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Passive satellite remote sensing

Clouds as appearing in different spectral channels of the ERS-2/ATSR-2 satellite instrument. Upper: 0.87 microns (near infrared); lower: 10.8 microns (thermal infrared).

The remote sensing activities at the Institute of Atmospheric Physics aim at improving our understanding of the influence of clouds on climate and atmospheric chemistry and at the validation of global models. According to the Intergovernmental Panel on Climate Change (IPCC) clouds and their interaction with radiation are still the largest source of uncertainty in our understanding of the climate system.

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

• One- and three-dimensional radiative transfer models: libRadtran, MYSTIC, MOM
• Cloud classification schemes and remote sensing algorithms for the retrieval of physical properties of water and ice clouds (for Meteosat/MVIRI, MSG/SEVIRI, TERRA and AQUA/MODIS)
• Operational algorithms for the detection and the temporal  tracking  of line-shaped contrails and ice clouds   (für MSG/SEVIRI, TERRA und AQUA/MODIS, NOAA und MetOp/AVHRR, ENVISAT/AATSR)

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.