scholarly journals Evaluation and comparison of multiangle implementation of the atmospheric correction algorithm, Dark Target, and Deep Blue aerosol products over China

2019 ◽  
Vol 19 (12) ◽  
pp. 8243-8268 ◽  
Author(s):  
Ning Liu ◽  
Bin Zou ◽  
Huihui Feng ◽  
Wei Wang ◽  
Yuqi Tang ◽  
...  
Keyword(s):  
Zenith Angle ◽  
Atmospheric Correction ◽  
Ground Truth ◽  
The North ◽  
Deep Blue ◽  
Aerosol Retrieval ◽  
Angle Scattering ◽  
Retrieval Algorithms ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Land Types

Abstract. A new multiangle implementation of the atmospheric correction (MAIAC) algorithm has been applied in the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and has recently provided globally high-spatial-resolution aerosol optical depth (AOD) products at 1 km. Moreover, several improvements have been modified in the classical Dark Target (DT) and Deep Blue (DB) aerosol retrieval algorithms in MODIS Collection 6.1 products. Thus, validation and comparison of the MAIAC, DT, and DB algorithms are urgent in China. In this paper, we present a comprehensive assessment and comparison of AOD products at a 550 nm wavelength based on three aerosol retrieval algorithms in the MODIS sensor using ground-truth measurements from AErosol RObotic NETwork (AERONET) sites over China from 2000 to 2017. In general, MAIAC products achieved better accuracy than DT and DB products in the overall validation and accuracy improvement of DB products after the QA filter, demonstrating the highest values among the three products. In addition, the DT algorithms had higher aerosol retrievals in cropland, forest, and ocean land types than the other two products, and the MAIAC algorithms were more accurate in grassland, built-up, unoccupied, and mixed land types among the three products. In the geometry dependency analysis, the solar zenith angle, scattering angle, and relative azimuth angle, excluding the view zenith angle, significantly affected the performance of the three aerosol retrieval algorithms. The three products showed different accuracies with varying regions and seasons. Similar spatial patterns were found for the three products, but the MAIAC retrievals were smaller in the North China Plain and higher in Yunnan Province compared with the DT and DB retrievals before the QA filter. After the QA filter, the DB retrievals were significantly lower than the MAIAC retrievals in south China. Moreover, the spatiotemporal completeness of the MAIAC product was also better than the DT and DB products.

scholarly journals Evaluation and comparison of MAIAC, DT and DB aerosol products over China

2019 ◽  
Author(s):  
Ning Liu ◽  
Bin Zou ◽  
Huihui Feng ◽  
Yuqi Tang ◽  
Yu Liang
Keyword(s):  
Atmospheric Correction ◽  
Ground Truth ◽  
Coefficient Of Determination ◽  
Land Type ◽  
Deep Blue ◽  
Aerosol Retrieval ◽  
Geometry Dependence ◽  
Retrieval Algorithms ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. A new Multiangle Implementation of Atmospheric Correction (MAIAC) algorithm has been applied in Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and recently provides globally high spatial resolution Aerosol Optical Depth (AOD) products at 1 km. Meanwhile, several improvements are modified in classical Dark Target (DT) and Deep Blue (DB) aerosol retrieval algorithms in MODIS collection 6.1 products. However, validation and comparison for MAIAC, DT and DB algorithms is still lacking in China. In this paper, a comprehensive assessment and comparison of AOD products at 550 nm wavelength based three aerosol retrieval algorithms in MODIS sensor using ground-truth measurements from Aerosol Robotic Network (AERONET) sites over China during 2000 to 2017 is presented. In general, after quality assurance (QA) filter, the coefficient of determination (R2=0.854), correlation coefficient (R=0.929), root-mean-square error (RMSE=0.178), mean bias (Bias=0.019) and the fraction fall within expected error (Within_EE=67.10 %, EE=±(0.05+0.15×AOD)) results for MAIAC algorithm show better accuracy than those from DT and DB algorithms. While the R2, R, RMSE, Bias and Within_EE of DT algorithm are 0.817, 0.930, 0.192, 0.077, 55.36 %, respectively, those corresponding statistics for DB algorithm are 0.827, 0.921, 0.190, 0.018, 63.32 %. Moreover, the spatiotemporal completeness for MAIAC (29.69 %) product is also better than DT (8.00 %) and DB (19.50 %) products after QA filter. In addition, the land type dependence characteristic, view geometry dependence, spatiotemporal retrieval accuracy and spatial variation pattern difference for three products are also analyzed in details.

