Passive remote sensing utilizes either solar radiation reflected at the Earth's surface or scattered in the atmospere, or thermal radiation emitted by the surface or the atmosphere, to derive atmospheric or surface properties. Our remote sensing activities focus on water and ice clouds as well as contrails. Clouds generally reflect more solar radation than the underlying surface. The figure shows an observation of ERS-2/ATSR-2 from March 23, 2000, to the West of Chile. In the visible or near-infrared channel (0.87 micron, top) typical stratocumulus structures are visible. In the thermal infrared clouds are basically opaque and can be distinguished from the surface by their lower brightness temperature. The most striking feature in the lower image (10.8 micron, thermal infrared) are therefore the high (cold) cirrus clouds in the upper left part of the image which are hardly detectable in the visible channel due to their low optical thickness. Combining different spectral channels, clouds can be detected quantitatively. Furthermore, by comparison of the observed reflectivities and brightness temperatures with those predicted by a radiative transfer model, optical and microphysical parameters can be derived (among others, optical thickness, liquid and ice water content, effective droplet and particle sizes).
Our main tools for satellite remote sensing are
Our research concentrates on the development and application of remote sensing algorithms for Meteosat Second Generation (MSG/SEVIRI) and ENVISAT/AATSR. Currently we are engaged in developing algorithms that are based on the synergethic use of active instruments (CALIPSO/CALIOP) with passive instruments (MSG/SEVIRI). A validation of remote sensing algorithms is -amongst others- carried out with simulated radiances from libRadtran or from the 3-d radiative transfer model MYSTIC. These models are feeded with realistic cloud field input stemming from the DWD forecast models COSMO-EU or COSMO-DE.