Calibration model of polarimeters on board the Aerosol-UA space mission

Milinevsky, Gennadi; Oberemok, Yevgen; Syniavskyi, Ivan; Bovchaliuk, A.; Kolomiets, I. A.; Fesianov, I. V.; Wang, Yuke

doi:10.1016/j.jqsrt.2019.03.007

Cited by 14 publications

(20 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Over the past few decades, satellite remote sensing techniques have developed rapidly and extensively, and various (primarily photometric) instruments have been developed and deployed to monitor atmospheric aerosols from space (Bréon et al, 2011;Dubovik et al, 2019;King et al, 1999;Kokhanovsky et al, 2015;Li et al, 2009;Tanré et al, 2011). While the design and capabilities of the photometric observations are constantly evolving, the greatest improvement has been in the form of multi-angular multi-spectral polarimetry (MAP) measurements (Hansen et al, 1995;Hasekamp and Landgraf, 2007;Knobelspiesse et al, 2012;Mishchenko and Travis, 1997;Mishchenko et al, 2004;Waquet et al, 2009;Tanré et al, 2011). MAP measurements have enough inherent information content to greatly improve our understanding about aerosol properties.…”

Section: Introductionmentioning

confidence: 99%

Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring

Chen

Dubovik

Fuertes³

et al. 2020

Earth Syst. Sci. Data

111

View full text Add to dashboard Cite

Abstract. Proven by multiple theoretical and practical studies, multi-angular spectral polarimetry is ideal for comprehensive retrieval of properties of aerosols. Furthermore, a large number of advanced space polarimeters have been launched recently or planned to be deployed in the coming few years (Dubovik et al., 2019). Nevertheless, at present, practical utilization of aerosol products from polarimetry is rather limited, due to the relatively small number of polarimetric compared to photometric observations, as well as challenges in making full use of the extensive information content available in these complex observations. Indeed, while in recent years several new algorithms have been developed to provide enhanced aerosol retrievals from satellite polarimetry, the practical value of available aerosol products from polarimeters yet remains to be proven. In this regard, this paper presents the analysis of aerosol products obtained by the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm from POLDER/PARASOL observations. After about a decade of development, GRASP has been adapted for operational processing of polarimetric satellite observations and several aerosol products from POLDER/PARASOL observations have been released. These updated PARASOL/GRASP products are publicly available (e.g., http://www.icare.univ-lille.fr, last access: 16 October 2018, http://www.grasp-open.com/products/, last access: 28 March 2020); the dataset used in the current study is registered under https://doi.org/10.5281/zenodo.3887265 (Chen et al., 2020). The objective of this study is to comprehensively evaluate the GRASP aerosol products obtained from POLDER/PARASOL observations. First, the validation of the entire 2005–2013 archive was conducted by comparing to ground-based Aerosol Robotic Network (AERONET) data. The subjects of the validation are spectral aerosol optical depth (AOD), aerosol absorption optical depth (AAOD) and single-scattering albedo (SSA) at six wavelengths, as well as Ångström exponent (AE), fine-mode AOD (AODF) and coarse-mode AOD (AODC) interpolated to the reference wavelength 550 nm. Second, an inter-comparison of PARASOL/GRASP products with the PARASOL/Operational, MODIS Dark Target (DT), Deep Blue (DB) and Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol products for the year 2008 was performed. Over land both satellite data validations and inter-comparisons were conducted separately for different surface types, discriminated by bins of normalized difference vegetation index (NDVI): < 0.2, 0.2 ≤ and < 0.4, 0.4 ≤ and < 0.6, and ≥ 0.6. Three PARASOL/GRASP products were analyzed: GRASP/HP (“High Precision”), Optimized and Models. These different products are consistent but were obtained using different assumptions in aerosol modeling with different accuracies of atmospheric radiative transfer (RT) calculations. Specifically, when using GRASP/HP or Optimized there is direct retrieval of the aerosol size distribution and spectral complex index of refraction. When using GRASP/Models, the aerosol is approximated by a mixture of several prescribed aerosol components, each with their own fixed size distribution and optical properties, and only the concentrations of those components are retrieved. GRASP/HP employs the most accurate RT calculations, while GRASP/Optimized and GRASP/Models are optimized to achieve the best trade-off between accuracy and speed. In all