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Douglas Hayhoe, Shawn Bullock, and Katharine Hayhoe

Abstract

The authors used a 59-item survey to probe the understanding of climate change by 89 Ontario preservice teachers. The study investigated the usefulness of comparing real survey data from closed, binary choice items, with randomly generated data. Climate change was chosen to be the topic because it is a new emphasis in K–12 science curricula. If teachers had answered the survey randomly, according to Monte Carlo simulations, a normal distribution would result, with 56 of the 59 items answered correctly by 40%–60% of the respondents. A bimodal distribution resulted, however, with 34 items answered correctly by more than 60% and 18 items by less than 40%. Apparently, the teachers knew a lot about climate change, but also had many misconceptions, some identified here for the first time. Item discrimination indices and correlation coefficients, however, were the same for the real versus Monte Carlo data, suggesting that preservice teachers’ knowledge was a “kaleidoscope of understanding,” rather than a coherent picture. This may be because their understanding of climate change came primarily from unconnected sources in the media, or because climate change science involves many different fields of study including astronomy, biology, chemistry, ecology, oceanography, and physics. In conclusion, the analysis herein demonstrates the benefit of comparing real and random data for binary-choice item surveys in multidiscipline topics such as climate change. For those interested in climate change education, these results suggest the importance of emphasizing the difference between reliable and unreliable sources of information and giving careful attention to how to draw on concepts from different scientific fields.

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Norman L. Miller, Katharine Hayhoe, Jiming Jin, and Maximilian Auffhammer

Abstract

Over the twenty-first century, the frequency of extreme-heat events for major cities in heavily air conditioned California is projected to increase rapidly. Extreme heat is defined here as the temperature threshold for the 90th-percentile excedence probability (T90) of the local warmest summer days under the current climate. Climate projections from three atmosphere–ocean general circulation models, with a range of low to midhigh temperature sensitivity forced by the Special Report on Emission Scenarios higher, middle, and lower emission scenarios, indicate that these increases in temperature extremes and variance are projected to exceed the rate of increase in mean temperature. Overall, projected increases in extreme heat under the higher A1fi emission scenario by 2070–99 tend to be 20%–30% higher than those projected under the lower B1 emission scenario. Increases range from approximately 2 times the present-day number of days for inland California cities (e.g., Sacramento and Fresno), up to 4 times for previously temperate coastal cities (e.g., Los Angeles and San Diego), implying that present-day “heat wave” conditions may dominate summer months—and patterns of electricity demand—in the future. When the projected extreme heat and observed relationships between high temperature and electricity demand for California are mapped onto current availability, maintaining technology and population constant for demand-side calculations, a potential for electricity deficits as high as 17% during T90 peak electricity demand periods is found. Similar increases in extreme-heat days are likely for other southwestern U.S. urban locations, as well as for large cities in developing nations with rapidly increasing electricity demands. In light of the electricity response to recent extreme-heat events, such as the July 2006 heat waves in California, Missouri, and New York, these results suggest that future increases in peak electricity demand will challenge current transmission and supply methods as well as future planned supply capacities when population and income growth are taken into account.

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Anne Marie K. Stoner, Katharine Hayhoe, and Donald J. Wuebbles

Abstract

The ability of coupled atmosphere–ocean general circulation models (AOGCMs) to simulate variability in regional and global atmospheric dynamics is an important aspect of model evaluation. This is particularly true for recurring large-scale patterns known to be correlated with surface climate anomalies. Here, the authors evaluate the ability of all Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) historical Twentieth-Century Climate in Coupled Models (20C3M) AOGCM simulations for which the required output fields are available to simulate three patterns of large-scale atmospheric internal variability in the North Atlantic region: the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), and the Atlantic multidecadal oscillation (AMO); and three in the North Pacific region: the El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the Pacific–North American Oscillation (PNA). These patterns are evaluated in two ways: first, in terms of their characteristic temporal variability and second, in terms of their magnitude and spatial locations.

It is found that historical total-forcing simulations from many of the AOGCMs produce seasonal spatial patterns that clearly resemble the teleconnection patterns resulting from identical calculation methods applied to reanalysis and/or observed fields such as the 40-yr ECMWF Re-Analysis, NCEP–NCAR, or Kaplan sea surface temperatures (SSTs), with the exception of the lowest-frequency pattern, AMO, which is only reproduced by a few models. AOGCM simulations also show some significant biases in both spatial and temporal characteristics of the six patterns. Many models tend to either under- or overestimate the strength of the spatial patterns and exhibit rotation about the polar region or east–west displacement. Based on spectral analysis of the time series of each index, models also appear to vary in their ability to simulate the temporal variability of the teleconnection patterns, with some models producing oscillations that are too fast and others that are too slow relative to those observed. A few models produce a signal that is too periodic, most likely because of a failure to adequately simulate the natural chaotic behavior of the atmosphere. These results have implications for the selection and use of specific AOGCMs to simulate climate over the Northern Hemisphere, with some models being clearly more successful at (i.e., displaying less bias in) simulating large-scale, low-frequency patterns of temporal and spatial variability over the North Atlantic and Pacific regions relative to others.

