanjing, China

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