Studying the fingerprints of Human Actions over the Extreme Climatic Events of 2013. AMS Report (by Diego Fdez-Sevilla)
In September 2014 the American Meteorological Society has published a special report presenting assessments of how climate change may have affected the strength and likelihood of individual extreme events.
This publication has already found echo in the news media in which different points from the report are highlighted. It is a matter of concern how biased can be the information being fed into the debate about the impact of anthropogenic development on planetary environmental evolution. Therefore, here I just present from the report the Abstract, Summary and Broader Context followed by the Table of Contents. You can always access the original report following this link.
This report has been selected based on the adding value that represents in the study of the potential impact from anthropogenic development on planetary environmental evolution, altogether with previous “related posts” (at the bottom).
Attribution of extreme events is a challenging science and one that is currently undergoing considerable evolution. In this paper, 20 different research groups explored the causes of 16 different events that occurred in 2013. The findings indicate that human-caused climate change greatly increased the risk for the extreme heat waves assessed in this report. How human influence affected other types of events such as droughts, heavy rain events, and storms was less clear, indicating that natural variability likely played a much larger role in these extremes. Multiple groups chose to look at both the Australian heat waves and the California drought, providing an opportunity to compare and contrast the strengths and weaknesses of various methodologies. There was considerable agreement about the role anthropogenic climate change played in the events between the different assessments. This year three analyses were of severe storms and none found an anthropogenic signal. However, attribution assessments of these types of events pose unique challenges due to the often limited observational record. When human-influence for an event is not identified with the scientific tools available to us today, this means that if there is a human contribution, it cannot be distinguished from natural climate variability.
Climatic Events Studied
- CALIFORNIA DROUGHT 3 studies
- NORTHEAST COLORADO EXTREME RAINS 1 study
- A U.S. FOCUSED ANALYSIS PRECIPITATION EXTREMES 1 study
- WESTERN SOUTH DAKOTA BLIZZARD 1 study
- AUSTRALIA AND PACIFIC EXTREME WARM ANOMALIES 4 studies
- AUSTRALIA BIG DRY 1 study
- NORTH ISLAND, NZ DROUGHT 1 study
- KOREA HEAT WAVE 1 study
- JAPAN HEAT WAVES 1 study
- CENTRAL EASTERN CHINA HOT SUMMER 1 study
- NORTHERN INDIA SEVERE PRECIPITATION 1 study
- WESTERN EUROPE DRY SUMMER 1 study
- SOUTHERN EUROPE WET WINTER 1 study
- UPPER DANUBE-ELBE BASINS HEAVY PRECIPITATION EVENT 1 study
- SPANISH PYRENEES EXTREME SNOW ACCUMULATION 1 study
- GERMANY AND DENMARK A VIOLENT MIDLATITUDE STORM 1 study
- UNITED KINGDOM COLD SPRING 1 study
SUMMARY AND BROADER CONTEXT
We acknowledge that these reports represent a small and nonrandom sampling of extreme events from around the world. However, with 22 studies looking at 16 events, a few interesting patterns emerge. Examining Table 24.1 reveals that the nine analyses of extreme heat events overwhelmingly showed that human-caused climate change is having an influence. In some cases, events have become as much as 10 times more likely due to the current cumulative effects of human-induced climate change, as found for the Korean heat wave of summer 2013. These individual examples are consistent with the broader trends captured in the latest IPCC (Stocker et al. 2014) statement, “it is likely that the frequency of heat waves has increased in large parts of Europe, Asia and Australia.” At the other end of the temperature distribution, the one analysis of a cold event found that such events were becoming much less likely.
In contrast, the role of human influences on extreme precipitation events observed in 2013 is decidedly mixed (Table 24.1). The analysis of the extreme June monthly averaged precipitation in northern India found evidence suggesting an increase of the event probability in the present climate compared to preindustrial climate (see “Severe Precipitation in Northern India in June 2013: Causes, Historical Context, and Changes in Probability” in this report), whereas analyses of seasonal and annual precipitation extreme values over the north-central and eastern United States (see “Seasonal and Annual Mean Precipitation Extremes Occurring During 2013: A U.S. Focused Analysis” in this report) showed an anthropogenic contribution. The high profile and high impact extreme rainfall event in northeast Colorado in early September happened despite global warming making the event less likely according to this analysis (see “Northeast Colorado Extreme Rains Interpreted in a Climate Change Context” in this report). Two additional heavy precipitation analyses did not find anthropogenic influences.