these three options, the underlying surface reflectance is retrieved simultaneously with the aerosol properties, and the radiative transfer calculations are performed “online” during the retrieval. All validation results obtained for the full archive of PARASOL/GRASP products show solid quality of retrieved aerosol characteristics. The GRASP/Models retrievals, however, provided the most solid AOD products, e.g., AOD (550 nm) is unbiased and has the highest correlation (R ∼ 0.92) and the highest fraction of retrievals (∼ 55.3 %) satisfying the accuracy requirements of the Global Climate Observing System (GCOS) when compared to AERONET observations. GRASP/HP and GRASP/Optimized AOD products show a non-negligible positive bias (∼ 0.07) when AOD is low (< 0.2). On the other hand, the detailed aerosol microphysical characteristics (AE, AODF, AODC, SSA, etc.) provided by GRASP/HP and GRASP/Optimized correlate generally better with AERONET than do the results of GRASP/Models. Overall, GRASP/HP processing demonstrates the high quality of microphysical characteristics retrieval versus AERONET. Evidently, the GRASP/Models approach is more adapted for retrieval of total AOD, while the detailed aerosol microphysical properties are limited when a mixture of aerosol models with fixed optical properties are used. The results of a comparative analysis of PARASOL/GRASP and MODIS products showed that, based on validation against AERONET, the PARASOL/GRASP AOD (550 nm) product is of similar and sometimes of higher quality compared to the MODIS products. All AOD retrievals are more accurate and in good agreement over ocean. Over land, especially over bright surfaces, the retrieval quality degrades and the differences in total AOD products increase. The detailed aerosol characteristics, such as AE, AODF and AODC from PARASOL/GRASP, are generally more reliable, especially over land. The global inter-comparisons of PARASOL/GRASP versus MODIS showed rather robust agreement, though some patterns and tendencies were observed. Over ocean, PARASOL/Models and MODIS/DT AOD agree well with the correlation coefficient of 0.92. Over land, the correlation between PARASOL/Models and the different MODIS products is lower, ranging from 0.76 to 0.85. There is no significant global offset; though over bright surfaces MODIS products tend to show higher values compared to PARASOL/Models when AOD is low and smaller values for moderate and high AODs. Seasonal AOD means suggest that PARASOL/GRASP products show more biomass burning aerosol loading in central Africa and dust over the Taklamakan Desert, but less AOD in the northern Sahara. It is noticeable also that the correlation for the data over AERONET sites are somewhat higher, suggesting that the retrieval assumptions generally work better over AERONET sites than over the rest of the globe. One of the potential reasons may be that MODIS retrievals, in general, rely more on AERONET climatology than GRASP retrievals. Overall, the analysis shows that the quality of AOD retrieval from multi-angular polarimetric observations like POLDER is at least comparable to that of single-viewing MODIS-like imagers. At the same time, the multi-angular polarimetric observations provide more information on other aerosol properties (e.g., spectral AODF, AODC, AE), as well as additional parameters such as AAOD and SSA.

show abstract

Section: Introductionmentioning

confidence: 99%

Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring

Chen

Dubovik

Fuertes³

et al. 2020

Earth Syst. Sci. Data

111

View full text Add to dashboard Cite

show abstract

“…e spectral characteristics of the individual dichroic mirrors and spectral filters and the resulting characteristics for spectral channels 865 nm, 1378 nm, and 1620 nm of the optical units IR are shown in Figure 4. Note that the individual spectral transmittance values of the VIS and IR optical units will be taken into account in the calibration procedure described in detail in [14].…”

Section: Spectral Selection Systemmentioning

confidence: 99%

“…At this stage, we have not considered the following: the probable difference in the transmission coefficients of the different optical paths of ScanPol, the finite polarization contrast (extinction ratio) of polarizing prisms, the possible optical anisotropy of the camera lenses, and the other imperfections in the optical characteristics of the PSA ScanPol, which can also significantly affect the field parameters. [14,[16][17][18]. Because the mount and determination of the orientation of the polarizing axes of the Wollaston prisms are the simplest operations in the PSA ScanPol, it makes sense to investigate separately their effect on the accuracy of measuring the polarization parameters of the light flux.…”

