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  • at SciVerse ScienceDirect

    Atmospheric Environment 46 (2012) 299e308

    Contents lists available

    Atmospheric Environment

    journal homepage: www.elsevier .com/locate/atmosenv

    Long-range transport of spring dust storms in Inner Mongolia and impacton the China seas

    Sai-Chun Tan a,b,*, Guang-Yu Shi a, Hong Wang c,d

    a State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences,Beijing 100029, ChinabKey Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, ChinacCentre for Atmosphere Watch and Services, Chinese Academy of Meteorological Sciences, Beijing 100081, Chinad State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China

    a r t i c l e i n f o

    Article history:Received 29 March 2011Received in revised form18 August 2011Accepted 27 September 2011

    Keywords:Dust stormTransportDepositionProbabilityThe China seas

    * Corresponding author. State Key Laboratory of Nuspheric Sciences and Geophysical Fluid Dynamics, InstChinese Academy of Sciences, Beijing 100029, Chifax: 86 10 82995097.

    E-mail address: sctan@mail.iap.ac.cn (S.-C. Tan).

    1352-2310/$ e see front matter 2011 Elsevier Ltd.doi:10.1016/j.atmosenv.2011.09.058

    a b s t r a c t

    Analysis of daily observations from 43 meteorological stations in the Inner Mongolia Autonomous Region,China, showed the distribution of spring dust storm events during 2000e2007. Guaizihu and Sunitezuoqistations had the highest frequencies of dust storms. The interannual and seasonal variations of duststorms were closely related to weather conditions, especially the wind speed. A forward trajectory modeland satellite observations were used to investigate the transport paths and dust layers of dust storms fromGuaizihu and Sunitezuoqi stations to the China seas and their probability of influencing the seas duringspring 2000e2007. Forward trajectories showed that dust storms at Guaizihu and Sunitezuoqi stationshad the highest probability of affecting the Yellow Sea, followed by the Bohai Sea, the East China Sea, andthe northern South China Sea. The dust particles from Sunitezuoqi station affected these four seas directlythrough coastal areas, while those from Guaizihu station were transported via the Inner Mongoliandeserts and/or the Loess Plateau. The dust storms from Sunitezuoqi station impacting the four seas werecharacterized by a single dust source and a short transport distance, while those from Guaizihu stationwere characterized by multiple sources and relatively long transport distances. The dust particles fromthese two stations were mostly transported in a

  • S.-C. Tan et al. / Atmospheric Environment 46 (2012) 299e308300

    Qian et al., 2006) and is responsible for approximately 31% of thetotal dust production (Zhang et al., 2003b).

    Transport of dust particles is closely related to synoptic condi-tions and the characteristics of the source regions (Tsai et al., 2008).Asian dust is usually associated with frontal systems and/orcyclones (Sun et al., 2001; Uno et al., 2004; Tsai et al., 2008). Dustparticles can be transported by surface-level northwesterly windsassociatedwith the Asianwintermonsoon over the Asian continentand by westerly winds in the free troposphere from the easternAsian continent to the Pacific Ocean (Uematsu et al., 1983; Unoet al., 2004; Zhao et al., 2006). Lidar observations and modelsimulations indicated that dust particles from the Gobi Desert areusually entrained in a lower layer (3 km) and can be deposited inproximal regions. Dust from the Taklimakan Desert uplifted to5 km has a better chance of being transported over long distances,because the surrounding high mountains exceed 5 km in heightand the stronger westerly jet dominates in this altitude range(Iwasaka et al., 1983, 2003; Sun et al., 2001; Matsuki et al., 2003;Uno et al., 2004).

    Many studies of the transport of Asian dust to downwind areas,including the China seas, have been reported. Zhang and Gao(2007) analyzed the source and movement route of dust stormsto downwind seas during 2000e2002 based on meteorology datafrom the Meteorological Information Comprehensive Analysis andProcess System (MICAPS). Gao et al. (2009) reviewed previousstudies of the transport pathways of Asian dust and its influenceareas. However, most studies concentrated on the transport of duststorms across the continent (Zhang et al., 2003a; Chen et al., 2006)or performed a case study of the influence of Asian dust storm ondownwind areas or seas (Iwasaka et al., 1983; Liu et al., 1998; Fanget al., 1999; Husar et al., 2001; Kim and Park, 2001; Lin et al., 2007).Studies of the long-term impacts of dust storms on the seas are stillrare. In addition, lidar and balloon observations and model simu-lations were used to monitor and understand the vertical distri-bution and transport processes of dust storms generally. Withadvances in remote sensing technology, satellites will increasinglybe able to monitor dust transport, including even the verticalstructure of transported dust (Winker et al., 2009). In this study, wetried to clarify the influence of dust storms on the China seas duringa long-term period.

