A Critical Look at Deriving Monthly Aerosol Optical Depth From Satellite Data

Levy, Robert C.; Leptoukh, G.; Kahn, Ralph A.; Zubko, V. G.; Gopalan, Arun; Remer, L. A.

doi:10.1109/tgrs.2009.2013842

Cited by 131 publications

(109 citation statements)

References 25 publications

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“…2007; Levy et al, 2009;Sayer et al, 2010b). However, even over oceans, measurements made by past and current spaceborne sensors do not provide sufficient information to retrieve unambiguously all relevant (surface and atmospheric) parameters of interest (Hasekamp and Landgraf, 2005).…”

Section: A M Sayer Et Al: Smoke Aerosol Propertiesmentioning

confidence: 99%

“…Jethva and Torres, 2011), and is strongly dependent on composition, with black carbon having a roughly spectrally neutral refractive index but absorption of organic carbon increasing at shorter visible and UV wavelengths (Bond, 2001;Kirchstetter et al, 2004, Andreae andGelencsér, 2006;Lewis et al, 2008). As such the spectral dependence of UV AOD and absorption, as in the visible, may show strong variations dependent on combustion phase and fuel type (e.g.…”

Section: A M Sayer Et Al: Smoke Aerosol Propertiesmentioning

confidence: 99%

See 1 more Smart Citation

AERONET-based models of smoke-dominated aerosol near source regions and transported over oceans, and implications for satellite retrievals of aerosol optical depth

et al. 2014

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Abstract. Smoke aerosols from biomass burning are an important component of the global aerosol system. Analysis of Aerosol Robotic Network (AERONET) retrievals of aerosol microphysical/optical parameters at 10 sites reveals variety between biomass burning aerosols in different global source regions, in terms of aerosol particle size and single scatter albedo (SSA). Case studies of smoke observed at coastal/island AERONET sites also mostly lie within the range of variability at the near-source sites. Differences between sites tend to be larger than variability at an individual site, although optical properties for some sites in different regions can be quite similar. Across the sites, typical midvisible SSA ranges from ∼ 0.95-0.97 (sites dominated by boreal forest or peat burning, typically with larger fine-mode particle radius and spread) to ∼ 0.88-0.9 (sites most influenced by grass, shrub, or crop burning, typically smaller finemode particle radius and spread). The tropical forest site Alta Floresta (Brazil) is closer to this second category, although with intermediate SSA ∼ 0.92. The strongest absorption is seen in southern African savannah at Mongu (Zambia), with average midvisible SSA ∼ 0.85. Sites with stronger absorption also tend to have stronger spectral gradients in SSA, becoming more absorbing at longer wavelengths. Microphysical/optical models are presented in detail so as to facilitate their use in radiative transfer calculations, including extension to UV (ultraviolet) wavelengths, and lidar ratios. One intended application is to serve as candidate optical models for use in satellite aerosol optical depth (AOD) retrieval algorithms. The models presently adopted by these algorithms over ocean often have insufficient absorption (i.e. too high SSA) to represent these biomass burning aerosols. The underestimates in satellite-retrieved AOD in smoke outflow regions, which have important consequences for applications of these satellite data sets, are consistent with the level of underestimated absorption.

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Section: A M Sayer Et Al: Smoke Aerosol Propertiesmentioning

confidence: 99%

Section: A M Sayer Et Al: Smoke Aerosol Propertiesmentioning

confidence: 99%

AERONET-based models of smoke-dominated aerosol near source regions and transported over oceans, and implications for satellite retrievals of aerosol optical depth

et al. 2014

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“…After explaining the coincidence criteria adopted here, it is well known that this type of comparison shows major differences depending on the spatial and/or temporal resolution taken for the MODIS sensor in relation to the groundbased instruments used (Santese et al, 2007;Levy et al, 2009;Bennouna et al, 2011Bennouna et al, , 2013. The justification for using a single-observation data set and a collocated daily means data set separately to analyse this comparison is based on (a) the characteristics of the surface area under study, with nearby areas of water and land; (b) the difference concerning how cloud cover affects data during the overpass time of the Terra and Aqua platforms; (c) the possibility of including the largest amount of data; and (d) the fact that only single observations can be compared in the case of BAOD pyrheliometer measurements.…”

