A Sinusoidal Temperature Model for Major Cities in Georgia

Authors

  • Meagan Bridges Savannah State University, USA Author
    • Jessica Foster Savannah State University, USA Author
      • Samuel Luogon Dolo Savannah State University, USA Author

        DOI:

        https://doi.org/10.31686/ijier.vol5.iss10.838

        Abstract

        One of the periodic natural phenomena in life is temperature patterns.  A mathematical model based on periodicity called a sinusoidal temperature model has been formulated to describe and estimate the maximum and minimum temperature characteristics for the major cities in Georgia. The four parameters in the proposed sinusoidal temperature model that are used to predict or estimate temperature patterns are based on a thirty-year monthly means of the maximum and minimum temperature of cities in Georgia obtained from weather.com.  The model shows a high level of accuracy in predicting maximum and minimum temperature for major cities in Georgia.

        Author Biographies

        • Meagan Bridges, Savannah State University, USA

          Faculty: Department of Math

        • Jessica Foster, Savannah State University, USA

          Faculty: Department of Math

        • Samuel Luogon Dolo, Savannah State University, USA

          Faculty: Department of Math

        References

        Larson, A. Pre-calculus; 8th Edition, Brooks/Cole, 2007

        McCloskey, J.W. A model for atmospheric temperature. The Journal of Undergraduate mathematics and its Applications, Vol. II, No. 4, pages 5 – 12, 1981

        McCloskey, J.W. Seasonal Temperature Patterns of Selected cities in and Around Ohio. The Ohio Journal of Science, 86 (1), pages 5 – 10, 1986

        Wei, William. Time Series Analysis; 2nd Edition, Pearson, 2006

        Weather.com

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        Published

        2017-10-01

        How to Cite

        Bridges, M., Foster, J., & Dolo, S. L. (2017). A Sinusoidal Temperature Model for Major Cities in Georgia. International Journal for Innovation Education and Research, 5(10), 133-139. https://doi.org/10.31686/ijier.vol5.iss10.838