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More on SCIAMACHY PMD Identication of Clouds and Ice/snow method (SPICI): Degradation correction

J.M. Krijger(1), I. Aben(1) and H. Schrijver(1)

(1) SRON, Sorbonnelaan 2, 3584 CA Utrecht, Netherlands

Abstract

Clouds in observed scenes from space can severely hinder the observation of tropospheric gases such as those from SCIAMACHY on ENVISAT which measures different trace gases including those most abundant in the troposphere (e.g. CO, NO2, CH4). Several cloud detection algorithms have been developed for GOME on ERS-2 which have also been applied to SCIAMACHY. The GOME cloud algorithms, however, suffer from the inadequacy of not being able to distinguish between clouds and ice/snow covered surfaces because GOME only covers the UV, VIS and part of the NIR wavelength range (240-790 nm). As a result snow/ice covered areas are always flagged as clouded, and therefore often not used.

Previously (Krijger, 2005) a method was presented which uses the SCIAMACHY Polarisation Measurement Device (PMD) measurements in the wavelength range between 450 nm and 1600 nm to make a distinction between clouds and these ice/snowcovered surfaces, called SCIAMACHY PMD Identication of Clouds and Ice/snow method (SPICI). We now present an update and improvement to the SPICI algorithm; the new version being not only able to better detect cloud-free scenes over forests partly covered in snow, but also compensating for the increasing degradation of the SCIAMACHY PMDs.