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Risa Palm, Toby Bolsen, and Justin T. Kingsland

1. Introduction Climate change arguably presents the most challenging collective action problem the world has ever faced. Rising global temperatures due to the increasing accumulation of greenhouse gases in the atmosphere will fundamentally reshape societies, threatening economies, health care systems, and geopolitical relations. It is projected that state-of-the-art behavioral interventions, such as providing targeted information to consumers about high-impact individual and household energy

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Catherine Morin Boulais

observation ( Bernard 2011 ) consisted of first-hand involvement in storm-chasing tours’ day-to-day activities. Long drives, along with numerous waiting periods, were good opportunities to spark discussions about the activity’s attractiveness and severe weather becoming a tourist attraction through storm-chasing tourism. As observed by Lewis (2003) , informal discussions complementing participant observation were fruitful: led in a convivial atmosphere, participants felt secure to share their views and

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Emmanuel Nyadzi, E. Saskia Werners, Robbert Biesbroek, Phi Hoang Long, Wietse Franssen, and Fulco Ludwig

). The score measures the probability that any two (distinguishable) observations can be correctly discriminated by the corresponding forecasts. Thus, GDS can be interpreted as an indication of how often the forecasts are “correct” regardless of whether forecasts are binary, categorical, continuous, or probabilistic ( Mason and Weigel 2009 ). The relative operating curve skill score was also used to compute the skills in tercile forecasts (i.e., probability forecasts for upper, middle, and lower

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Jason A. Otkin, Tonya Haigh, Anthony Mucia, Martha C. Anderson, and Christopher Hain

impact. b. Evaporative stress index The evaporative stress index (ESI) depicts standardized anomalies in the ratio of actual to reference ET, where the actual ET flux is estimated from remote sensing data using the Atmosphere–Land Exchange Inverse (ALEXI; Anderson et al. 1997 , 2007a , b , 2011 ) surface energy balance model, and the reference ET flux is computed using a Penman–Monteith formulation for a grass reference surface ( Allen et al. 1998 ). Normalization of actual ET by a reference ET

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Jadwiga R. Ziolkowska, Christopher A. Fiebrich, J. D. Carlson, Andrea D. Melvin, Albert J. Sutherland, Kevin A. Kloesel, Gary D. McManus, Bradley G. Illston, James E. Hocker, and Reuben Reyes

originated in 1992 with a National Science Foundation (NSF)-supported EarthStorm workshop (1992–2011) offered to middle school science (and other discipline) teachers with the aim to provide computer-supported meteorology training ( McPherson and Crawford 1996 ). In addition to the EarthStorm workshops, many new STEM-focused workshops were offered by the Mesonet, where 398 teachers and 59 emergency managers from across 28 states participated in professional development and became strong advocates for the

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Calum G. Turvey and Megan K. Mclaurin

1. Healthy vegetation has the highest positive values, while bare soil, water, snow, ice, or clouds have NDVI values of zero or that are slightly negative. Vegetation under stress or with a small leaf area has lower positive NDVI values. Typically the NDVI values from healthy vegetation will increase as plant cover increases at the beginning of the growing season, reach a peak sometime during the middle of the growing season, and will then decrease as the season comes to its end ( Mkhabela et al

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Kelsey J. Mulder, Matthew Lickiss, Natalie Harvey, Alison Black, Andrew Charlton-Perez, Helen Dacre, and Rachel McCloy

that volcanic eruptions occur 20–25 times every 100 years, with approximately three-quarters of these eruptions being explosive ( Thordarson and Larsen 2007 ). Some of these eruptions can release much more ash into the atmosphere and erupt for longer (months to years) than the 2010 Eyjafjallajökull eruption ( Thordarson and Larsen 2007 ). Globally, volcanic eruptions occur nearly daily. The decision of whether to fly during volcanic eruptions is solely the responsibility of the airline operator

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George C. Nche

change) although some have inaccurate information about which human activities contribute to climate change (see Table 2 ). Table 2. Summary of responses on the causes of climate change. For instance, when asked about the major causes of climate change, Michael of Christ Embassy, Kano, responds “definitely, human activities contribute much to climate change.” Explaining further how human activities contribute to climate change, Michael says, The release of gas into the atmosphere…affects the ozone

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Thomas W. Corringham and Daniel R. Cayan

patterns over the Pacific Ocean. We found MEI to be better correlated with insured losses than either the Southern Oscillation index or Niño-3.4 (results not shown). Of the 40 winters in our sample [or extended cool seasons, which we define as the months of October through March (ONDJFM)], average MEI was 0.035. We conduct split-sample analyses of flood insurance claims and insured losses by region against MEI by breaking ONDJFM monthly MEI into upper, lower, and middle terciles, with break points of

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Joshua J. Hatzis, Jennifer Koch, and Harold E. Brooks

arbitrarily defined high-risk areas as all areas estimated to have had at least two violent tornado days per century as the one violent tornado day per century area covered most of the middle part of the country. We tested for trends in the number of hits, near-misses, far-misses, observed exposure, median and maximum potential exposure, and the probability that a tornado would impact at least 5000 persons. We used a quadrat analysis with a chi-squared test ( ; Griffith and Haining 2006 ; Arnold et al

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