Aerosol Optical Depth for Atmospheric Correction of AVHRR Composite Data

Abstract. Satellite aerosol retrievals have been a popular alternative to monitoring the surface-based PM2.5 concentration due to their extensive spatial and temporal coverage. Satellite-derived PM2.5 estimations strongly rely on an accurate representation of the relationship between ground-level PM2.5 and satellite aerosol optical depth (AOD). Due to the limitations of satellite AOD data, most studies have examined the relationship at a coarse resolution (i.e., ≥ 10 km); thus, more effort is still needed to better understand the relationship between “in situ” PM2.5 and AOD at finer spatial scales. While PM2.5 and AOD could have obvious temporal variations, few studies have examined the diurnal variation in their relationship. Therefore, considerable uncertainty still exists in satellite-derived PM2.5 estimations due to these research gaps. Taking advantage of the newly released fine-spatial-resolution satellite AOD data derived from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm and real-time ground aerosol and PM2.5 measurements, this study explicitly explored the relationship between PM2.5 and AOD as well as its plausible impact factors, including meteorological parameters and topography, in mainland China during 2019, at various spatial and temporal scales. The coefficient of variation, the Pearson correlation coefficient and the slope of the linear regression model were used. Spatially, stronger correlations mainly occurred in northern and eastern China, and the linear slope was larger on average in northern inland regions than in other areas. Temporally, the PM2.5–AOD correlation peaked at noon and in the afternoon, and reached a maximum in winter. Simultaneously, considering relative humidity (RH) and the planetary boundary layer height (PBLH) in the relationship can improve the correlation, but the effect of RH and the PBLH on the correlation varied spatially and temporally with respect to both strength and direction. In addition, the largest correlation occurred at 400–600 m primarily in basin terrain such as the Sichuan Basin, the Shanxi–Shaanxi basins and the Junggar Basin. MAIAC 1 km AOD can better represent the ground-level fine particulate matter in most domains with exceptions, such as in very high terrain (i.e., Tibetan Plateau) and northern central China (i.e., Qinghai and Gansu). The findings of this study have useful implications for satellite-based PM2.5 monitoring and will further inform the understanding of the aerosol variation and PM2.5 pollution status of mainland China.

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A multi-angle aerosol optical depth retrieval algorithm for geostationary satellite data over the United States

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-11-12519-2011 ◽

2011 ◽

Vol 11 (4) ◽

pp. 12519-12560

Author(s):

H. Zhang ◽

A. Lyapustin ◽

Y. Wang ◽

S. Kondragunta ◽

I. Laszlo ◽

...

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Atmospheric Correction ◽

The United States ◽

Retrieval Algorithm ◽

High Temporal Resolution ◽

Surface Reflectance ◽

Western Us ◽

Moderate Resolution Imaging Spectroradiometer ◽

Polar Orbiting Satellite

Abstract. Aerosol optical depth (AOD) retrieval from geostationary satellites has high temporal resolution compared to the polar orbiting satellites and thus enables us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosol and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day composite images from the visible channel to derive surface reflectance, which can produce large uncertainties. In this work, we develop a new AOD retrieval algorithm for the GOES imager by applying a modified multi-angle Implementation of Atmospheric Correction (MAIAC) algorithm. The algorithm assumes the surface Bidirectional Reflectance Distribution Function (BRDF) at channel 1 of GOES is proportional to seasonal average BRDF in the 2.1 μm channel from MODIS. The ratios between them are derived through time series analysis of the GOES visible channel images. The results of the AOD and surface reflectance retrievals are evaluated through comparison against those from Aerosol Robotic Network (AERONET), GASP, and MODIS. The AOD retrievals from the new algorithm demonstrate good agreement with AERONET retrievals at several sites across the US. They are comparable to the GASP retrievals in the eastern-central sites and are more accurate than GASP retrievals in the western sites. In the western US where surface reflectance is high, the new algorithm also produces larger AOD retrieval coverage than both GASP and MODIS.

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Aerosol Optical Depth (AOD) retrieval using simultaneous GOES-East and GOES-West reflected radiances over the Western US

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-5-7945-2012 ◽

2012 ◽

Vol 5 (5) ◽

pp. 7945-7981

Author(s):

