Economic Contributions of Winter Sports in a Changing Climate

In mountain towns across the United States that rely on winter tourism, snow is currency. For snow lovers and the winter sports industry, predictions of a future with warmer winters, reduced snowfall, and shorter snow seasons is inspiring them to innovate, increase their own efforts to address emissions, and speak publicly on the urgent need for action. This report examines the economic contribution of winter snow sports tourism to U.S. national and state-level economies. In a 2012 analysis, Protect Our Winters and the Natural Resources Defense Council found that the winter sports tourism industry generates $12.2 billion and 23 million Americans participate in winter sports annually. That study found that changes in the winter season driven by climate change were costing the downhill ski resort industry approximately$1.07 billion in aggregated revenue over high and low snow years over the last decade

Trends in wintertime climate variability in the northeastern United States

Humans experience climate variability and climate change primarily through changes in weather at local and regional scales. In this work, changes in northeastern United States winter climate are documented using meteorological observations from 1965-2005. Spatial coherence analysis is utilized to remove stations with non-climatic influences from the analysis. Trends over the past four decades in snowfall, snow-covered days, mean, minimum, and maximum temperature are estimated using linear regression. Northeastern United States regional winter maximum temperatures (+0.43 +/-.08°C/decade) are warming greater rate than minimum (+0.37 +/-0.10°C/decade) and mean (+0.39 +/-0.10°C/decade). Regional winter snowfall decreased by -2.5 +/-0.8 inches/decade. Overall snowfall decreases are greatest in December (-2.3 +/-0.5 inches/decade) and February (-1.1 +/-0.2 inches/decade). The reduction in winter snow-covered days (-2.6 +/-0.7 days/decade) is likely tied to increases in winter maximum temperature via a snow-albedo feedback. These results have important implications on the climate system, ecosystems, and society in the northeastern United States

Trends in wintertime climate in the northeastern United States: 1965–2005

Humans experience climate variability and climate change primarily through changes in weather at local and regional scales. One of the most effective means to track these changes is through detailed analysis of meteorological data. In this work, monthly and seasonal trends in recent winter climate of the northeastern United States (NE-US) are documented. Snow cover and snowfall are important components of the region\u27s hydrological systems, ecosystems, infrastructure, travel safety, and winter tourism and recreation. Temperature, snowfall, and snow depth data were collected from the merged United States Historical Climate Network (USHCN) and National Climatic Data Center Cooperative Network (COOP) data set for the months of December through March, 1965–2005. Monthly and seasonal time series of snow-covered days (snow depth \u3e2.54 cm) are constructed from daily snow depth data. Spatial coherence analysis is used to address data quality issues with daily snowfall and snow depth data, and to remove stations with nonclimatic influences from the regional analysis. Monthly and seasonal trends in mean, minimum, and maximum temperature, total snowfall, and snow-covered days are evaluated over the period 1965–2005, a period during which global temperature records and regional indicators exhibit a shift to warmer climate conditions. NE-US regional winter mean, minimum, and maximum temperatures are all increasing at a rate ranging from 0.42° to 0.46°C/decade with the greatest warming in all three variables occurring in the coldest months of winter (January and February). The regional average reduction in number of snow-covered days in winter (−8.9 d/decade) is also greatest during the months of January and February. Further analysis with additional regional climate modeling is required to better investigate the causal link between the increases in temperature and reduction in snow cover during the coldest winter months of January and February. In addition, regionally averaged winter snowfall has decreased by about 4.6 cm/decade, with the greatest decreases in snowfall occurring in December and February. These results have important implications for the impacts of regional climate change on the northeastern United States hydrology, natural ecosystems, and economy

Are New Hampshire’s Winters Warming? Yes, But Fewer Than Half of State Residents Recognize the Trend

In this brief, authors Elizabeth Burakowski and Lawrence Hamilton review some basic evidence about winter warming in New Hampshire, explore to what extent state residents are aware of this trend, and ask who is aware, in terms of characteristics such as age, education, or participation in winter sports. Results from two statewide surveys find limited awareness of the trend overall, and no significant differences by age, education, or winter sports participation. Instead, perceptions of this winter trend depend on political identity: conservatives are much less likely than other groups to recognize that warming has occurred

A simple model for predicting snow albedo decay using observations from the Community Collaborative Rain, Hail, and Snow-Albedo (CoCoRAHS-Albedo) Network

