scholarly journals Understanding the aerosol information content in multi-spectral reflectance measurements using a synergetic retrieval algorithm

2010 ◽  
Vol 3 (6) ◽  
pp. 1589-1598 ◽  
Author(s):  
D. Martynenko ◽  
T. Holzer-Popp ◽  
H. Elbern ◽  
M. Schroedter-Homscheidt
Keyword(s):  
Content Analysis ◽  
Information Content ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Degrees Of Freedom ◽  
Surface Albedo ◽  
Water Soluble ◽  
Retrieval Algorithm ◽  
Aerosol Types ◽  
Reflectance Measurements

Abstract. An information content analysis for multi-wavelength SYNergetic AErosol Retrieval algorithm SYNAER was performed to quantify the number of independent pieces of information that can be retrieved. In particular, the capability of SYNAER to discern various aerosol types is assessed. This information content depends on the aerosol optical depth, the surface albedo spectrum and the observation geometry. The theoretical analysis is performed for a large number of scenarios with various geometries and surface albedo spectra for ocean, soil and vegetation. When the surface albedo spectrum and its accuracy is known under cloud-free conditions, reflectance measurements used in SYNAER is able to provide for 2–4° of freedom that can be attributed to retrieval parameters: aerosol optical depth, aerosol type and surface albedo. The focus of this work is placed on an information content analysis with emphasis to the aerosol type classification. This analysis is applied to synthetic reflectance measurements for 40 predefined aerosol mixtures of different basic components, given by sea salt, mineral dust, biomass burning and diesel aerosols, water soluble and water insoluble aerosols. The range of aerosol parameters considered through the 40 mixtures covers the natural variability of tropospheric aerosols. After the information content analysis performed in Holzer-Popp et al. (2008) there was a necessity to compare derived degrees of freedom with retrieved aerosol optical depth for different aerosol types, which is the main focus of this paper. The principle component analysis was used to determine the correspondence between degrees of freedom for signal in the retrieval and derived aerosol types. The main results of the analysis indicate correspondence between the major groups of the aerosol types, which are: water soluble aerosol, soot, mineral dust and sea salt and degrees of freedom in the algorithm and show the ability of the SYNAER to discern between this aerosol types. The results of the work will be further used for the development of the promising methodology of the construction error covariance matrices in the assimilation system.

scholarly journals Understanding the aerosol information content in multi-spectral reflectance measurements using a synergetic retrieval algorithm

2010 ◽  
Vol 3 (3) ◽  
pp. 2579-2602 ◽  
Author(s):  
D. Martynenko ◽  
T. Holzer-Popp ◽  
H. Elbern ◽  
M. Schroedter-Homscheidt
Keyword(s):  
Content Analysis ◽  
Information Content ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Degrees Of Freedom ◽  
Surface Albedo ◽  
Retrieval Algorithm ◽  
Multi Wavelength ◽  
Aerosol Types ◽  
Reflectance Measurements

Abstract. The multi-wavelength SYNergetic AErosol Retrieval algorithm SYNAER (Holzer-Popp et al., 2002) is used to retrieve aerosol parameters from the Advanced Along Tracking Scanning Radiometer (AATSR) and the Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY). An information content analysis (Holzer-Popp et al., 2008) was performed to quantify the number of independent pieces of information can be retrieved from the combined reflectance measurements of aerosols by both instruments. In particular, the capability of SYNAER to discern various aerosol types is assessed. The focus of this work is further placed on an information content analysis with emphasis to the aerosol type classification. This analysis is applied to synthetic reflectance measurements for 40 predefined aerosol mixtures of different basic components, given by sea salt, mineral dust, biomass burning and diesel aerosols, water soluble and water insoluble aerosols. The range of aerosol parameters considered through the 40 mixtures covers the natural variability of tropospheric aerosols. In this work the capability of the multi-wavelength algorithm to discern aerosol types is investigated. After the information content analysis performed in Holzer-Popp et al. (2008) there was a necessity to compare derived degrees of freedom with retrieved aerosol optical depth for different aerosol types, which is the main focus of this paper. This information content depends on the aerosol optical depth, the surface albedo spectrum and the observation geometry. This theoretical analysis is performed for a large number of scenarios with various geometries and surface albedo spectra for ocean, soil and vegetation. When the surface albedo spectrum and its accuracy is known under cloud-free conditions, reflectance measurements used in SYNAER is able to provide for 2 to 4 degrees of freedom that can be attributed to retrieval parameters: aerosol optical depth, aerosol type and surface albedo.

scholarly journals Synergetic aerosol retrieval from SCIAMACHY and AATSR onboard ENVISAT

