Comment on 'High-income does not protect against hurricane losses'

Geiger et al (Environ. Res. Lett. 2016 11 084012) employ two functional relationships to characterize hurricane damage in the USA—either based on GDP (one exponent) or on per capita GDP and population (two exponents). From the Akaike Information Criterion the authors cannot reject the former kind in favor of the latter. The different approaches, however, lead to divergent projections of future hurricane losses. In this comment, we argue that there is no rigorous evidence in [1] to give preference to one or the other approach, and the conclusion that high-income does not protect against hurricane losses needs to be revisited. As a perspective, it needs to be mentioned that the previously published relationship between GDP and population could unify both approaches

Selective preservation of organic matter in marine environments; processes and impact on the sedimentary record

© The Authors, 2010. This article is distributed under the terms of the Creative Commons Attribution 3.0 License. The definitive version was published in Biogeosciences 7 (2010): 483-511, doi: 10.5194/bg-7-483-2010The present paper is the result of a workshop sponsored by the DFG Research Center/Cluster of Excellence MARUM "The Ocean in the Earth System", the International Graduate College EUROPROX, and the Alfred Wegener Institute for Polar and Marine Research. The workshop brought together specialists on organic matter degradation and on proxy-based environmental reconstruction. The paper deals with the main theme of the workshop, understanding the impact of selective degradation/preservation of organic matter (OM) in marine sediments on the interpretation of the fossil record. Special attention is paid to (A) the influence of the molecular composition of OM in relation to the biological and physical depositional environment, including new methods for determining complex organic biomolecules, (B) the impact of selective OM preservation on the interpretation of proxies for marine palaeoceanographic and palaeoclimatic reconstruction, and (C) past marine productivity and selective preservation in sediments. It appears that most of the factors influencing OM preservation have been identified, but many of the mechanisms by which they operate are partly, or even fragmentarily, understood. Some factors have not even been taken carefully into consideration. This incomplete understanding of OM breakdown hampers proper assessment of the present and past carbon cycle as well as the interpretation of OM based proxies and proxies affected by OM breakdown. To arrive at better proxy-based reconstructions "deformation functions" are needed, taking into account the transport and diagenesis-related molecular and atomic modifications following proxy formation. Some emerging proxies for OM degradation may shed light on such deformation functions. The use of palynomorph concentrations and selective changes in assemblage composition as models for production and preservation of OM may correct for bias due to selective degradation. Such quantitative assessment of OM degradation may lead to more accurate reconstruction of past productivity and bottom water oxygenation. Given the cost and effort associated with programs to recover sediment cores for paleoclimatological studies, as well as with generating proxy records, it would seem wise to develop a detailed sedimentological and diagenetic context for interpretation of these records. With respect to the latter, parallel acquisition of data that inform on the fidelity of the proxy signatures and reveal potential diagenetic biases would be of clear value.We acknowledge generous financial support by the DFG Research Center/Cluster of Excellence MARUM “The Ocean in the Earth System”, the International Graduate College EUROPROX and the Alfred Wegener Institute for Polar and Marine Research enabling the realisation of the “Workshop on Selective Preservation of Organic Matter: Processes and Impact on the Fossil Record” which formed the basis of this paper. GJMV acknowledges support by the German Science Foundation (DFG grant VE486/2)

Projections of global warming-induced impacts on winter storm losses in the German private household sector

We present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statistical-dynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971–2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6–35 % for 2011–2040, of 20–30 % for 2041–2070, and of 40–55 % for 2071–2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses

Research and Design of a Routing Protocol in Large-Scale Wireless Sensor Networks

无线传感器网络，作为全球未来十大技术之一，集成了传感器技术、嵌入式计算技术、分布式信息处理和自组织网技术，可实时感知、采集、处理、传输网络分布区域内的各种信息数据，在军事国防、生物医疗、环境监测、抢险救灾、防恐反恐、危险区域远程控制等领域具有十分广阔的应用前景。 本文研究分析了无线传感器网络的已有路由协议，并针对大规模的无线传感器网络设计了一种树状路由协议，它根据节点地址信息来形成路由，从而简化了复杂繁冗的路由表查找和维护，节省了不必要的开销，提高了路由效率，实现了快速有效的数据传输。 为支持此路由协议本文提出了一种自适应动态地址分配算——ADAR（AdaptiveDynamicAddre...As one of the ten high technologies in the future, wireless sensor network, which is the integration of micro-sensors, embedded computing, modern network and Ad Hoc technologies, can apperceive, collect, process and transmit various information data within the region. It can be used in military defense, biomedical, environmental monitoring, disaster relief, counter-terrorism, remote control of haz...学位：工学硕士院系专业：信息科学与技术学院通信工程系_通信与信息系统学号：2332007115216