Of the four analyses of drought, the one focused on New Zealand drought found global warming contributed to the severity of that event. However, the three papers that looked at the California drought did not find a clear anthropogenic influence. “Examining the Contribution of the Observed Global Warming Trend to the California Droughts of 2012/13 and 2013/14” and “Causes of the Extreme Dry Conditions Over California During Early 2013” looked directly at the precipitation deficits associated with the California drought and their link to SSTs and found no appreciable effect from long-term SST warming. “The Extraordinary California Drought of 2013/14: Character, Context, and the Role of Climate Change” took a different approach and focused on particular circulation patterns that contributed to the drought, rather than examining precipitation directly. While they found global warming to increase the probability of certain large-scale atmospheric circulations, the implications for extremely low precipitation over California were found to be uncertain. This comparison of three studies for the same extreme event, each using different methods and metrics, strengthened the attribution evidence (in this case, against a substantial effect of global warming on the severe precipitation deficits), and revealed the sources of uncertainty more deeply than might have been evident from a single study alone.
This year, we also had a few very exciting additions that looked at different types of extreme events: an assessment of a blizzard that hit South Dakota, Cyclone “Christian” that caused significant damage in northwestern Europe, and an extreme snowfall event in the Pyrenees Mountains. None of these analyses found an anthropogenic signal, in part because attribution assessments of storm events such as these pose unique challenges due to the often limited observational record. As stated earlier, this failure to find anthropogenic signals does not prove anthropogenic climate change had no role to play in these events. Rather, a substantial anthropogenic contribution to these events cannot be supported by these analyses.
Broader context of attribution research. As we conclude our third annual report on explaining extreme events, the dialog around the value of attribution science is intensifying (Kerr 2013). Perhaps the most evident and widely applicable value of event attribution is to interpret what an event occurrence means for the future. The annual State of the Climate report (Blunden and Arndt 2014) puts current conditions into historical perspective, while our report also seeks to explain the events in the context of the future as well by identifying how our changing climate system is currently influencing events.
In addition to interpreting how the risk of an extreme event may be changing, event attribution is also valuable to the overall scientific enterprise of improving predictions and projections. As stated in the World Climate Research Program Grand Challenges white paper for Science Underpinning the Prediction and Attribution of Extreme Events, “There are strong links between the development of routine event attribution methods and those used to make sub-seasonal to interannual predictions” (Karoly et al. 2012). The physical understanding of extreme events is valuable in determining if models are capable of representing and simulating those processes and events realistically. Assessments of extremes can, therefore, elucidate strengths and limitations of models. The ultimate goal is to develop new prediction products relating to extremes that better meet the needs of the public and decision makers, who must make choices about how to prepare for extremes.
Beyond the science, there is an ongoing public dialog around climate change and its impacts. It is clear that extreme events capture the public’s attention. And, indeed, they should because “people, plants and animals tend to be more impacted by changes in extremes compared to changes in average climate” (Peterson et al. 2008). And, with or without the availability of a robust scientific analysis, the public often associates extreme events such as these with climate change. Scientific event attribution can help inform the public’s understanding of our changing environment.
The challenges in event attribution are high both from a technological perspective of improving scientific knowledge and from a communication perspective of explaining what that science knowledge means. Observed events, such as those analyzed in this report, demonstrate the vulnerabilities of societies to extremes of weather and climate. In the face of such vulnerabilities, citizens are faced with decisions in the presence of uncertainty, for instance whether climate change may be increasing their exposure to drought or flooding. Enhancing scientific knowledge through attribution helps build environmental intelligence, thereby enabling better decisions than would be possible without such understanding.
It remains that after an extreme event there is a window of opportunity to engage the public on climate change impacts and science more broadly (Peterson et al. 2008). Being able to deliver scientifically robust attribution statements about the event in a timely manner is an important first step in this dialog.