Satellite- and ground-based stereo analysis of clouds

Gabriela Seiz, Manos Baltsavias, Armin Grün, / Eidgenössische Technische Hochschule Zürich Institut Für Geodäsie Und Photogrammetrie
2003
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, coincident images of MISR (on EOS Terra), ASTER (on EOS Terra) and ATSR2 (on ERS-2) are used. For the ground-based part, stereo images from our newly developed imager
more » ... tem are used. The cameras were installed during the Mesoscale Alpine Programme (MAP) in the target area 'Rhine Valley' in October 1999 and at Zurich-Airport, Switzerland, in September 2001 and April 2002, in coincidence with overpasses of EOS-Terra and ERS-2. In principle, the same stereo matching algorithms, based on least-squares matching, are applied on both the satellite-based and ground-based images. With respect to the different spatial resolution of the sensors, the matching strategy has to be adjusted accordingly. Furthermore, the main differences in the processing chain between the satellite-based and ground-based data sets are the geometric calibration of the sensors, the preprocessing procedures and the quality-control algorithms. Finally, two case studies of coincident groundand satellite-based retrieval of cloud-base/cloud-top height and motion are presented. The ground measurements with our new stereo camera system showed to be an interesting technique to validate satellite-based cloud-top height and motion of vertically thin clouds and to additionally detect smaller scale cloud features, which is particularly important for accurate nowcasting in mountainous terrain. Furthermore, the 3D results from coincident satellite and ground measurements can be taken as input data for numerical cloud and very high resolution weather models.
doi:10.3929/ethz-a-004659070 fatcat:lmvhcg6hbbe2fefnwpihf3q2ji