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München, Germany

Munich Reinsurance Company

München, Germany
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Sander J.,German Aerospace Center | Sander J.,Munich Reinsurance Company | Eichner J.F.,Munich Reinsurance Company | Faust E.,Munich Reinsurance Company | Steuer M.,Munich Reinsurance Company
Weather, Climate, and Society | Year: 2013

Thunderstorm-related normalized economic and insured losses in the United States east of the Rockies from the period 1970-2009 (March-September) exhibit higher peaks and greater variability in the last two decades than in the preceding two decades. To remove the bias from increasingly detected losses over time due to newly built-up locations, only large events that incurred normalized losses of at least $250 million (U.S. dollars) economically ($150 million insured) were selected. These are multistate damage events that are unlikely to have been missed at any time within the analysis period, thus providing for homogeneity of the events covered. Those losses, if aggregated, account for the major proportion (∼80%) of all thunderstormrelated losses in the period 1970-2009. This study demonstrates that the pattern of variability in the time series of these losses can be seen as a reflection ("fingerprint") of the temporal variability in severe thunderstorm forcing. The meteorological information on forcing is inferred from NCEP-NCAR reanalysis data. No final attribution of the climatic variability identified in thunderstorm forcing and losses - either to natural climate variability or to anthropogenic climate change - can be conclusively arrived at in this study because of the chosen methodology. Nevertheless, the expected impacts of anthropogenic climate change on the forcing of convective storms appear consistent with these findings. © 2013 American Meteorological Society.


Schmidt S.,Humboldt University of Berlin | Kemfert C.,German Institute for Economic Research | Hoppe P.,Munich Reinsurance Company
Regional Environmental Change | Year: 2010

Tropical cyclones that make landfall on the coast of the USA are causing increasing economic losses. It is assumed that the increase in losses is largely due to socio-economic developments, i.e. growing wealth and greater settlement of exposed areas. However, it is also thought that the rise in losses is caused by increasing frequency of severe cyclones resulting from climate change, whether due to natural variability or as a result of human activity. The object of this paper is to investigate how sensitive the losses are to socio-economic changes and climate changes and how these factors have evolved over the last 50 years. We will then draw conclusions about the part the factors concerned play in the observed increase in losses. For analysis purposes, storm loss is depicted as a function of the value of material assets affected by the storm (the capital stock) and storm intensity. The findings show the increase in losses due to socio-economic changes to have been approximately three times greater than that due to climate-induced changes. © Springer-Verlag 2009.


Jongman B.,VU University Amsterdam | Winsemius H.C.,Deltares | Aerts J.C.J.H.,VU University Amsterdam | Coughlan De Perez E.,VU University Amsterdam | And 6 more authors.
Proceedings of the National Academy of Sciences of the United States of America | Year: 2015

The global impacts of river floods are substantial and rising. Effective adaptation to the increasing risks requires an in-depth understanding of the physical and socioeconomic drivers of risk. Whereas the modeling of flood hazard and exposure has improved greatly, compelling evidence on spatiotemporal patterns in vulnerability of societies around the world is still lacking. Due to this knowledge gap, the effects of vulnerability on global flood risk are not fully understood, and future projections of fatalities and losses available today are based on simplistic assumptions or do not include vulnerability. We show for the first time (to our knowledge) that trends and fluctuations in vulnerability to river floods around the world can be estimated by dynamic high-resolution modeling of flood hazard and exposure. We find that rising per-capita income coincided with a global decline in vulnerability between 1980 and 2010, which is reflected in decreasing mortality and losses as a share of the people and gross domestic product exposed to inundation. The results also demonstrate that vulnerability levels in low- and high-income countries have been converging, due to a relatively strong trend of vulnerability reduction in developing countries. Finally, we present projections of flood losses and fatalities under 100 individual scenario and model combinations, and three possible global vulnerability scenarios. The projections emphasize that materialized flood risk largely results from human behavior and that future risk increases can be largely contained using effective disaster risk reduction strategies. © 2015, National Academy of Sciences. All rights reserved.


