Abstract
The performance of the cloud properties algorithm of the future Global Change Observation Mission-Climate/Second-Generation Global Imager (GCOM-C/SGLI) satellite is compared with that of a spectrally compatible sensor, the moderate resolution image spectroradiometer (MODIS). The results obtained are evaluated against the target accuracy of the GCOM-C/SGLI satellite mission. Three direct cloud parameters: the cloud optical thickness (COT), the cloud particle effective radius (CLER), and the cloud top temperature (CTT), and an indirect parameter: the cloud liquid water path (CLWP), are the cloud properties that are evaluated. The satellite–satellite comparison shows a good alignment between the retrievals of the GCOM-C/SGLI algorithm and those of MODIS in most of the areas and agreement with the accuracy targets of the new satellite mission. However, the COT comparison shows an increasing dispersion with the increase of the cloud thickness along the GCOM-C/SGLI-MODIS 1∶1 line. The CTT is systematically overestimated by the GCOM-C/SGLI (against MODIS), particularly in mid-thermal clouds. This is found to be due to an insufficient cloud emissivity correction of the thermal radiances by the GCOM-C/SGLI algorithm. The lowest COT, CLER, and CLWP accuracies, noticed in forest areas, are found to be related to the cloud detection uncertainty and the nonabsorption channel sensitivity differences.
Highlights
Earth observation satellites missions, such as the Aqua/Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (Aqua/AMSR-E), the Global Change Observation Mission-Water/ Advanced Microwave Scanning Radiometer 2 (GCOM-W/AMSR2), the Terra- and AquaModerate Resolution Imaging Spectroradiometer (Terra- or Aqua-moderate resolution image spectroradiometer (MODIS)), the National Oceanic and Atmospheric Administration/Advanced Very-High-Resolution Radiometer (NOAA-AVHRR), the ENVIronmental SATellite-MEdium Resolution Imaging Spectrometer (ENVISAT-MERIS) as well as the future GCOM-C/SGLI,[1,2,3] are expected to monitor continuously various atmospheric constituents and to contribute to the development of useful geophysical products with high accuracy and reliability to be considered as “climate data records.”[4]
Among the parameters retrieved by the GCOM-C/ SGLI algorithm, three direct cloud properties [the cloud optical thickness (COT), cloud particle effective radius (CLER), and cloud top temperature (CTT)] and one indirect property [the cloud liquid water path (CLWP)] are examined for the study
In contrast with the GCOM-C/SGLI cloud algorithm, where all the retrievals are made from a single program, the MODIS retrievals are obtained through two algorithms: the optical thickness, effective particle radius, and thermodynamic phase algorithm (MOD05) for the COT and CLER retrievals,[7] and the cloud top properties and thermodynamic phase algorithm[21] for the retrievals of the CTT, the cloud top pressure (CTP), etc
Summary
Earth observation satellites missions, such as the Aqua/Advanced Microwave Scanning Radiometer for EOS (Aqua/AMSR-E), the Global Change Observation Mission-Water/ Advanced Microwave Scanning Radiometer 2 (GCOM-W/AMSR2), the Terra- and AquaModerate Resolution Imaging Spectroradiometer (Terra- or Aqua-MODIS), the National Oceanic and Atmospheric Administration/Advanced Very-High-Resolution Radiometer (NOAA-AVHRR), the ENVIronmental SATellite-MEdium Resolution Imaging Spectrometer (ENVISAT-MERIS) as well as the future GCOM-C/SGLI,[1,2,3] are expected to monitor continuously various atmospheric constituents and to contribute to the development of useful geophysical products with high accuracy and reliability to be considered as “climate data records.”[4]. Radiances and geometrical parameters from the Advanced Earth Observation Satellite-II/Global Imager (ADEOS-II/GLI), precursor of the GCOM-C/SGLI, serve as input data for the implementation of the cloud algorithm evaluated in this article. As in most of the algorithms, such as those of the GCOM-C/SGLI or MODIS, geophysical properties (COT and CLER) retrievals are typically solved by comparing the measured reflectances with entries in a lookup table (LUT) and by searching for the combination of COT and CLER that gives the best fit.[7] The first property to be retrieved in the GCOM-C/SGLI algorithm is the CTT It is obtained through the infrared window method using atmospherically corrected brightness temperatures at 10.8 μm. With optically thick clouds and large values of ground albedo, the effect is relatively large at visible wavelengths
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