Über Schadensfunktionen zur Abschätzung von Sturmschäden und deren Generalisierung für klimabezogene Naturgefahren

Globally the number of climate-related disasters and the associated loss figures are on the rise. The changing climate as well as the increasing exposure in terms of people and assets could induce unprecedented damage levels. Damage functions constitute the crucial link between hazard, exposure and the resulting damage. As such, they provide vulnerability and damage-cost information, which are essential for disaster risk reduction and for the evaluation of climate-change adaptation options. With this purpose in mind, the overarching goal of the work at hand is to contribute to the fundamental understanding of damage functions and to provide systematic and versatile damage assessment. Only few damage functions are available for a regional damage assessment. Data scarcity, for example, is a major obstacle for the development of storm damage functions. For the work at hand, newly available data on German storm loss permit a fresh look at the wind--loss relation. Based on these data, a novel storm damage function is developed and compared against existing approaches. The results show that the wind--loss relation is well described by power-law curves with exponents that are considerably higher than previously expected. While the steepness of the curves at extreme wind speeds is comparable to other damage functions, the novel damage function is capable of predicting damages over a wider range of wind speeds. It is found that the uncertainty of the damage estimates is mainly driven by uncertainty from the wind measurement and approximates to a log-normal uncertainty distribution. Exploring further damage functions beyond the domain of storm damage, analogous approaches are identified for coastal flooding and, schematically, for heat-related mortality. Together, these are formulated as a unified damage function. With its wide applicability the unified approach forms the basis for undertaking a fundamental analysis of uncertainty. Here, in contrast to prior studies, the work at hand puts emphasis on the propagation of uncertainty from the microscale to the macroscale level. The results show that the relevance of intrinsic uncertainties on the microscale level is carried over to the aggregate macroscale level. However, extrinsic sources of uncertainty, such as the aforementioned measurement error of wind speed, dominate overall. In summary, this work delivers multiple contributions to the understanding of damage functions. The novel storm damage function provides improved loss estimates and will help to assess the significance of changes in storm climate. The comparison brings together the rather fragmented research on storm damage functions and sheds light on their performance. Furthermore, the findings suggest a rebuttal of the cubic power-law assumption for macroscale storm loss. Finally, the unified approach for damage estimation facilitates knowledge transfer between various climate-related hazards. As one example, the findings on the relevance of uncertainty sources have broad applicability and may guide future research to reduce the uncertainty of damage estimation. With its interdisciplinary approach, this work has strong relevance to practitioners in the various domains of natural hazards research and in the atmospheric sciences.Im globalen Maßstab sind sowohl die Anzahl als auch die Schäden klimabedingter Naturkatastrophen im Anstieg begriffen. Durch das Zusammenspiel von Klimawandel und zunehmender Exposition von Menschen und Vermögen ist von einem weiterhin zunehmenden Schadensniveau auszugehen. Schadensfunktionen beschreiben die Schnittstelle zwischen den verursachten Schäden, der Exposition, sowie der zugrunde liegenden Naturgefahr. Sie ermöglichen die Abschätzung der Gefährdung sowie des potentiellen Schadenaufwands und liefern somit essentielle Informationen für den Umgang mit künftigen Katastrophenschäden und die Evaluierung von möglichen Anpassungsmaßnahmen. Es ist daher das vorrangige Ziel dieser Arbeit, das grundlegende Verständnis von Schadensfunktionen zu stärken, um eine systematische und übergreifende Schadensabschätzung zu ermöglichen. Schadensfunktionen zur Abschätzung regionaler Schäden sind oft nur eingeschränkt verfügbar, da mangelnde Datenverfügbarkeit ein wesentliches Hindernis für deren Entwicklung und Kalibrierung darstellt. In der vorliegenden Arbeit erlauben neu verfügbare und hoch aufgelöste Sturmschadensdaten einen frischen Blick auf die Relation zwischen Windstärke und Sturmschaden. Auf Grundlage dieser Daten, wird eine neuartige Sturmschadensfunktion entwickelt und mit bestehenden Schadensfunktionen verglichen. Es zeigt sich, dass die Relation des Schadens zum verursachenden Wind einem einfachen Potenzgesetz folgt, dessen Exponent jedoch einen signifikant höheren Wert annimmt als eingangs erwartet. Während der Verlauf der Kurve bei extremen Windgeschwindigkeiten bestehenden Schadensfunktionen ähnelt, lässt die neu entwickelte Schadenfunktion die Abschätzung potentieller Schäden über einen deutlich breiteren Windbereich zu. Bezüglich beobachteter Schäden zeigt sich, dass die Schwankungen der Schadenswerte im Wesentlichen durch Unsicherheit in der Windermittlung begründet sind. Diese Schwankungen lassen sich in guter Näherung durch eine Lognormalverteilung beschreiben. Über das Spektrum von Windschäden hinaus werden analoge Ansätze zur Abschätzung von Schäden durch Küstenfluten sowie, auf schematischer Ebene, zur Modellierung von hitzebedingten Todesfällen identifiziert. Diese Ansätze lassen sich in eine einheitliche mathematische Form bringen und dienen als Basis für die Analyse des Einflusses verschiedener Unsicherheitsfaktoren auf die Schadenshöhe. Hierbei liegt der Schwerpunkt der Unsicherheitsanalyse, im Gegensatz zu vorhergehenden Studien, auf der Transformation von Unsicherheit zwischen der Mikro- und der Makroskala. Die Ergebnisse zeigen, dass die Relevanz mikroskaliger Unsicherheiten auf der Makroebene erhalten bleibt. Schlussendlich dominieren jedoch extrinsische Unsicherheitsquellen, wie die bereits erwähnte Unsicherheit aus der Windermittlung. Insgesamt liefert die vorliegende Arbeit eine Vielfalt von Erkenntnissen für das Verständnis von Schadensfunktionen. So bietet die neuartige Sturmschadensfunktion eine Verbesserung der Schadensprognose und ermöglicht eine genauere Beurteilung der negativen Auswirkungen des Klimawandels. In einem umfassenden Vergleich werden zudem erstmals die bestehenden Ansätze zusammengebracht und quantitativ verglichen. Darüber hinaus sprechen die Ergebnisse für die Widerlegung der Hypothese einer kubischen Wind-Schaden-Relation. Es ist im Weiteren davon auszugehen, dass die Vereinheitlichung klimarelevanter Schadensfunktionen den Wissenstransfer zwischen den verschiedenen Feldern der Naturgefahrenforschung erleichtert. So bildet z.B. die Unsicherheitsanalyse eine Grundlage um künftige Arbeiten zur Reduzierung von Unsicherheiten auf wesentliche Unsicherheitsquellen zu fokussieren. Mit ihrem interdisziplinären Ansatz ist die vorliegende Arbeit von hoher Relevanz für die Naturgefahrenforschung sowie die Atmosphärenwissenschaften

