scholarly journals Verification of extreme event attribution: Using out-of-sample observations to assess changes in probabilities of unprecedented events

2020 ◽  
Vol 6 (12) ◽  
pp. eaay2368 ◽  
Author(s):  
Noah S. Diffenbaugh
Keyword(s):  
Global Warming ◽  
21St Century ◽  
Extreme Event ◽  
Climate Forcing ◽  
Anthropogenic Influence ◽  
Independent Verification ◽  
Event Attribution ◽  
Verification Period ◽  
Out Of Sample ◽  
Climate Events

Independent verification of anthropogenic influence on specific extreme climate events remains elusive. This study presents a framework for such verification. This framework reveals that previously published results based on a 1961–2005 attribution period frequently underestimate the influence of global warming on the probability of unprecedented extremes during the 2006–2017 period. This underestimation is particularly pronounced for hot and wet events, with greater uncertainty for dry events. The underestimation is reflected in discrepancies between probabilities predicted during the attribution period and frequencies observed during the out-of-sample verification period. These discrepancies are most explained by increases in climate forcing between the attribution and verification periods, suggesting that 21st-century global warming has substantially increased the probability of unprecedented hot and wet events. Hence, the use of temporally lagged periods for attribution—and, more broadly, for extreme event probability quantification—can cause underestimation of historical impacts, and current and future risks.

scholarly journals Quantifying the influence of global warming on unprecedented extreme climate events

2017 ◽  
Vol 114 (19) ◽  
pp. 4881-4886 ◽  
Author(s):  
Noah S. Diffenbaugh ◽  
Deepti Singh ◽  
Justin S. Mankin ◽  
Daniel E. Horton ◽  
Daniel L. Swain ◽  
...  
Keyword(s):  
Global Warming ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
Climate Forcing ◽  
Sea Ice Extent ◽  
Extreme Climate Events ◽  
Atmospheric Circulation Patterns ◽  
Extreme Climate ◽  
Substantial Progress ◽  
Climate Events

Efforts to understand the influence of historical global warming on individual extreme climate events have increased over the past decade. However, despite substantial progress, events that are unprecedented in the local observational record remain a persistent challenge. Leveraging observations and a large climate model ensemble, we quantify uncertainty in the influence of global warming on the severity and probability of the historically hottest month, hottest day, driest year, and wettest 5-d period for different areas of the globe. We find that historical warming has increased the severity and probability of the hottest month and hottest day of the year at >80% of the available observational area. Our framework also suggests that the historical climate forcing has increased the probability of the driest year and wettest 5-d period at 57% and 41% of the observed area, respectively, although we note important caveats. For the most protracted hot and dry events, the strongest and most widespread contributions of anthropogenic climate forcing occur in the tropics, including increases in probability of at least a factor of 4 for the hottest month and at least a factor of 2 for the driest year. We also demonstrate the ability of our framework to systematically evaluate the role of dynamic and thermodynamic factors such as atmospheric circulation patterns and atmospheric water vapor, and find extremely high statistical confidence that anthropogenic forcing increased the probability of record-low Arctic sea ice extent.

scholarly journals Attributing compound events to anthropogenic climate change

2021 ◽  
pp. 1-45
Author(s):  
Jakob Zscheischler ◽  
Flavio Lehner
Keyword(s):  
Climate Change ◽  
South Africa ◽  
Climate Model ◽  
Extreme Event ◽  
Synthetic Data ◽  
Anthropogenic Climate Change ◽  
Anthropogenic Influence ◽  
Western Cape ◽  
Event Attribution ◽  
Compound Events

AbstractExtreme event attribution answers the question whether and by how much anthropogenic climate change has contributed to the occurrence or magnitude of an extreme weather event. It is also used to link extreme event impacts to climate change. Impacts, however, are often related to multiple compounding climate drivers. Because extreme event attribution typically focuses on univariate assessments, these assessments might only provide a partial answer to the question of anthropogenic influence to a high-impact event. We present a theoretical extension to classical extreme event attribution for certain types of compound events. Based on synthetic data we illustrate how the bivariate fraction of attributable risk (FAR) differs from the univariate FAR depending on the extremeness of the event as well as the trends in and dependence between the contributing variables. Overall, the bivariate FAR is similar in magnitude or smaller than the univariate FAR if the trend in the second variable is comparably weak and the dependence between both variables is moderate or high, a typical situation for temporally co-occurring heatwaves and droughts. If both variables have similarly large trends or the dependence between both variables is weak, bivariate FARs are larger and are likely to provide a more adequate quantification of the anthropogenic influence. Using multiple climate model large ensembles, we apply the framework to two case studies, a recent sequence of hot and dry years in the Western Cape region of South Africa and two spatially co-occurring droughts in crop-producing regions in South Africa and Lesotho.

scholarly journals Can the Issuance of Hazardous-Weather Warnings Inform the Attribution of Extreme Events to Climate Change?

