The Samoa Hurricane, 15-16 March 1889

Analysing historical weather extremes such as the tropical cyclone in Samoa in March 1889 could add to our understanding of extreme events. However, up to now the availability of suitable data was limiting the analysis of historical extremes, particularly in remote regions. The new “Twentieth Century Reanalysis” (20CR), which provides six-hourly, three-dimensional data for the entire globe back to 1871, might provide the means to study this and other early events. While its suitability for studying historical extremes has been analysed for events in the northern extratropics (see other papers in this volume), the representation of tropical cyclones, especially in early times, remains unknown. The aim of this paper is to study to the hurricane that struck Samoa on 15-16 March 1889. We analyse the event in 20CR as well as in contemporary observations. We find that the event is not reproduced in the ensemble mean of 20CR, nor is it within the ensemble spread. We argue that this is due to the paucity of data assimilated into 20CR. A preliminary compilation of historical observations from ships for that period, in contrast, provides a relatively consistent picture of the event. This shows that more observations would be available and implies that future versions of surface-based reanalyses might profit from digitizing further observations in the tropical region.

Why Monte Carlo Simulations are Inferences and not Experiments

Monte Carlo simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the inference by ordinary argumentation of conclusions from assumptions built into the simulations. We show that Monte Carlo simulations cannot produce knowledge other than by inference, and that they resemble other computer simulations in the manner in which they derive their conclusions. Simple examples of Monte Carlo simulations are analysed to identify the underlying inferences.

More than just Good Luck. How to Explain the Success of Monte Carlo Simulations

Monte Carlo simulation is a powerful method in many natural and social sciences. But what sort of method is it? And where does its power come from? Are Monte Carlo simulations experiments, theories or something else? The aim of this talk is to answer these questions and to explain the power of Monte Carlo simulations. I provide a classification of Monte Carlo techniques and defend the claim that Monte Carlo simulation is a sort of inference.

Ein Forschungsreisender als Notbehelf: Hermann von Wissmann und der erste Überseeeinsatz des Deutschen Reichs (1889-1891)

When the German government faced for the first time an irregular war in German East Africa in 1888, it realised that it did not have the necessary means for such a conflict. Hermann Wissmann, an explorer, was therefore given the mandate to form and lead a force of mercenaries that was bound to him personally on the basis of contracts. Although Wissmann was successful in crushing the disturbances, the government of the Reich refused to give him a leading administrative position in the new formed protectorate subordinate directly to the Kaiser. It feared that the entrepreneur of violence, which had up to then been backed up, would not accept the regulations of colonial rule that should be implemented. Soon, however, it became clear that due to entrenched local views on sovereignty and legitimacy it would be difficult to transfer the western European concept of the monopoly of the state on violence to Africa.

Saddlepoint approximations to sensitivities of tail probabilities of random sums and comparisons with Monte Carlo estimators

This article proposes computing sensitivities of upper tail probabilities of random sums by the saddlepoint approximation. The considered sensitivity is the derivative of the upper tail probability with respect to the parameter of the summation index distribution. Random sums with Poisson or Geometric distributed summation indices and Gamma or Weibull distributed summands are considered. The score method with importance sampling is considered as an alternative approximation. Numerical studies show that the saddlepoint approximation and the method of score with importance sampling are very accurate. But the saddlepoint approximation is substantially faster than the score method with importance sampling. Thus, the suggested saddlepoint approximation can be conveniently used in various scientific problems.

A critical evaluation of secondary cancer risk models applied to Monte Carlo dose distributions of 2-dimensional, 3-dimensional conformal and hybrid intensity-modulated radiation therapy for breast cancer

The comparison of radiotherapy techniques regarding secondary cancer risk has yielded contradictory results possibly stemming from the many different approaches used to estimate risk. The purpose of this study was to make a comprehensive evaluation of different available risk models applied to detailed whole-body dose distributions computed by Monte Carlo for various breast radiotherapy techniques including conventional open tangents, 3D conformal wedged tangents and hybrid intensity modulated radiation therapy (IMRT). First, organ-specific linear risk models developed by the International Commission on Radiological Protection (ICRP) and the Biological Effects of Ionizing Radiation (BEIR) VII committee were applied to mean doses for remote organs only and all solid organs. Then, different general non-linear risk models were applied to the whole body dose distribution. Finally, organ-specific non-linear risk models for the lung and breast were used to assess the secondary cancer risk for these two specific organs. A total of 32 different calculated absolute risks resulted in a broad range of values (between 0.1% and 48.5%) underlying the large uncertainties in absolute risk calculation. The ratio of risk between two techniques has often been proposed as a more robust assessment of risk than the absolute risk. We found that the ratio of risk between two techniques could also vary substantially considering the different approaches to risk estimation. Sometimes the ratio of risk between two techniques would range between values smaller and larger than one, which then translates into inconsistent results on the potential higher risk of one technique compared to another. We found however that the hybrid IMRT technique resulted in a systematic reduction of risk compared to the other techniques investigated even though the magnitude of this reduction varied substantially with the different approaches investigated. Based on the epidemiological data available, a reasonable approach to risk estimation would be to use organ-specific non-linear risk models applied to the dose distributions of organs within or near the treatment fields (lungs and contralateral breast in the case of breast radiotherapy) as the majority of radiation-induced secondary cancers are found in the beam-bordering regions.