Validation of JAXA Himawari-8 Aerosol Optical Depth Products over China with AERONET and CARSNET Observations

2020 ◽  
Author(s):  
Ling Gao ◽  
Chengcai Li ◽  
Lin Chen ◽  
Jun Li ◽  
Huizheng Che
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Southern China ◽  
Correlation Coefficients ◽  
Northern China ◽  
Temporal Variations ◽  
Retrieval Algorithm ◽  
High Temporal Resolution ◽  
Surface Reflectance ◽  
Modis Aod

<p>The performance of JAXA Himawari-8 Advanced Himawari Imager (AHI) aerosol optical depth (AOD) products over China is evaluated with ground-based AErosol RObotic NETwork (AERONET) and Sun-Sky Radiometer Observation Network (CARSNET) observations as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products. Considering the quality and quantity of valid data, the study was limited to AOD products from AHI with a Quality Assurance Flag (QA_Flag) of “good” and “very good.” The spatial distribution of the AHI AOD product is similar to that of the MODIS AOD product. The AOD correlation between AHI and MODIS is better in the morning than in the afternoon after March, however, using MODIS AOD as a reference resulted in underestimation in the morning and overestimation in the afternoon. The bias is also larger in spring and autumn than in summer and winter. Validation with sun-photometer observations indicates good correlation between AHI AOD and ground-based observations with correlation coefficients larger than 0.75 (N>1000) when barren and sparsely vegetated surfaces are excluded. At 02:30 UTC, 53% of the collocated AHI AOD observations fall in the expected error (EE) range and at 5:30 UTC, 59.3% fall above the EE. The AHI AOD overestimation was apparent at the Northern China stations in April and after October, whereas the underestimation was apparent in southern China throughout the year. The temporal variations of AHI and AERONET AOD also show that the overestimation occurred in the afternoon and underestimation occurred in the morning.</p><p>The assumption that the solar geometries were nearly identical and the surface reflectance unchanged for a month causes the surface reflectance underestimation and leads to the AOD overestimation for barren surfaces in autumn and winter. Because background aerosols were neglected, the surface reflectance was overestimated, leading to AOD underestimation in vegetated surfaces.</p><p>Overall, the JAXA AOD provides a reliable and high temporal resolution aerosol product for environmental and climate research and the aerosol retrieval algorithm requires improvement.</p>

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

2011 ◽  
Vol 11 (23) ◽  
pp. 11977-11991 ◽  
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.

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

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.

scholarly journals Comparison of MODIS 3 km and 10 km resolution aerosol optical depth retrievals over land with airborne sunphotometer measurements during ARCTAS summer 2008

