A method to overcome the problem of 'slow' sensors Jan H. Schween1, Jochen Reuder2 1Meteorological Institute University Munich, Germany , jan.schween@lrz.uni-muenchen.de 2Geophysical Institute, University of Bergen, Norway - PowerPoint PPT Presentation

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A method to overcome the problem of 'slow' sensors Jan H. Schween1, Jochen Reuder2 1Meteorological Institute University Munich, Germany , jan.schween@lrz.uni-muenchen.de 2Geophysical Institute, University of Bergen, Norway

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A method to overcome the problem of 'slow' sensors. Jan H. Schween1, Jochen Reuder2 ... In general sensors have a certain inertia, they follow a sudden change of the ... – PowerPoint PPT presentation

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Title: A method to overcome the problem of 'slow' sensors Jan H. Schween1, Jochen Reuder2 1Meteorological Institute University Munich, Germany , jan.schween@lrz.uni-muenchen.de 2Geophysical Institute, University of Bergen, Norway


1
A method to overcome the problem of 'slow'
sensorsJan H. Schween1, Jochen
Reuder21Meteorological Institute University
Munich, Germany , jan.schween_at_lrz.uni-muenchen.de
2Geophysical Institute, University of Bergen,
Norway
Intro In general sensors have a certain inertia,
they follow a sudden change of the measured
quantity with a certain delay. As a result the
signal received appears to be smooothed in time.
In many cases it is desirable to have a faster
response of the sensor. We are measuring
Temperature (T) and Humiditiy (rH) on the cable
cars at Zugspitze mountain, Germany (see Poster
EGU06-A-01076). Every ride of the cable cars a
profile is measured. Due to the inertia of the
sensors the measured values of the ride up differ
from the ride down resulting in a hysteresis like
effect (see fig. 1). We use a numerical method to
get around this Problem.
Results Figure 2 shows the result for the
temperature profiles of the Vaisala Sensor (V)
shown in Figure 1b. The original measured values
were smoothed with the filter according to
equation 4 and a time constant ?f 6s (i.e.
the sensor was made artificially slower).
Reconstruction of the ambiance Temperature was
made using equation 1 with ?x 50s. The
effect of noise is visible in Figure 3 The
signal of the Fischer Sensor (F) is noisy and
even a filtering with ?f 14s leads to strong
noise in the reconstructed Profile (?x 162s).
Despite this noise there is general agreement
between the two reconstructed Profiles indicating
that the reconstruction is a good approximation
to reality.
Acknowledgements We thank the Bayerische
Zugspitzbahn (BZB) for the possibility to equip
the cable cars with our instruments. The
Bannerwolken project is granted by the German
Research Foundation (DFG)
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