    We investigated the impacts of spring (MarcheMay) duststorms on the China seas (the Bohai Sea, Yellow Sea, East China Sea,and South China Sea) through combinations of surface observa-tions, satellite observations, trajectories, and dust model simula-tions during the period 2000e2007. First, the transport processesof dust storms from the source regions to the seas were analyzedusing a forward trajectorymodel and satellite vertical observations.Second, the probability of spring dust storms affecting the Chinaseas was examined through the forward trajectory model. Finally,satellite-derived aerosol index and dust deposition from a numer-ical model were used to test the influence of dust storms on theChina seas derived from the forward trajectory model.

    Fig. 1. The distribution of averaged annual occurrence frequency of spring dust storms(days year1) for the period 2000e2007 in Inner Mongolia. Plus sign shows thelocations of 43 meteorological stations.

    2. Data and methods

    The daily occurrence time records of dust storms at 43 meteo-rological observation stations in Inner Mongolia, China during2000e2007 were obtained from the National MeteorologicalInformation Center of the China Meteorological Administration(NMIC/CMA). The records contained the starting and ending timesof dust storms each day at each station, allowing for calculation ofthe occurrence frequency of dust storms (days month1 ordays year1) at each station. At each station, dust storm weatherphenomenon were defined as storms with minimum visibility of

    1 km and instantaneous maximum wind speed of 10 m s1(Qian et al., 1997).

    Daily mean wind speed, pressure, temperature and relativehumidity and daily rainfall (mm) datasets at the same 43 meteo-rological stations were used to examine the relationships of thesefactors to dust storm occurrence frequency. These data were alsoprovided by the NMIC/CMA.

    The aerosol index is an effective measure of the dust loading inthe atmosphere (Herman et al., 1997). Many studies found that theaerosol index correlated closely with modeled dust loading (Unoet al., 2004; Zhao et al., 2006). Here, we used the aerosol index tomeasure the dust loading over the China seas. From 2000 to 2004,the aerosol index was retrieved from the Total Ozone MappingSpectrometer (TOMS, resolution 1.25 1), and from 2005 to 2007it was retrieved from the Ozone Monitoring Instrument (OMI,resolution 1 1). The TOMS data were interpolated into the samespatial resolution as the OMI data.

    Dust deposition (including dry and wet depositions) from theGlobal/Regional Assimilation and Prediction System/the ChineseUnified Atmospheric Chemistry Environment for Dust AtmosphericChemistry Module (GRAPES/CUACE-Dust) numerical model wasalso used to detect the impacts of spring dust storms in InnerMongolia on the China seas. The GRAPES/CUACE-Dust model wasdeveloped by the Numerical Prediction Research Center, CMA, andCenter for AtmosphereWatch and Services of the Chinese Academyof Meteorological Sciences (Wang et al., 2010). The model domaincovers 70e140E and 15e60N, including the source regions ofdust storms in East Asia. Comparisons of real-time predictionoutputs with surface observations and the TOMS aerosol indexhave indicated that the model can predict the outbreak, develop-ment, transport and depletion processes of dust storms accuratelyover China and the East Asian region (Wang et al., 2010). Details ofthe model have been described by Wang et al. (2010). Dust depo-sition was used in this study at 0.5 0.5 spatial resolution.

    The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)is a two-wavelength polarization lidar. It is the primary instrumenton the Cloud-Aerosol Lidar and Infrared Pathfinder SatelliteObservations (CALIPSO) satellite. CALIOP has provided a directmeasure of the vertical structure of aerosols in the troposphere andlower stratosphere since June 2006 (Winker et al., 2009). Theaerosol type data from CALIOP Level 2 products were used to detectthe vertical structure of dust aerosols in this paper. Six distinctaerosol types were labeled desert dust, smoke, clean continental,polluted continental, clean marine and polluted dust (Dubovik andKing, 2000; Omar et al., 2005; Winker et al., 2009). The verticalresolution was 30 m for altitudes from 0.5 to 8.2 km, 60 m foraltitudes from 8.2 to 20.2 km and 180 m for altitudes from 20.2 to30.1 km.

    To understand the impacts of dust storms from different sourceareas on the China seas, a forward trajectory analysis was

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