Srama R.,Max Planck Institute for Nuclear Physics |
Srama R.,Universtitat Stuttgart |
Kempf S.,Universtitat Braunschweig |
Kempf S.,Universtitat Colorado |
And 48 more authors.
CEAS Space Journal | Year: 2011
The interplanetary space probe Cassini/Huygens reached Saturn in July 2004 after 7 years of cruise phase. The German cosmic dust analyser (CDA) was developed under the leadership of the Max Planck Institute for Nuclear Physics in Heidelberg under the support of the DLR e. V. This instrument measures the interplanetary, interstellar and planetary dust in our solar system since 1999 and provided unique discoveries. In 1999, CDA detected interstellar dust in the inner solar system followed by the detection of electrical charges of interplanetary dust grains during the cruise phase between Earth and Jupiter. The instrument determined the composition of interplanetary dust and the nanometre-sized dust streams originating from Jupiter's moon Io. During the approach to Saturn in 2004, similar streams of submicron grains with speeds in the order of 100 km/s were detected from Saturn's inner and outer ring system and are released to the interplanetary magnetic field. Since 2004 CDA measured more than one million dust impacts characterising the dust environment of Saturn. The instrument is one of the three experiments which discovered the active ice geysers located at the south pole of Saturn's moon Enceladus in 2005. Later, a detailed compositional analysis of the water ice grains in Saturn's E ring system led to the discovery of large reservoirs of liquid water (oceans) below the icy crust of Enceladus. Finally, the determination of the dust-magnetosphere interaction and the discovery of the extended E ring (at least twice as large as predicted) allowed the definition of a dynamical dust model of Saturn's E ring describing the observed properties. This paper summarizes the discoveries of a 10-year story of success based on reliable measurements with the most advanced dust detector flown in space until today. This paper focuses on cruise results and findings achieved at Saturn with a focus on flux and density measurements. CDA discoveries related to the detailed dust stream dynamics, E ring dynamics, its vertical profile and E ring compositional analysis are published elsewhere (see Hus et al. in AIP Conference Proccedings 1216:510-513, 2010; Hsu et al. in Icarus 206:653-661, 2010; Kempf et al. in Icarus 193:420, 2008; 206(2):446, 2010; Postberg et al. in Icarus 193(2):438, 2008; Nature 459:1098, 2009; Nature, 2011, doi:10.1038/nature10175). © 2011 CEAS.
Shebalin P.N.,CNRS Paris Institute of Global Physics |
Narteau C.,CNRS Paris Institute of Global Physics |
Zechar J.D.,ETH Zurich |
Holschneider M.,Universtitat Potsdam
Earth, Planets and Space | Year: 2014
We describe an iterative method to combine seismicity forecasts. With this method, we produce the next generation of a starting forecast by incorporating predictive skill from one or more input forecasts. For a single iteration, we use the differential probability gain of an input forecast relative to the starting forecast. At each point in space and time, the rate in the next-generation forecast is the product of the starting rate and the local differential probability gain. The main advantage of this method is that it can produce high forecast rates using all types of numerical forecast models, even those that are not rate-based. Naturally, a limitation of this method is that the input forecast must have some information not already contained in the starting forecast. We illustrate this method using the Every Earthquake a Precursor According to Scale (EEPAS) and Early Aftershocks Statistics (EAST) models, which are currently being evaluated at the US testing center of the Collaboratory for the Study of Earthquake Predictability. During a testing period from July 2009 to December 2011 (with 19 target earthquakes), the combined model we produce has better predictive performance - in terms of Molchan diagrams and likelihood - than the starting model (EEPAS) and the input model (EAST). Many of the target earthquakes occur in regions where the combined model has high forecast rates. Most importantly, the rates in these regions are substantially higher than if we had simply averaged the models. © 2014 Shebalin et al.; licensee Springer.
Shebalin P.,Prediction Institute |
Narteau C.,University Paris Diderot |
Holschneider M.,Universtitat Potsdam
Bulletin of the Seismological Society of America | Year: 2012
We propose a conversion method from alarm-based to rate-based earthquake forecast models. A differential probability gaing ref alarm is the absolute value of the local slope of the Molchan trajectory that evaluates the performance of the alarm-based model with respect to the chosen reference model. We consider that this differential probability gain is constant over time. Its value at each point of the testing region depends only on the alarm function value. The rate-based model is the product of the event rate of the reference model at this point multiplied by the corresponding differential probability gain. Thus, we increase or decrease the initial rates of the reference model according to the additional amount of information contained in the alarm-based model. Here, we apply this method to the Early Aftershock STatistics (EAST)model, an alarm-based model in which early aftershocks are used to identify space-time regions with a higher level of stress and, consequently, a higher seismogenic potential. The resulting rate-based model shows similar performance to the original alarm-based model for all ranges of earthquake magnitude in both retrospective and prospective tests. This conversion method offers the opportunity to perform all the standard evaluation tests of the earthquake testing centers on alarm-based models. In addition, we infer that it can also be used to consecutively combine independent forecast models and, with small modifications, seismic hazard maps with short- and medium-term forecasts.