2008 ◽  
Vol 8 (1) ◽  
pp. 2903-2951 ◽  
Author(s):  
T. Holzer-Popp ◽  
M. Schroedter-Homscheidt ◽  
H. Breitkreuz ◽  
D. Martynenko ◽  
L. Klüser
Keyword(s):  
Information Content ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Brightness ◽  
Dark Field ◽  
Water Soluble ◽  
Least Square ◽  
Aerosol Retrieval ◽  
First Case ◽  
Satellite Platform

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 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 to do accurate cloud screening, and subsequently to quantify the aerosol optical depth (AOD) at 550 nm and spectral surface brightness through a dark field technique. In the second step the spectrometer is applied to choose the most plausible aerosol type through a least square fit of the measured spectrum with simulated spectra using the 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. However, due to instrumental limitations the coverage of SYNAER/ERS-2 and the AERONET network in 1997/98 is very sparse and thus only few coincidences with AERONET were found. Therefore, SYNAER was transferred to similar sensors AATSR and SCIAMACHY onboard ENVISAT. While transferring to the new sensor pair a thorough evaluation of the synergetic methodology and its information content has been conducted, which led to significant improvements in the methodology: an update of the aerosol model, an improved cloud detection, and an enhanced dark field albedo characterization. This paper describes the information content analysis and these improvements in detail and presents first results of applying the SYNAER methodology to AATSR and SCIAMACHY.

scholarly journals Simulation study of the aerosol information content in OMI spectral reflectance measurements

2007 ◽  
Vol 7 (1) ◽  
pp. 1785-1821 ◽  
Author(s):  
B. Veihelmann ◽  
P. F. Levelt ◽  
P. Stammes ◽  
J. P. Veefkind
Keyword(s):  
Information Content ◽  
Degrees Of Freedom ◽  
Surface Albedo ◽  
Principal Component ◽  
Aerosol Layer ◽  
Wavelength Band ◽  
Ozone Monitoring Instrument ◽  
Anthropogenic Aerosol ◽  
Aerosol Parameters ◽  
Reflectance Measurements

Abstract. The Ozone Monitoring Instrument (OMI) is designed and used primarily to retrieve trace gases like O3 and NO2 from the measured Earth reflectance spectrum in the UV-visible (270–500 nm). However, also aerosols are an important science target of OMI. Therefore, a Principal Component Analysis (PCA) is performed to quantify the information content of OMI reflectance measurements on aerosols. This analysis is applied to synthetic reflectance measurements for desert dust, biomass burning aerosols, and weakly absorbing anthropogenic aerosol with a variety of aerosol optical thicknesses, aerosol layer altitudes, refractive indices and size distributions. The range of aerosol parameters considered covers the natural variability of tropospheric aerosols. This theoretical analysis is performed for a large number of scenarios with various geometries and surface albedo spectra for ocean, soil and vegetation. When the surface albedo spectrum is accurately known and clouds are absent, OMI reflectance measurements have 2 to 4 degrees of freedom that can be attributed to aerosol parameters. This information content depends on the observation geometry, the surface albedo spectrum, and on the aerosol parameters themselves. An additional wavelength band is evaluated, that comprises the O2-O2 absorption band at a wavelength of 477 nm. It is found that this wavelength band adds significantly more information than any other individual band. The PCA is applied to assess the capability of the aerosol retrieval to discern various aerosol types as well as clouds.

scholarly journals Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

2015 ◽  
Vol 8 (10) ◽  
pp. 4083-4110 ◽  
Author(s):  
R. C. Levy ◽  
L. A. Munchak ◽  
S. Mattoo ◽  
F. Patadia ◽  
L. A. Remer ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Infrared Imaging ◽  
Quantitative Information ◽  
Environmental Data ◽  
Retrieval Algorithm ◽  
Climate Data ◽  
Data Record ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångström Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March–April–May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ~ 0.025), while reducing the differences between AE. We characterize algorithm retrievability through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

scholarly journals Improving GOES Advanced Baseline Imager (ABI) aerosol optical depth (AOD) retrievals using an empirical bias correction algorithm

2020 ◽  
Vol 13 (11) ◽  
pp. 5955-5975
Author(s):  
Hai Zhang ◽  
Shobha Kondragunta ◽  
Istvan Laszlo ◽  
Mi Zhou
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Bias Correction ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Infrared Imaging ◽  
Retrieval Algorithm ◽  
Correction Algorithm ◽  
Time Step

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 multiband algorithm similar to those of polar-orbiting satellites' sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS). However, this work demonstrates that the current version of GOES-16 (GOES-East) ABI AOD has diurnally varying biases due to limitations in the land surface reflectance relationships between the 0.47 µm band and the 2.2 µm band and between the 0.64 µm band and 2.2 µm band used in the ABI AOD retrieval algorithm, which vary with the Sun–satellite geometry and NDVI (normalized difference vegetation index). To reduce these biases, an empirical bias correction algorithm has been developed based on the lowest observed ABI AOD of an adjacent 30 d 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 6 August to 31 December 2018 are used to evaluate the bias correction algorithm. After bias correction, the correlation between the top 2 quality 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 corrected high-quality ABI AOD. By using the top 2 qualities of ABI AOD in conjunction with the bias correction algorithm, the areal coverage of ABI AOD is increased by about 100 % without loss of data accuracy.

