Validation of MODIS derived aerosol optical depth over the Yangtze River Delta in China

He, Qianshan; Li, Chengcai; Tang, Xiangru; Li, Huiling; Geng, Feng; Wu, Ying

doi:10.1016/j.rse.2010.02.015

Cited by 93 publications

(72 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, caution must be taken here that α is even more sensitive to the assumptions on the spectral dependence of the land surface than the AOD, followed by uncertainties of aerosol properties (such as particle size and ω 0 ). He et al (2010) compared MODIS derived α with sunphotometer CE318 measurements from 7 sites located at YRD in East China from July to October, 2007. They divided all MODIS derived α samples into two categories according to air flow sources in order to further clarify the influencing factors of MODIS derived α.…”

Section: Summary Of Aerosol Distributions In East Chinamentioning

confidence: 99%

Study on Long-term Aerosol Distribution over the Land of East China Using MODIS Data

Geng

et al. 2012

Aerosol Air Qual. Res.

Self Cite

View full text Add to dashboard Cite

East China is among the fastest developing area in Asia, where atmospheric aerosol loading is high due to heavy urban and industrial emission. The Moderate Resolution Imaging Spectroradiometer (MODIS) level 2 aerosol products (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007) were used to study aerosol spatial and temporal distributions, as well as their variations with local meteorological conditions over East China. By combining Aerosol Optical Depth (AOD) and aerosol Fine Mode Fraction (FMF), we found that the urban/industrial aerosol and soil dust are possibly two dominant species over northern part, whereas continental and marine aerosols possibly dominate the southern part of East China. Both annual mean AOD and area with high AOD increased from 2000 to 2007, with the largest increase seen in Yangtze River Delta region (YRD). In summer, AOD in East China reached the maximum of about 0.8 in YRD, dominated by fine mode particles. The minimum AOD occurred in winter with mostly coarse mode particles. Local aerosol properties were analyzed in three typical zones: the northern dry zone (I), the central urban/industrial zone (II) and the southern natural background zone (III). Monthly mean AODs in zone I and II were above 0.5 throughout the entire year, with the maximum AOD in June. High FMFs in this period indicated heavy urban and industrial pollution. Monthly mean AODs and FMFs in zone III reached maximum of 0.51 in April and September (up to 90.7%) respectively. High AOD in spring in zone III appears mostly due to the long-range dust transport from the North.

show abstract

Section: Summary Of Aerosol Distributions In East Chinamentioning

confidence: 99%

Study on Long-term Aerosol Distribution over the Land of East China Using MODIS Data

Geng

et al. 2012

Aerosol Air Qual. Res.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Remote-sensing retrieval of AOD has been applied over many regions He et al, 2010;Breon et al, 2011), but uncertainty in remote sensing has been high over the TP due to its low aerosol load . Previous investigations based on ground observation have indicated that the annual mean AOD observed at different sites of TP was usually less than 0.15 (Cong et al, 2009;Che et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Similarities and differences of aerosol optical properties between southern and northern sides of the Himalayas

Panday

et al. 2014

Atmos. Chem. Phys.

