A series of polls provides new tests for how weather influences public beliefs about climate change. Statewide data from 5000 random-sample telephone interviews conducted on 99 days over 2.5 yr (2010–12) are merged with temperature and precipitation indicators derived from U.S. Historical Climatology Network (USHCN) station records. The surveys carry a question designed around scientific consensus statements that climate change is happening now, caused mainly by human activities. Alternatively, respondents can state that climate change is not happening, or that it is happening but mainly for natural reasons. Belief that humans are changing the climate is predicted by temperature anomalies on the interview day and the previous day, controlling for season, survey, and individual characteristics. Temperature effects concentrate among one subgroup, however: individuals who identify themselves as independent, rather than aligned with a political party. Interviewed on unseasonably warm days, independents tend to agree with the scientific consensus regarding anthropogenic climate change. On unseasonably cool days, they tend not to agree. Although temperature effects are sharpest for just a 2-day window, positive effects are seen for longer windows as well. As future climate change shifts the distribution of anomalies and extremes, this will first affect beliefs among unaligned voters.

Quantifying local people's perceptions to climate change, and their assessments of which changes matter, is fundamental to addressing the dual challenge of land conservation and poverty alleviation in densely populated tropical regions To develop appropriate policies and responses, it will be important not only to anticipate the nature of expected changes, but also how they are perceived, interpreted and adapted to by local residents. The Albertine Rift region in East Africa is one of the world's most threatened biodiversity hotspots due to dense smallholder agriculture, high levels of land and resource pressures, and habitat loss and conversion. Results of three separate household surveys conducted in the vicinity of Kibale National Park during the late 2000s indicate that farmers are concerned with variable precipitation. Many survey respondents reported that conditions are drier and rainfall timing is becoming less predictable. Analysis of daily rainfall data for the climate normal period 1981 to 2010 indicates that total rainfall both within and across seasons has not changed significantly, although the timing and transitions of seasons has been highly variable. Results of rainfall data analysis also indicate significant changes in the intra-seasonal rainfall distribution, including longer dry periods within rainy seasons, which may contribute to the perceived decrease in rainfall and can compromise food security. Our results highlight the need for fine-scale climate information to assist agro-ecological communities in developing effective adaptive management.

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Abstract:The Community Collaborative Rain, Hail & Snow (CoCoRaHS) Network is a community-based network of weather observers and the largest provider of daily precipitation observations in the USA. In this study, we embrace the CoCoRaHS mission to use low-cost measurement tools, provide training and education, and utilize an interactive website to create the first volunteer snow albedo network to collect high-quality albedo data for research and education applications. We trained a sub-set of 18 CoCoRaHS observers in the state of New Hampshire to collect albedo, snow depth, and snow density between 23 November 2011 and 15 March 2012. At less than $700 per observer, CoCoRAHS data measured using an Apogee MP-200 pyranometer fall within AE0.05 of albedo values collected from a Kipp and Zonen CMA6 at local solar noon. CoCoRAHS values range from 0.99 for fresh snow to 0.34 for shallow, aged snow. Snowfree albedo ranges from 0.09 to 0.39, depending on the underlying ground cover. In the 2011/2012 dataset, albedo increases logarithmically with snow depth and decreases linearly with snow density. The latter relationship is inferred to be a proxy for increasing snow grain size as snowpack ages and compacts, supported by spectral albedo measurements collected with an Analytical Spectral Devices FieldSpec 4 spectrometer.

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