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When Do Losses Count?
Six Fallacies of Natural Hazards Loss Data
Current global and national databases that monitor losses from natural hazards suffer from a number of limitations, which in turn lead to misinterpretation and fallacies concerning the “truthfulness” of hazard loss data. These biases often go undetected by end users and are generally a product of the type of information stored in loss databases and how they are constructed. This paper highlights some common shortcomings and root causes for data misinterpretation by asking what biases are present in existing databases and how these then manifest themselves in actual loss figures. For illustrative purposes, four widely used, nonproprietary, Web-based hazard databases are examined: the international Emergency Events Database (EM-DAT), the international Natural Hazards Assessment Network (NATHAN), the Spatial Hazard Events and Losses Database for the United States (SHELDUS), and the National Weather Service's Storm Events. We identify six general biases: hazard bias, temporal bias, threshold bias, accounting bias, geographic bias, and systemic bias. To achieve resilient and sustainable communities, we need systematic and comprehensive inventories at the national as well as international level, and data that are temporally and geographically comparable.
Current global and national databases that monitor losses from natural hazards suffer from a number of limitations, which in turn lead to misinterpretation and fallacies concerning the “truthfulness” of hazard loss data. These biases often go undetected by end users and are generally a product of the type of information stored in loss databases and how they are constructed. This paper highlights some common shortcomings and root causes for data misinterpretation by asking what biases are present in existing databases and how these then manifest themselves in actual loss figures. For illustrative purposes, four widely used, nonproprietary, Web-based hazard databases are examined: the international Emergency Events Database (EM-DAT), the international Natural Hazards Assessment Network (NATHAN), the Spatial Hazard Events and Losses Database for the United States (SHELDUS), and the National Weather Service's Storm Events. We identify six general biases: hazard bias, temporal bias, threshold bias, accounting bias, geographic bias, and systemic bias. To achieve resilient and sustainable communities, we need systematic and comprehensive inventories at the national as well as international level, and data that are temporally and geographically comparable.
The state of knowledge regarding trends and an understanding of their causes is presented for a specific subset of extreme weather and climate types. For severe convective storms (tornadoes, hailstorms, and severe thunderstorms), differences in time and space of practices of collecting reports of events make using the reporting database to detect trends extremely difficult. Overall, changes in the frequency of environments favorable for severe thunderstorms have not been statistically significant. For extreme precipitation, there is strong evidence for a nationally averaged upward trend in the frequency and intensity of events. The causes of the observed trends have not been determined with certainty, although there is evidence that increasing atmospheric water vapor may be one factor. For hurricanes and typhoons, robust detection of trends in Atlantic and western North Pacific tropical cyclone (TC) activity is significantly constrained by data heterogeneity and deficient quantification of internal variability. Attribution of past TC changes is further challenged by a lack of consensus on the physical link- ages between climate forcing and TC activity. As a result, attribution of trends to anthropogenic forcing remains controversial. For severe snowstorms and ice storms, the number of severe regional snowstorms that occurred since 1960 was more than twice that of the preceding 60 years. There are no significant multidecadal trends in the areal percentage of the contiguous United States impacted by extreme seasonal snowfall amounts since 1900. There is no distinguishable trend in the frequency of ice storms for the United States as a whole since 1950.
The state of knowledge regarding trends and an understanding of their causes is presented for a specific subset of extreme weather and climate types. For severe convective storms (tornadoes, hailstorms, and severe thunderstorms), differences in time and space of practices of collecting reports of events make using the reporting database to detect trends extremely difficult. Overall, changes in the frequency of environments favorable for severe thunderstorms have not been statistically significant. For extreme precipitation, there is strong evidence for a nationally averaged upward trend in the frequency and intensity of events. The causes of the observed trends have not been determined with certainty, although there is evidence that increasing atmospheric water vapor may be one factor. For hurricanes and typhoons, robust detection of trends in Atlantic and western North Pacific tropical cyclone (TC) activity is significantly constrained by data heterogeneity and deficient quantification of internal variability. Attribution of past TC changes is further challenged by a lack of consensus on the physical link- ages between climate forcing and TC activity. As a result, attribution of trends to anthropogenic forcing remains controversial. For severe snowstorms and ice storms, the number of severe regional snowstorms that occurred since 1960 was more than twice that of the preceding 60 years. There are no significant multidecadal trends in the areal percentage of the contiguous United States impacted by extreme seasonal snowfall amounts since 1900. There is no distinguishable trend in the frequency of ice storms for the United States as a whole since 1950.