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Jin-Tai Lin, Kenneth O. Patten, Katharine Hayhoe, Xin-Zhong Liang, and Donald J. Wuebbles

Abstract

Future projections of near-surface ozone concentrations depend on the climate/emissions scenario used to drive future simulations, the direct effects of the changing climate on the atmosphere, and the indirect effects of changing temperatures and CO2 levels on biogenic ozone precursor emissions. The authors investigate the influence of these factors on potential future changes in summertime daily 8-h maximum ozone over the United States and China by comparing Model for Ozone and Related Chemical Tracers, version 2.4, (MOZART-2.4) simulations for the period 1996–2000 with 2095–99, using climate projections from NCAR–Department of Energy Parallel Climate Model simulations driven by the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios A1fi (higher) and B1 (lower) emission scenarios, with corresponding changes in biogenic emissions. The effect of projected climate changes alone on surface ozone is generally less than 3 ppb over most regions. Regional ozone increases and decreases are driven mainly by local warming and marine air dilution enhancement, respectively. Changes are approximately the same magnitude under both scenarios, although spatial patterns of responses differ. Projected increases in isoprene emissions (32%–94% over both countries), however, result in significantly greater changes in surface ozone. Increases of 1–15 ppb are found under A1fi and of 0–7 ppb are found under B1. These increases not only raise the frequency of “high ozone days,” but are also projected to occur nearly uniformly across the distribution of daily ozone maxima. Thus, projected future ozone changes appear to be more sensitive to changes in biogenic emissions than to direct climate changes, and the spatial patterns and magnitude of future ozone changes depend strongly on the future emissions scenarios used.

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Edward Maibach, Raphael Mazzone, Robert Drost, Teresa Myers, Keith Seitter, Katharine Hayhoe, Bob Ryan, Joe Witte, Ned Gardiner, Susan Hassol, Jeffrey K. Lazo, Bernadette Placky, Sean Sublette, and Heidi Cullen

Abstract

Findings from the most recent surveys of TV weathercasters—which are methodologically superior to prior surveys in a number of important ways—suggest that weathercasters’ views of climate change may be rapidly evolving. In contrast to prior surveys, which found many weathercasters who were unconvinced of climate change, newer results show that approximately 80% of weathercasters are convinced of human-caused climate change. A majority of weathercasters now indicate that climate change has altered the weather in their media markets over the past 50 years, and many feel there have also been harmful impacts to water resources, agriculture, transportation resources, and human health. Nearly all weathercasters—89%—believe their viewers are at least slightly interested in learning about local impacts. The majority of weathercasters are interested in reporting on local impacts, including extreme precipitation and flooding, drought and water shortages, extreme heat events, air quality, and harm to local wildlife, crops and livestock, and human health; and nearly half had reported on the local impacts in at least one channel over the past 12 months. Thus, it appears that a strong majority of weathercasters are now convinced that human-caused climate change is happening, many feel they are already witnessing harmful impacts in their communities, and many are beginning to explore ways of educating their viewers about these local impacts of global climate change. We believe that the role of local climate educator will soon become a normative practice for broadcast meteorologists—adding a significant and important new role to their job descriptions.

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Donald Wuebbles, Gerald Meehl, Katharine Hayhoe, Thomas R. Karl, Kenneth Kunkel, Benjamin Santer, Michael Wehner, Brian Colle, Erich M. Fischer, Rong Fu, Alex Goodman, Emily Janssen, Viatcheslav Kharin, Huikyo Lee, Wenhong Li, Lindsey N. Long, Seth C. Olsen, Zaitao Pan, Anji Seth, Justin Sheffield, and Liqiang Sun

This is the fourth in a series of four articles on historical and projected climate extremes in the United States. Here, we examine the results of historical and future climate model experiments from the phase 5 of the Coupled Model Intercomparison Project (CMIP5) based on work presented at the World Climate Research Programme (WCRP) Workshop on CMIP5 Climate Model Analyses held in March 2012. Our analyses assess the ability of CMIP5 models to capture observed trends, and we also evaluate the projected future changes in extreme events over the contiguous Unites States. Consistent with the previous articles, here we focus on model-simulated historical trends and projections for temperature extremes, heavy precipitation, large-scale drivers of precipitation variability and drought, and extratropical storms. Comparing new CMIP5 model results with earlier CMIP3 simulations shows that in general CMIP5 simulations give similar patterns and magnitudes of future temperature and precipitation extremes in the United States relative to the projections from the earlier phase 3 of the Coupled Model Intercomparison Project (CMIP3) models. Specifically, projections presented here show significant changes in hot and cold temperature extremes, heavy precipitation, droughts, atmospheric patterns such as the North American monsoon and the North Atlantic subtropical high that affect interannual precipitation, and in extratropical storms over the twenty-first century. Most of these trends are consistent with, although in some cases (such as heavy precipitation) underestimate, observed trends.

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