Seminaire Du Gap Biophotonics "xbaer: a Generic Algorithm for the Retrieval of Aerosol Properties from Satel-lite Observations"
نویسنده
چکیده
Because of a long-term synergy with other observations from ENVISAT, there is advan-tage to derive aerosol optical thickness (AOT) using the MEdium Resolution Imaging Spectrometer (MERIS) instrument. Although limited in spectral coverage, it is possible to derive accurate AOT from MERIS. Here, we introduce a new AOT retrieval algorithm for MERIS over land surfaces, henceforth called eXtensible Bremen AErosol Retrieval (XBAER). XBAER is similar to the dark-target retrieval algorithm used for Moderate Imaging Resultion Spectroradiometer (MODIS), in that it uses a lookup table (LUT) approach, and that minimum differences between observed and LUT spectral reflectance represents the aerosol solution. However, instead of global parameterization of surface spectral reflectance, XBAER uses a set of spectral libraries to prescribe surface properties. Thus, XBAER retrieves AOT over both dark surfaces (vegetation) and bright surface (desert, semiarid, and urban areas). Cloud mask is an essential step for XBAER. However, establishing an accurate and adequate cloud mask is a challenging task for passive aerosol remote sensing from space base instrumentation. This is especially true for those instruments without infrared channels. Aerosol retrievals require a particular cloud masking approach since a mask based on too conservative thresholds and assumptions will screen out strong aerosol episodes and a less conservative approach could allow cloud contamination significantly affecting the subsequently retrieved aerosol optical properties (e.g. AOT). In this context, a cloud mask algorithm utilizing MERIS instrument characteristics has been developed for the MERIS operational aerosol retrieval algorithm XBAER. The XBAER Cloud Mask (XBAERCM) algorithm is a threshold-based method that does not require any auxiliary data. MERIS Top Of Atmosphere (TOA) reflectances have been evaluated not only taking into account the brightness of the scenes, but also of its texturing/variability and of the cloud altitude.
منابع مشابه
XBAER-derived aerosol optical thickness from OLCI/Sentinel-3 observation
A cloud-masking algorithm based on the spatial variability of reflectances at the top of the atmosphere in visible wavelengths was developed for the retrieval of aerosol properties by MODIS. It is shown that the spatial pattern of cloud reflectance as observed from space is very different from that of aerosols. Clouds show a very high spatial variability in the scale of a hundred metres to a fe...
متن کاملInteractive comment on “XBAER derived aerosol optical thickness from OLCI/Sentinel-3
This paper presents an expansion of XBAER (eXtensible Bremen Aerosol Retrieval) algorithm, which was developed based on previous MERIS (Medium Resolution Imaging Spectrometer), to a new OLCI (Ocean Land Color Instrument) sensor onboard sentinel-3. This contains the details of algorithm and results during December 2016 with specific heavy haze case analysis in Beijing and North China plain regio...
متن کاملLite Aerosol Retrievals with Improved Calibration and Retrieval Approaches in Support of Calipso
14 Two of the biggest uncertainties in understanding and predicting climate change are the effects of aerosols and clouds. NASA's satellite mission, CALIPSO (CloudAerosol Lidar and Infrared Pathfinder Satellite Observations), will provide vertical, curtain-like images of the atmosphere on a global scale and assist scientists in better determining how aerosols and clouds affect the Earth's radia...
متن کاملAerosol properties derived from aircraft multiangle imaging over Monterey Bay
The first generic and climatological aerosol retrievals using AirMISR data are presented. Multiangle observations at 672 and 867 nm, in a cloud-free region over dark water in Monterey Bay on June 29, 1999, yield complementary generic and climatological results. The generic retrieval produces cross-section-weighted, column-mean aerosol properties: midvisible aerosol optical depth between 0.05 an...
متن کاملSpatio-temporal variability of aerosol characteristics in Iran using remotely sensed datasets
The present study is the first attempt to examine temporal and spatial characteristics of aerosol properties and classify their modes over Iran. The data used in this study include the records of Aerosol Optical Depth (AOD) and Angstrom Exponent (AE) from MODerate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Index (AI) from the Ozone Monitoring Instrument (OMI), obtained from 2005 t...
متن کامل