Damage and protection cost curves for coastal flooding at the 600 largest coastal cities within Europe

Costs of coastal flooding and protection are essential information for risk assessment and natural hazards research, but there are few systematic attempts to quantify cost curves beyond the case study level. Here, we present a set of systematically derived damage and protection cost curves for the 600 largest (by area) European coastal cities. The city clusters were identified by an automated cluster algorithm from CORINE land cover 2012 data, following the Urban Morphological Zone (UMZ) definition. The data provides detailed cost curves for direct flood damages at flood heights between 0 and 12 m on a 0.5 m increment. Costs estimates are based on depth damage functions for different land use obtained from the European Joint Research Center. The necessary mapping between land use and land cover is based on Land Use/Cover Area frame Survey (LUCAS) 2015 primary data. The underlying inundation maps were derived from the European Digital Elevation Model (EU-DEM). Furthermore, the data contain curves for the cost of protection at the same heights and increments as the damage curves, assuming no previously installed protection. These curves are available both for a low and high cost scenario and are based on hypothetical protection courses derived from cluster data and inundation maps. All cost estimates are given in Euro and were inflation-adjusted to 2016 price levels. For spatial reference, we include the individual raster tiles depicting the extent of each city cluster. The research leading to these results has received funding from the European Community's Seventh Framework Programme under Grant Agreement No. 308497 (Project RAMSES)