2020 ◽  
Vol 101 (8) ◽  
pp. E1452-E1463
Author(s):  
Dale R. Durran
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Extreme Events ◽  
Weather Forecasting ◽  
Extreme Event ◽  
Probability Of Detection ◽  
False Alarms ◽  
Event Attribution ◽  
Hazardous Weather

Abstract When extreme weather occurs, the question often arises whether the event was produced by climate change. Two types of errors are possible when attempting to answer this question. One type of error is underestimating the role of climate change, thereby failing to properly alert the public and appropriately stimulate efforts at adaptation and mitigation. The second type of error is overestimating the role of climate change, thereby elevating climate anxiety and potentially derailing important public discussions with false alarms. Long before societal concerns about global warming became widespread, meteorologists were addressing essentially the same trade-off when faced with a binary decision of whether to issue a warning for hazardous weather. Here we review forecast–verification statistics such as the probability of detection (POD) and the false alarm ratio (FAR) for hazardous-weather warnings and examine their potential application to extreme-event attribution in connection with climate change. Empirical and theoretical evidence suggests that adjusting tornado-warning thresholds in an attempt to reduce FAR produces even larger reductions in POD. Similar tradeoffs between improving FAR and degrading POD are shown to apply using a rubric for the attribution of extreme high temperatures to climate change. Although there are obviously significant differences between the issuance of hazardous-weather warnings and the attribution of extreme events to global warming, the experiences of the weather forecasting community can provide qualitative guidance for those attempting to set practical thresholds for extreme-event attribution in a changing climate.

scholarly journals A protocol for probabilistic extreme event attribution analyses

2020 ◽  
Vol 6 (2) ◽  
pp. 177-203
Author(s):  
Sjoukje Philip ◽  
Sarah Kew ◽  
Geert Jan van Oldenborgh ◽  
Friederike Otto ◽  
Robert Vautard ◽  
...  
Keyword(s):  
Global Warming ◽  
Extreme Event ◽  
Analysis Model ◽  
Future Event ◽  
Starting Point ◽  
Event Attribution ◽  
The World ◽  
One Step ◽  
Sizeable Fraction ◽  
Event Definition

Abstract. Over the last few years, methods have been developed to answer questions on the effect of global warming on recent extreme events. Many “event attribution” studies have now been performed, a sizeable fraction even within a few weeks of the event, to increase the usefulness of the results. In doing these analyses, it has become apparent that the attribution itself is only one step of an extended process that leads from the observation of an extreme event to a successfully communicated attribution statement. In this paper we detail the protocol that was developed by the World Weather Attribution group over the course of the last 4 years and about two dozen rapid and slow attribution studies covering warm, cold, wet, dry, and stormy extremes. It starts from the choice of which events to analyse and proceeds with the event definition, observational analysis, model evaluation, multi-model multi-method attribution, hazard synthesis, vulnerability and exposure analysis and ends with the communication procedures. This article documents this protocol. It is hoped that our protocol will be useful in designing future event attribution studies and as a starting point of a protocol for an operational attribution service.

Climate attribution of environmental catastrophes

2020 ◽  
Author(s):  
Theodore Shepherd
Keyword(s):  
Extreme Event ◽  
Climatic Factors ◽  
Coarse Graining ◽  
Ecological Perspective ◽  
Ecological Literature ◽  
Event Attribution ◽  
Climate Events ◽  
Scientific Questions ◽  
Complex Question

<p>The role of climate change in environmental or ecological catastrophes is generally a complex question to address, because of the importance of non-climatic factors. From a climate perspective, the latter are confounding factors, whereas from an ecological perspective, they are often the heart of the matter. How these factors are treated affects the nature of the scientific questions that can be answered. In particular, the coarse-graining required to address probabilistic questions inevitably blurs the details of any particular event, whereas these details can be retained when addressing singular questions. In this paper, based on an analysis done jointly with Lisa Lloyd, I will present several published case studies of environmental catastrophes associated with extreme weather or climate events. Whilst both the singular ‘storyline’ and probabilistic ‘risk-based’ approaches to extreme-event attribution have uses in the descriptions of such events, we find the storyline approach to be more readily aligned with the forensic approach to evidence that is prevalent in the ecological literature. Implications for the study of environmental catastrophes are discussed.</p>

About the Nature of Global Warming Decrease at the Beginning of 21st Century

2018 ◽  
Vol 482 (3) ◽  
pp. 315-318
Author(s):  
E. Volodin ◽  
◽  
A. Gritsun ◽  
Keyword(s):  
Global Warming ◽  
21St Century

Climate change attribution with large ensembles

2021 ◽  
Author(s):  
Megan Kirchmeier-Young ◽  
Xuebin Zhang ◽  
Hui Wan
Keyword(s):  
Extreme Precipitation ◽  
Extreme Event ◽  
Extreme Temperature ◽  
Anthropogenic Forcing ◽  
Robust Detection ◽  
Continental Scale ◽  
Extreme Precipitation Events ◽  
Event Attribution ◽  
Large Ensembles ◽  
Precipitation Events

<p>The large sample sizes from single-model large ensembles are beneficial for a robust attribution of climate changes to anthropogenic forcing. This presentation will review examples using large ensembles in two types of attribution:  standard detection and attribution of spatio-temporal changes and extreme event attribution. First, increases in extreme precipitation have been attributed to anthropogenic forcing at large scales (global and hemispheric). We present results from a study that used three large ensembles, including two Earth System Models and one Regional Climate Model, to find a robust detection of a combined anthropogenic and natural forcing signal in the intensification of extreme precipitation at the continental scale and some regional scales in North America. Second, we use six large ensembles to assess the robustness of the attribution of extreme temperature and precipitation events. An event attribution framework is used and each large ensemble is treated as a perfect model. Robustness of the attribution is defined based on consistent agreement between the different models on a significant change in the probability of an event with the inclusion of anthropogenic forcing. We demonstrate that the attribution of extreme temperature events is robust. Meanwhile, the attribution of extreme precipitation events becomes robust in many regions under additional warming, but uncertainties pertaining to changes in atmospheric dynamics hinder attribution confidence in other regions. We also demonstrate that smaller ensembles bring larger uncertainty to event attribution.</p>

Paleoanalogues of global warming in the 21st century

2011 ◽  
Vol 438 (1) ◽  
pp. 681-685 ◽  
Author(s):  
A. A. Velichko ◽  
O. K. Borisova
Keyword(s):  
Global Warming ◽  
21St Century
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