We would like to thank the anonymous reviewers for their constructive comments on the manuscript. Thanks also to Dr. Andrew Grundstein for his assistance with GIS analyses. This work is supported in part by NCAR’s Collaborative Program on the Societal Impacts and Economic Benefits of Weather Information (SIP), which is funded by the National Science Foundation and the National Oceanic and Atmospheric Administration through the U.S. Weather Research Program. NCAR is sponsored by the National Science Foundation. The views and opinions in this paper are those of the authors.
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From the Köppen classification system, a “B” climate is predominantly dry in which evapotranspiration regularly exceeds precipitation. A “C” climate is a midlatitude climate with moist, subtropical characteristics that underlie a mild winter and warm to hot and humid summers. We refer to these climates as temperate. A “D” climate is a moist midlatitude continental type of climate with mild summers and cold winters. Further specific information about these major climate times and their subtypes (i.e., distribution of precipitation and seasonal variability) can be found in many standard climatology texts (e.g., Robinson & Henderson-Sellers 1999).
We reported the partial eta-squared statistic (η2) to indicate the magnitude of the relationships between the independent and dependent variables in the one-way analyses of variance that we conducted. Using Ferguson’s (2009) criteria, a small effect is associated with η2 ≤ 0.04. A medium effect size involves η2 ≈ 0.25 and a large effect characterizes η2 ≥ 0.64. Most of the effect sizes reported in this article are small in magnitude. Such effect sizes are common in the psychological and behavioral sciences where the variables under investigation involve attitudes, beliefs, and values (i.e., variables that are measured psychologically via surveys rather than physical variables that can be measured directly and with a greater degree of precision, Cohen 1988). We calculated 90% confidence intervals for each effect size and none of the effect sizes contained the zero point. Further all but two analyses did not contain the zero point when we calculated 95% confidence intervals. Therefore, although the effects we observed were small in magnitude, they generally appear to be reliable.