PubMed | Deltares, Red Cross, VU University Amsterdam and Munich Reinsurance Company
Type: Journal Article | Journal: Proceedings of the National Academy of Sciences of the United States of America | Year: 2015

The global impacts of river floods are substantial and rising. Effective adaptation to the increasing risks requires an in-depth understanding of the physical and socioeconomic drivers of risk. Whereas the modeling of flood hazard and exposure has improved greatly, compelling evidence on spatiotemporal patterns in vulnerability of societies around the world is still lacking. Due to this knowledge gap, the effects of vulnerability on global flood risk are not fully understood, and future projections of fatalities and losses available today are based on simplistic assumptions or do not include vulnerability. We show for the first time (to our knowledge) that trends and fluctuations in vulnerability to river floods around the world can be estimated by dynamic high-resolution modeling of flood hazard and exposure. We find that rising per-capita income coincided with a global decline in vulnerability between 1980 and 2010, which is reflected in decreasing mortality and losses as a share of the people and gross domestic product exposed to inundation. The results also demonstrate that vulnerability levels in low- and high-income countries have been converging, due to a relatively strong trend of vulnerability reduction in developing countries. Finally, we present projections of flood losses and fatalities under 100 individual scenario and model combinations, and three possible global vulnerability scenarios. The projections emphasize that materialized flood risk largely results from human behavior and that future risk increases can be largely contained using effective disaster risk reduction strategies.


Grune L.,University of Bayreuth | Pannek J.,Ludwig Maximilians University of Munich | Seehafer M.,Munich Reinsurance Company | Worthmann K.,University of Bayreuth
Proceedings of the IEEE Conference on Decision and Control | Year: 2012

For nonlinear discrete time systems satisfying a controllability condition, we present a stability condition for model predictive control without stabilizing terminal constraints or costs. The condition is given in terms of an analytical formula which can be employed in order to determine a prediction horizon length for which asymptotic stability or a performance guarantee is ensured. Based on this formula a sensitivity analysis with respect to the prediction and the possibly time varying control horizon is carried out. © 2012 IEEE.


Rumpf J.,University of Ulm | Weindl H.,Munich Reinsurance Company | Faust E.,Munich Reinsurance Company | Schmidt V.,University of Ulm
Tellus, Series A: Dynamic Meteorology and Oceanography | Year: 2010

The influence of sea surface temperature (SST) on the locations of the genesis and of landfall of tropical cyclones in the North Atlantic is analyzed. For that purpose, these locations are calculated from HURDAT and split into two disjoint subsets according to whether SST in the North Atlantic was above or below average in the year the corresponding storms occurred. Landfalls are investigated separately for the groups of cyclones categorized as tropical storms, minor hurricanes, or major hurricanes at the moment of landfall. The locations are considered realizations of inhomogeneous Poisson point processes, and the corresponding density functions are estimated with kernel estimation methods. In this way, any spatial structure inherent in the data is taken into account. These density functions are then compared with Monte Carlo methods from spatial statistics, which allows the detection of areas of statistically significant differences in the two sets with high and low SST, respectively. Results show many such areas, which is of relevance for the insurance industry and mathematical modelling of cyclones, as well as for decision support during the preparation for natural disasters. © 2010 The Authors Journal compilation © 2010 Blackwell Munksgaard.


Kriesche B.,University of Ulm | Weindl H.,Munich Reinsurance Company | Smolka A.,Munich Reinsurance Company | Schmidt V.,University of Ulm
Natural Hazards | Year: 2014

We consider a spatial stochastic model for the simulation of tropical cyclone tracks, which has recently been introduced. Cyclone tracks are represented as labeled polygonal lines, which are described by the movement directions, translational speeds, and wind speeds of the cyclones in regular 6-h intervals. In the present paper, we compare return levels for wind speeds of historically observed cyclone tracks with those generated by the simulator, where a mismatch is shown for most of the considered coastal regions. To adjust this discrepancy, we develop a stochastic algorithm for acceptance and rejection of simulated cyclone tracks with landfall. It is based on the fact that the locations, translational speeds, and wind speeds of cyclones at landfall constitute three-dimensional Poisson point processes, which are a basic model type in stochastic geometry. Due to that, a well-known thinning property of Poisson processes can be applied. This means that to each simulated cyclone, an acceptance probability is assigned, which is higher for cyclones with suitable landfall characteristics and lower for implausible ones. More intuitively, the algorithm comprises the simulation of a more comprehensive cyclone event set than needed and the random selection of those tracks that best match historical observations at landfall. A particular advantage of our algorithm is its applicability to multiple landfalls, i.e., to cyclones that successively make landfall at two geographically distinct coastlines, which is the most relevant case in applications. It turns out that the extended simulator provides a much better accordance between landfall characteristics of historical and simulated cyclone tracks. © 2014 Springer Science+Business Media Dordrecht.