The albedo of seasonal snow cover plays an important role in the global climate system due to its influence on Earth’s radiation budget and energy balance. Volunteer CoCoRaHS-Albedo observers collected 3,249 individual daily albedo, snow depth, and density measurements using standardized techniques at dozens of sites across New Hampshire, USA over four winter seasons. The data show that albedo increases rapidly with snow depth up to ~ 0.14 m. Multiple linear regression models using snowpack age, snow depth or density, and air temperature provide reasonable approximations of surface snow albedo during times of albedo decay. However, the linear models also reveal systematic biases that highlight an important non-linearity in snow albedo decay. Modeled albedo values are reasonably accurate within the range of 0.6 to 0.9, but exhibit a tendency to over-estimate lower albedo values and under-estimate higher albedo values. We hypothesize that rapid reduction in high albedo fresh snow results from a decrease in snow specific surface area, while during melt-events the presence of liquid water in the snowpack accelerates metamorphism and grain growth. We conclude that the CoCoRaHS-Albedo volunteer observer network provides useful snow albedo, depth, and density measurements and serves as an effective model for future measurement campaigns

Climate Change in Northern New Hampshire: Past, Present and Future

EARTH’S CLIMATE CHANGES. It always has and always will. However, an extensive and growing body of scientific evidence indicates that human activities—including the burning of fossil fuel (coal, oil, and natural gas) for energy, clearing of forested lands for agriculture, and raising livestock—are now the primary force driving change in the Earth’s climate system. This report describes how the climate of northern New Hampshire has changed over the past century and how the future climate of the region will be affected by a warmer planet due to human activities

Synopsis of Polish spedes of the family Cicindelidae (Coleoptera)

Ten species of tiger-beetles (Coleoptera, Cicindelidae) occuring in Central Europe are described and figured. Keys to the adults and known larvae, with brief notes on their distribution and bionomics, are provided.Zadanie pt. „Digitalizacja i udostępnienie w Cyfrowym Repozytorium Uniwersytetu Łódzkiego kolekcji czasopism naukowych wydawanych przez Uniwersytet Łódzki” nr 885/P-DUN/2014 dofinansowane zostało ze środków MNiSW w ramach działalności upowszechniającej naukę

A qualitative analysis of athletic apparel and equipment sponsorship and student-athlete recruitment at the football championship

The purpose of this study was to extend previous literature on student-athlete college choice by examining part of the recruitment process as a precursor to student-athlete decision-making. More specifically, this exploratory study aimed to empirically examine the extent to which apparel sponsorships affect student-athlete recruitment. Semi-structured interviews were conducted with ten football players at a state-supported NCAA Football Championship Subdivision (FCS) institution in the Rocky Mountain region. An inductive approach was used in identifying three emergent themes. These themes suggest that football players at this institution did not hold the apparel and equipment sponsorship as a deciding factor for the commitment to a school, though they did hold strong opinions towards New Balance, and the other three brands referenced during the interviews. The values expressed by these participants can provide a basis for future apparel and equipment contracts at this institution. As this study was exploratory in nature, the findings lay the framework for similar research across gender, sport, school, and conference

Climate Change in the Piscataqua/Great Bay Region: Past, Present, and Future

Earth ’s climate changes. It always has and always will. However, an extensive body of scientific evidence indicates that human activities are now a significant force driving change in the Earth’s climate system. This report describes how the climate of the Piscataqua/Great Bay region of coastal New Hampshire in the United States has changed over the past century and how the future climate of the region will be affected by human activities that are warming the planet. Overall, the region has been getting warmer and wetter over the last century, and the rate of change has increased over the last four decades. To generate future climate projections for the region, simulated temperature and precipitation from four general circulation models were fitted to local, long-term weather observations. Unknowns regarding future fossil fuel consumption were accounted for by using two future emissions scenarios. As greenhouse gases continue to accumulate in the atmosphere, temperatures will rise, extreme heat days are projected to occur more often and will be hotter, extreme cold temperatures are projected to occur less often, and cold days will be warmer.. Annual average precipitation is projected to increase 12 to 17% by end-of-century and the region can expect to see more extreme precipitation events in the future. Tidal gauge data indicates relative sea level at Portsmouth has risen 0.7 inches per decade over the past eight decades. Projected sea level rise of 1.7 to 6.3 feet will result in higher storm surges and more frequent flooding in coastal New Hampshire

On implementation of efficient inline DDoS detector based on AATAC algorithm

Distributed Denial of Service (DDoS) attacks constitute a major threat in the current Internet. These cyber‑attacks aim to flood the target system with tailored malicious network traffic overwhelming its service capacity and consequently severely limiting legitimate users from using the service. This paper builds on the state-of-the-art AATAC algorithm (Autonomous Algorithm for Traffic Anomaly Detection) and provides a concept of a dedicated inline DDoS detector capable of real-time monitoring of network traffic and near-real-time anomaly detection.The inline DDoS detector consists of two main elements: 1) inline probe(s) responsible for link-rate real-time processing and monitoring of network traffic with custom-built packet feature counters, and 2) an analyser that performs the near-real-time statistical analysis of these counters for anomaly detection. These elements communicate asynchronously via the Redis database, facilitating a wide range of deployment scenarios. The inline probes are based on COTS servers and utilise the DPDK framework (Data Plane Development Kit) and parallel packet processing on multiple CPU cores to achieve link rate traffic analysis, including tailored DPI analysis