2014 ◽  
Vol 14 (4) ◽  
pp. 2015-2038 ◽  
Author(s):  
J. M. Livingston ◽  
J. Redemann ◽  
Y. Shinozuka ◽  
R. Johnson ◽  
P. B. Russell ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Retrieval Algorithm ◽  
Grid Cells ◽  
Data Set ◽  
Clear Sky ◽  
Modis Aod ◽  
Research Aircraft ◽  
Bright Surface ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Airborne sunphotometer measurements acquired by the NASA Ames Airborne Tracking Sunphotometer (AATS-14) aboard the NASA P-3 research aircraft are used to evaluate dark-target over-land retrievals of extinction aerosol optical depth (AOD) from spatially and temporally near-coincident measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) during the summer 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign. The new MODIS Collection 6 aerosol data set includes retrievals of AOD at both 10 km × 10 km and 3 km × 3 km (at nadir) resolution. In this paper we compare MODIS and AATS AOD at 553 nm in 58 10 km and 134 3 km retrieval grid cells. These AOD values were derived from data collected over Canada on four days during short time segments of five (four Aqua and one Terra) satellite overpasses of the P-3 during low-altitude P-3 flight tracks. Three of the five MODIS–AATS coincidence events were dominated by smoke: one included a P-3 transect of a well-defined smoke plume in clear sky, but two were confounded by the presence of scattered clouds above smoke. The clouds limited the number of MODIS retrievals available for comparison, and led to MODIS AOD retrievals that underestimated the corresponding AATS values. This happened because the MODIS aerosol cloud mask selectively removed 0.5 km pixels containing smoke and clouds before the aerosol retrieval. The other two coincidences (one Terra and one Aqua) occurred during one P-3 flight on the same day and in the same general area, in an atmosphere characterized by a relatively low AOD (< 0.3), spatially homogeneous regional haze from smoke outflow with no distinguishable plume. For the ensemble data set for MODIS AOD retrievals with the highest-quality flag, MODIS AOD agrees with AATS AOD within the expected MODIS over-land AOD uncertainty in 60% of the retrieval grid cells at 10 km resolution and 69% at 3 km resolution. These values improve to 65 % and 74%, respectively, when the cloud-affected case with the strongest plume is excluded. We find that the standard MODIS dark-target over-land retrieval algorithm fails to retrieve AOD for thick smoke, not only in cloud-contaminated regions but also in clear sky. We attribute this to deselection, by the cloud and/or bright surface masks, of 0.5 km resolution pixels that contain smoke.

scholarly journals Retrieving High-Resolution Aerosol Optical Depth from GF-4 PMS Imagery in Eastern China

2021 ◽  
Vol 13 (18) ◽  
pp. 3752
Author(s):  
Zhendong Sun ◽  
Jing Wei ◽  
Ning Zhang ◽  
Yulong He ◽  
Yu Sun ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Zenith Angle ◽  
Rural Areas ◽  
Urban Areas ◽  
Eastern China ◽  
Practical Significance ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Surface Reflectance

Gaofen 4 (GF-4) is a geostationary satellite, with a panchromatic and multispectral sensor (PMS) onboard, and has great potential in observing atmospheric aerosols. In this study, we developed an aerosol optical depth (AOD) retrieval algorithm for the GF-4 satellite. AOD retrieval was realized based on the pre-calculated surface reflectance database and 6S radiative transfer model. We customized the unique aerosol type according to the long time series aerosol parameters provided by the Aerosol Robotic Network (AERONET) site. The solar zenith angle, relative azimuth angle, and satellite zenith angle of the GF-4 panchromatic multispectral sensor image were calculated pixel-by-pixel. Our 1 km AOD retrievals were validated against AERONET Version 3 measurements and compared with MOD04 C6 AOD products at different resolutions. The results showed that our GF-4 AOD algorithm had a good robustness in both bright urban areas and dark rural areas. A total of 71.33% of the AOD retrievals fell within the expected errors of ±(0.05% + 20%); root-mean-square error (RMSE) and mean absolute error (MAE) were 0.922 and 0.122, respectively. The accuracy of GF-4 AOD in rural areas was slightly higher than that in urban areas. In comparison with MOD04 products, the accuracy of GF-4 AOD was much higher than that of MOD04 3 km and 10 km dark target AOD, but slightly worse than that of MOD04 10 km deep blue AOD. For different values of land surface reflectance (LSR), the accuracy of GF-4 AOD gradually deteriorated with an increase in the LSR. These results have theoretical and practical significance for aerosol research and can improve retrieval algorithms using the GF-4 satellite.

scholarly journals Operational Retrieval of aerosol optical depth over Indian subcontinent and Indian Ocean using INSAT-3D/Imager product validation

2014 ◽  
Vol XL-8 ◽  
pp. 277-282 ◽  
Author(s):  
M. K. Mishra ◽  
G. Rastogi ◽  
P. Chauhan
Keyword(s):  
Indian Ocean ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Linear Correlation ◽  
Indian Subcontinent ◽  
Correlation Coefficients ◽  
Retrieval Algorithm ◽  
Multiple Channel ◽  
Geo Satellite ◽  
Ocean Region