Dust Aerosol Optical Depth Retrieval over a Desert Surface Using the SEVIRI Window Channels

2009 ◽  
Vol 26 (4) ◽  
pp. 704-718 ◽  
Author(s):  
Bart De Paepe ◽  
Steven Dewitte
Keyword(s):  
Surface Temperature ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Radiation ◽  
Retrieval Algorithm ◽  
Aerosol Layer ◽  
Surface Emissivity ◽  
Ir Radiation ◽  
Clear Sky ◽  
A Minor

Abstract The authors present a new algorithm to retrieve aerosol optical depth (AOD) over a desert using the window channels centered at 8.7, 10.8, and 12.0 μm of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the Meteosat Second Generation satellite. The presence of dust aerosols impacts the longwave outgoing radiation, allowing the aerosols over the desert surfaces to be detected in the thermal infrared (IR) wavelengths. To retrieve the aerosol properties over land, the surface contribution to the satellite radiance measured at the top of the atmosphere has to be taken into account. The surface radiation depends on the surface temperature, which is characterized by a strong diurnal variation over the desert, and the surface emissivity, which is assumed to be constant over a time span of 24 h. The surface emissivity is based on clear-sky observations that are corrected for atmospheric absorption and emission. The clear-sky image is a composite of pixels that is characterized by the highest brightness temperature (BT) of the SEVIRI channel at 10.8 μm, and by a negative BT difference between the channels at 8.7 and 10.8 μm. Because of the lower temperatures of clouds and aerosols compared to clear-sky conditions, the authors assume that the selected pixel values are obtained for a clear-sky day. A forward model is used to simulate the thermal IR radiation transfer in the dust layer. The apparent surface radiation for the three window channels in the presence of aerosols is calculated as a function of the surface emissivity and the surface temperature, the aerosol layer temperature, and the AOD for different aerosol loadings. From these simulations two emissivity ratios, which are stored in lookup tables (LUT), are calculated. The retrieval algorithm consists of processing the clear-sky image and computing the surface emissivity, processing the instantaneous image, and computing the apparent surface radiation for the three window channels. The two emissivity ratios are computed using the radiances at 8.7 and 10.8 μm and at 8.7 and 12.0 μm, respectively. The SEVIRI AOD is obtained by the inversion of these emissivity ratios using the corresponding LUT. The algorithm is applied to a minor dust event over the Sahara between 19 and 22 June 2007. For the validation the SEVIRI AOD is compared with the AOD from the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) along the satellite track.

scholarly journals The potential of elastic and polarization lidars to retrieve extinction profiles

2020 ◽  
Vol 13 (2) ◽  
pp. 893-905 ◽  
Author(s):  
Elina Giannakaki ◽  
Panos Kokkalis ◽  
Eleni Marinou ◽  
Nikolaos S. Bartsotas ◽  
Vassilis Amiridis ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Dust Particles ◽  
Depolarization Ratio ◽  
Lidar System ◽  
Lidar Measurements ◽  
Lidar Ratio ◽  
Linear Depolarization Ratio ◽  
Aerosol Types ◽  
532 Nm

Abstract. A new method, called ElEx (elastic extinction), is proposed for the estimation of extinction coefficient lidar profiles using only the information provided by the elastic and polarization channels of a lidar system. The method is applicable to lidar measurements both during daytime and nighttime under well-defined aerosol mixtures. ElEx uses the particle backscatter profiles at 532 nm and the vertically resolved particle linear depolarization ratio measurements at the same wavelength. The particle linear depolarization ratio and the lidar ratio values of pure aerosol types are also taken from literature. The total extinction profile is then estimated and compared well with Raman retrievals. In this study, ElEx was applied in an aerosol mixture of marine and dust particles at Finokalia station during the CHARADMExp campaign. Any difference between ElEx and Raman extinction profiles indicates that the nondust component could be probably attributed to polluted marine or polluted continental aerosols. Comparison with sun photometer aerosol optical depth observations is performed as well during daytime. Differences in the total aerosol optical depth are varying between 1.2 % and 72 %, and these differences are attributed to the limited ability of the lidar to correctly represent the aerosol optical properties in the near range due to the overlap problem.

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