Indirect estimation of absorption properties for fine aerosol  particles using AATSR observations: a case study of wildfires   in Russia in 2010

Abstract. The Advanced Along-Track Scanning Radiometer (AATSR) on board the ENVISAT satellite is used to study aerosol properties. The retrieval of aerosol properties from satellite data is based on the optimized fit of simulated and measured reflectances at the top of the atmosphere (TOA). The simulations are made using a radiative transfer model with a variety of representative aerosol properties. The retrieval process utilizes a combination of four aerosol components, each of which is defined by their (lognormal) size distribution and a complex refractive index: a weakly and a strongly absorbing fine-mode component, coarse mode sea salt aerosol and coarse mode desert dust aerosol). These components are externally mixed to provide the aerosol model which in turn is used to calculate the aerosol optical depth (AOD). In the AATSR aerosol retrieval algorithm, the mixing of these components is decided by minimizing the error function given by the sum of the differences between measured and calculated path radiances at 3–4 wavelengths, where the path radiances are varied by varying the aerosol component mixing ratios. The continuous variation of the fine-mode components allows for the continuous variation of the fine-mode aerosol absorption. Assuming that the correct aerosol model (i.e. the correct mixing fractions of the four components) is selected during the retrieval process, also other aerosol properties could be computed such as the single scattering albedo (SSA). Implications of this assumption regarding the ratio of the weakly/strongly absorbing fine-mode fraction are investigated in this paper by evaluating the validity of the SSA thus obtained. The SSA is indirectly estimated for aerosol plumes with moderate-to-high AOD resulting from wildfires in Russia in the summer of 2010. Together with the AOD, the SSA provides the aerosol absorbing optical depth (AAOD). The results are compared with AERONET data, i.e. AOD level 2.0 and SSA and AAOD inversion products. The RMSE (root mean square error) is 0.03 for SSA and 0.02 for AAOD lower than 0.05. The SSA is further evaluated by comparison with the SSA retrieved from the Ozone Monitoring Instrument (OMI). The SSA retrieved from both instruments show similar features, with generally lower AATSR-estimated SSA values over areas affected by wildfires.

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A Theoretical Analysis for Improving Aerosol-Induced CO2 Retrieval Uncertainties Over Land Based on TanSat Nadir Observations Under Clear Sky Conditions

Remote Sensing ◽

10.3390/rs11091061 ◽

2019 ◽

Vol 11 (9) ◽

pp. 1061 ◽

Cited By ~ 1

Author(s):

Xi Chen ◽

Yi Liu ◽

Dongxu Yang ◽

Zhaonan Cai ◽

Hongbin Chen ◽

...

Keyword(s):

Carbon Dioxide ◽

Refractive Index ◽

Estimation Method ◽

Radiative Transfer Model ◽

Retrieval Algorithm ◽

Transfer Model ◽

Aerosol Model ◽

Coarse Mode ◽

Fine Mode ◽

Aerosol Parameters

Aerosols significantly affect carbon dioxide (CO2) retrieval accuracy and precision by modifying the light path. Hyperspectral measurements in the near infrared and shortwave infrared (NIR/SWIR) bands from the generation of new greenhouse gas satellites (e.g., the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite, TanSat) contain aerosol information for correction of scattering effects in the retrieval. Herein, a new approach is proposed for optimizing the aerosol model used in the TanSat CO2 retrieval algorithm to reduce CO2 uncertainties associated with aerosols. The weighting functions of hyperspectral observations with respect to elements in the state vector are simulated by a forward radiative transfer model. Using the optimal estimation method (OEM), the information content and each component of the CO2 column-averaged dry-air mole fraction (XCO2) retrieval errors from the TanSat simulations are calculated for typical aerosols which are described by Aerosol Robotic Network (AERONET) inversion products at selected sites based on the a priori and measurement assumptions. The results indicate that the size distribution parameters (reff, veff), real refractive index coefficient of fine mode (arf) and fine mode fraction (fmf) dominate the interference errors, with each causing 0.2–0.8 ppm of XCO2 errors. Given that only 4–7 degrees of freedom for signal (DFS) of aerosols can be obtained simultaneously and CO2 information decreases as more aerosol parameters are retrieved, four to seven aerosol parameters are suggested as the most appropriate for inclusion in CO2 retrieval. Focusing on only aerosol-induced XCO2 errors, forward model parameter errors, rather than interference errors, are dominant. A comparison of these errors across different aerosol parameter combination groups reveals that fewer aerosol-induced XCO2 errors are found when retrieving seven aerosol parameters. Therefore, the model selected as the optimal aerosol model includes aerosol optical depth (AOD), peak height of aerosol profile (Hp), width of aerosol profile (Hw), effective variance of fine mode aerosol (vefff), effective radius of coarse mode aerosol (reffc), coefficient a of the real part of the refractive index for the fine mode and coarse mode (arf and arc), with the lowest error of less than 1.7 ppm for all aerosol and surface types. For marine aerosols, only five parameters (AOD, Hp, Hw, reffc and arc) are recommended for the low aerosol information. This optimal aerosol model therefore offers a theoretical foundation for improving CO2 retrieval precision from real TanSat observations in the future.