Section: Coincidence Criteria For Modis and Sun Photometer Observationsmentioning

confidence: 99%

“…This comparative analysis does not aim to be a validation study of the MODIS sensor since many works during the long history of the MODIS sensor on the Terra and Aqua platforms have sought to improve its features (these include Kaufman et al, 1997a, b;Tanré et al, 1997;Remer et al, 2002Remer et al, , 2005Remer et al, , 2006Hsu, et al, 2004Hsu, et al, , 2006Hsu, et al, , 2013Levy et al, 2007Levy et al, , 2009Levy et al, , 2010Levy et al, , 2013Levy et al, , 2015Sayer et al, 2013Sayer et al, , 2014 https://darktarget.gsfc.nasa.gov/atbd/overview, last access: 9 April 2018). However, compared to other areas of the world, no studies have been reported in the Caribbean region and in Cuba in particular (Papadimas et al, 2009;Mishchenko et al, 2010;Kahn et al, 2011;Bennouna et al, 2011Bennouna et al, , 2013Witte et al, 2011;Gkikas et al, 2013Gkikas et al, , 2016Levy et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

Marrero¹,

Revilla

Parrado³

et al. 2018

Atmos. Meas. Tech.

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Abstract. In the present study, we report the first comparison between the aerosol optical depth (AOD) and Ångström exponent (AE) of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra (AOD t ) and Aqua (AOD a ) satellites and those measured using a sun photometer (AOD SP ) at Camagüey, Cuba, for the period 2008 to 2014. The comparison of Terra and Aqua data includes AOD derived with both deep blue (DB) and dark target (DT) algorithms from MODIS Collection 6. Combined Terra and Aqua (AOD ta ) data were also considered. Assuming an interval of ±30 min around the overpass time and an area of 25 km around the sun photometer site, two coincidence criteria were considered: individual pairs of observations and both spatial and temporal mean values, which we call collocated daily means. The usual statistics (root mean square error, RMSE; mean absolute error, MAE; median bias, BIAS), together with linear regression analysis, are used for this comparison. Results show very similar values for both coincidence criteria: the DT algorithm generally displays better statistics and higher homogeneity than the DB algorithm in the behaviour of AOD t , AOD a , AOD ta compared to AOD SP . For collocated daily means, (a) RMSEs of 0.060 and 0.062 were obtained for Terra and Aqua with the DT algorithm and 0.084 and 0.065 for the DB algorithm, (b) MAE follows the same patterns, (c) BIAS for both Terra and Aqua presents positive and negative values but its absolute values are lower for the DT algorithm; (d) combined AOD ta data also give lower values of these three statistical indicators for the DT algorithm; (e) both algorithms present good correlations for comparing AOD t , AOD a , AOD ta vs. AOD SP , with a slight overestimation of satellite data compared to AOD SP , (f ). The DT algorithm yields better figures with slopes of 0.96 (Terra), 0.96 (Aqua) and 0.96 (Terra + Aqua) compared to the DB algorithm (1.07, 0.90, 0.99), which displays greater variability. Multi-annual monthly means of AOD ta establish a first climatology that is more comparable to that given by the sun photometer and their statistical evaluation reveals better agreement with AOD SP for the DT algorithm. Results of the AE comparison showed similar results to those reported in the literature concerning the two algorithms' capacity for retrieval. A comparison between broadband aerosol optical depth (BAOD), derived from broadband pyrheliometer observations at the Camagüey site and three other meteorological stations in Cuba, and AOD observations from MODIS on board Terra and Aqua show a poor correlation with slopes below 0.4 for both algorithms. Aqua (Terra) showed RMSE values of 0.073 (0.080) and 0.088 (0.087) for the DB and DT algorithms. As expected, RMSE values are higher than those from the MODIS-sun photometer comparison, but within the same order of magnitude. Results from the BAOD derived from solar radiation measurements demonstrate its reliability in describing climatological AOD series estimates.

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“…Levy et al [17] tried to quantify a global "average" AOD, but found that its value was highly dependent on how the average was computed. Depending on which method of aggregation was used, global mean AOD could vary by 20% or more.…”

Section: Collection 6 Viirs and Mature Climate Data Recordsmentioning

confidence: 99%

Growing up MODIS: Towards a mature aerosol climate data record

Levy¹

2013

AIP Conference Proceedings

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A Critical Look at Deriving Monthly Aerosol Optical Depth From Satellite Data

Cited by 131 publications

References 25 publications

AERONET-based models of smoke-dominated aerosol near source regions and transported over oceans, and implications for satellite retrievals of aerosol optical depth

AERONET-based models of smoke-dominated aerosol near source regions and transported over oceans, and implications for satellite retrievals of aerosol optical depth

Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

Growing up MODIS: Towards a mature aerosol climate data record

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