The role of event attribution in compound flood-related displacement and anthropogenic climate change

Author(s):  
Lisa Thalheimer ◽  
Jesus Crespo Cuaresma ◽  
Reinhard Mechler ◽  
Raya Muttarak ◽  
Sihan Li ◽  
...  

<p>Compound events lead to substantial risks to societies around the globe. As climate change is increasingly exacerbating the intensity and frequency of many hazards in vulnerable regions, ex situ responses to climate change including human mobility and displacement are starkly moving into the spotlight. Whilst proactive migration is often used as an adaptation response to the impact of climate and weather events, reactive migration following unprecedented climatic shocks is often involuntarily and can seriously disrupt livelihoods and undermine human security. The extent to which human mobility (here, measured by internal displacement) can be attributed to extreme weather and compound events and in turn, whether and to what extent extreme weather events and consequently human mobility can be attributed to anthropogenic climate change, has been largely unexplored. </p><p>Applying a framework based on probabilistic event attribution (PEA) of extreme weather events, we investigate, for the first time, human mobility responses attributed to anthropogenic climate change along a causal chain from anthropogenic climate change and changing frequencies and intensities of extreme weather and climate events to human mobility outcomes. We use the April 2020 extreme precipitation which lead to flooding and associated displacement in Somalia as a feasibility study to present the state of the art of this method. Our attribution model investigates two locations: First, we attribute extreme precipitation at the origin region of the extreme event to then attribute the resulting flood event in the displacement impact region. Event though the analysis shows no attributable link to anthropogenic climate change, our method advances the field of climate impact research regarding statistical approaches, model development and evaluation. For our feasibility study, we also find that sparsity of climate observations reveal one of many reasons for a lack of a climate change signal, which suggests an application of our model to other climate event contexts is needed to further test our method.</p>


2019 ◽  
Vol 25 (4) ◽  
pp. 189-190
Author(s):  
Kent E. Pinkerton ◽  
Emily Felt ◽  
Heather E. Riden

Abstract. A warming climate has been linked to an increase in the frequency and severity of extreme weather events, including heat and cold waves, extreme precipitation, and wildfires. This increase in extreme weather results in increased risks to the health and safety of farmworkers. Keywords: Climate change, Extreme weather, Farmworkers, Global warming, Health and safety.



2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Michael E. Mann ◽  
Stefan Rahmstorf ◽  
Kai Kornhuber ◽  
Byron A. Steinman ◽  
Sonya K. Miller ◽  
...  


Author(s):  
Sarah E Perkins-Kirkpatrick ◽  
Daithi Stone ◽  
Dann M. Mitchell ◽  
Suzanne M. Rosier ◽  
Andrew David King ◽  
...  

Abstract Investigations into the role of anthropogenic climate change in extreme weather events are now starting to extend into analysis of anthropogenic impacts on non-climate (e.g. socio-economic) systems. However, care needs to be taken when making this extension, because methodological choices regarding extreme weather attribution can become crucial when considering the events’ impacts. The fraction of attributable risk (FAR) method, useful in extreme weather attribution research, has a very specific interpretation concerning a class of events, and there is potential to misinterpret results from weather event analyses as being applicable to specific events and their impact outcomes. Using two case studies of meteorological extremes and their impacts, we argue that FAR is not generally appropriate when estimating the magnitude of the anthropogenic signal behind a specific impact. Attribution assessments on impacts should always be carried out in addition to assessment of the associated meteorological event, since it cannot be assumed that the anthropogenic signal behind the weather is equivalent to the signal behind the impact because of lags and nonlinearities in the processes through which the impact system reacts to weather. Whilst there are situations where employing FAR to understand the climate change signal behind a class of impacts is useful (e.g. “system breaking” events), more useful results will generally be produced if attribution questions on specific impacts are reframed to focus on changes in the impact return value and magnitude across large samples of factual and counterfactual climate model and impact simulations. We advocate for constant interdisciplinary collaboration as essential for effective and robust impact attribution assessments.



