scholarly journals Integration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaigns

2021 ◽  
Vol 14 (6) ◽  
pp. 4575-4592
Author(s):  
Hyunkwang Lim ◽  
Sujung Go ◽  
Jhoon Kim ◽  
Myungje Choi ◽  
Seoyoung Lee ◽  
...  
Keyword(s):  
Data Fusion ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Near Infrared ◽  
Likelihood Estimation ◽  
Low Earth Orbit ◽  
Bias Error ◽  
Ensemble Mean ◽  
Low Earth Orbit Satellites ◽  
Shortwave Infrared

Abstract. The Yonsei Aerosol Retrieval (YAER) algorithm for the Geostationary Ocean Color Imager (GOCI) retrieves aerosol optical properties only over dark surfaces, so it is important to mask pixels with bright surfaces. The Advanced Himawari Imager (AHI) is equipped with three shortwave-infrared and nine infrared channels, which is advantageous for bright-pixel masking. In addition, multiple visible and near-infrared channels provide a great advantage in aerosol property retrieval from the AHI and GOCI. By applying the YAER algorithm to 10 min AHI or 1 h GOCI data at 6 km×6 km resolution, diurnal variations and aerosol transport can be observed, which has not previously been possible from low-Earth-orbit satellites. This study attempted to estimate the optimal aerosol optical depth (AOD) for East Asia by data fusion, taking into account satellite retrieval uncertainty. The data fusion involved two steps: (1) analysis of error characteristics of each retrieved result with respect to the ground-based Aerosol Robotic Network (AERONET), as well as bias correction based on normalized difference vegetation indexes, and (2) compilation of the fused product using ensemble-mean and maximum-likelihood estimation (MLE) methods. Fused results show a better statistics in terms of fraction within the expected error, correlation coefficient, root-mean-square error (RMSE), and median bias error than the retrieved result for each product. If the RMSE and mean AOD bias values used for MLE fusion are correct, the MLE fused products show better accuracy, but the ensemble-mean products can still be useful as MLE.

scholarly journals Integration of GOCI and AHI Yonsei Aerosol Optical Depth Products During the 2016 KORUS-AQ and 2018 EMeRGe Campaigns

2020 ◽  
Author(s):  
Hyunkwang Lim ◽  
Sujung Go ◽  
Jhoon Kim ◽  
Myungje Choi ◽  
Seoyoung Lee ◽  
...  
Keyword(s):  
Data Fusion ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Near Infrared ◽  
Likelihood Estimation ◽  
Low Earth Orbit ◽  
Estimation Methods ◽  
Bias Error ◽  
Low Earth Orbit Satellites ◽  
Shortwave Infrared

Abstract. The Yonsei AErosol Retrieval (YAER) algorithm for the Geostationary Ocean Color Imager (GOCI) retrieves aerosol optical properties only over dark surfaces, so it is important to mask pixels with bright surfaces. The Advanced Himawari Imager (AHI) is equipped with three shortwave-infrared and nine infrared channels, which is advantageous for bright-pixel masking. In addition, multiple visible and near-infrared channels provide a great advantage in aerosol property retrieval from the AHI and GOCI. By applying the YAER algorithm to 10 minutes AHI or 1 hour GOCI data at 6 km × 6 km resolution, diurnal variations and aerosol transport can be observed, which has not previously been possible from low-earth-orbit satellites. This study attempted to estimate the optimal aerosol optical depth (AOD) for East Asia by data fusion, taking into account satellite retrieval uncertainty. The data fusion involved two steps: (1) analysis of error characteristics of each retrieved result with respect to the ground-based Aerosol Robotic Network (AERONET), and bias correction based on normalized difference vegetation indexes; and (2) estimation of the fused product using ensemble-mean and maximum-likelihood estimation methods. Fused results show a better statistics in terms of fraction within the expected error, correlation coefficient, root-mean-square error, median bias error than the retrieved result for each product.

scholarly journals Composite Aerosol Optical Depth Mapping over Northeast Asia from GEO-LEO Satellite Observations

2021 ◽  
Vol 13 (6) ◽  
pp. 1096
Author(s):  
Soi Ahn ◽  
Sung-Rae Chung ◽  
Hyun-Jong Oh ◽  
Chu-Yong Chung
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Northeast Asia ◽  
Low Earth Orbit ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Radiometric Calibration ◽  
Climate Data ◽  
Error Statistics ◽  
Spatiotemporal Resolution