Kron W.,Munich Reinsurance Company
Water Policy | Year: 2015

Various disasters in recent decades have confirmed that the risk from water-related events has been increasing significantly worldwide. Among those events are tsunamis, storm surges, river floods, flash floods, mass movements and droughts. The driving factors of this risk are the unabated increase in global population, the concentration of people in high-risk areas such as coasts, flood plains and hillsides, the rise in vulnerability of assets, infrastructure and social systems, and the consequences of environmental and climatic changes. Risk reduction requires general awareness at all levels of society and a partnership between the public sector, the people concerned and the insurance industry. Structural and nonstructural precautionary measures are always cheaper in the long run than paying losses. Overall economic consequences are significantly less severe in societies with a high insurance penetration. © IWA Publishing 2015.


Kron W.,Munich Reinsurance Company
Natural Hazards | Year: 2013

No other region is more threatened by natural perils than coasts. Fierce winds, storm surges, large waves and tsunamis expend their destructive energy when they reach the coastline. Constituting, in many cases, the boundary between continental plates, coasts experience earthquakes and volcanic eruptions more frequently. The changing climate poses the threat of sea level rise. Most global trade crosses the oceans; ports are the entry and exit points of a nation's trade. As a consequence, coasts attract people, businesses and industries. Some coastal regions rank among the top places in the world in terms of population and value accumulation. Enormous catastrophe loss potentials have been created and are increasing. Risk is the result of a natural hazard, the values at risk and their vulnerability. Living with and reducing the risk requires awareness at all levels of society and partnership between the public authorities, the people and enterprises concerned, and the financial sector. Great natural events are not avoidable, great disasters are. Catastrophes are not only products of chance but also the outcome of the interaction between political, financial, social, technical and natural circumstances. Effective safeguards are both achievable and indispensable, but they will never provide complete protection. In order to manage the risks faced by a society, we have to be aware of that. © 2012 Springer Science+Business Media B.V.


Wirtz A.,Munich Reinsurance Company | Kron W.,Munich Reinsurance Company | Low P.,Munich Reinsurance Company | Steuer M.,Munich Reinsurance Company
Natural Hazards | Year: 2014

Hundreds of natural catastrophes occur worldwide every year-there were 780 loss events per year on average over the last 10 years. Since 1980, these disasters have claimed over two million lives and caused losses worth US$ 3,000 billion. The deadliest disasters were caused by earthquakes: the tsunami following the Sumatra quake (2004) and the Haiti earthquake (2010) claimed more than 220,000 lives each. The Great East Japan Earthquake of 11 March 2011 was the costliest natural disaster of all times, with total losses of US$ 210 billion. Hurricane Katrina, in 2005, was the second costliest disaster, with total losses of US$ 140 billion (in 2010 values). To ensure that high-quality natural disaster analyses can be performed, the data have to be collected, checked and managed with a high degree of expertise and professionality. Scientists, governmental and non-governmental organisations and the finance industry make use of global databases that contain losses attributable to natural catastrophes. At present, there are three global and multi-peril loss databases: NatCatSERVICE (Munich Re), Sigma (Swiss Re) and EM-Dat (Centre for Research on the Epidemiology of Disasters). They are supplemented by numerous databases focusing on national or regional issues, certain hazards and specific sectors. This paper outlines the criteria and definitions relating to how global and multi-peril databases are operated, and the efforts being made to ensure consistent and internationally recognised standards of data management. In addition, it presents the concept and methodology underlying the NatCatSERVICE database, and points out the many challenges associated with data acquisition and data management. © 2012 Springer Science+Business Media B.V.

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