scholarly journals Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements

2017 ◽  
Vol 122 (18) ◽  
pp. 9945-9967 ◽  
Author(s):  
A. M. Sayer ◽  
N. C. Hsu ◽  
J. Lee ◽  
N. Carletta ◽  
S.-H. Chen ◽  
...  
Keyword(s):  
Deep Blue ◽  
Aerosol Retrieval ◽  
Retrieval Algorithms

scholarly journals Analysis of the MODIS Above-Cloud Aerosol Retrieval Algorithm Using MCARS

2021 ◽  
Author(s):  
Galina Wind ◽  
Arlindo M. da Silva ◽  
Kerry G. Meyer ◽  
Steven Platnick ◽  
Peter M. Norris
Keyword(s):  
Boundary Layer ◽  
Optical Thickness ◽  
Marine Boundary Layer ◽  
Single Case ◽  
Ground Truth ◽  
Retrieval Algorithm ◽  
Boundary Layer Clouds ◽  
Aerosol Retrieval ◽  
Source Data ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. The Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS) presently produces synthetic radiance data from Goddard Earth Observing System version 5 (GEOS-5) model output as if the Moderate Resolution Imaging Spectroradiometer (MODIS) was viewing a combination of atmospheric column inclusive of clouds, aerosols and a variety of gases and land/ocean surface at a specific location. In this paper we use MCARS to study the MODIS Above-Cloud AEROsol retrieval algorithm (MOD06ACAERO). MOD06ACAERO is presently a regional research algorithm able to retrieve aerosol optical thickness over clouds, in particular absorbing biomass burning aerosols overlying marine boundary layer clouds in the Southeastern Atlantic Ocean. The algorithm's ability to provide aerosol information in cloudy conditions makes it a valuable source of information for modeling and climate studies in an area where current clear sky-only operational MODIS aerosol retrievals effectively have a data gap between the months of June and October. We use MCARS for a verification and closure study of the MOD06ACAERO algorithm. Our simulations indicate that the MOD06ACAERO algorithm performs well for marine boundary layer clouds in the SE Atlantic provided some specific screening rules are observed. For the present study, a combination of five simulated MODIS data granules was used for a dataset of 13.5 million samples with known input conditions. When pixel retrieval uncertainty was less than 30 %, optical thickness of the underlying cloud layer was greater than 4 and scattering angle range within the cloud bow was excluded, MOD06ACAERO retrievals agreed with the underlying ground truth (GEOS-5 cloud and aerosol profiles used to generate the synthetic radiances) with a slope of 0.913, offset of 0.06, and RMSE = 0.107. When only near-nadir pixels were considered (view zenith angle within +/−20 degrees) the agreement with source data further improved (0.977, 0.051 and 0.096 respectively). Algorithm closure was examined using a single case out of the five used for verification. For closure, the MOD06ACAERO code was modified to use GEOS-5 temperature and moisture profiles as ancillary. Agreement of MOD06ACAERO retrievals with source data for the closure study had a slope of 0.996 with offset −0.007 and RMSE of 0.097 at pixel uncertainty level of less than 40 %, illustrating the benefits of high-quality ancillary atmospheric data for such retrievals.

scholarly journals Exploring systematic offsets between aerosol products from the two MODIS sensors

2018 ◽  
Vol 11 (7) ◽  
pp. 4073-4092 ◽  
Author(s):  
Robert C. Levy ◽  
Shana Mattoo ◽  
Virginia Sawyer ◽  
Yingxi Shi ◽  
Peter R. Colarco ◽  
...  
Keyword(s):  
Ground Truth ◽  
Retrieval Algorithm ◽  
Polarization Sensitivity ◽  
Ground Truth Data ◽  
Diurnal Cycles ◽  
Aerosol Retrieval ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Modis ◽  
Cross Calibration