This study aimed to generate a near real time composite of aerosol optical depth (AOD) to improve predictive model ability and provide current conditions of aerosol spatial distribution and transportation across Northeast Asia. AOD, a proxy for aerosol loading, is estimated remotely by various spaceborne imaging sensors capturing visible and infrared spectra. Nevertheless, differences in satellite-based retrieval algorithms, spatiotemporal resolution, sampling, radiometric calibration, and cloud-screening procedures create significant variability among AOD products. Satellite products, however, can be complementary in terms of their accuracy and spatiotemporal comprehensiveness. Thus, composite AOD products were derived for Northeast Asia based on data from four sensors: Advanced Himawari Imager (AHI), Geostationary Ocean Color Imager (GOCI), Moderate Infrared Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). Cumulative distribution functions were employed to estimate error statistics using measurements from the Aerosol Robotic Network (AERONET). In order to apply the AERONET point-specific error, coefficients of each satellite were calculated using inverse distance weighting. Finally, the root mean square error (RMSE) for each satellite AOD product was calculated based on the inverse composite weighting (ICW). Hourly AOD composites were generated (00:00–09:00 UTC, 2017) using the regression equation derived from the comparison of the composite AOD error statistics to AERONET measurements, and the results showed that the correlation coefficient and RMSE values of composite were close to those of the low earth orbit satellite products (MODIS and VIIRS). The methodology and the resulting dataset derived here are relevant for the demonstrated successful merging of multi-sensor retrievals to produce long-term satellite-based climate data records.

scholarly journals Ground Reflectance Retrieval on Horizontal and Inclined Terrains Using the Software Package REFLECT

2018 ◽  
Vol 10 (10) ◽  
pp. 1638
Author(s):  
Yacine Bouroubi ◽  
Wided Batita ◽  
François Cavayas ◽  
Nicolas Tremblay
Keyword(s):  
Optical Properties ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Software Package ◽  
Near Infrared ◽  
Solar Spectrum ◽  
Sensor Calibration ◽  
Topographic Effects ◽  
Atmospheric Conditions ◽  
Spectral Bands

This paper presents the software package REFLECT for the retrieval of ground reflectance from high and very-high resolution multispectral satellite images. The computation of atmospheric parameters is based on the 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) routines. Aerosol optical properties are calculated using the OPAC (Optical Properties of Aerosols and Clouds) model, while aerosol optical depth is estimated using the dark target method. A new approach is proposed for adjacency effect correction. Topographic effects were also taken into account, and a new model was developed for forest canopies. Validation has shown that ground reflectance estimation with REFLECT is performed with an accuracy of approximately ±0.01 in reflectance units (for the visible, near-infrared, and mid-infrared spectral bands), even for surfaces with varying topography. The validation of the software was performed through many tests. These tests involve the correction of the effects that are associated with sensor calibration, irradiance, and viewing conditions, atmospheric conditions (aerosol optical depth AOD and water vapour), adjacency, and topographic conditions.

The Spectral Model Construction between MODIS SWIR and HJ-1 CCD Blue Channel and its Application in Aerosol Retrieval

2013 ◽  
Vol 726-731 ◽  
pp. 4631-4635 ◽  
Author(s):  
Chang Kui Sun ◽  
Lin Sun ◽  
Dan Li ◽  
Zheng Zhao ◽  
Kun Yu
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Reflectance ◽  
Blue Band ◽  
Retrieval Method ◽  
Aerosol Retrieval ◽  
Swir Band ◽  
Blue Channel ◽  
Typical Object ◽  
Shortwave Infrared

For the lacks of a shortwave infrared (SWIR) band, aerosol optical depth (AOD) retrieval by HJ-1 A/B CCD datasets is limited obviously. This article simulated the relationships of surface reflectance between HJ-1 CCD blue band and MODIS SWIR channel using typical object spectra from ASTER spectral library. A new surface reflectance determining model at HJ-1 CCD blue band was constructed by introducing MODIS SWIR channel as support, and was used in HJ-1 A/B CCD aerosol optical depth retrieval. The validation using AERONET ground measurements indicated that the proposed aerosol retrieval method has preferable accuracy and stability.

scholarly journals Nocturnal aerosol optical depth measurements with modified skyradiometer POM-02 using the moon as a light source

2019 ◽  
Author(s):  
Akihiro Uchiyama ◽  
Masataka Shiobara ◽  
Hiroshi Kobayashi ◽  
Tsuneo Matsunaga ◽  
Akihiro Yamazaki ◽  
...  
Keyword(s):  
Light Source ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Phase Angle ◽  
Near Infrared ◽  
Wavelength Region ◽  
High Spectral Resolution ◽  
The Sun ◽  
The Moon ◽  
Calibration Constant

