International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B5. Istanbul 2004
Figure 9: Volsh rendering of a whole GB scene
XAnim: cuftib2 mov (01
Figure 10:CLC cloud cover from aLMo NWP model
3. CONCLUSIONS AND FURTHER WORK
From the short literature study that we did, we have seen that
the problem of modelling and rendering cloud-type data can be
approached from different routes. There is a trade-off between
the simulation accuracy of the physical phenomenon and the
time required to deliver visualisation. One can focus on keeping
a realistic image of cloud formation and movement together
with interactive rendering speed, but in scientific visualization
this would mean drifting away from the results of the
measurements. On the other hand, by using strictly the results
of measurements, we move to the other end of visualization
difficult to understand without detailed knowledge of the
instruments used and possible errors that may happen. In the
present work, we demonstrated the several problems and
difficulties that arise from using real measurements in cloud
modelling and rendering. If visualization is about delivery of
desired information in a quick and comprehensive way, then the
field of 3D volume rendering has a lot of open issues in fields
such as environmental sciences and meteorology.
The present combination of particle systems, soft body
modelling, hardware accelerated graphics and software-based
volume rendering had the purpose to teach us the benefits that
scientific visualization can gain from following and adjusting
current advances in computer graphics.
In the current status of the presented work we would like to
improve the search algorithm that adds up the metaball weights
for every grid cell, since at the moment is a straighforward loop
that traverses all the metaballs, without taking into account if
they will contribute finally or not. We are interested in
continuimg the work on temporal interpolation from several
time steps in order to deliver animations over time. This will be
possible to do on the aLMo NWP model since it provides 3D
values every hour. Application of this idea on the combined
CBH and CTH measurements seems difficult because of the
temporal resolution of the satellite images.
4. ACKNOWLEDGEMENTS
The aLMo NWP data were supplied by Gabriela Seiz and
MeteoSwiss, Zurich Weather Office. We would like to thank
our CLOUDMAP2 colleague Tobias Zinner at DLR, for
supplying us with three-dimensional cloud liquid water from
the combined CLOUDMAP2 measurements in Zurich Kloten
airport, taken on 12 April 2002. This work was funded by the
Bundesamt fir Bildung unf Wissenschaft (BBW), within the
EU project CLOUDMAP2 (BBW Nr. 00.0355-1).
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