Attribution of Extreme Weather Events in the Context of Climate Change (2016) / Chapter Skim
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2 Framing
2 Framing
Pages 27-46
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From page 27... ...
The interest in extreme events is typically driven by their impacts on society, which raises further framing issues when non-climate anthropogenic factors come into play. Finally, because the choice of which events to study is 27
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From page 28... ...
For extreme events, for which the probability of an event is generally low, climate change (which is always present in the factual climate) cannot be a sufficient cause.
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, f while on the other hand, the entire climate system, and therefore all extreme events, are being affected by climate change (as discussed further below) , thereby obviating the question.
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In studies of the 2010 Russian heat wave, for example, one study concluded that the event was largely natural because the temperature anomalies were greatly in excess of those explainable by long-term trends (Dole et al., 2011) , whereas another concluded that the anthropogenic influence was significant because long-term climate change, though small, greatly increased the probability of exceeding specified temperature thresholds (Rahmstorf and Coumou, 2011)
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corresponds to a large change in likelihood arising from climate change (from a 99-year return time to a 33-year return time, indicated by the horizontal arrow in the top figure and the vertical arrow in the bottom figure) , but to a small (compared to the overall anomaly of 2010 with respect to average July conditions [dashed line]
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From page 32... ...
For example, studies of the recent California drought focusing on precipitation deficit have tended to find no discernible anthropogenic influence (Seager et al., 2015) , while those focusing on a combination of precipitation deficit and high temperature (which affects evaporation)
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show that the probability of necessary causation is the maximum of 0 and the calculated FAR, and therefore it will be zero in cases of decreasing likelihood. Hence, the aggregation of attribution results using this metric would provide a biased overview of human influences on extreme events.
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From page 34... ...
For instance, a member of the public is apt to be familiar with a statement such as "Smoking increases the probability of lung cancer by a factor of X." Although the RR does not have the same causal interpretation as the FAR ( annart et al., 2015a) , that may not be disadvantageous if, as suggested earlier, the H probabilistic causal interpretation of individual extreme events (as opposed to collections of events)
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From page 35... ...
The Null Hypothesis Estimating the unconditional probabilities of very rare events is extremely challenging because of observational and model limitations, and it is difficult to quantify the uncertainties in the calculations. In addition, it becomes more difficult to discern human influence at smaller spatio-temporal scales (Angelil et al., 2014; Bindoff et al., 2013; Fischer et al., 2013)
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From page 36... ...
that are known to be important in altering the likelihood of extreme events. One can go even further and condition on the specific weather situation (see Chapter 3)
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. Probabilistic Formulation The trade-off involved in conditioning is that it improves the signal-to-noise ratio of the anthropogenic influence while providing a more realistic simulation of the event, but a full estimate of the change in likelihood of the event would require an explicit estimate of the change in the probability or intensity of the anomalous climatic or weather state on which the inference is conditioned (see below)
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Pc ( E , N ) to get an unconditional RR concerning the joint occurrence of the event and El Niño in the factual and counterfactual worlds.
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From page 39... ...
. OTHER FACTORS AFFECTING IMPACTS OF EXTREME EVENTS Attribution of extreme events is primarily anchored in discussions about anthropogenic climate change, yet many extreme events also are affected by other types of anthropogenic processes, which raise additional framing issues in terms of event impacts.
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greatly increases the costs associated with fires and firefighting. Perhaps the best example of the intersection of land use decisions and extreme events is in coastal areas: Not only have people made major changes to the morphology of coasts that in some cases exacerbate the impacts of coastal storms, many of the major cities around the globe are located in or near coastal areas as well.
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From page 41... ...
Therefore, attribution studies should clearly distinguish such climate factors from the effects of climate change, and the results should be framed accordingly. Apart from more accurately isolating the anthropogenic climate change effect, this also has the benefit of identifying risk factors that could potentially be mitigated at the local level.
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From page 42... ...
Potential biases in attribution results are of concern for collective assessment of anthropogenic influence on extreme events, but they may not be relevant if the focus is on a climatological understanding of events or on the implications of attribution analyses for adaptation and planning in specific contexts. Some of the issues discussed below also arise in meta-analysis in the medical literature, in which the goal is to improve statistical power by analyzing results from multiple studies that assess the same scientific question.
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From page 43... ...
Occurrence bias could result in a scientific literature that suggests that extreme events are generally becoming more common because of anthropogenic influence. Suppose there are 100 event classes (across regions and types of events)
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Further framing issues arise for impacts of extreme events because other anthropogenic factors (e.g., land use) apart from climate change often significantly affect the magnitude of impacts.
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From page 45... ...
Such selection biases interfere with the ability to draw general conclusions about anthropogenic influence on extreme events collectively. Overall, it is useful to perform event attribution with all factors explicitly assessed and discussed: thermodynamic and dynamic aspects of anthropogenic climate change, non-climate anthropogenic factors, and natural variability.
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