scholarly journals Aerosol optical thickness and spatial variability along coastal and offshore waters of the eastern Arabian Sea

2011 ◽  
Vol 68 (4) ◽  
pp. 745-750 ◽  
Author(s):  
Harilal B. Menon ◽  
Nutan Sangekar ◽  
Aneesh Lotliker ◽  
Krishnaswamy Krishna Moorthy ◽  
Ponnumani Vethamony
Keyword(s):  
Spatial Variability ◽  
Optical Thickness ◽  
Coastal Waters ◽  
Arabian Sea ◽  
Aerosol Optical Thickness ◽  
Aerosol Size Distribution ◽  
Wave Radiation ◽  
Transfer Model ◽  
Eastern Arabian Sea

Abstract Menon, H. B., Sangekar, N., Lotliker, A., Krishna Moorthy, K., and Vethamony, P. 2011. Aerosol optical thickness and spatial variability along coastal and offshore waters of the eastern Arabian Sea. – ICES Journal of Marine Science, 68: 745–750. Data from the ocean-colour monitor (OCM) on board the Indian Remote Sensing Satellite P4 were used to analyse the spatial and temporal distribution of aerosol optical thickness (AOT) over the coastal and offshore waters of the eastern Arabian Sea. Zero water-leaving radiance from the near infrared (NIR) region was assumed for oceanic (open ocean) waters, because of the absorption of long-wave radiation by water molecules. As this assumption fails in coastal waters, it was necessary to correct for water-leaving radiance and sun glint to the NIR bands. The aerosol size-distribution parameter (α) was derived from a relationship between two NIR bands. The Ångström turbidity parameter (β) was obtained using an algorithm relating in situ hand-held, sun-photometer measurements and aerosol radiance (La) at 490 nm. The relationship between β and La (490) was derived with a sensitivity analysis, using a calibrated radiative transfer model. AOTs were retrieved for each pixel of 500 nm. The algorithm's performance was tested by comparing OCM-derived AOT values with in situ AOT and MODIS-derived values. Aerosol maps thus generated from January to December 2005 demonstrate the potential of this new retrieval method for producing AOT climatology from OCM data over coastal waters.

scholarly journals In Situ Profiling of Eastern Arabian Sea Coastal Waters Using a New Autonomous Vertical Profiler

2013 ◽  
Vol 38 (1) ◽  
pp. 43-54 ◽  
Author(s):  
Elgar Desa ◽  
R. Madhan ◽  
Nitin Dabholkar ◽  
Shivanand Prabhudesai ◽  
Gajanan Navelkar ◽  
...  
Keyword(s):  
Coastal Waters ◽  
Arabian Sea ◽  
Eastern Arabian Sea

Consistent retrieval of cloud/aerosol single scattering properties and surface reflectance

2021 ◽  
Author(s):  
Marta Luffarelli ◽  
Yves Govaerts
Keyword(s):  
Radiative Transfer ◽  
Optical Thickness ◽  
Solution Space ◽  
Single Scattering ◽  
Aerosol Optical Thickness ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Surface Reflectance ◽  
Earth System ◽  
System Components

<p>The CISAR (Combined Inversion of Surface and AeRosols) algorithm is exploited in the framework of the ESA Aerosol Climate Change Initiatiave (CCI) project, aiming at providing a set of atmospheric (cloud and aerosol) and surface reflectance products derived from S3A/SLSTR observations using the same radiative transfer physics and assumptions. CISAR is an advance algorithm developed by Rayference originally designed for the retrieval of aerosol single scattering properties and surface reflectance from both geostationary and polar orbiting satellite observations.  It is based on the inversion of a fast radiative transfer model (FASTRE). The retrieval mechanism allows a continuous variation of the aerosol and cloud single scattering properties in the solution space.</p><p> </p><p>Traditionally, different approaches are exploited to retrieve the different Earth system components, which could lead to inconsistent data sets. The simultaneous retrieval of different atmospheric and surface variables over any type of surface (including bright surfaces and water bodies) with the same forward model and inversion scheme ensures the consistency among the retrieved Earth system components. Additionally, pixels located in the transition zone between pure clouds and pure aerosols are often discarded from both cloud and aerosol algorithms. This “twilight zone” can cover up to 30% of the globe. A consistent retrieval of both cloud and aerosol single scattering properties with the same algorithm could help filling this gap.</p><p> </p><p>The CISAR algorithm aims at overcoming the need of an external cloud mask, discriminating internally between aerosol and cloud properties. This approach helps reducing the overestimation of aerosol optical thickness in cloud contaminated pixels. The surface reflectance product is delivered both for cloud-free and cloudy observations.  </p><p> </p><p>Global maps obtained from the processing of S3A/SLSTR observations will be shown. The SLSTR/CISAR products over events such as, for instance, the Australian fire in the last months of 2019, will be discussed in terms of aerosol optical thickness, aerosol-cloud discrimination and fine/coarse mode fraction.</p>

Influence of environmental variables on the distribution and community structure of mesozooplankton in the coastal waters of the eastern Arabian Sea

2020 ◽  
Vol 39 ◽  
pp. 101480
Author(s):  
P. Ezhilarasan ◽  
Vishnu Vardhan Kanuri ◽  
P. Sathish Kumar ◽  
M. Kumaraswami ◽  
G. Durga Rao ◽  
...  
Keyword(s):  
Community Structure ◽  
Coastal Waters ◽  
Environmental Variables ◽  
Arabian Sea ◽  
Eastern Arabian Sea

scholarly journals Error sources in the retrieval of aerosol information over bright surfaces from satellite measurements in the oxygen A-band

2017 ◽  
Author(s):  
Swadhin Nanda ◽  
Martin de Graaf ◽  
Maarten Sneep ◽  
Johan F. de Haan ◽  
Piet Stammes ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Surface Albedo ◽  
High Surface ◽  
Aerosol Optical Thickness ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Critical Surface ◽  
Layer Height

Abstract. Retrieving aerosol optical thickness and aerosol layer height over a bright surface from measured top of atmosphere reflectance spectrum in the oxygen A-band is known to be challenging, often resulting in large errors. In certain atmospheric conditions and viewing geometries, a loss of sensitivity to aerosol optical thickness has been reported in literature. This loss of sensitivity has been attributed to a phenomenon known as critical surface albedo regime, which is a range of surface albedos for which the top of atmosphere reflectance has minimal sensitivity to aerosol optical thickness. This paper extends the concept of critical surface albedo for aerosol layer height retrievals in the oxygen A-band, and discusses its implications. The underlying physics are introduced by analysing top of atmosphere reflectance spectra obtained using a radiative transfer model. Furthermore, error analysis of the aerosol layer height retrieval algorithm are conducted over dark and bright surfaces to show the dependency on surface reflectance. The analysis shows that the information on aerosol layer height from atmospheric path contribution and the surface contribution to the top of atmosphere are opposite in sign – an increase in surface brightness results in a decrease in information content. In the case of aerosol optical thickness, these contributions are anti-correlated, leading to large retrieval errors in high surface albedo regimes. The consequence of this anti-correlation is demonstrated with measured spectra in the oxygen A-band from GOME-2A instrument on board the Metop-A satellite over the 2010 Russian wildfires incident.

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