Section: Mount Of Wollaston Prisms and Requirements To Eirmentioning

confidence: 99%

“…A complete polarization model of the ScanPol is described in [14]. In particular, it takes into account the individual transmittance values of the ScanPol optical paths, the individual spectral sensitivities of the photodetectors, the noise characteristics of the photodetectors, the individual optical anisotropy of the camera lenses, the finite individual value of the polarization contrast of the Wollaston prisms, and the partial depolarization of light by scattering in optical elements.…”

Section: Analysis Of the Field Aperture Images In Thementioning

confidence: 99%

“…In particular, it takes into account the individual transmittance values of the ScanPol optical paths, the individual spectral sensitivities of the photodetectors, the noise characteristics of the photodetectors, the individual optical anisotropy of the camera lenses, the finite individual value of the polarization contrast of the Wollaston prisms, and the partial depolarization of light by scattering in optical elements. In [14], a complex procedure of polarization calibration of ScanPol optical channels was successfully developed and tested using a numerical experiment based on the mentioned model, given the fixed values of the imperfections of its optical elements.…”

Section: Analysis Of the Field Aperture Images In Thementioning

confidence: 99%

See 2 more Smart Citations

Multispectral Polarization State Analyzer of Scanning Polarimeter ScanPol

Syniavskyi

Oberemok

Ivanov

et al. 2020

International Journal of Optics

Self Cite

View full text Add to dashboard Cite

We present the results of the development of a representational model of the multispectral polarization state analyzer of the ScanPol scanning polarimeter for the space experiment Aerosol-UA. The aim of the Ukrainian space mission Aerosol-UA is to create a database based on continuous satellite measurements of the optical characteristics of aerosol and cloud particles in the Earth’s atmosphere over a long period of time. The ScanPol polarimeter is designed to acquire spatial, temporal, and spectral-polarimetric measurements simultaneously to minimize instrumental “parasitic” effects and effects of “false” polarizations due to scene movement. Simultaneity is provided by separation of the initial spatial field by a pair of conjugated telescopes and a pair of Wollaston prisms. ScanPol provides to measure the first three Stokes parameters I, Q, and U of the radiation reflected by atmospheric aerosols and the Earth’s surface for a six solar reflectance spectral bands in the near ultraviolet (NUV), visible (VIS), and near-infrared (NIR) spectral channels centered in the wavelengths 370 nm, 410 nm, 555 nm, 865 nm, 1378 nm, and 1620 nm. Stokes parameters I, Q, and U are used to determine a degree of linear polarization of radiation that will allow obtaining the phase function and polarization characteristics of aerosol particle scattering, estimate their size, and determine the aerosol type and optical thickness. The polarimeter optical layout is considered, and the spectral characteristics of the transmission of optical channels are given. Obtained signal-to-noise ratio exceeded 500 for wavelengths 370 nm and 410 nm and exceeded 1000 for other wavelengths. The design of the chosen photodetectors is based on surface mount type photodiodes: Si-photodiodes Hamamatsu S10356-01 for the optical range of 370–860 nm and InGaAs-photodiodes Hamamatsu G8941-011620 for wavelengths 1378 nm and 1620 nm. The effect of orientation of Wollaston prisms axes on polarization measurement error is considered. The errors of azimuth mount of Wollaston prisms ≤2 arcmin in ScanPol leads to error of degree of linear polarization ≤0.0012.

show abstract

Big Data Analysis for Sustainable Land Management on Geospatial Cloud Framework

Bhunia,

Shit

2024

Environmental Science and Engineering

View full text Add to dashboard Cite

Calibration model of polarimeters on board the Aerosol-UA space mission

Cited by 14 publications

References 13 publications

Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring

Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring

Multispectral Polarization State Analyzer of Scanning Polarimeter ScanPol

Big Data Analysis for Sustainable Land Management on Geospatial Cloud Framework

Contact Info

Product

Resources

About