2018 ◽  
Vol 99 (8) ◽  
pp. 1557-1568 ◽  
Author(s):  
Julien Cattiaux ◽  
Aurélien Ribes

AbstractWeather extremes are the showcase of climate variability. Given their societal and environmental impacts, they are of great public interest. The prevention of natural hazards, the monitoring of single events, and, more recently, their attribution to anthropogenic climate change constitute key challenges for both weather services and scientific communities. Before a single event can be scrutinized, it must be properly defined; in particular, its spatiotemporal characteristics must be chosen. So far, this definition is made with some degree of arbitrariness, yet it might affect conclusions when explaining an extreme weather event from a climate perspective. Here, we propose a generic road map for defining single events as objectively as possible. In particular, as extreme events are inherently characterized by a small probability of occurrence, we suggest selecting the space–time characteristics that minimize this probability. In this way, we are able to automatically identify the spatiotemporal scale at which the event has been the most extreme. According to our methodology, the European heat wave of summer 2003 would be defined as a 2-week event over France and Spain and the Boulder, Colorado, intense rainfall of September 2013 a 5-day local event. Importantly, we show that in both cases, maximizing the rarity of the event does not maximize (or minimize) its fraction of attributable risk to anthropogenic climate change.



2020 ◽  
Vol 10 (1) ◽  
Author(s):  
R. M. B. Harris ◽  
F. Loeffler ◽  
A. Rumm ◽  
C. Fischer ◽  
P. Horchler ◽  
...  


2018 ◽  
Author(s):  
Junxi Zhang ◽  
Yang Gao ◽  
Kun Luo ◽  
L. Ruby Leung ◽  
Yang Zhang ◽  
...  

Abstract. The Weather Research and Forecasting model with Chemistry (WRF/Chem) was used to study the effect of extreme weather events on ozone in US for historical (2001–2010) and future (2046–2055) periods under RCP8.5 scenario. During extreme weather events, including heat waves, atmospheric stagnation, and their compound events, ozone concentration is much higher compared to non-extreme events period. A striking enhancement of effect during compound events is revealed when heat wave and stagnation occur simultaneously and both high temperature and low wind speed promote the production of high ozone concentrations. In regions with high emissions, compound extreme events can shift the high-end tails of the probability density functions (PDFs) of ozone to even higher values to generate extreme ozone episodes. In regions with low emissions, extreme events can still increase high ozone frequency but the high-end tails of the PDFs are constrained by the low emissions. Despite large anthropogenic emission reduction projected for the future, compound events increase ozone more than the single events by 10 % to 13 %, comparable to the present, and high ozone episodes are not eliminated. Using the CMIP5 multi-model ensemble, the frequency of compound events is found to increase more dominantly compared to the increased frequency of single events in the future over the US, Europe, and China. High ozone episodes will likely continue in the future due to increases in both frequency and intensity of extreme events, despite reductions in anthropogenic emissions of its precursors. However, the latter could reduce or eliminate extreme ozone episodes, so improving projections of compound events and their impacts on extreme ozone may better constrain future projections of extreme ozone episodes that have detrimental effects on human health.



2020 ◽  
Vol 12 (3) ◽  
pp. 435-452 ◽  
Author(s):  
Nadine Fleischhut ◽  
Stefan M. Herzog ◽  
Ralph Hertwig

AbstractAs climate change unfolds, extreme weather events are on the rise worldwide. According to experts, extreme weather risks already outrank those of terrorism and migration in likelihood and impact. But how well does the public understand weather risks and forecast uncertainty and thus grasp the amplified weather risks that climate change poses for the future? In a nationally representative survey (N = 1004; Germany), we tested the public’s weather literacy and awareness of climate change using 62 factual questions. Many respondents misjudged important weather risks (e.g., they were unaware that UV radiation can be higher under patchy cloud cover than on a cloudless day) and struggled to connect weather conditions to their impacts (e.g., they overestimated the distance to a thunderstorm). Most misinterpreted a probabilistic forecast deterministically, yet they strongly underestimated the uncertainty of deterministic forecasts. Respondents with higher weather literacy obtained weather information more often and spent more time outside but were not more educated. Those better informed about climate change were only slightly more weather literate. Overall, the public does not seem well equipped to anticipate weather risks in the here and now and may thus also fail to fully grasp what climate change implies for the future. These deficits in weather literacy highlight the need for impact forecasts that translate what the weather may be into what the weather may do and for transparent communication of uncertainty to the public. Boosting weather literacy may help to improve the public’s understanding of weather and climate change risks, thereby fostering informed decisions and mitigation support.



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