Abstract. Long-term measurements of global aerosol loading and optical properties are essential for assessing climate-related questions. Using observations of spectral reflectance and radiance, the dark-target (DT) aerosol retrieval algorithm is applied to Moderate Resolution Imaging Spectroradiometer sensors on both Terra (MODIS-T) and Aqua (MODIS-A) satellites, deriving products (known as MOD04 and MYD04, respectively) of global aerosol optical depth (AOD at 0.55 µm) over both land and ocean, and an Ångström exponent (AE derived from 0.55 and 0.86 µm) over ocean. Here, we analyze the overlapping time series (since mid-2002) of the Collection 6 (C6) aerosol products. Global monthly mean AOD from MOD04 (Terra with morning overpass) is consistently higher than MYD04 (Aqua with afternoon overpass) by ∼ 13 % (∼ 0.02 over land and ∼ 0.015 over ocean), and this offset (MOD04 – MYD04) has seasonal as well as long-term variability. Focusing on 2008 and deriving yearly gridded mean AOD and AE, we find that, over ocean, the MOD04 (morning) AOD is higher and the AE is lower. Over land, there is more variability, but only biomass-burning regions tend to have AOD lower for MOD04. Using simulated aerosol fields from the Goddard Earth Observing System (GEOS-5) Earth system model and sampling separately (in time and space) along each MODIS-observed swath during 2008, the magnitudes of morning versus afternoon offsets of AOD and AE are smaller than those in the C6 products. Since the differences are not easily attributed to either aerosol diurnal cycles or sampling issues, we test additional corrections to the input reflectance data. The first, known as C6+, corrects for long-term changes to each sensor's polarization sensitivity and the response versus the scan angle and to cross-calibration from MODIS-T to MODIS-A. A second convolves the detrending and cross-calibration into scaling factors. Each method was applied upstream of the aerosol retrieval using 2008 data. While both methods reduced the overall AOD offset over land from 0.02 to 0.01, neither significantly reduced the AOD offset over ocean. The overall negative AE offset was reduced. A collection (C6.1) of all MODIS Atmosphere products was released, but we expect that the C6.1 aerosol products will maintain similar overall AOD and AE offsets. We conclude that (a) users should not interpret global differences between Terra and Aqua aerosol products as representing a true diurnal signal in the aerosol. (b) Because the MODIS-A product appears to have an overall smaller bias compared to ground-truth data, it may be more suitable for some applications. However (c), since the AOD offset is only ∼ 0.02 and within the noise level for single retrievals, both MODIS products may be adequate for most applications.

scholarly journals Exploring systematic offsets between aerosol products from the two MODIS sensors

2018 ◽  
Author(s):  
Robert C. Levy ◽  
Shana Mattoo ◽  
Virginia Sawyer ◽  
Yingxi Shi ◽  
Peter R. Colarco ◽  
...  
Keyword(s):  
Ground Truth ◽  
Retrieval Algorithm ◽  
Polarization Sensitivity ◽  
Diurnal Cycles ◽  
Earth Observing System ◽  
Aerosol Retrieval ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Modis ◽  
Cross Calibration

Abstract. Long-term measurements of global aerosol loading and optical properties are essential for assessing climate-related questions. Using observations of spectral reflectance and radiance, the dark-target (DT) aerosol retrieval algorithm has been applied to Moderate-resolution Imaging Spectroradiometer sensors on both Terra (MODIS-T) and Aqua (MODIS-A) satellites, deriving products (known as MOD04 and MYD04, respectively) of global aerosol optical depth (AOD at 0.55 μm) over both land and ocean, and Angstrom Exponent (AE derived from 0.55 and 0.86 μmm) over ocean. Here, we analyse the overlapping time series (since mid-2002) of the Collection 6 (C6) aerosol products. Global monthly mean AOD from MOD04 (Terra with morning overpass) is consistently higher than MYD04 (Aqua with afternoon overpass) by ~13 % (~0.02 over land and ~0.015 over ocean), and this offset (MOD04 – MYD04), has seasonal as well as long-term variability. Focusing on 2008, and deriving yearly gridded mean AOD and AE, we find that over ocean, the MOD04 (morning) AOD is higher and the AE is lower. Over land, there is more variability, but only biomass-burning regions tend to have AOD lower for MOD04. Using simulated aerosol fields from the Goddard Earth Observing System (GEOS-5) Earth system model, and sampling separately (in time and space) along each MODIS-observed swath during 2008, the magnitudes of morning versus afternoon offsets of AOD and AE are smaller than those in the C6 products. Since the differences are not easily attributed to either aerosol diurnal cycles or sampling issues, we test additional corrections to the input reflectance data. The first, known as C6+, corrects for long-term changes to each sensors' polarization sensitivity, response-versus-scan angle, and to cross-calibration from MODIS-T to MODIS-A. A second convolves the de-trending and cross-calibration into scaling factors. Each method was applied upstream of the aerosol retrieval, using 2008 data. While both methods reduced the overall AOD offset over land from 0.02 to 0.01, neither significantly reduced the AOD offset over ocean. The overall negative AE offset was reduced. A Collection (C6.1) of all MODIS-atmosphere products was released, but we expect that the C6.1 aerosol products will maintain similar overall AOD and AE offsets. We conclude that: a) users should not interpret global differences between Terra and Aqua aerosol products as representing a true diurnal signal in the aerosol. b) Because the MODIS-A product appears to have overall smaller bias compared to ground-truth, it may be more suitable for some applications, however c) since the AOD offset is only ~0.02 and within noise level for single retrievals, both MODIS products may be adequate for most applications.

