Project Title

Analyzing Winter Weather and Climate Trends of the Ski Resorts in North Carolina Through the Use of Community Collaborative Rain, Hail & Snow Network (CoCoRaHS) Stations

Authors' Affiliations

Danika Mosher, Department of Geosciences, College of Arts and Sciences, East Tennessee State University, Johnson City, TN Andrew Joyner, Department of Geosciences, College of Arts and Sciences, East Tennessee State University, Johnson City, TN Ingrid Luffman, Department of Geosciences, College of Arts and Sciences, East Tennessee State University, Johnson City, TN

Location

Ballroom

Start Date

4-12-2019 9:00 AM

End Date

4-12-2019 2:30 PM

Poster Number

11

Faculty Sponsor’s Department

Geosciences

Name of Project's Faculty Sponsor

Dr. Andrew Joyner

Type

Poster: Competitive

Classification of First Author

Graduate Student-Master’s

Project's Category

Business Planning or Policy, Global Change, Parks and Recreation Management

Abstract Text

Changes in climate result in wide-ranging economic impacts, especially for businesses that rely on consistent weather patterns. The North Carolina ski resorts (Beech Mountain Ski Resort, Appalachian Ski Resort, Sugar Mountain Ski Resort, Wolf Ridge Ski Resort, Cataloochee Ski Area, and Sapphire Valley Ski Area) are the southernmost resorts on the east coast in the US. They are able to stay in business because of the diverse terrain and elevation of the Appalachian Mountains where they can see low record temperatures of -34°F. Observable increases in temperature and less snowfall accumulations generate concern for these businesses that rely not only on snow but temperatures low enough to produce their own snow. To understand what may happen in the future, it is pertinent to examine past and ongoing trends. Yearly snowfall data from fall 2010 to spring 2018 were obtained from the Community Collaborative Rain, Hail & Snow Network (CoCoRaHS) and interpolated using ordinary kriging. Teleconnections (Arctic Oscillation, El Niño Southern Oscillation, and North Atlantic Oscillation) were examined to help compare similar years to observe possible relationships. The stations that had data for all of the years observed were spatially analyzed through regression kriging (RK) to determine how climate change will affect those areas. A kernel density map was then created from active CoCoRaHS stations to observe which areas need more stations to generate better interpolation data for future years. The results are impactful for the ski resorts, helping them to make effective business decisions based on climate trends and to promote the use of citizen science to improve research efforts.

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Apr 12th, 9:00 AM Apr 12th, 2:30 PM

Analyzing Winter Weather and Climate Trends of the Ski Resorts in North Carolina Through the Use of Community Collaborative Rain, Hail & Snow Network (CoCoRaHS) Stations

Ballroom

Changes in climate result in wide-ranging economic impacts, especially for businesses that rely on consistent weather patterns. The North Carolina ski resorts (Beech Mountain Ski Resort, Appalachian Ski Resort, Sugar Mountain Ski Resort, Wolf Ridge Ski Resort, Cataloochee Ski Area, and Sapphire Valley Ski Area) are the southernmost resorts on the east coast in the US. They are able to stay in business because of the diverse terrain and elevation of the Appalachian Mountains where they can see low record temperatures of -34°F. Observable increases in temperature and less snowfall accumulations generate concern for these businesses that rely not only on snow but temperatures low enough to produce their own snow. To understand what may happen in the future, it is pertinent to examine past and ongoing trends. Yearly snowfall data from fall 2010 to spring 2018 were obtained from the Community Collaborative Rain, Hail & Snow Network (CoCoRaHS) and interpolated using ordinary kriging. Teleconnections (Arctic Oscillation, El Niño Southern Oscillation, and North Atlantic Oscillation) were examined to help compare similar years to observe possible relationships. The stations that had data for all of the years observed were spatially analyzed through regression kriging (RK) to determine how climate change will affect those areas. A kernel density map was then created from active CoCoRaHS stations to observe which areas need more stations to generate better interpolation data for future years. The results are impactful for the ski resorts, helping them to make effective business decisions based on climate trends and to promote the use of citizen science to improve research efforts.