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Retrieval of aerosol absorption properties using the AATSR satellite instrument: a case study of wildfires over Russia 2010

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-7-9839-2014 ◽

2014 ◽

Vol 7 (9) ◽

pp. 9839-9868 ◽

Cited By ~ 1

Author(s):

E. Rodríguez ◽

P. Kolmonen ◽

T. H. Virtanen ◽

L. Sogacheva ◽

A.-M. Sundström ◽

...

Keyword(s):

Optical Depth ◽

Complex Refractive Index ◽

Single Scattering ◽

Radiative Transfer Model ◽

Retrieval Algorithm ◽

Transfer Model ◽

Ozone Monitoring Instrument ◽

Aerosol Model ◽

Definition Of ◽

Aerosol Properties

Abstract. The retrieval of aerosol properties from satellite data is based on the optimized fit of simulated and measured radiances at the top of the atmosphere (TOA). The simulations are made using a radiative transfer model with a variety of representative aerosol properties.The optimum fit is obtained for a certain combination of aerosol components, which are externally mixed to provide the aerosol model which in turn is used to calculate the aerosol optical depth (AOD). However, other aerosol properties could be provided. In the aerosol retrieval algorithm (ADV) applied to data from the Advanced Along Track Scanning Radiometer (AATSR), four aerosol components are used, each of which is defined by their (lognormal) size distribution and a complex refractive index. The fine mode fraction is a continuous mixture of weakly and strongly absorbing components which allows for the definition of any absorbing aerosol model within the specified limits. Hence, assuming that the correct aerosol model is selected during the retrieval process, also the single scattering albedo (SSA) should correctly be retrieved. In this paper we present the SSA retrieval using the ADV algorithm by application to wildfires over Russia in the summer of 2010. Together with the AOD, the SSA provides the aerosol absorbing optical depth (AAOD). The results are compared with AERONET data, i.e. AOD level 2.0 and SSA and AAOD inversion products. The RMSE is 0.03 for SSA and 0.02 for AAOD. The SSA is further evaluated by comparison with the SSA retrieved from the Ozone Monitoring Instrument (OMI). The SSA retrieved from both instruments show similar features, but the AATSR-retrieved SSA values over areas affected by wildfires are lower.

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Retrieval of ash properties from IASI measurements

10.5194/amt-2016-143 ◽

2016 ◽

Cited By ~ 1

Author(s):

Lucy J. Ventress ◽

Don Grainger ◽

Gregory McGarragh ◽

Elisa Carboni ◽

Andrew J. Smith

Keyword(s):

Covariance Matrix ◽

Optical Depth ◽

Sensitivity Study ◽

Covariance Matrices ◽

Effective Radius ◽

Radiative Transfer Model ◽

Retrieval Algorithm ◽

Transfer Model ◽

Ancillary Data ◽

Clear Sky

Abstract. A new optimal estimation algorithm for the retrieval of volcanic ash properties has been developed for use with hyperspectral satellite instruments such as the Infrared Atmospheric Sounding Interferometer (IASI). The retrieval method uses the wavenumber range 680–1200 cm−1, which contains window channels, the CO2 ν2 band (used for the height retrieval), and the O3 ν3 band. Assuming a single infinitely (geometrically) thin ash plume and combining this with the output from the radiative transfer model RTTOV, the retrieval algorithm produces the most probable values for the ash optical depth (AOD), particle effective radius, plume top height and surface temperature. A comprehensive uncertainty budget is obtained for each pixel. Improvements to the algorithm through the use of different measurement error covariance matrices is explored, comparing the results from a sensitivity study of the retrieval process using covariance matrices trained on either clear-sky or cloudy scenes. The result exhibited that, due to the smaller variance contained within it, the clear-sky covariance matrix is preferable. However, if the retrieval fails to pass the quality control tests, the cloudy covariance matrix is implemented. The retrieval algorithm is applied to scenes from the Eyjafjallajökull eruption in 2010 and the retrieved parameters are compared to ancillary data sources. The ash optical depth gives an RMS difference of 0.46 when compared to retrievals from the MODIS instrument for all pixels and an improved RMS of 0.2 for low optical depths. Measurements from the FAAM and DLR flight campaigns are used to verify the retrieved particle effective radius, with the retrieved distribution of sizes for the scene showing excellent consistency. Further, the plume top altitudes are compared to derived cloud-top altitudes from the CALIOP instrument and show agreement with RMS values of less than 1 km.

