ORIGINAL PAPER Spatio-temporal long-term (1950–2009) temperature trend analysis in North Carolina, United States Mohammad Sayemuzzaman & Manoj K. Jha & Ademe Mekonnen Received: 14 August 2013 /Accepted: 30 March 2014 # Springer-Verlag Wien 2014 Abstract 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 mag- nitude 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 re- vealed 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 ex- plained partially by the NAO index for North Carolina. 1 Introduction Surface air temperature is an important climatic parameter, and its variability severely affects hydrological processes and the environment. Understanding and being able to predict its spatial and temporal variability both at the local and global scales is a challenging task (Shi and Xu 2008; Moral 2009; Xu et al. 2010; Ceppi et al. 2012). The Intergovernmental Panel on Climate Change (IPCC)’ s 4th Assessment Report (AR4) reported 0.74 °C (range 0.56 to 0.92 °C) increment in global mean air temperature over the past 100 years (1906–2005). Degaetano and Allen (2002) analyzed the extreme tempera- ture trends across the United States and found a significant increase in extreme temperature (both maximum and mini- mum) over the 1950–96 periods, particularly at urban sites. Wang et al. (2009) found warming temperature trends of surface air temperature (mean) during the winter (DJF), spring (MAM), and early summer (JJA) along with a modest coun- trywide cooling trend in late summer and autumn (SON). Trenberth et al. (2007) concluded that the Southeastern United States is one of the few regions of the Earth showing a cooling trend during the twentieth century. Portmann et al. (2009) added that this cooling trend is strongest in the late spring–early summer period. However, Wang et al. (2009) found a countrywide cooling trend in the late summer and autumn. Robinson et al. (2002) showed that annually-averaged air tem- peratures in the southern Great Plains have decreased during 1988–1997 from those of 1951–1980. In the very recent study of Rogers (2013), it show similar findings with previous researchers that the portions of the Southern and Southeastern United States are experiencing downward air temperature trends in all the seasons from 1895–2007. Extremely warm or freezing M. Sayemuzzaman (*) : A. Mekonnen Energy and Environmental System Department, North Carolina A&T State University, Greensboro, NC 27411, USA e-mail: msayemuz@aggies.ncat.edu M. K. Jha Department of Civil, Architectural and Environmental Engineering, North Carolina A&T State University, Greensboro, NC, USA Theor Appl Climatol DOI 10.1007/s00704-014-1147-6