GOES 8 retrieval of dust aerosol optical thickness over the Atlantic Ocean during PRIDE

Wang, Jun; Christopher, Sundar A.; Reid, Jeffrey S.; Maring, Hal; Savoie, Dennis L.; Holben, B. N.; Livingston, J. M.; Russell, Philip B.; Yang, Seungmi

doi:10.1029/2002jd002494

Cited by 64 publications

(96 citation statements)

References 80 publications

(184 reference statements)

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“…Larger hematite concentrations can be found only in restricted areas as the Sahel area, Northern India and Eastern Australia (Claquin et al, 1999). Also, measurements from the GOES-8 satellite optimally reproduce ground measurements of mineral dust concentrations if an imaginary part of 0.0015 is assumed (Wang et al, 2003).…”

Section: Extension Of the Aerosol Modelmentioning

confidence: 92%

Improvements of synergetic aerosol retrieval for ENVISAT

Popp

Schroedter-Homscheidt

Breitkreuz

et al. 2008

Atmos. Chem. Phys.

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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 predefined 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 Correspondence to: T. Holzer-Popp (thomas.holzer-popp@dlr.de) 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 intercomparison to earlier results of SYNAER version 1.0 is made for both the validation and the example datasets.

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Section: Extension Of the Aerosol Modelmentioning

confidence: 92%

Improvements of synergetic aerosol retrieval for ENVISAT

Popp

Schroedter-Homscheidt

Breitkreuz

et al. 2008

Atmos. Chem. Phys.

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“…The sampled subpoint spatial resolution is 0.57 × 1 km for the visible channel and 2.3 × 4 km for the other channels [ Menzel and Purdom , 1994]. For the PRIDE study period, Wang et al [2003] have used half‐hourly GOES 8 imager data in combination with a pre‐calculated radiance/AOD lookup table approach [ Zhang et al , 2001; Christopher and Zhang , 2002; Christopher et al , 2002] to retrieve dust AOD in the visible channel over the ocean.…”

Section: Instrumentationmentioning

confidence: 99%

Airborne Sun photometer measurements of aerosol optical depth and columnar water vapor during the Puerto Rico Dust Experiment and comparison with land, aircraft, and satellite measurements

et al. 2003

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[1] Analyses of aerosol optical depth (AOD) and columnar water vapor (CWV) measurements obtained with the six-channel NASA Ames Airborne Tracking Sunphotometer (AATS-6) mounted on a twin-engine aircraft during the summer 2000 Puerto Rico Dust Experiment are presented. In general, aerosol extinction values calculated from AATS-6 AOD measurements acquired during aircraft profiles up to 5 km above sea level (asl) reproduce the vertical structure measured by coincident aircraft in situ measurements of total aerosol number concentration. AATS-6 extinction retrievals also agree with corresponding values derived from ground-based lidar measurements for altitudes above the trade inversion. The spectral behavior of AOD within specific layers beneath the top of the aircraft profile is consistent with attenuation of incoming solar radiation by large dust particles or by dust plus sea salt, with mean Å ngström wavelength exponents of $0.20. Values of CWV calculated from profile measurements by AATS-6 at 941.9 nm and from aircraft in situ measurements agree to within $4% (0.13 g/cm 2 ). AATS-6 AOD values measured on the ground at Roosevelt Roads Naval Air Station and during low-altitude aircraft runs over the adjacent Cabras Island aerosol/radiation ground site agree to within 0.004-0.030 with coincident data obtained with an AERONET Sun/ sky radiometer located on Cabras Island. For the same observation times, AERONET retrievals of CWV exceed AATS-6 values by $21%. AATS-6 AOD values measured during low-altitude aircraft traverses over the ocean are compared with corresponding AOD values retrieved over water from upwelling radiance measurements by the Moderate-Resolution Imaging Spectroradiometer (MODIS), Total Ozone Mapping Spectrometer (TOMS), and GOES 8 Imager satellite sensors, with mixed results.

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“…The radiance or reflectance data collected by currently operational passive remote sensing instruments for aerosol retrieval are mostly at the atmospheric window channels in the visible spectrum. Therefore, they offer little information on aerosol vertical distribution beyond the retrieval of columnar properties such as aerosol optical thickness (AOT) (Wang et al, 2003a). In the near UV spectrum, the slope of the reflectance is regulated by height-dependent Rayleigh scattering and aerosol absorption, and this relationship can be used to estimate the centroid height of absorbing aerosols (Torres et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Improved algorithm for MODIS satellite retrievals of aerosol optical thickness over land in dusty atmosphere: Implications for air quality monitoring in China

Wang

Spurr

et al. 2010

Remote Sensing of Environment

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Wang, Jun; Xu, Xiaoguang; Spurr, R.; Wang, Yuxuang; and Drury, Easan, "Improved algorithm for MODIS satellite retrievals of aerosol optical thickness over land in dusty atmosphere: Implications for air quality monitoring in China" (2010 A new algorithm, using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite reflectance and aerosol single scattering properties simulated from a chemistry transport model (GEOS-Chem), is developed to retrieve aerosol optical thickness (AOT) over land in China during the spring dust season. The algorithm first uses a "dynamic lower envelope" approach to sample the MODIS dark-pixel reflectance data in low AOT conditions, to derive the local surface visible (0.65 μm)/near infrared (NIR, 2.1 μm) reflectance ratio. Joint retrievals of AOT at 0.65 μm and surface reflectance at 2.1 μm are then performed, based on the time, location, and spectraldependent single scattering properties of the dusty atmosphere as simulated by the GEOS-Chem. A linearized vector radiative transfer model (VLIDORT) that simultaneously computes the top-of-atmosphere reflectance and its Jacobian with respect to AOT, is used in the forward component of the inversion of MODIS reflectance to AOT. Comparison of retrieved AOT results in April and May of 2008 with AERONET observations shows a strong correlation (R = 0.83), with small bias (0.01), and small RMSE (0.17); the figures are a substantial improvement over corresponding values obtained with the MODIS Collection 5 AOT algorithm for the same study region and time period. The small bias is partially due to the consideration of dust effect at 2.1 μm channel, without which the bias is − 0.05. The surface PM 10 (particulate matter with diameter less than 10 μm) concentrations derived using this improved AOT retrieval show better agreement with ground observations than those derived from GEOSChem simulations alone, or those inferred from the MODIS Collection 5 AOT. This study underscores the value of using satellite reflectance to improve the air quality modeling and monitoring.

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GOES 8 retrieval of dust aerosol optical thickness over the Atlantic Ocean during PRIDE

Cited by 64 publications

References 80 publications

Improvements of synergetic aerosol retrieval for ENVISAT

Improvements of synergetic aerosol retrieval for ENVISAT

Airborne Sun photometer measurements of aerosol optical depth and columnar water vapor during the Puerto Rico Dust Experiment and comparison with land, aircraft, and satellite measurements

Improved algorithm for MODIS satellite retrievals of aerosol optical thickness over land in dusty atmosphere: Implications for air quality monitoring in China

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