Intercomparing the Aerosol Optical Depth Using the Geostationary Satellite Sensors (AHI, GOCI and MI) from Yonsei AErosol Retrieval (YAER) Algorithm

2018 ◽  
Vol 39 (2) ◽  
pp. 119-130 ◽  
Author(s):  
Hyunkwang Lim ◽  
Myungje Choi ◽  
Mijin Kim ◽  
Jhoon Kim ◽  
Sujung Go ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Geostationary Satellite ◽  
Aerosol Retrieval ◽  
Satellite Sensors

scholarly journals Aerosol optical depth measurements by airborne sun photometer in SOLVE II: Comparisons to SAGE III, POAM III and airborne spectrometer measurements

2005 ◽  
Vol 5 (5) ◽  
pp. 1311-1339 ◽  
Author(s):  
P. Russell ◽  
J. Livingston ◽  
B. Schmid ◽  
J. Eilers ◽  
R. Kolyer ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Stratospheric Aerosol ◽  
Line Of Sight ◽  
Aerosol Measurement ◽  
Validation Experiment ◽  
Satellite Sensors ◽  
Beam Transmission ◽  
Relative Differences ◽  
Polar Ozone

Abstract. The 14-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14) measured solar- beam transmission on the NASA DC-8 during the second SAGE III Ozone Loss and Validation Experiment (SOLVE II). This paper presents AATS-14 results for multiwavelength aerosol optical depth (AOD), including comparisons to results from two satellite sensors and another DC-8 instrument, namely the Stratospheric Aerosol and Gas Experiment III (SAGE III), the Polar Ozone and Aerosol Measurement III (POAM III) and the Direct-beam Irradiance Airborne Spectrometer (DIAS). AATS-14 provides aerosol results at 13 wavelengths λ spanning the range of SAGE III and POAM III aerosol wavelengths. Because most AATS measurements were made at solar zenith angles (SZA) near 90°, retrieved AODs are strongly affected by uncertainties in the relative optical airmass of the aerosols and other constituents along the line of sight (LOS) between instrument and sun. To reduce dependence of the AATS-satellite comparisons on airmass, we perform the comparisons in LOS transmission and LOS optical thickness (OT) as well as in vertical OT (i.e., optical depth, OD). We also use a new airmass algorithm that validates the algorithm we previously used to within 2% for SZA<90°, and in addition provides results for SZA≥90°. For 6 DC-8 flights, 19 January-2 February 2003, AATS and DIAS results for LOS aerosol OT at λ=400nm agree to ≤12% of the AATS value. Mean and root-mean-square (RMS) differences, (DIAS-AATS)/AATS, are -2.3% and 7.7%, respectively. For DC-8 altitudes, AATS-satellite comparisons are possible only for λ>440nm, because of signal depletion for shorter λ on the satellite full-limb LOS. For the 4 AATS-SAGE and 4 AATS-POAM near-coincidences conducted 19-31 January 2003, AATS-satellite AOD differences were ≤0.0041 for all λ>440nm. RMS differences were ≤0.0022 for SAGE-AATS and ≤0.0026 for POAM-AATS. RMS relative differences in AOD ([SAGE-AATS]/AATS) were ≤33% for λ<~755nm, but grew to 59% for 1020nm and 66% at 1545nm. For λ>~755nm, AATS-POAM differences were less than AATS-SAGE differences, and RMS relative differences in AOD ([AATS-POAM]/AATS) were ≤31% for all λ between 440 and 1020nm. Unexplained differences that remain are associated with transmission differences, rather than differences in gas subtraction or conversion from LOS to vertical quantities. The very small stratospheric AOD values that occurred during SOLVE II added to the challenge of the comparisons, but do not explain all the differences.