Abstract. The majority of aerosol data are obtained from daytime measurements, and there are few datasets available for studying nighttime aerosol characteristics. In order to estimate the aerosol optical depth (AOD) and the precipitable water vapor (PWV) during the nighttime using the moon as a light source, a skyradiometer POM-02 (Prede Ltd., Japan) was modified. The amplifier was adjusted so that POM-02 could measure lower levels of input irradiance. In order to track the moon based on the calculated values, a simplified formula was incorporated into the firmware. A new position sensor with a four-quadrant detector to adjust tracking of the sun and the moon was also developed. The calibration constant, which is the sensor output for the extra-terrestrial solar and lunar irradiance at the mean earth-sun distance, was determined by using the Langley method. The measurements for the Langley calibration were conducted at the NOAA/MLO in October and November 2017. By assuming that the relative variation of the reflectance of the Robotic Lunar Observatory (ROLO) irradiance model is correct, the calibration constant for the lunar direct irradiance was successfully determined using the Langley method. The ratio of the calibration constant for the moon to that for the sun was often greater than 1; the value of the ratio was 0.95 to 1.18 in the visible near-infrared wavelength region. This means that the ROLO model often underestimates the reflectance. In addition, this ratio depended on the phase angle. In this study, this ratio was approximated by a quadratic expression of the phase angle. By using this approximation, the reflectance of the moon can be calculated to within an accuracy of 1 % or less. In order to validate the estimates of the AOD and PWV, continuous measurements with POM-02 were conducted at MRI/JMA from January 2018 to May 2018, and the AOD and PWV were estimated. The results were compared with the AOD and PWV obtained by independent methods. The AOD was compared with that estimated from NIES High Spectral Resolution Lidar measurements (wavelength: 532 nm), and the PWV was compared with the PWV obtained from a radiosonde and the Global Positioning System. As a result, the estimations of the AOD and the PWV using the moon as the light source were made with the same degree of precision and accuracy as the estimates using the sun as the light source.

scholarly journals Aerosol radiative effects in the ultraviolet, visible, and near-infrared spectral ranges using long-term aerosol data series over the Iberian Peninsula

2014 ◽  
Vol 14 (7) ◽  
pp. 8779-8818 ◽  
Author(s):  
D. Mateos ◽  
M. Antón ◽  
C. Toledano ◽  
V. E. Cachorro ◽  
L. Alados-Arboledas ◽  
...  
Keyword(s):  
Iberian Peninsula ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Near Infrared ◽  
Radiative Properties ◽  
Radiative Effects ◽  
Spectral Ranges ◽  
Aerosol Radiative Effects ◽  
Aerosol Radiative

Abstract. A better understanding of the aerosol radiative properties is a crucial challenge for climate change studies. This study aims to provide a complete characterization of aerosol radiative effects in different spectral ranges within the shortwave (SW) solar spectrum. For this purpose, long-term datasets of aerosol properties from six AERONET stations located in the Iberian Peninsula (Southwestern Europe) are analyzed in term of climatology characterization and trends. Aerosol information is used as input to the libRadtran model in order to determine the aerosol radiative effect at the surface in the ultraviolet (AREUV), visible (AREVIS), near-infrared (ARENIR), and the entire SW range (ARESW) under cloud-free conditions. Over the whole Iberian Peninsula, aerosol radiative effects in the different spectral ranges are: −1.1 < AREUV < −0.7 W m−2, −5.7 < AREVIS < −3.8 W m−2, −2.8 < ARENIR < −1.7 W m−2, and −9.5 < ARESW < −6.1 W m−2. The four variables showed positive statistically significant trends between 2004 and 2012, e.g., ARESW increased +3.6 W m−2 per decade. This fact is linked to the decrease in the aerosol load, which presents a trend of −0.04 per unit of aerosol optical depth at 500 nm per decade, hence a reduction of aerosol effect on solar radiation at the surface is seen. Monthly means of ARE show a seasonal pattern with larger values in spring and summer. The aerosol forcing efficiency (AFE), ARE per unit of aerosol optical depth, is also evaluated in the four spectral ranges. AFE exhibits a dependence on single scattering albedo and a weaker one on Ångström exponent. AFE is larger (in absolute value) for small and absorbing particles. The contributions of the UV, VIS, and NIR ranges to the SW efficiency vary with the aerosol types. Aerosol size determines the fractions of AFEVIS/AFESW and AFENIR/AFESW. VIS range is the dominant region for all types, although non-absorbing large particles cause a more equal contribution of VIS and NIR intervals. The AFEUV / AFESW ratio shows a higher contribution for absorbing fine particles.

