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Geographica Helvetica
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Volume 58, issue 2
Geogr. Helv., 58, 90–98, 2003
https://doi.org/10.5194/gh-58-90-2003
© Author(s) 2003. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geogr. Helv., 58, 90–98, 2003
https://doi.org/10.5194/gh-58-90-2003
© Author(s) 2003. This work is distributed under
the Creative Commons Attribution 3.0 License.

  30 Jun 2003

30 Jun 2003

3D cloud products for weather prediction and climate modelling

G. Seiz1, E. P. Baltsavias2, and A. Gruen2 G. Seiz et al.
  • 1Institut für Geodäsie und Photogrammetrie, ETH Hönggerberg, 8093 Zürich, und MeteoSchweiz, Krähbühlstrasse 58, 8044 Zürich, Switzerland
  • 2Institut für Geodäsie und Photogrammetrie, ETH Hönggerberg, 8093 Zürich, Switzerland

Abstract. In this paper, the possibilities of satellite-based and ground-based stereoscopy of clouds are examined, with the objective to derive cloud top and cloud base heights and motion. These parameters are very important for a better description of clouds for nowcasting and numerical weather prediction models. For the satellite part, images of ATSR2 (on ERS-2) and MISR (on EOS Terra) are used. As stereo image pairs from polar-orbiting satellites are never perfectly synchronous (time delay of some seconds between the image reeeption from the different viewing angles), the height error of the cloud top heights, introduced by the along-track motion component, is corrected with the cloud top winds extracted from Meteosat-6 and -7. For MISR, with nine viewing angles, this height correction is not needed when at least three images from non-symmetric cameras are used; then, it is possible to directly separate the along-track parallax (due to cloud height) from the along-track wind contribution (due to cloud motion). Our new ground-based imager System was operated in eoineidence with an overpass of ERS-2 in October 1999. The ground measurements proved to be an interesting technique to validate satellite-based cloud top height and motion of vertically thin clouds and to additionally detect more detailed cloud features, which is particularly important for aecurate noweasting in mountainous terrain.

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