scholarly journals Analysis of the MODIS above-cloud aerosol retrieval algorithm using MCARS

2022 ◽  
Vol 15 (1) ◽  
pp. 1-14
Author(s):  
Galina Wind ◽  
Arlindo M. da Silva ◽  
Kerry G. Meyer ◽  
Steven Platnick ◽  
Peter M. Norris
Keyword(s):  
Boundary Layer ◽  
Optical Thickness ◽  
Marine Boundary Layer ◽  
Single Case ◽  
Ground Truth ◽  
Retrieval Algorithm ◽  
Boundary Layer Clouds ◽  
Aerosol Retrieval ◽  
Source Data ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. The Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS) presently produces synthetic radiance data from Goddard Earth Observing System version 5 (GEOS-5) model output as if the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of atmospheric column inclusive of clouds, aerosols, and a variety of gases and land–ocean surface at a specific location. In this paper we use MCARS to study the MODIS Above-Cloud AEROsol retrieval algorithm (MOD06ACAERO). MOD06ACAERO is presently a regional research algorithm able to retrieve aerosol optical thickness over clouds, in particular absorbing biomass-burning aerosols overlying marine boundary layer clouds in the southeastern Atlantic Ocean. The algorithm's ability to provide aerosol information in cloudy conditions makes it a valuable source of information for modeling and climate studies in an area where current clear-sky-only operational MODIS aerosol retrievals effectively have a data gap between the months of June and October. We use MCARS for a verification and closure study of the MOD06ACAERO algorithm. The purpose of this study is to develop a set of constraints a model developer might use during assimilation of MOD06ACAERO data. Our simulations indicate that the MOD06ACAERO algorithm performs well for marine boundary layer clouds in the SE Atlantic provided some specific screening rules are observed. For the present study, a combination of five simulated MODIS data granules were used for a dataset of 13.5 million samples with known input conditions. When pixel retrieval uncertainty was less than 30 %, optical thickness of the underlying cloud layer was greater than 4, and scattering angle range within the cloud bow was excluded, MOD06ACAERO retrievals agreed with the underlying ground truth (GEOS-5 cloud and aerosol profiles used to generate the synthetic radiances) with a slope of 0.913, offset of 0.06, and RMSE=0.107. When only near-nadir pixels were considered (view zenith angle within ±20∘) the agreement with source data further improved (0.977, 0.051, and 0.096 respectively). Algorithm closure was examined using a single case out of the five used for verification. For closure, the MOD06ACAERO code was modified to use GEOS-5 temperature and moisture profiles as an ancillary. Agreement of MOD06ACAERO retrievals with source data for the closure study had a slope of 0.996 with an offset of −0.007 and RMSE of 0.097 at a pixel uncertainty level of less than 40 %, illustrating the benefits of high-quality ancillary atmospheric data for such retrievals.

scholarly journals 250-m Aerosol Retrieval from FY-3 Satellite in Guangzhou

2021 ◽  
Vol 13 (5) ◽  
pp. 920
Author(s):  
Zhongting Wang ◽  
Ruru Deng ◽  
Pengfei Ma ◽  
Yuhuan Zhang ◽  
Yeheng Liang ◽  
...  
Keyword(s):  
Mixing Model ◽  
Blue Band ◽  
Aerosol Retrieval ◽  
Aerosol Distribution ◽  
Medium Resolution ◽  
Fine Spatial Resolution ◽  
Yearly Average ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Aerosol distribution with fine spatial resolution is crucial for atmospheric environmental management. This paper proposes an improved algorithm of aerosol retrieval from 250-m Medium Resolution Spectral Image (MERSI) data of Chinese FY-3 satellites. A mixing model of soil and vegetation was used to calculate the parameters of the algorithm from moderate-resolution imaging spectroradiometer (MODIS) reflectance products in 500-m resolution. The mixing model was used to determine surface reflectance in blue band, and the 250-m aerosol optical depth (AOD) was retrieved through removing surface contributions from MERSI data over Guangzhou. The algorithm was used to monitor two pollution episodes in Guangzhou in 2015, and the results displayed an AOD spatial distribution with 250-m resolution. Compared with the yearly average of MODIS aerosol products in 2015, the 250-m resolution AOD derived from the MERSI data exhibited great potential for identifying air pollution sources. Daily AODs derived from MERSI data were compared with ground results from CE318 measurements. The results revealed a correlation coefficient between the AODs from MERSI and those from the ground measurements of approximately 0.85, and approximately 68% results were within expected error range of ±(0.05 + 15%τ).