Aerosol optical depth (AOD) over Indian subcontinent and Indian Ocean region is derived operationally for the first time from the geostationary earth orbit (GEO) satellite INSAT-3D Imager data at 0.65 μm wavelength. Single visible channel algorithm based on clear sky composites gives larger retrieval error in AOD than other multiple channel algorithms due to errors in estimating surface reflectance and atmospheric property. However, since MIR channel signal is insensitive to the presence of most aerosols, therefore in present study, AOD retrieval algorithm employs both visible (centred at 0.65 μm) and mid-infrared (MIR) band (centred at 3.9 μm) measurements, and allows us to monitor transport of aerosols at higher temporal resolution. Comparisons made between INSAT-3D derived AOD (τ<sub>I</sub>) and MODIS derived AOD (τ<sub>M</sub>) co-located in space (at 1&deg; resolution) and time during January, February and March (JFM) 2014 encompasses 1165, 1052 and 900 pixels, respectively. Good agreement found between τ<sub>I</sub> and τ<sub>M</sub> during JFM 2014 with linear correlation coefficients (R) of 0.87, 0.81 and 0.76, respectively. The extensive validation made during JFM 2014 encompasses 215 co-located AOD in space and time derived by INSAT 3D (τ<sub>I</sub>) and 10 sun-photometers (τ<sub>A</sub>) that includes 9 AERONET (Aerosol Robotic Network) and 1 handheld sun-photometer site. INSAT-3D derived AOD i.e. τ<sub>I</sub>, is found within the retrieval errors of τ<sub>I</sub> = ±0.07 ±0.15τ<sub>A</sub> with linear correlation coefficient (R) of 0.90 and root mean square error equal (RMSE) to 0.06. Present work shows that INSAT-3D aerosol products can be used quantitatively in many applications with caution for possible residual clouds, snow/ice, and water contamination.

scholarly journals Improving GOES Advanced Baseline Imager (ABI) Aerosol Optical Depth (AOD) Retrievals using an Empirical Bias Correction Algorithm

2020 ◽  
Author(s):  
Hai Zhang ◽  
Shobha Kondragunta ◽  
Istvan Laszlo ◽  
Mi Zhou
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Bias Correction ◽  
Land Surface ◽  
Infrared Imaging ◽  
Retrieval Algorithm ◽  
Correction Algorithm ◽  
Time Step ◽  
Modis Aod ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. The Advanced Baseline Imager (ABI) on board the Geostationary Operational Environmental Satellite-R (GOES-R) series enables retrieval of aerosol optical depth (AOD) from geostationary satellites using a multi-band algorithm similar to those of polar-orbiting satellites’ sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS). Therefore, ABI AOD is expected to have accuracy and precision comparable to MODIS AOD and VIIRS AOD. However, this work demonstrates that the current version of GOES-16 (GOES-East) ABI AOD has diurnally varying biases due to errors in the land surface reflectance relationship between the bands used in the ABI AOD retrieval algorithm, which vary with respect to the Sun-satellite geometry. To reduce these biases, an empirical bias correction algorithm has been developed based on the lowest observed ABI AOD of an adjacent 30-day period and the background AOD at each time step and at each pixel. The bias correction algorithm improves the performance of ABI AOD compared to AErosol RObotic NETwork (AERONET) AOD, especially for the high and medium (top 2) quality ABI AOD. AOD data for the period August 6 to December 31, 2018 are used to validate the bias correction algorithm. For the top 2 qualities ABI AOD, after bias correction, the correlation between ABI AOD and AERONET AOD improves from 0.87 to 0.91, the mean bias improves from 0.04 to 0.00, and root mean square error (RMSE) improves from 0.09 to 0.05. These results for the bias corrected top 2 qualities ABI AOD are comparable to those of the uncorrected high-quality ABI AOD. Thus, by using the top 2 qualities of ABI AOD in conjunction with the bias correction algorithm, the area coverage of ABI AOD is substantially increased without loss of data accuracy.