scholarly journals Improvements of synergetic aerosol retrieval for ENVISAT

2008 ◽  
Vol 8 (24) ◽  
pp. 7651-7672 ◽  
Author(s):  
T. Holzer-Popp ◽  
M. Schroedter-Homscheidt ◽  
H. Breitkreuz ◽  
D. Martynenko ◽  
L. Klüser
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Brightness ◽  
Dark Field ◽  
Water Soluble ◽  
Aerosol Composition ◽  
Aerosol Retrieval ◽  
First Case ◽  
Satellite Platform ◽  
Version 2.0

Abstract. The synergetic aerosol retrieval method SYNAER (Holzer-Popp et al., 2002a) has been extended to the use of ENVISAT measurements. It exploits the complementary information of a radiometer and a spectrometer onboard one satellite platform to extract aerosol optical depth (AOD) and speciation (as a choice from a representative set of pre-defined mixtures of water-soluble, soot, mineral dust, and sea salt components). SYNAER consists of two retrieval steps. In the first step the radiometer is used for accurate cloud screening, and subsequently to quantify the aerosol optical depth (AOD) at 550 nm and spectral surface brightness through a dark field technique for different pre-defined aerosol mixtures. In the second step the spectrometer is applied to choose the most plausible aerosol mixture through a least square fit of the measured spectrum with simulated spectra using the mixture-dependent values of AOD and surface brightness retrieved in the first step. This method was developed and a first case study evaluation against few (15) multi-spectral ground-based AERONET sun photometer observations was conducted with a sensor pair (ATSR-2 and GOME) onboard ERS-2. Due to instrumental limitations the coverage of SYNAER/ERS-2 is very sparse. Therefore, SYNAER was transferred to similar sensors AATSR and SCIAMACHY onboard ENVISAT. While transferring to the new sensor pair significant improvements in the methodology were made based on a thorough evaluation of the methodology: (1) an update of the aerosol model, (2) improved cloud detection in the tropics and sub tropics, and (3) an enhanced dark field albedo characterization. This paper describes these improvements in detail and assesses their combined impact on the results. After a brief assessment of atmospheric noise impact on comparisons of pixel and station measurements a validation against ground-based measurements establishes error bars for the SYNAER/ENVISAT method version 2.0. A theoretical analysis of the information content with regard to aerosol composition (second retrieval step) is presented to quantify the potential and limitations of this new capability provided by the SYNAER method. Building on this analysis, first seasonal and monthly composition results calculated by applying SYNAER version 2.0 to AATSR and SCIAMACHY are shown to demonstrate the potential of the approach. An inter-comparison to earlier results of SYNAER version 1.0 is made for both the validation and the example datasets.

scholarly journals Retrieval of aerosol optical depth over land surfaces from AVHRR data

2013 ◽  
Vol 6 (1) ◽  
pp. 2227-2251 ◽  
Author(s):  
L. Mei ◽  
Y. Xue ◽  
A. A. Kokhanovsky ◽  
W. von Hoyningen-Huene ◽  
G. de Leeuw ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Reflectance ◽  
Aerosol Retrieval ◽  
Avhrr Data ◽  
Land Surfaces ◽  
Very High

Abstract. The Advanced Very High Resolution Radiometer (AVHRR) radiance data provide a global, long-term, consistent time series having high spectral and spatial resolution and thus being valuable for the retrieval of surface spectral reflectance, albedo and surface temperature. Long term time series of such data products are necessary for studies addressing climate change, sea ice distribution and movement, and ice sheet coastal configuration. These data have also been used to retrieve aerosol properties over ocean and land surfaces. However, the retrieval of aerosol over land and land surface albedo are challenging because of the information content of the measurement is limited and the inversion of these data products being ill defined. Solving the radiative transfer equations requires additional information and knowledge to reduce the number of unknowns. In this contribution we utilise an empirical linear relationship between the surface reflectances in the AVHRR channels at wavelengths of 3.75 μm and 2.1 μm, which has been identified in Moderate Resolution Imaging Spectroradiometer (MODIS) data. Next, following the MODIS dark target approach, the surface reflectance at 0.64 μm was obtained. The comparison of the estimated surface reflectance at 0.64 μm with MODIS reflectance products (MOD09) shows a strong correlation (R = 0.7835). Once this was established, the MODIS "dark-target" aerosol retrieval method was adapted to Advanced Very High Resolution Radiometer (AVHRR) data. A simplified Look-Up Table (LUT) method, adopted from Bremen AErosol Retrieval (BAER) algorithm, was used in the retrieval. The Aerosol Optical Depth (AOD) values retrieved from AVHRR with this method compare favourably with ground-based measurements, with a correlation coefficient R = 0.861 and Root Mean Square Error (RMSE) = 0.17. This method can be easily applied to other satellite instruments which do not have a 2.1 μm channel, such as those currently planned to geostationary satellites.