scholarly journals Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian Ocean

2021 ◽  
Vol 13 (2) ◽  
pp. 184
Author(s):  
Rongjie Liu ◽  
Jie Zhang ◽  
Tingwei Cui ◽  
Haocheng Yu
Keyword(s):  
Remote Sensing ◽  
Indian Ocean ◽  
Infrared Imaging ◽  
Atmospheric Correction ◽  
Spatiotemporal Pattern ◽  
Anthropogenic Aerosols ◽  
Remote Sensing Reflectance ◽  
The Indian Ocean ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Modis

Spectral remote sensing reflectance (Rrs(λ), sr−1) is one of the most important products of ocean color satellite missions, where accuracy is essential for retrieval of in-water, bio-optical, and biogeochemical properties. For the Indian Ocean (IO), where Rrs(λ) accuracy has not been well documented, the quality of Rrs(λ) products from Moderate Resolution Imaging Spectroradiometer onboard both Terra (MODIS-Terra) and Aqua (MODIS-Aqua), and Visible Infrared Imaging Radiometer Suite onboard the Suomi National Polar-Orbiting Partnership spacecraft (VIIRS-NPP), is evaluated and inter-compared based on a quality assurance (QA) system, which can objectively grade each individual Rrs(λ) spectrum, with 1 for a perfect spectrum and 0 for an unusable spectrum. Taking the whole year of 2016 as an example, spatiotemporal pattern of Rrs(λ) quality in the Indian Ocean is characterized for the first time, and the underlying factors are elucidated. Specifically, QA analysis of the monthly Rrs(λ) over the IO indicates good quality with the average scores of 0.93 ± 0.02, 0.92 ± 0.02 and 0.92 ± 0.02 for VIIRS-NPP, MODIS-Aqua, and MODIS-Terra, respectively. Low-quality (~0.7) data are mainly found in the Bengal Bay (BB) from January to March, which can be attributed to the imperfect atmospheric correction due to anthropogenic absorptive aerosols transported by the northeasterly winter monsoon. Moreover, low-quality (~0.74) data are also found in the clear oligotrophic gyre zone (OZ) of the south IO in the second half of the year, possibly due to residual sun-glint contributions. These findings highlight the effects of monsoon-transported anthropogenic aerosols, and imperfect sun-glint removal on the Rrs(λ) quality. Further studies are advocated to improve the sun-glint correction in the oligotrophic gyre zone and aerosol correction in the complex ocean–atmosphere environment.

scholarly journals Extreme levels of Canadian wildfire smoke in the stratosphere over central Europe on 21–22 August 2017

2018 ◽  
Vol 18 (16) ◽  
pp. 11831-11845 ◽  
Author(s):  
Albert Ansmann ◽  
Holger Baars ◽  
Alexandra Chudnovsky ◽  
Ina Mattis ◽  
Igor Veselovskii ◽  
...  
Keyword(s):  
Central Europe ◽  
Volcanic Eruptions ◽  
Light Extinction ◽  
Ozone Monitoring Instrument ◽  
Wildfire Smoke ◽  
The North ◽  
Radiative Power ◽  
Peak Mass ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Light extinction coefficients of 500 Mm−1, about 20 times higher than after the Pinatubo volcanic eruptions in 1991, were observed by European Aerosol Research Lidar Network (EARLINET) lidars in the stratosphere over central Europe on 21–22 August 2017. Pronounced smoke layers with a 1–2 km vertical extent were found 2–5 km above the local tropopause. Optically dense layers of Canadian wildfire smoke reached central Europe 10 days after their injection into the upper troposphere and lower stratosphere which was caused by rather strong pyrocumulonimbus activity over western Canada. The smoke-related aerosol optical thickness (AOT) identified by lidar was close to 1.0 at 532 nm over Leipzig during the noon hours on 22 August 2017. Smoke particles were found throughout the free troposphere (AOT of 0.3) and in the pronounced 2 km thick stratospheric smoke layer at an altitude of 14–16 km (AOT of 0.6). The lidar observations indicated peak mass concentrations of 70–100 µg m−3 in the stratosphere. In addition to the lidar profiles, we analyzed Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power (FRP) over Canada, and the distribution of MODIS AOT and Ozone Monitoring Instrument (OMI) aerosol index across the North Atlantic. These instruments showed a similar pattern and a clear link between the western Canadian fires and the aerosol load over Europe. In this paper, we also present Aerosol Robotic Network (AERONET) sun photometer observations, compare photometer and lidar-derived AOT, and discuss an obvious bias (the smoke AOT is too low) in the photometer observations. Finally, we compare the strength of this record-breaking smoke event (in terms of the particle extinction coefficient and AOT) with major and moderate volcanic events observed over the northern midlatitudes.

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