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Synergistic angular and spectral estimation of aerosol properties using CHRIS/PROBA-1 and simulated Sentinel-3 data

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-7-5381-2014 ◽

2014 ◽

Vol 7 (6) ◽

pp. 5381-5422

Author(s):

W. H. Davies ◽

P. R. J. North

Keyword(s):

Physical Model ◽

Spectral Estimation ◽

Single Scattering ◽

Radiative Transfer Model ◽

Transfer Model ◽

Imaging Spectrometer ◽

Fine Mode ◽

Land Surfaces ◽

General Physical ◽

Aerosol Properties

Abstract. A method has been developed to estimate Aerosol Optical Depth (AOD), Fine Mode Fraction (FMF) and Single Scattering Albedo (SSA) over land surfaces using simulated Sentinel-3 data. The method uses inversion of a coupled surface/atmosphere radiative transfer model, and includes a general physical model of angular surface reflectance. An iterative process is used to determine the optimum value of the aerosol properties providing the best fit of the corrected reflectance values for a number of view angles and wavelengths with those provided by the physical model. A method of estimating AOD using only angular retrieval has previously been demonstrated on data from the ENVISAT and PROBA-1 satellite instruments, and is extended here to the synergistic spectral and angular sampling of Sentinel-3 and the additional aerosol properties. The method is tested using hyperspectral, multi-angle Compact High Resolution Imaging Spectrometer (CHRIS) images. The values obtained from these CHRIS observations are validated using ground based sun-photometer measurements. Results from 22 image sets using the synergistic retrieval and improved aerosol models show an RMSE of 0.06 in AOD, reduced to 0.03 over vegetated targets.

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Aerosol radiative impact during the summer 2019 heatwave produced partly by an inter-continental Saharan dust outbreak – Part 2: Long-wave and net dust direct radiative effect

10.5194/acp-2021-419 ◽

2021 ◽

Author(s):

Michaël Sicard ◽

Carmen Córdoba-Jabonero ◽

María-Ángeles López-Cayuela ◽

Albert Ansmann ◽

Adolfo Comerón ◽

...

Keyword(s):

Surface Temperature ◽

Saharan Dust ◽

Dust Particles ◽

Radiative Transfer Model ◽

Transfer Model ◽

Radiative Effect ◽

Radiative Efficiency ◽

Total Dust ◽

Coarse Mode ◽

Fine Mode

Abstract. This paper is the companion paper of Córdoba-Jabonero et al. (2021). It deals with the estimation of the longwave (LW) and net dust direct radiative effect (DRE) during the dust episode that occurred between 23 and 30 June, 2019, and coincided with a mega-heatwave. The analysis is performed at two European sites where polarized-Micro-Pulse Lidars ran continuously to retrieve the vertical distribution of the dust optical properties: Barcelona, Spain, 23–30 June, and Leipzig, Germany, 29–30 June. The radiative effect is computed with the GAME radiative transfer model separately for the fine- and coarse-mode dust. The instantaneous and daily radiative effect and radiative efficiency (DREff) are provided for the fine-mode, coarse-mode and total dust at the surface, top of the atmosphere (TOA) and in the atmosphere. The fine-mode daily LW DRE is small (< 6 % of the shortwave (SW) component) which makes the coarse-mode LW DRE the main modulator of the total dust net DRE. The coarse-mode LW DRE starts exceeding (in absolute values) the SW component in the middle of the episode which produces positive coarse-mode net DRE at both the surface and TOA. Such an unusual tendency is attributed to increasing coarse-mode size and surface temperature along the episode. This has the effect of reducing the SW cooling in Barcelona up to the point of reaching total dust net DRE positive (+0.9 W m−2) on one occasion at the surface and quasi-neutral (−0.6 W m−2) at TOA. When adding the LW component, the total dust SW radiative efficiency is reduced by a factor 1.6 at both surface (on average over the episode, the total dust net DREff is −54.1 W m−2 τ−1) and TOA (−37.3 W m−2 τ−1). A sensitivity study performed on the surface temperature and the air temperature in the dust layer, both linked to the heatwave and upon which the LW DRE strongly depends, shows that the heatwave contributed to reduce the dust net cooling effect at the surface and that it had nearly no effect at TOA. Its subsequent effect was thus to reduce the heating of the atmosphere produced by the dust particles.

