Cloud and surface classification using SCIAMACHY polarization measurement devices

Abstract

A simple scheme has been developed to discriminate surface, sun glint and cloud properties in satellite based spectrometer data utilizing visible and near infrared information. It has been designed for the use with data measured by SCIAMACHY's (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY) Polarization Measurement Devices (PMD) but the applicability is not strictly limited to this instrument. The scheme is governed by a set of constraints and thresholds developed by using satellite imagery and meteorological data. Classification targets are ice, water and generic clouds, sun glint and surface parameters, such as water, land, snow/ice, desert and vegetation. The validation has been done using MERIS (MEdium Resolution Imaging Spectrometer) and meteorological data from METAR (MÉTéorologique Aviation Régulière – a network for the provision of meteorological data for aviation). Qualitative validation using MERIS satellite imagery shows good agreement. However, the quantitative agreement is hampered by the heterogeneity of MERIS classifications within each SCIAMACHY PMD ground pixel. The comparison with METAR data shows good agreement. The comparison for sun glint classifications and MERIS results exhibits excellent agreement.