Inhaltsverzeichnis - Mathematisches Institut der Universität zu Köln

DMV Tagung 2011 - Köln, 19. - 22. September
Jörn Behrens
Universität Hamburg, KlimaCampus
A Practical Application of Uncertainty Propagation for Tsunami Early Warning
The challenge of near-field tsunami early warning is to assess the situation precisely within a few minutes,
limited by few and uncertain measurements of key indicators. In other words, in a short timeframe only
limited information is available, but this information has to be interpreted in such a way, that false warnings
are minimized. This challenge had not been addressed in existing tsunami early warning systems
until recently and still leads to a large number of false positive (to be on the save side) tsunami warning
messages world wide. In the course of development of the German Indonesian Tsunami Early Warning
System (GITEWS), operational since 2008 in Jakarta, Indonesia, a new method to assess the situation
has been developed [Behrens et al., 2010]. This method utilizes a simple, yet effective uncertainty propagation
model, which leads to more robust and accurate situation assessments under the large uncertainty
of the first few minutes after an earthquake event. The system is designed as an analog forecasting system,
based on pre-computed scenarios. This allows for a forecast within seconds after measurements
are available. In this presentation the basic design of the system is introduced. Examples for the high
sensitivity and uncertainty of the forecasting problem are given and an analysis with a simple uncertainty
propagation model is given. Based on the analysis, a new method that decreases uncertainties in a robust
way, is derived. Finally, examples of successful application of the new method are given.
Literatur
Behrens, J., A. Androsov, A. Y. Babeyko, S. Harig, F. Klaschka, L. Mentrup. (2010). A new multi-sensor
approach to simulation assisted tsunami early warning. Nat. Hazards Earth Syst. Sci., 10, 1085 - 1100.
Katrin Bentel, Gabriel Goebel, Michael Schmidt, Christian Gerlach
Norwegian University of Life Sciences, Deutsches Geodätisches Forschungsinstitut (DGFI), Bavarian
Academy of Sciences and Humanities
Point grid positions for radial base functions and their effect in regional gravity field
representations
Global gravity fields are most common represented in spherical harmonic base functions. However, the
main drawback of this representation is that regional signals are not necessarily represented in an optimal
way. Spherical harmonics have global support, thus, the gravity models are globally optimized best-fit
solutions. That means, it is difficult to represent small spatial details, they can even be masked in the
solutions.
To represent a gravity signal in a specified region on a sphere appropriately, we use localizing radial base
functions for regional gravity field modeling. The distribution of these individual base functions follows
a predefined point grid. The type of grid, number of points, area boundaries, point density, and other
parameters play a very important role in the representation of a signal. Depending on the type of grid and
its characteristics, artificial structures occur in the estimation of gravity field parameters. In this study we
present some of these typical structures and investigate in detail various effects of different point grid
parameters in the representation of a regional gravity field.
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