H. Zhang ◽

R. M. Hoff ◽

S. Kondragunta ◽

I. Laszlo ◽

A. Lyapustin

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Atmospheric Correction ◽

Correlation Coefficients ◽

Western United States ◽

Retrieval Algorithm ◽

Hybrid Technique ◽

Retrieval Accuracy ◽

Western Us ◽

Data Coverage

Abstract. Aerosol Optical Depth (AOD) in the Western United States is observed independently by both the GOES-East and GOES-West imagers. The GASP (GOES Aerosol/Smoke Product) aerosol optical depth retrieval algorithm treats each satellite as a unique sensor and thus NOAA obtains two separate aerosol optical depth values at the same time for the same location. The TOA radiances and the associated derived optical depths can be quite different due to the different viewing geometries with large difference in solar-scattering angles. In order to fully exploit the simultaneous observations and generate consistent AOD retrievals from the two satellites, the authors develop a new aerosol optical depth retrieval algorithm that uses data from both satellites. The algorithm uses combined GOES-East and GOES-West visible channel TOA reflectance and daily average AOD from GOES Multi-Angle Implementation of Atmospheric Correction (GOES-MAIAC) on clear days (AOD less than 0.3), when diurnal variation of AOD is low, to retrieve surface BRDF. The known BRDF shape is applied on subsequent days to retrieve BRDF and AOD. The algorithm is validated at three AERONET sites over the Western US. The AOD retrieval accuracy from the hybrid technique using the two satellites is similar to that from one satellite over UCSB and Railroad Valley. Improvement of the accuracy is observed at Boulder. The correlation coefficients between the GOES AOD and AERONET AOD are in the range of 0.67 to 0.81 over the three sites. The hybrid algorithm has more data coverage compared to the single satellite retrievals over surfaces with high reflectance. The number of coincidences with AERONET observations increases from the use of two-single satellite algorithms by 5–80% for the three sites. With the application of the new algorithm, consistent AOD retrievals and better retrieval coverages can be obtained using the data from the two GOES satellite imagers.

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A multi-angle aerosol optical depth retrieval algorithm for geostationary satellite data over the United States

Atmospheric Chemistry and Physics ◽

10.5194/acp-11-11977-2011 ◽

2011 ◽

Vol 11 (23) ◽

pp. 11977-11991 ◽

Cited By ~ 27

Author(s):

H. Zhang ◽

A. Lyapustin ◽

Y. Wang ◽

S. Kondragunta ◽

I. Laszlo ◽

...

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Atmospheric Correction ◽

Correlation Coefficients ◽

The United States ◽

Retrieval Algorithm ◽

High Temporal Resolution ◽

Surface Reflectance ◽

Moderate Resolution Imaging Spectroradiometer ◽

Polar Orbiting Satellite

Abstract. Aerosol optical depth (AOD) retrievals from geostationary satellites have high temporal resolution compared to the polar orbiting satellites and thus enable us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosols and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day composite images from the visible channel to derive surface reflectance, which can produce large uncertainties. In this work, we develop a new AOD retrieval algorithm for the GOES imager by applying a modified Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. The algorithm assumes the surface Bidirectional Reflectance Distribution Function (BRDF) in the channel 1 of GOES is proportional to seasonal average MODIS BRDF in the 2.1 μm channel. The ratios between them are derived through time series analysis of the GOES visible channel images. The results of AOD and surface reflectance retrievals are evaluated through comparisons against those from Aerosol Robotic Network (AERONET), GASP, and MODIS. The AOD retrievals from the new algorithm demonstrate good agreement with AERONET retrievals at several sites across the US with correlation coefficients ranges from 0.71 to 0.85 at five out of six sites. At the two western sites Railroad Valley and UCSB, the MAIAC AOD retrievals have correlations of 0.8 and 0.85 with AERONET AOD, and are more accurate than GASP retrievals, which have correlations of 0.7 and 0.74 with AERONET AOD. At the three eastern sites, the correlations with AERONET AOD are from 0.71 to 0.81, comparable to the GASP retrievals. In the western US where surface reflectance is higher than 0.15, the new algorithm also produces larger AOD retrieval coverage than both GASP and MODIS.

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The Climatology of Australian Aerosol

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-5131-2017 ◽

2017 ◽

Vol 17 (8) ◽

pp. 5131-5154 ◽

Cited By ~ 10

Author(s):

Ross M. Mitchell ◽

Bruce W. Forgan ◽

Susan K. Campbell

Keyword(s):

Time Series ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Atmospheric Correction ◽

