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Juan Liu, Chunhua Men, Victor E. Cabrera, Stan Uryasev, and Clyde W. Fraisse

1. Introduction The climate and market risks have substantial impact on the performance of the crop industry. One way for farmers to reduce these risks is to purchase appropriate crop-insurance products. There are numerous crop-insurance products available in the market, and therefore it is meaningful to study the optimal crop-insurance selection strategy. In some regions, crop production is heavily dependent on climate conditions in El Niño–Southern Oscillation (ENSO; Trenberth 1997 ) phases

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Jonghun Kam and Justin Sheffield

climate change ( Seager et al. 2007 ) that may be changing the risk of drought. About 45% of California’s annual precipitation occurs in winter and originates mainly from advected moisture via westerly winds over the extratropical Pacific Ocean ( Gimeno et al. 2012 ). In turn, this is driven by variations in the Pacific, as characterized by El Niño–Southern Oscillation (ENSO; Schonher and Nicholson 1989 ) and the Pacific decadal oscillation (PDO; McCabe et al. 2004 ), and modulated by conditions in

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Fiona Paumgarten, Bruno Locatelli, and Ed T. F. Witkowski

adaptive capacity) ( Pachauri et al. 2014 ; Kok et al. 2016 ). Risk involves the potential for impacts resulting from the interaction of climate-related hazards with the vulnerability and exposure of human and natural systems, with exposure now described as a separate component ( Pachauri et al. 2014 ). This revised framework has rarely been applied at the household level (but see Karim 2018 ). We combine this framework with the SLF ( DFID 1999 ) and develop a conceptual framework for the assessment

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Abigail Sullivan and Dave D. White

1. Introduction Understanding how the public perceives climate change impacts is critical to motivating successful adaptation and mitigation efforts ( Leiserowitz 2006 ; Lorenzoni and Pidgeon 2006 ). In the United States, approximately 40% of the public believes that climate change will impact them personally, while most believe it will harm people globally ( Marlon et al. 2016 ). In western nations more generally, this lack of personal risk perception has been identified as a barrier to

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Gutemberg Borges França, Antonio Nascimento de Oliveira, Célia Maria Paiva, Leonardo de Faria Peres, Michael Bezerra da Silva, and Luciana Maria Temponi de Oliveira

Sens. , 30 , 231 – 248 , doi:10.1109/36.134074 . UNEP , 2002 : Spreading like wildfire—Tropical forest fires in Latin America and the Caribbean: Prevention, assessment and early warning. U.N. Environment Programme, 16 pp. [Available online at http://www.unep.org/publications/search/pub_details_s.asp?ID=246 .] Verdon , D. C. , A. S. Kiem , and S. W. Franks , 2004 : Multi-decadal variability of forest fire risk—Eastern Australia . Int. J. Wildland Fire , 13 , 165 – 171 , doi:10

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Danielle C. Verdon-Kidd and Anthony S. Kiem

the first step in any drought (or flood, bushfire, or any other climate-driven extreme) risk assessment should be to understand the climate mechanisms that drive periods of elevated risk. For example, numerous studies [refer to Diaz and Markgraf (2000) and references therein] have shown that strong relationships exist between eastern Australian rainfall and streamflow, and the global-scale ocean–atmospheric circulation process known as the El Niño–Southern Oscillation (ENSO). ENSO refers to the

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Todd A. Crane, Carla Roncoli, Joel Paz, Norman Breuer, Kenneth Broad, Keith T. Ingram, and Gerrit Hoogenboom

milieus. The perceived relevance (salience) of seasonal climate forecasts is thus determined by the importance of climate uncertainty vis-à-vis other decision drivers. Because of this, assessment efforts must take into account the multivariate nature of farming decision to determine whether and how climate-based decision support systems serve the different goals that animate farmers’ risk-management strategies ( Moser 2009 ). As with salience, credibility (perceived reliability or accuracy) is not

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

also involves other complex and interacting drivers, for example in assessments of biological impacts ( Parmesan et al. 2011 ). While it is recognized that there is a compelling case to better understand the impacts of a changing climate and the potential change in risk from extreme weather events ( Moss et al. 2013 ), these impacts have not yet been universally adopted by stakeholders ( Schiermeier 2011 ; Stott and Walton 2013 ). Nonetheless, it has been shown that robust decision

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Sabrina T. Jauernic and Matthew S. Van Den Broeke

how I act now]. I grew up in Nebraska, so I can tell when a tornado is actually coming, and when it’s just a warning that my area might be hit. These responses show a tendency to use personal knowledge to decide when there might genuinely be danger and show a high need for personalization of risk. How do such students know for sure that they will or will not be impacted by a tornado in any given warning situation? The level of confidence in their own self-assessment of personal risk underscores

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Shannon M. McNeeley and Heather Lazrus

1. Introduction The role that culture plays in contemporary climate change adaptation is not a well understood or studied area ( Adger et al. 2009 ). Yet, culture, the full range of learned ideas and behavior patterns that are acquired, shared, and modified by people as members of a society, is ever present, guiding and lending meaning to perceptions of climate risk, decisions about whether to address climate change, and if deciding to take action, what it will be. Culture is present at many

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