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Role of Coarse and Fine Mode Aerosols in MODIS AOD Retrieval: a case study over southern India

Atmospheric Measurement Techniques ◽

10.5194/amt-7-907-2014 ◽

2014 ◽

Vol 7 (4) ◽

pp. 907-917 ◽

Cited By ~ 12

Author(s):

M. N. Sai Suman ◽

H. Gadhavi ◽

V. Ravi Kiran ◽

A. Jayaraman ◽

S. V. B. Rao

Keyword(s):

Regression Line ◽

Single Scattering ◽

Southern India ◽

Retrieval Algorithm ◽

Aerosol Model ◽

Coarse Mode ◽

Modis Aod ◽

Fine Mode ◽

R Value ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. In the present study we compare the MODIS (Moderate Resolution Imaging Spectroradiometer) derived aerosol optical depth (AOD) data with that obtained from operating sky-radiometer at a remote rural location in southern India (Gadanki, 13.45° N, 79.18° E) from April 2008 to March 2011. While the comparison between total (coarse mode + fine mode) AODs shows correlation coefficient (R) value of about 0.71 for Terra and 0.77 for Aqua, if one separates the AOD into fine and coarse mode, the comparison becomes very poor, particularly for fine mode with an R value of 0.44 for both Terra and Aqua. The coarse mode AOD derived from MODIS and sky-radiometer compare better with an R value of 0.74 for Terra and 0.66 for Aqua. The seasonal variation is also well captured by both ground-based and satellite measurements. It is shown that both the total AOD and fine mode AOD are significantly underestimated with slope of regression line 0.75 and 0.35 respectively, whereas the coarse mode AOD is overestimated with a slope value of 1.28 for Terra. Similar results are found for Aqua where the slope of the regression line for total AOD and fine mode AOD are 0.72 and 0.27 whereas 0.95 for coarse mode. The fine mode fraction derived from MODIS data is less than one-half of that derived from the sky-radiometer data. Based on these observations and comparison of single scattering albedo observed using sky-radiometer with that of MODIS aerosol models, we argue that the selection of aerosol types used in the MODIS retrieval algorithm may not be appropriate particularly in the case of southern India. Instead of selecting a moderately absorbing aerosol model (as being done currently in the MODIS retrieval) a more absorbing aerosol model could be a better fit for the fine mode aerosols, while reverse is true for the coarse mode aerosols, where instead of using "dust aerosols" which is relatively absorbing type, usage of coarse sea-salt particles which is less absorbing is more appropriate. However, not all the differences could be accounted based on aerosol model, other factors like errors in retrieval of surface reflectance may also be significant in causing underestimation of AOD by MODIS.

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Sub-Mode Aerosol Volume Size Distribution and Complex Refractive Index from the Three-Year Ground-Based Measurements in Chengdu China

Atmosphere ◽

10.3390/atmos10020046 ◽

2019 ◽

Vol 10 (2) ◽

pp. 46 ◽

Cited By ~ 1

Author(s):

Chi Zhang ◽

Ying Zhang ◽

Zhengqiang Li ◽

Yongqian Wang ◽

Hua Xu ◽

...

Keyword(s):

Refractive Index ◽

Size Distribution ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Complex Refractive Index ◽

Observation Data ◽

Aerosol Model ◽

Coarse Mode ◽

Fine Mode ◽

Volume Size

Chengdu is a typical basin city of Southwest China with rare observations of remote sensing measurements. To assess the climate change and establish a region aerosol model, a deeper understanding of the separated volume size distribution (VSD) and complex refractive index (CRI) is required. In this study, we employed the sub-mode VSD and CRI in Chengdu based on the three years observation data to investigate the sub-mode characteristics and climate effects. The annual average fraction of the fine-mode aerosol optical depth (AODf) is 92%, which has the same monthly tendency as the total AOD. But the coarse-mode aerosol optical depth (AODc) has little variation in different months. There are four distinguishing modes of VSD in Chengdu; the median radii are 0.17 μm ± 0.05, 0.31 μm ± 0.12, 1.62 μm ± 0.45, 3.25 μm ± 0.99, respectively. The multi-year average and seasonal variations of fine- and coarse-mode VSD and CRI are also analyzed to characterize aerosols over this region. The fine-mode single scattering albedos (SSAs) are higher than the coarse-mode ones, which suggests that the coarse-mode aerosols have a stronger absorbing effect on solar light than the small-size aerosol particles in Chengdu.

