This paper presents the validation results of ENVISAT MERIS and TERRA MODIS retrieval algorithms for atmospheric Water Vapour Content (WVC) estimation in clear sky condition on land. The MERIS algorithm exploits the radiance ratio of the absorbing channel at 900 nm with the almost absorption-free reference at 890 nm, while the MODIS one is based on the ratio of measurements centred at near 0.905, 0.936, and 0.94 mu m with atmospheric window reflectance at 0.865 and 1.24 mu m. The first test was performed in the Mediterranean area using WVC provided from both ECMWF and AERON-ET. As a second step, the performances of the algorithms were tested exploiting WVC computed from radiosoundings (RAOBs) in the North East Australia. The different comparisons with respect to reference WVC values showed an overestimation of WVC by MODIS (root mean square error percentage greater than 20%) and an acceptable performance of MERIS algorithms (root mean square error percentage around 10%).

Validation of near infrared satellite based algorithms to retrieve atmospheric water vapour content over land

Biondi, R;
2009

Abstract

This paper presents the validation results of ENVISAT MERIS and TERRA MODIS retrieval algorithms for atmospheric Water Vapour Content (WVC) estimation in clear sky condition on land. The MERIS algorithm exploits the radiance ratio of the absorbing channel at 900 nm with the almost absorption-free reference at 890 nm, while the MODIS one is based on the ratio of measurements centred at near 0.905, 0.936, and 0.94 mu m with atmospheric window reflectance at 0.865 and 1.24 mu m. The first test was performed in the Mediterranean area using WVC provided from both ECMWF and AERON-ET. As a second step, the performances of the algorithms were tested exploiting WVC computed from radiosoundings (RAOBs) in the North East Australia. The different comparisons with respect to reference WVC values showed an overestimation of WVC by MODIS (root mean square error percentage greater than 20%) and an acceptable performance of MERIS algorithms (root mean square error percentage around 10%).
2009
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3415696
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