A sea surface reflectance model for (A)ATSR, and application to aerosol retrievals

Sayer, A. M.; Thomas, G. E.; Grainger, R. G.

doi:10.5194/amt-3-813-2010

Cited by 103 publications

(107 citation statements)

References 63 publications

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“…Ocean surface reflectance can generally be modelled with lower uncertainties than that over land, and most algorithms parametrise oceanic surface reflectance as a combination of wind-roughened sun glint and foam, with an additional contribution linked to oceanic chlorophyll concentration (e.g. Sayer et al, 2010a). However, aerosol properties present greater difficulty.…”

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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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%

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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“…If this increase in sea salt aerosol increases the variance in AI, this may result in an increase of d(CF). Another possible explanation is the effect of whitecaps increasing the aerosol retrieval (Sayer et al, 2010a), as significant whitecaps begin to occur above about 5 m s −1 , although how this would increase d(CF) unclear.…”

Section: Meteorologymentioning

confidence: 99%

Satellite observations of cloud regime development: the role of aerosol processes

2014

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Abstract. Many different interactions between aerosols and clouds have been postulated, based on correlations between satellite retrieved aerosol and cloud properties. Previous studies highlighted the importance of meteorological covariations to the observed correlations.In this work, we make use of multiple temporally-spaced satellite retrievals to observe the development of cloud regimes. The observation of cloud regime development allows us to account for the influences of cloud fraction (CF) and meteorological factors on the aerosol retrieval. By accounting for the aerosol index (AI)-CF relationship, we reduce the influence of meteorological correlations compared to "snapshot" studies, finding that simple correlations overestimate any aerosol effect on CF by at least a factor of two.We find an increased occurrence of transitions into the stratocumulus regime over ocean with increases in MODIS AI, consistent with the hypothesis that aerosols increase stratocumulus persistence. We also observe an increase in transitions into the deep convective regime over land, consistent with the aerosol invigoration hypothesis. We find changes in the transitions from the shallow cumulus regime in different aerosol environments. The strength of these changes is strongly dependent on Low Troposphere Static Stability and 10 m windspeed, but less so on other meteorological factors.Whilst we have reduced the error due to meteorological and CF effects on the aerosol retrieval, meteorological covariation with the cloud and aerosol properties is harder to remove, so these results likely represent an upper bound on the effect of aerosols on cloud development and CF.

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“…-ORAC requires knowledge of the surface reflectance for each visible/near-infrared channel, which is provided by MODIS surface BRDF products (MCD43B) over land and a sea surface reflectance model over the ocean (Sayer et al, 2010). The surface temperature is a retrieved parameter, with the emissivity at each thermal channel determined using the University of WisconsinMadison Baseline Fit Emissivity Database (Seemann et al, 2008).…”

Section: Optimal Estimation Cloud Retrieval Algorithmmentioning

confidence: 99%

Synergy of stereo cloud top height and ORAC optimal estimation cloud retrieval: evaluation and application to AATSR

et al. 2016

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Abstract. In this paper we evaluate the impact on the cloud parameter retrievals of the ORAC (Optimal Retrieval of Aerosol and Cloud) algorithm following the inclusion of stereo-derived cloud top heights as a priori information. This is performed in a mathematically rigorous way using the ORAC optimal estimation retrieval framework, which includes the facility to use such independent a priori information. Key to the use of a priori information is a characterisation of their associated uncertainty. This paper demonstrates the improvements that are possible using this approach and also considers their impact on the microphysical cloud parameters retrieved. The Along-Track Scanning Radiometer (AATSR) instrument has two views and three thermal channels, so it is well placed to demonstrate the synergy of the two techniques. The stereo retrieval is able to improve the accuracy of the retrieved cloud top height when compared to collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), particularly in the presence of boundary layer inversions and high clouds. The impact of the stereo a priori information on the microphysical cloud properties of cloud optical thickness (COT) and effective radius (RE) was evaluated and generally found to be very small for single-layer clouds conditions over open water (mean RE differences of 2.2 (±5.9) microns and mean COD differences of 0.5 (±1.8) for single-layer ice clouds over open water at elevations of above 9 km, which are most strongly affected by the inclusion of the a priori).

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A sea surface reflectance model for (A)ATSR, and application to aerosol retrievals

Cited by 103 publications

References 63 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

Satellite observations of cloud regime development: the role of aerosol processes

Synergy of stereo cloud top height and ORAC optimal estimation cloud retrieval: evaluation and application to AATSR

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