Peter Höppe

Stochastic modelling of tropical cyclone tracks

A stochastic model for the tracks of tropical cyclones that allows for the computerised generation of a large number of synthetic cyclone tracks is introduced. This will provide a larger dataset than previously available for the assessment of risks in areas affected by tropical cyclones. To improve homogeneity, the historical tracks are first split into six classes. The points of cyclone genesis are modelled as a spatial Poisson point process, the intensity of which is estimated using a generalised version of a kernel estimator. For these points, initial values of direction, translation speed, and wind speed are drawn from histograms of the historical values of these variables observed in the neighbourhood of the respective points, thereby generating a first 6-h segment of a track. The subsequent segments are then generated by drawing changes in theses variables from histograms of the historical data available near the cyclone’s current location. A termination probability for the track is determined after each segment as a function of wind speed and location. In the present paper, the model is applied to historical cyclone data from the western North Pacific, but it is general enough to be transferred to other ocean basins with only minor adjustments. A version for the North Atlantic is currently under preparation.

Tropical Cyclone Losses in the USA and the Impact of Climate Change: A Trend Analysis Based on a New Dataset

Economic losses caused by tropical cyclones have increased dramatically. It can be assumed that most losses are due to increased prosperity and a greater tendency for people to settle in exposed areas, but also that the growing incidence of severe cyclones is due to climate change. This paper aims to isolate the socio-economic effects and ascertain the potential impact of climate change on this trend. Storm losses for the period 1950-2005 have been adjusted to 2005 socio-economic values so that any remaining trend cannot be ascribed to socio-economic developments. In the period 1971-2005, losses excluding socio-economic effects show an annual increase of 4% per annum.

Scientific and Economic Rationale for Weather Risk Insurance for Agriculture

Munich Re is one of the largest global reinsurers and has a long tradition in both the assessment of weather-related hazards and their impact on crop production and the development of appropriate risk management tools and crop insurance schemes. Munich Re’s underwriting of agricultural risks throughout the world is concentrated in its agricultural underwriting department. This department has long been a world-renowned centre of competence. It develops Munich Re’s strategy and underwriting guidelines and is responsible for the underwriting of agricultural insurance within the Munich Re Group. This involves a wide range of segments like crops, crop hail, multi-peril and named perils, livestock including aquaculture and greenhouses. With a premium income of about €400m in 2006, Munich Re is the world’s largest agricultural reinsurer.

The UTCI and the ISB

Thermal effects of the environment are the most prominent environmental influences on the human body. Keeping the body core temperature in a narrow optimum range is the dominating physiological process. Thus, assessing thermal environments has been a major field in biometeorology for many decades, which is also reflected in the number of respective articles and their citations. In the early days of thermal assessments, simple indices only considering a few environmental parameters were used. The next step has been the development of heat budget models describing all relevant heat/energy fluxes to and from the human body. One of the first was PET, which has been presented in the most cited IJBM publication ever (1999). All of these models created by individual scientists have some shortcomings and confinements in their application. In order to overcome such restrictions and to bring the state of the art scientists of thermal modelling together a working group to define a “universal” thermal climate index (UTCI) has been founded, backed and driven by an own commission of the International Society of Biometeorology. This working group has developed a comprehensive open source tool to calculate UTCI for the assessment of outdoor thermal environments for biometeorological applications (see the IJBM special issue 56 (2012) on UTCI).