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Characterisation of aerosol size properties from measurements of spectral optical depth: a global validation of the GRASP-AOD code using long-term AERONET data

10.5194/amt-2020-426 ◽

2020 ◽

Author(s):

Benjamin Torres ◽

David Fuertes

Keyword(s):

Size Distribution ◽

Optical Depth ◽

Volume Concentration ◽

Effective Radius ◽

Aerosol Size Distribution ◽

Retrieval Algorithm ◽

Aerosol Retrieval ◽

Coarse Mode ◽

Fine Mode ◽

Log Normal

Abstract. A validation study is conducted regarding aerosol optical size property retrievals from only measurements of the direct Sun beam (without the aid of diffuse radiation). The study focuses on testing with real data the new GRASP-AOD application which uses only spectral optical depth measurements to retrieve the total column aerosol size distributions, assumed as bimodal log-normal. In addition, a set of secondary integral parameters of aerosol size distribution and optical properties are provided: effective radius, total volume concentration and fine mode fraction of aerosol optical depth. The GRASP-AOD code is applied to almost three million observations acquired during twenty years (1997–2016) at thirty AERONET (Aerosol Robotic Network) sites. These validation sites have been selected based on known availability of an extensive data record, significant aerosol load variability along the year, wide worldwide coverage and divers aerosol types and source regions. The output parameters are compared to those coming from the operational AERONET retrievals. The retrieved fine mode fractions at 500 nm (τf(500)) obtained by GRASP-AOD application are compared to those retrieved by the Spectral Deconvolution Algorithm and by AERONET aerosol retrieval algorithm. The size distribution properties obtained by GRASP-AOD are compared to their equivalent values from the AERONET aerosol retrieval algorithm. The analysis showed the convincing capacity of GRASP-AOD approach to successfully discriminate between fine and coarse mode extinction to robustly retrieve τf(500). The comparisons of 2 million results of τf(500) retrieval by GRASP-AOD and SDA showed high correlation with a root-mean-square-error of 0.015. Also, the analysis showed that the τf(500) values computed by AERONET aerosol retrieval algorithm agree slightly better with GRASP-AOD (RMSE = 0.018, from 148526 comparisons) than with SDA (RMSE = 0.022, from 127203 comparisons). The comparisons of the size distribution retrieval showed the agreement for fine mode median radius between GRASP-AOD and AERONET aerosol retrieval algorithm results with RMSE of 0.032 μm (or 18.7 % in relative terms) for the situations when τ(440) > 0.2 that occurs for more than eighty thousand pairs of the study. For the cases where fine mode is dominant (i.e. α 0.2. The values of effective radius and total volume concentration computed from GRASP-AOD retrieval have been compared to those estimated by AERONET aerosol retrieval algorithm. The RMSE values of the correlations were of 30 % for the effective radius and 25 % for the total volume concentration when τ(440) > 0.2. Finally, the study discusses the importance of employing the assumption of bimodal log-normal size distribution. It also evaluates the potential of using ancillary data, in particular aureole measurements, for improving the characterization of the aerosol coarse mode properties.

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Characterization of aerosol size properties from measurements of spectral optical depth: a global validation of the GRASP-AOD code using long-term AERONET data

Atmospheric Measurement Techniques ◽

10.5194/amt-14-4471-2021 ◽

2021 ◽

Vol 14 (6) ◽

pp. 4471-4506

Author(s):

Benjamin Torres ◽

David Fuertes

Keyword(s):