scholarly journals Comparative measurements of total ozone amount and aerosol optical depth during a campaign at El Arenosillo, Huelva, Spain

2005 ◽  
Vol 23 (11) ◽  
pp. 3399-3406 ◽  
Author(s):  
A. de La Casinière ◽  
V. Cachorro ◽  
I. Smolskaia ◽  
J. Lenoble ◽  
M. Sorribas ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Total Ozone ◽  
Near Infrared ◽  
Relative Difference ◽  
Diurnal Variations ◽  
Near Ultraviolet ◽  
Ozone Amount ◽  
The Difference ◽  
Ozone Column

Abstract. A one week field campaign took place in September 2002 at El Arenosillo, Spain. The objective was to compare total ozone column (TOC) and aerosol optical depth (AOD) from near ultraviolet to near infrared, measured by several Spanish and French instruments. Three spectroradiometers, Brewer, SPUV02, and LICOR, and a CIMEL photometer, have been used simultaneously and the results are presented for four clear days. TOC values are given by the Brewer instrument, and by SPUV02, using two different methods. The ground instruments compare satisfactorily (within 5 DU) and the values are consistent with TOMS data (within 10 DU). AOD from the various instruments are compared at seven different wavelengths between 320 nm and 1020 nm: the agreement is very good at 350, 380, and 870 nm; at the four other wavelengths the difference is smaller than 0.03, which can be explained by a relative difference of 4% only between the calibrations of the various instruments. Larger AOD diurnal variations were observed at short wavelengths than in the visible and near infrared; this is most likely due to changes in aerosol size along the day, during the campaign.

scholarly journals Advancements in the Aerosol Robotic Network (AERONET) Version 3 Database – Automated Near Real-Time Quality Control Algorithm with Improved Cloud Screening for Sun Photometer Aerosol Optical Depth (AOD) Measurements

2018 ◽  
Author(s):  
David M. Giles ◽  
Alexander Sinyuk ◽  
Mikhail S. Sorokin ◽  
Joel S. Schafer ◽  
Alexander Smirnov ◽  
...  
Keyword(s):  
Quality Control ◽  
Standard Deviation ◽  
Real Time ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Near Infrared ◽  
Data Set ◽  
Automatic Data ◽  
Field Calibration ◽  
Cloud Screening

Abstract. The Aerosol Robotic Network (AERONET) provides highly accurate, ground-truth measurements of the aerosol optical depth (AOD) using Cimel Electronique Sun/Sky radiometers for more than 25 years. In Version 2 (V2) of the AERONET database, the near real-time AOD was semi-automatically quality controlled utilizing mainly cloud screening methodology, while additional AOD data contaminated by clouds or affected by instrument anomalies were removed manually before attaining quality assured status (Level 2.0). The large growth in the number of AERONET sites over the past 25 years resulted in significant burden to manually quality control millions of measurements in a consistent manner. The AERONET Version 3 (V3) algorithm provides fully automatic cloud screening and instrument anomaly quality controls. All of these new algorithm updates apply to near real-time data as well as post-field deployment processed data, and AERONET reprocessed the database in 2018. A full algorithm redevelopment provided the opportunity to improve data inputs and corrections such as unique filter specific temperature characterizations for all visible and near-infrared wavelengths, updated gaseous and water vapor absorption coefficients, and ancillary data sets. The Level 2.0 AOD quality assured data set is now available within a month after post-field calibration, reducing the lag time from up to several months. Near real-time estimated uncertainty is determined using data qualified as V3 Level 2.0 AOD and considering the difference between the AOD computed with the pre-field calibration and AOD computed with pre-field and post-field calibration. This assessment provides a near real-time uncertainty estimate where average differences of AOD suggest a +0.02 bias and one sigma uncertainty of 0.02, spectrally, but the bias and uncertainty can be significantly larger for specific instrument deployments. Long-term monthly averages analyzed for the entire V3 and V2 databases produced average differences (V3–V2) of +0.002 with a ±0.02 standard deviation, yet monthly averages calculated using time-matched observations in both databases were analyzed to compute an average difference of −0.002 with a ±0.004 standard deviation. The high statistical agreement in multi-year monthly averaged AOD validates the advanced automatic data quality control algorithms and suggests that migrating research to the V3 database will corroborate most V2 research conclusions and likely lead to more accurate results in some cases.

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