Periodic Variation ◽

Anthropogenic Aerosols ◽

Austral Spring ◽

Continental Scale ◽

Intercontinental Transport ◽

Periodic Components

Abstract. Airborne particles or aerosols have long been recognised for their major contribution to uncertainty in climate change. In addition, aerosol amounts must be known for accurate atmospheric correction of remotely sensed images, and are required to accurately gauge the available solar resource. However, despite great advances in surface networks and satellite retrievals over recent years, long-term continental-scale aerosol data sets are lacking. Here we present an aerosol assessment over Australia based on combined sun photometer measurements from the Bureau of Meteorology Radiation Network and CSIRO/AeroSpan. The measurements are continental in coverage, comprising 22 stations, and generally decadal in timescale, totalling 207 station-years. Monthly climatologies are given at all stations. Spectral decomposition shows that the time series can be represented as a weighted sum of sinusoids with periods of 12, 6 and 4 months, corresponding to the annual cycle and its second and third harmonics. Their relative amplitudes and phase relationships lead to sawtooth-like waveforms sharply rising to an austral spring peak, with a slower decline often including a secondary peak during the summer. The amplitude and phase of these periodic components show significant regional change across the continent. Fits based on this harmonic analysis are used to separate the periodic and episodic components of the aerosol time series. An exploratory classification of the aerosol types is undertaken based on (a) the relative periodic amplitudes of the Ångström exponent and aerosol optical depth, (b) the relative amplitudes of the 6- and 4-month harmonic components of the aerosol optical depth, and (c) the ratio of episodic to periodic variation in aerosol optical depth. It is shown that Australian aerosol can be broadly grouped into three classes: tropical, arid and temperate. Statistically significant decadal trends are found at 4 of the 22 stations. Despite the apparently small associated declining trends in mid-visible aerosol optical depth of between 0.001 and 0.002 per year, these trends are much larger than those projected to occur due to declining emissions of anthropogenic aerosols from the Northern Hemisphere. There is remarkable long-range coherence in the aerosol cycle across the continent, suggesting broadly similar source characteristics, including a possible role for intercontinental transport of biomass burning aerosol.

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Retrieval of Aerosol Optical Depth Based on MODIS

E3S Web of Conferences ◽

10.1051/e3sconf/202020602018 ◽

2020 ◽

Vol 206 ◽

pp. 02018

Author(s):

Jie Lv ◽

Xianglai Mao

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Yangtze River ◽

Global Climate ◽

National Level ◽

Atmospheric Correction ◽

The Yangtze River ◽

Rapid Urbanization ◽

Climate Effect ◽

Urban Agglomerations

Aerosol plays an important role in global climate effect, and Aerosol Optical Depth (AOD), as one of its important parameters, can not only monitor the turbidity of the atmosphere, but also is an important index of atmospheric correction quality in remote sensing. Urban agglomeration in the middle reaches of the Yangtze River is a key national-level urban agglomerations in China, and its rapid urbanization leads to the aggravation of urban diseases such as disorderly development of cities, waste of resources and environmental pollution, and the research on ecological environment problems of urban agglomerations is also the current key project.In view of the above problems, this paper studies the AOD inversion and its spatial and temporal distribution in the middle reaches of the Yangtze River, in order to provide important scientific materials for environmental monitoring and satellite atmospheric correction quality inspection.

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Aerosol optical depth (AOD) retrieval using simultaneous GOES-East and GOES-West reflected radiances over the western United States

Atmospheric Measurement Techniques ◽

10.5194/amt-6-471-2013 ◽

2013 ◽

Vol 6 (2) ◽

pp. 471-486 ◽

Cited By ~ 12

Author(s):

H. Zhang ◽

R. M. Hoff ◽

S. Kondragunta ◽

I. Laszlo ◽

A. Lyapustin

Keyword(s):

United States ◽

Aerosol Optical Depth ◽

Optical Depth ◽

High Surface ◽

Atmospheric Correction ◽

Correlation Coefficients ◽

Western United States ◽

Retrieval Algorithm ◽

Hybrid Technique ◽

Single Observation

Abstract. Aerosol optical depth (AOD) in the western United States is observed independently by both the (Geostationary Operational Environmental Satellites) GOES-East and GOES-West imagers. The GASP (GOES Aerosol/Smoke Product) aerosol optical depth retrieval algorithm treats each satellite as a unique sensor and thus obtains two separate aerosol optical depth values at the same time for the same location. The TOA (the top of the atmosphere) radiances and the associated derived optical depths can be quite different due to the different viewing geometries with large difference in solar-scattering angles. In order to fully exploit the simultaneous observations and generate consistent AOD retrievals from the two satellites, the authors develop a new "hybrid" aerosol optical depth retrieval algorithm that uses data from both satellites. The algorithm uses both GOES-East and GOES-West visible channel TOA reflectance and daily average AOD from GOES Multi-Angle Implementation of Atmospheric Correction (GOES-MAIAC) on low AOD days (AOD less than 0.3), when diurnal variation of AOD is low, to retrieve surface BRDF (Bidirectional Reflectance Distribution Function). The known BRDF shape is applied on subsequent days to retrieve BRDF and AOD. The algorithm is validated at three AERONET sites over the western US. The AOD retrieval accuracy from the "hybrid" technique using the two satellites is similar to that from one satellite over UCSB (University of California Santa Barbara) and Railroad Valley, Nevada. Improvement of the accuracy is observed at Boulder, Colorado. The correlation coefficients between the GOES AOD and AERONET AOD are in the range of 0.67 to 0.81. More than 74% of AOD retrievals are within the error of ±(0.05 + 0.15 τ) compared to AERONET AOD. The hybrid algorithm has more data coverage compared to the single satellite retrievals over surfaces with high surface reflectance. For single observation areas the number of valid AOD data increases from the use of two-single satellite algorithms by 5–80% for the three sites. With the application of the new algorithm, consistent AOD retrievals and better retrieval coverages can be obtained using the data from the two GOES satellite imagers.

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