Size Distribution ◽

Optical Depth ◽

Volume Concentration ◽

Effective Radius ◽

Retrieval Algorithm ◽

Aerosol Retrieval ◽

Coarse Mode ◽

Fine Mode ◽

Aerosol Types

Abstract. A validation study is conducted regarding aerosol optical size property retrievals from measurements of the direct sun beam only (without the aid of diffuse radiation). The study focuses on using real data to test the new GRASP-AOD application, which uses only spectral optical depth measurements to retrieve the total column aerosol size distributions, assumed to be bimodal lognormal. In addition, a set of secondary integral parameters of aerosol size distribution and optical properties are provided: effective radius, total volume concentration and fine-mode fraction of aerosol optical depth (AOD). The GRASP-AOD code is applied to almost 3 million observations acquired over 20 years (1997–2016) at 30 AERONET (Aerosol Robotic Network) sites. These validation sites have been selected based on known availability of an extensive data record, significant aerosol load variability throughout the year, wide worldwide coverage and diverse aerosol types and source regions. The output parameters are compared to those coming from the operational AERONET retrievals. The retrieved fine-mode fractions at 500 nm (τf(500)) obtained by the GRASP-AOD application are compared to those retrieved by the spectral deconvolution algorithm (SDA) and by the AERONET aerosol retrieval algorithm. The size distribution properties obtained by the GRASP-AOD are compared to their equivalent values from the AERONET aerosol retrieval algorithm. The analysis showed the convincing capacity of the GRASP-AOD approach to successfully discriminate between fine- and coarse-mode extinction to robustly retrieve τf(500). The comparisons of 2 million results of τf(500) retrieval by the GRASP-AOD and SDA showed high correlation with a root mean square error (RMSE) of 0.015. Also, the analysis showed that the τf(500) values computed by the AERONET aerosol retrieval algorithm agree slightly better with the GRASP-AOD (RMSE = 0.018, from 148 526 comparisons) than with the SDA (RMSE = 0.022, from 127 203 comparisons). The comparisons of the size distribution retrieval showed agreement for the fine-mode median radius between the GRASP-AOD and AERONET aerosol retrieval algorithm results with an RMSE of 0.032 µm (or 18.7 % in relative terms) for the situations when τ(440)>0.2 occur for more than 80 000 pairs of the study. For the cases where the fine mode is dominant (i.e., α>1.2), the RMSE is only of 0.023 µm (or 13.9 % in relative terms). Major limitations in the retrieval were found for the characterization of the coarse-mode details. For example, the analysis revealed that the GRASP-AOD retrieval is not sensitive to the small variations of the coarse-mode volume median radius for different aerosol types observed at different locations. Nonetheless the GRASP-AOD retrieval provides reasonable agreement with the AERONET aerosol retrieval algorithm for overall coarse-mode properties with with RMSE = 0.500 µm (RMSRE = 20 %) when τ(440)>0.2. The values of effective radius and total volume concentration computed from the GRASP-AOD retrieval have been compared to those estimated by the AERONET aerosol retrieval algorithm. The RMSE values of the correlations were 30 % for the effective radius and 25 % for the total volume concentration when τ(440)>0.2. Finally, the study discusses the importance of employing the assumption of bimodal lognormal size distribution. It also evaluates the potential of using ancillary data, in particular aureole measurements, for improving the characterization of the aerosol coarse-mode properties.

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Effect of Thin Cirrus Clouds on Dust Optical Depth Retrievals From MODIS Observations

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2011.2118762 ◽

2011 ◽

Vol 49 (6) ◽

pp. 2819-2827 ◽

Cited By ~ 3

Author(s):

Qian Feng ◽

N. Christina Hsu ◽

Ping Yang ◽

Si-Chee Tsay

Keyword(s):

Radiative Transfer ◽

Optical Depth ◽

Rayleigh Scattering ◽

Polarization State ◽

Cirrus Clouds ◽

Dust Particles ◽

Radiative Transfer Model ◽

Retrieval Algorithm ◽

Transfer Model ◽

Lookup Tables

The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector radiative transfer model is used to generate the lookup tables. In the forward radiative transfer simulations involved in generating the lookup tables, the Rayleigh scattering by atmospheric gaseous molecules and the reflection of the surface assumed to be Lambertian are fully taken into account. Additionally, the spheroid model is utilized to account for the nonsphericity of dust particles in computing their optical properties. For simplicity, the single-scattering albedo, scattering phase matrix, and optical depth are specified a priori for thin cirrus clouds assumed to consist of droxtal ice crystals. The present results indicate that the errors in the retrieved dust optical depths due to the contamination of thin cirrus clouds depend on the scattering angle, underlying surface reflectance, and dust optical depth. Under heavy dusty conditions, the absolute errors are comparable to the predescribed optical depths of thin cirrus clouds.

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