scholarly journals Validation, comparison, and integration of GOCI, AHI, MODIS, MISR, and VIIRS aerosol optical depth over East Asia during the 2016 KORUS-AQ campaign

2019 ◽  
Vol 12 (8) ◽  
pp. 4619-4641 ◽  
Author(s):  
Myungje Choi ◽  
Hyunkwang Lim ◽  
Jhoon Kim ◽  
Seoyoung Lee ◽  
Thomas F. Eck ◽  
...  
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Temporal Resolution ◽  
High Accuracy ◽  
The Yellow Sea ◽  
High Temporal Resolution ◽  
Earth Orbit ◽  
Satellite Sensors

Abstract. Recently launched multichannel geostationary Earth orbit (GEO) satellite sensors, such as the Geostationary Ocean Color Imager (GOCI) and the Advanced Himawari Imager (AHI), provide aerosol products over East Asia with high accuracy, which enables the monitoring of rapid diurnal variations and the transboundary transport of aerosols. Most aerosol studies to date have used low Earth orbit (LEO) satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging Spectroradiometer (MISR), with a maximum of one or two overpass daylight times per day from midlatitudes to low latitudes. Thus, the demand for new GEO observations with high temporal resolution and improved accuracy has been significant. In this study the latest versions of aerosol optical depth (AOD) products from three LEO sensors – MODIS (Dark Target, Deep Blue, and MAIAC), MISR, and the Visible/Infrared Imager Radiometer Suite (VIIRS), along with two GEO sensors (GOCI and AHI), are validated, compared, and integrated for a period during the Korea–United States Air Quality Study (KORUS-AQ) field campaign from 1 May to 12 June 2016 over East Asia. The AOD products analyzed here generally have high accuracy with high R (0.84–0.93) and low RMSE (0.12–0.17), but their error characteristics differ according to the use of several different surface-reflectance estimation methods. High-accuracy near-real-time GOCI and AHI measurements facilitate the detection of rapid AOD changes, such as smoke aerosol transport from Russia to Japan on 18–21 May 2016, heavy pollution transport from China to the Korean Peninsula on 25 May 2016, and local emission transport from the Seoul Metropolitan Area to the Yellow Sea in South Korea on 5 June 2016. These high-temporal-resolution GEO measurements result in more representative daily AOD values and make a greater contribution to a combined daily AOD product assembled by median value selection with a 0.5∘×0.5∘ grid resolution. The combined AOD is spatially continuous and has a greater number of pixels with high accuracy (fraction within expected error range of 0.61) than individual products. This study characterizes aerosol measurements from LEO and GEO satellites currently in operation over East Asia, and the results presented here can be used to evaluate satellite measurement bias and air quality models.

scholarly journals Retrieval of aerosol optical depth over land surfaces from AVHRR data

2014 ◽  
Vol 7 (8) ◽  
pp. 2411-2420 ◽  
Author(s):  
L. L. Mei ◽  
Y. Xue ◽  
A. A. Kokhanovsky ◽  
W. von Hoyningen-Huene ◽  
G. de Leeuw ◽  
...  
Keyword(s):  
Time Series ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Limited Information ◽  
Additional Information ◽  
Aerosol Retrieval ◽  
Avhrr Data ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Land Surfaces