View full text Add to dashboard Cite

Abstract. The Himalaya mountains along the southern edge of the Tibetan Plateau act as a natural barrier for the transport of atmospheric aerosols from the polluted regions of South Asia to the main body of the Tibetan Plateau. In this study, we investigate the seasonal and diurnal variations of aerosol optical properties measured at two Aerosol Robotic Network (AERONET) sites on the southern side of the Himalaya (Pokhara, 812 m above sea level (a.s.l.) and EVK2-CNR, 5079 m a.s.l. in Nepal) and one on the northern side (Qomolangma (Mt. Everest) station for Atmospheric and Environmental Observation and Research, Chinese Academy of Sciences (QOMS_CAS) in Tibet, 4076 m a.s.l. in China). While observations at QOMS_CAS and EVK2-CNR can generally be representative of a remote background atmosphere, Pokhara is a lower-elevation suburban site with much higher aerosol load due to both the influence of local anthropogenic activities and to its proximity to the Indo-Gangetic Plains. The annual mean aerosol optical depth (AOD) during the investigated period was 0.05 at QOMS_CAS, 0.04 at EVK2-CNR and 0.51 at Pokhara, respectively. Seasonal variations of aerosols are profoundly affected by large-scale atmospheric circulation. Vegetation fires, peaking during April in the Himalayan region and northern India, contribute to a growing fine mode AOD at the three stations. Dust transported to these sites, wind erosion and hydrated/cloudprocessed aerosols lead to an increase in coarse mode AOD during the monsoon season at QOMS_CAS and EVK2-CNR. Meanwhile, coarse mode AOD at EVK2-CNR is higher than at QOMS_CAS in August and September, indicating that the transport of coarse mode aerosols from the southern to the northern side may be effectively reduced. The effect of precipitation scavenging is clearly seen at Pokhara, which sees significantly reduced aerosol loads during the monsoon season. Unlike the seasonal variations, diurnal variations are mainly influenced by meso-scale systems and local topography. The diurnal pattern in precipitation appears to contribute to diurnal changes in AOD through the effect of precipitation scavenging. AOD exhibits diurnal patterns related to emissions in Pokhara, while it does not at the other two high-altitude sites. At EVK2-CNR, the daytime airflow carries aerosols up from lower-altitude polluted regions, leading to increasing AOD, while the other two stations are less influenced by valley winds. Surface heating influences the local convection, which further controls the vertical aerosol exchange and the diffusion rate of pollution to the surrounding areas. Fine and coarse mode particles Published by Copernicus Publications on behalf of the European Geosciences Union. C. Xu et al.: Similarities and differences of aerosol optical propertiesare mixed together on the southern side of the Himalaya in spring, which may lead to the greater inter-annual difference in diurnal cycles of Ångström exponent (AE) at EVK2-CNR than that at QOMS_CAS.

show abstract

“…A widely used collocation method is 50 km by 50 km box with the ground site in the center and corresponding ±30 min of MODIS overpass assuming that the aerosol diffusion speed is 50 km/h. But the relatively large averaging box may reduce the representativeness of averaged MODIS AODs because of topographic and/or aerosol type heterogeneity [15,21,25]. As shown in Figure 1, the ground site is located in a trough valley that is surrounded by mountains exceeding 500 m in height.…”

Section: Comparison Methodsmentioning

confidence: 99%

“…MBE stands for the overall systematic bias and indicates whether or not MODIS algorithms overestimate AODs. RMSE denotes the random errors, such as sub-pixel clouds contamination and variations of surface and aerosol properties [15,21]. MBE and RMSE are defined in the same way, as presented in de Miguel and Bilbao [51].…”

Section: Comparison Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of the MODIS C6 Aerosol Optical Depth Products over Chongqing, China

Shi

Liu²,

Wang

et al. 2017

Atmosphere

View full text Add to dashboard Cite

Abstract:The Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 (C6) aerosol optical depth (AOD) products from the 10/3 km Dark Target (DT) and Deep Blue (DB) algorithms are firstly evaluated using ground observed AODs by the sun photometer in Chongqing, a mountainous mega-city in southwest China. The validation results show that MODIS AODs from 10/3 km DT algorithm are comparable with those of the sun photometer, although there are slight overestimations. However, the DB algorithm substantially underestimates MODIS AODs when comparing with those of the sun photometer. Error analyses imply that the bias of surface reflectance estimation is the main error source for both algorithms. The cloud screening scheme of the DT algorithm is more effective than the DB algorithm. The cloud vicinity effect should be considered in the quality control processes for both of the algorithms. A sensitivity test suggests that in complex terrain area, like Chongqing, the collocation method in the validation of satellite products should be carefully selected according to local circumstances. When comparing the monthly mean AODs of MODIS products with sun photometer observations, it shows that the Terra MODIS AOD products are valid to represent the mean statuses in summer and autumn, but the monthly mean of Aqua MODIS AODs are limited in Chongqing.

show abstract

Validation of MODIS derived aerosol optical depth over the Yangtze River Delta in China

Cited by 93 publications

References 28 publications

Study on Long-term Aerosol Distribution over the Land of East China Using MODIS Data

Study on Long-term Aerosol Distribution over the Land of East China Using MODIS Data

Similarities and differences of aerosol optical properties between southern and northern sides of the Himalayas

Evaluation of the MODIS C6 Aerosol Optical Depth Products over Chongqing, China

Contact Info

Product

Resources

About