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Sebastian Sippel, Peter Walton, and Friederike E. L. Otto

Abstract

Recent extreme weather events and their impacts on societies have highlighted the need for timely adaptation to the changing odds of their occurrence. Such measures require appropriate information about likely changes in event frequency and magnitude on relevant spatiotemporal scales. However, to support robust climate information for decision-making, an effective communication between scientists and stakeholders is crucial. In this context, weather event attribution studies are increasingly raising attention beyond academic circles, although the understanding of how to take it beyond academia is still evolving. This paper presents the results of a study that involved in-depth interviews with stakeholders from a range of sectors about potential applications and the general usefulness of event attribution studies. A case study of the hot and dry summer 2012 in southeast Europe is used as a concrete example, with a focus on the applicability of attribution results across sectors. An analysis of the interviews reveals an abundant interest among the interviewed stakeholders and highlights the need for information on the causes and odds of extreme events, in particular on regional scales. From this data key aspects of stakeholder engagement are emerging, which could productively feed back into how probabilistic event attribution studies are designed and communicated to ensure practical relevance and usefulness for the stakeholder community.

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Peter J. Walton, Morgan B. Yarker, Michel D. S. Mesquita, and Friederike E. L. Otto

Abstract

Globally, decision-makers are increasingly using high-resolution climate models to support policy and planning; however, many of these users do not have the knowledge needed to use them appropriately. This problem is compounded by not having access to quality learning opportunities to better understand how to apply the models and interpret results. This paper discusses and proposes an educational framework based on two independent online courses on regional climate modeling, which addresses the accessibility issue and provides guidance to climate science professors, researchers, and institutions who want to create their own online courses.

The role of e-learning as an educational tool is well documented, highlighting the benefits of improved personal efficiency through “anywhere, anytime” learning with the flexibility to support professional development across different sectors. In addition, improved global Internet means increased accessibility. However, e-learning’s function as a tool to support understanding of atmospheric physics and high-resolution climate modeling has not been widely discussed. To date, few courses, if any, support understanding that takes full advantage of e-learning best practices.

There is a growing need for climate literacy to help inform decision-making on a range of scales, from individual households to corporate CEOs. And while there is a plethora of climate information online, educational theory suggests that people need to be guided in how to convert this information into applicable knowledge.

Here, we present how the experience of the courses we designed and ran independent of each other, both engaging learners with better understanding benefits and limitations of regional climate modeling, lead to a framework of designing e-learning for climate modeling.

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Geert Jan van Oldenborgh, Friederike E. L. Otto, Karsten Haustein, and Krishna AchutaRao
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Sebastian Sippel, Friederike E. L. Otto, Milan Flach, and Geert Jan van Oldenborgh
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Sarah f. Kew, Sjoukje Y. Philip, Geert Jan van Oldenborgh, Gerard van der Schrier, Friederike E. L. Otto, and Robert Vautard
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Neven Stjepan Fučkar, Friederike E.L. Otto, Flavio Lehner, Izidine Pinto, Sarah Sparrow, Sihan Li, and David Wallom
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Karsten Haustein, Friederike E. L. Otto, Victor Venema, Peter Jacobs, Kevin Cowtan, Zeke Hausfather, Robert G. Way, Bethan White, Aneesh Subramanian, and Andrew P. Schurer

Abstract

The early twentieth-century warming (EW; 1910–45) and the mid-twentieth-century cooling (MC; 1950–80) have been linked to both internal variability of the climate system and changes in external radiative forcing. The degree to which either of the two factors contributed to EW and MC, or both, is still debated. Using a two-box impulse response model, we demonstrate that multidecadal ocean variability was unlikely to be the driver of observed changes in global mean surface temperature (GMST) after AD 1850. Instead, virtually all (97%–98%) of the global low-frequency variability (>30 years) can be explained by external forcing. We find similarly high percentages of explained variance for interhemispheric and land–ocean temperature evolution. Three key aspects are identified that underpin the conclusion of this new study: inhomogeneous anthropogenic aerosol forcing (AER), biases in the instrumental sea surface temperature (SST) datasets, and inadequate representation of the response to varying forcing factors. Once the spatially heterogeneous nature of AER is accounted for, the MC period is reconcilable with external drivers. SST biases and imprecise forcing responses explain the putative disagreement between models and observations during the EW period. As a consequence, Atlantic multidecadal variability (AMV) is found to be primarily controlled by external forcing too. Future attribution studies should account for these important factors when discriminating between externally forced and internally generated influences on climate. We argue that AMV must not be used as a regressor and suggest a revised AMV index instead [the North Atlantic Variability Index (NAVI)]. Our associated best estimate for the transient climate response (TCR) is 1.57 K (±0.70 at the 5%–95% confidence level).

Open access
Friederike E. L. Otto, Luke Harrington, Katharina Schmitt, Sjoukje Philip, Sarah Kew, Geert Jan van Oldenborgh, Roop Singh, Joyce Kimutai, and Piotr Wolski

Abstract

The science of event attribution has emerged to routinely answer the question whether and to what extent human-induced climate change altered the likelihood and intensity of recently observed extreme weather events. In Europe a pilot program to operationalize the method started in November 2019, highlighting the demand for timely information on the role of climate change when it is needed most: in the direct aftermath of an extreme event. Independent of whether studies are provided operationally or as academic studies, the necessity of good observational data and well-verified climate models imply most attributions are currently made for highly developed countries only. Current attribution assessments therefore provide very little information about those events and regions where the largest damages and socio-economic losses are incurred. Arguably, these larger damages signify a much greater need for information on how the likelihood and intensity of such high-impact events have been changing and are likely to change in a warmer world. In short, why do we not focus event attribution research efforts on the whole world, and particularly events in the developing world? The reasons are not just societal and political but also scientific. We simply cannot attribute these events in the same probabilistic framework employed in most studies today. We outline six focus areas to lessen these barriers, but we will not overcome them in the near future.

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Sebastian Sippel, Tarek S. El-Madany, Mirco Migliavacca, Miguel D. Mahecha, Arnaud Carrara, Milan Flach, Thomas Kaminski, Friederike E. L. Otto, Kirsten Thonicke, Michael Vossbeck, and Markus Reichstein
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Friederike E. L. Otto, Luke J. Harrington, David Frame, Emily Boyd, Kristian Cedervall Lauta, Michael Wehner, Ben Clarke, Emmanuel Raju, Chad Boda, Mathias Hauser, Rachel A. James, and Richard G. Jones
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