Abstract. The Advanced Very High Resolution Radiometer (AVHRR) provides a global, long-term, consistent time series of radiance data in several wavebands which are used for the retrieval of surface spectral reflectance, albedo and surface temperature. Long-term time series of such data products are necessary for studies addressing climate change, sea ice distribution and movement, and ice sheet coastal configuration. AVHRR radiances have also been used to retrieve aerosol properties over ocean and land surfaces. However, the retrieval of aerosol over land is challenging because of the limited information content in the data which renders the inversion problem ill defined. Solving the radiative transfer equations requires additional information to reduce the number of unknowns. In this contribution we utilise an empirical linear relationship between the surface reflectances in the AVHRR channels at wavelengths of 3.75 μm and 2.1 μm, which has been identified in the Moderate Resolution Imaging Spectroradiometer (MODIS) data. Following the MODIS dark target approach, this relationship is used to obtain the surface reflectance at 0.64 μm. The comparison of the estimated surface reflectances with MODIS reflectance products (MOD09) shows a strong correlation. Once this was established, the MODIS "dark-target" aerosol retrieval method was adapted to AVHRR data. A simplified look-up table (LUT) method, adopted from the Bremen AErosol Retrieval (BAER) algorithm, was used in the retrieval. The aerosol optical depth (AOD) values retrieved from AVHRR with this method compare favourably with ground-based measurements, with 71.8% of the points located within ±(0.1 + 0.15τ) (τ is the AOD) of the identity line. This method can be easily applied to other satellite instruments which do not have a 2.1 μm channel, such as those currently planned to be used on geostationary satellites.

scholarly journals Validation of MODIS 3 km Land Aerosol Optical Depth from NASA's EOS Terra and Aqua Missions

2018 ◽  
Author(s):  
Pawan Gupta ◽  
Lorraine A. Remer ◽  
Robert C. Levy ◽  
Shana Mattoo
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Aerosol Retrieval ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Sensor Degradation ◽  
Over Time

Abstract. The two MODerate Resolution Imaging Spectroradiometer (MODIS) sensors, aboard Earth Observing Satellites (EOS) Terra and Aqua, have been making aerosol observations for more than 15 years. From these observations, the MODIS dark target (DT) aerosol retrieval algorithm provides aerosol optical depth (AOD) products, globally over both land and ocean. In addition to the standard resolution product (10 × 10 km2), the MODIS collection 6 (C006) data release included a higher resolution (3 × 3 km2). Other than accommodations for the two different resolutions, the 10 km, and 3 km DT algorithms are basically the same. In this study, we perform global validation of the higher resolution AOD over global land by comparing against AERONET measurements. The MODIS-AERONET collocated data sets consist of 161,410 high-confidence AOD pairs from 2000 to 2015 for MODIS Terra and 2003 to 2015 for MODIS-Aqua. We find that 62.5 % and 68.4 % of AODs retrieved from MODIS-Terra and MODIS-Aqua, respectively, fall within previously published expected error bounds of ±(0.05 + 0.2*AOD), with a high correlation (R = 0.87). The scatter is not random but exhibits a mean positive bias of ~ 0.06 for Terra and ~ 0.03 for Aqua. These biases for the 3 km product are approximately 0.03 larger than the biases found in similar validations of the 10 km product. The validation results for the 3 km product did not have a relationship to aerosol loading (i.e. true AOD) but did exhibit dependence on quality flags, region, viewing geometry, and aerosol spatial variability. Time series of global MODIS-AERONET differences show that validation is not static, but has changed over the course of both sensors' lifetimes, with MODIS-Terra showing more change over time. The likely cause of the change of validation over time is sensor degradation, but changes in the distribution of AERONET stations and differences in the global aerosol system itself could be contributing to the temporal variability of validation.

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