Theoretical and Applied Climatology

, Volume 120, Issue 1–2, pp 159–171 | Cite as

Spatio-temporal long-term (1950–2009) temperature trend analysis in North Carolina, United States

  • Mohammad SayemuzzamanEmail author
  • Manoj K. Jha
  • Ademe Mekonnen
Original Paper


This study analyzed long-term (1950–2009) annual and seasonal time series data of maximum and minimum temperature from 249 uniformly distributed stations across the State of North Carolina, United States. The Mann-Kendall and Theil-Sen approach were applied to quantify the significance and magnitude of trend, respectively. A pre-whitening technique was applied to eliminate the effect of lag-1 serial correlation. For most stations over the period of the past 60 years, the difference between minimum and maximum temperatures was found decreasing with an overall increasing trend in the mean temperature. However, significant trends (confidence level ≥ 95 %) in the mean temperature analysis were detected only in 20, 3, 23, and 20 % of the stations in summer, winter, autumn, and spring, respectively. The magnitude of the highest warming trend in minimum temperature and the highest cooling trend in maximum temperature was +0.073 °C/year in the autumn season and −0.12 °C/year in the summer season, respectively. Additional analysis in mean temperature trend was conducted on three regions of North Carolina (mountain, piedmont, and coastal). The results revealed a warming trend for the coastal zone, a cooling trend for the mountain zone, and no distinct trend for the piedmont zone. The Sequential Mann-Kendall test results indicated that the significant increasing trends in minimum temperature and decreasing trend in maximum temperature had begun around 1970 and 1960 (change point), respectively, in most of the stations. Finally, the comparison between mean surface air temperature (SAT) and the North Atlantic Oscillation (NAO) concluded that the variability and trend in SAT can be explained partially by the NAO index for North Carolina.


North Atlantic Oscillation North Atlantic Oscillation Index Mountain Zone Piedmont Zone Hydrometeorological Time Series 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



M. Sayemuzzaman like to express his special gratitude to Dr. Keith A. Schimmel, Chair in Energy and Environmental System Department for his supports. Authors also like to thank the anonymous reviewers for their suggestion to improve the contents of this paper.


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Copyright information

© Springer-Verlag Wien 2014

Authors and Affiliations

  • Mohammad Sayemuzzaman
    • 1
    Email author
  • Manoj K. Jha
    • 2
  • Ademe Mekonnen
    • 1
  1. 1.Energy and Environmental System DepartmentNorth Carolina A&T State UniversityGreensboroUSA
  2. 2.Department of Civil, Architectural and Environmental EngineeringNorth Carolina A&T State UniversityGreensboroUSA

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