The absence of trends in normalized disaster burden indicators appears to be largely consistent with the absence of trends in extreme weather events. This conclusion is more qualitative for the number of people killed. As a consequence, vulnerability is also largely stable over the period of analysis.The top line conclusion here is not surprising, though it is interesting because it uses independent methods on largely independent data. It is consistent with previous data and analyses (e.g., Bouwer 2011, Neumayer and Bartel 2011, Mohleji and Pielke 2014) as well as with the conclusions of the recent IPCC assessments (SREX and AR5).
What is perhaps most interesting about this new paper is their discussion of vulnerability. Some have argued that our methodological inability to fully account for possible changes in vulnerability to losses over time may mask a climate change signal in the data. (It's gotta be there somewhere!) This line of argument has always been suspect, because there are not relevant trends in phenomena such as floods and hurricanes which would lead to an expectation of increasing normalized losses.
Visser et al. take this issue on and offer several explanations as to why vulnerability does not mask any hidden signals:
Firstly, global disaster management initiatives have only recently been put in place. The Hyogo Framework for Action (HFA) was adopted by 168 Member States of the United Nations in 2005 to take action to reduce vulnerabilities and risks to disasters (UNISDR, 2011). Although these highly important efforts will certainly pay off in the near future, it is unclear whether they are reflected in the sample period chosen for this study. Similar conclusions are drawn in IPCC (2014). . .In short, those who claim that a signal of human caused-climate change is somehow hidden in the disaster loss record are engaging in a bit of unjustified wishful thinking. The data and evidence says otherwise.
Secondly, it is unclear to what extent adaptation measures work in practice. Heffernan (2012) argues that many countries, and even the richest, are ill-prepared for weather extremes. As an example, he names Hurricane Sandy, which wreaked a loss of 50 billion USD along the northeast coast of the US in 2012. As for early warning systems, Heffernan states that not all systems are functioning well. For example, in 2000, Mozambique was hit by a flood worse than any in its history, and the event was not at all anticipated. Warnings of above-average rainfall came too late and failed to convey the magnitude of the coming flood.
Thirdly, a positive trend in vulnerability may be offset by the increasing number of people moving from rural to urban environments, often situated in at-risk areas (UN 2012). Since many large cities lie along coastlines, these movements will make people more vulnerable to land-falling hurricanes (Pielke et al. 2008), coastal flooding and heatwaves (due the urban heat island effect). With regard to economic losses, Hallegatte (2011) argues that these migration movements may have caused disaster losses to grow faster than wealth.
Fourthly, it is unclear how political tensions and violent conflicts have evolved over large regional scales since 1980. On the one hand, Theisen et al. (2013) show that the number of armed conflicts and the number of battle deaths have decreased slightly at the global scale since 1980. On the other hand, these methods are rather crude as far as covering all aspects of political tensions are concerned (Leaning and Guha-Sapir et al. 2013).
We conclude that quantitative information on time-varying vulnerability patterns is lacking. More qualitatively, we judge that a stable vulnerability V t, as derived in this study, is not in contrast with estimates in the literature.
The bottom line? Once again, we see further reinforcement for the conclusion that there is no detectable evidence of a role for human-caused climate change in increasing disaster losses. In plain English: Disaster losses have been increasing, but it is not due to climate change.