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

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.

scholarly journals MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water

2017 ◽  
Author(s):  
Yi WANG ◽  
Jun Wang ◽  
Robert C Levy ◽  
Xiaoguang Xu ◽  
Jeffrey S Reid
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Coastal Water ◽  
Visible Spectrum ◽  
Single Scattering ◽  
Retrieval Algorithm ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Large Water

We present a new approach to retrieve Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) over the turbid coastal water. This approach supplements the operational Dark Target (DT) aerosol retrieval algorithm that currently don&rsquo;t conduct any AOD retrieval in the regions with large water-leaving radiances in the visible spectrum. Over the global coastal water regions in all cloud-free conditions, this unavailability of AOD retrievals due to the inherent limitation in existing DT algorithm is ~20%. Here, we refine the MODIS DT algorithm by considering that water-leaving radiance at 2.1 &mu;m is negligible regardless of water turbidity. This refinement, with the assumption that the aerosol single scattering properties over coastal turbid water are similar to that over the adjacent open-ocean pixels, yields ~18% more of MODIS-AERONET collocated pairs for six AEROENT stations in the coastal water regions. Furthermore, comparison with these AERONET observations show that the new AOD retrievals are in either equivalent or better accuracy than those retrieved by the MODIS operational algorithm (over coastal land and non-turbid coastal water). Combining the new retrievals with the existing MODIS operational retrievals not only yield an overall improvement of AOD over those coastal water regions, but also successfully extend the spatial and temporal coverage of MODIS AOD retrievals over the coastal regions where 60% of human population resides, and thereby, aerosol impacts on regional air quality and climate are expected to be significant.

scholarly journals A Dual-Channel Aerosol Optical Depth Retrieval Algorithm Incorporating the BRDF Effect from AVHRR over Eastern Asia

2021 ◽  
Vol 13 (3) ◽  
pp. 365
Author(s):  
Ying Wang ◽  
Xingfa Gu ◽  
Jian Li ◽  
Xiaofei Mi
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Retrieval Algorithm ◽  
Surface Reflectance ◽  
Eastern Asia ◽  
Angular Variation ◽  
Dual Channel ◽  
Noaa Avhrr ◽  
Dual Channels ◽  
Reflectance Ratio

A NOAA/AVHRR dual-channel method over land is proposed to simultaneously retrieve aerosol optical depth (AOD) at 0.55 μm, and surface reflectance at 0.63 and 0.85 μm. Compared with previous well-established one-channel retrieval algorithms, this algorithm takes advantage of the surface reflectance ratio between 0.63 and 0.85 μm in an attempt to account for the effect induced by the surface bidirectional reflectance distribution function (BRDF). This effect cannot be negligible due to the orbit drift and phasing running of NOAA satellites, both of which potentially cause large solar angular variation. Meanwhile, the observation posture change of AVHRR would cause large sensor angular variation in time series measurements. The used surface reflectance ratio based on dual channels at 0.63 and 0.85 μm is found more reasonable to be assumed as unchanged during a certain period of time, compared to the traditional ratio when addressing the BRDF issue. AOD retrievals have been carried out over Eastern Asia. Validation against aerosol robotic network (AERONET) measurements shows that up to 83% of AOD validation collocations are within error lines (±0.15 ± 0.15τ, τ is AOD) with an R of 0.88 and an root mean square error (RMSE) of 0.15. The dual-channel algorithm taking into account the surface BRDF effect is proved outperforming the conventional 0.63 μm-channel method. It indicates that our algorithm has the potential to be applied to the retrieval of long series of AOD, especially to the AOD retrieval of the sensors which lack a shortwave infrared channel required in the MODerate resolution Imaging Spectroradiometer (MODIS) dark target AOD algorithm.

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