Trend and Periodicity of Temperature Time Series in Ontario
Affiliation(s)
1 School of Engineering, Thornborough Building, University of Guelph, Guelph, Canada. 2 Engineer, Manitoba Government, Winnipeg, Canada.
1 School of Engineering, Thornborough Building, University of Guelph, Guelph, Canada. 2 Engineer, Manitoba Government, Winnipeg, Canada.
ABSTRACT
The trends and periodicities in the annual and seasonal temperature time series at fifteen weather stations within Ontario Great Lakes Basins have been analyzed, for the period 1941-2005, using the statistical analyses (Fourier series analysis, t-test, and Mann-Kendall test). The stations were spatially divided into three regions: northwest (NW), southwest (SW), and southeast (SE) to evaluate spatial variability in temperature. The results of the study reveal that the annual maximum mean temperature showed increasing trend for NW, and mixed trends for SW and SE regions. The variability was found to be more for northern stations as compared to southern stations for annual extreme minimum temperature. In addition, the trend slope per 100 years for the average annual extreme minimum temperature increased within the range of -0.8°C (Stratford) to 15°C (Porcupine). The seasonal analysis demonstrated that extreme maximum temperature has an increasing trend and maximum mean temperature has a decreasing trend during summer and winter. The extreme minimum temperature for winter illustrated an increasing trend (90%) with 22% statistically significant for NW region. For the SW region, the trend is also increasing (80%) for most of the temperature variables and 25% of temperature data were significantly increased in the SW region. The SE region stations showed overall very clear increasing trends (95%) for all the temperature variables. The data also showed that 47% of data were statistically significant in the SE region. The analysis of variance accounted for by trend, significant periodicities, and random component show that the pattern is similar for the percent of variance accounted for periodicities, and random component contribute dominantly for the four temperature variables and frost free days (FFD) for all three regions. Overall, the study reveals that the extreme minimum temperature is increasing annually and seasonally, with statistically significant at many stations.
The trends and periodicities in the annual and seasonal temperature time series at fifteen weather stations within Ontario Great Lakes Basins have been analyzed, for the period 1941-2005, using the statistical analyses (Fourier series analysis, t-test, and Mann-Kendall test). The stations were spatially divided into three regions: northwest (NW), southwest (SW), and southeast (SE) to evaluate spatial variability in temperature. The results of the study reveal that the annual maximum mean temperature showed increasing trend for NW, and mixed trends for SW and SE regions. The variability was found to be more for northern stations as compared to southern stations for annual extreme minimum temperature. In addition, the trend slope per 100 years for the average annual extreme minimum temperature increased within the range of -0.8°C (Stratford) to 15°C (Porcupine). The seasonal analysis demonstrated that extreme maximum temperature has an increasing trend and maximum mean temperature has a decreasing trend during summer and winter. The extreme minimum temperature for winter illustrated an increasing trend (90%) with 22% statistically significant for NW region. For the SW region, the trend is also increasing (80%) for most of the temperature variables and 25% of temperature data were significantly increased in the SW region. The SE region stations showed overall very clear increasing trends (95%) for all the temperature variables. The data also showed that 47% of data were statistically significant in the SE region. The analysis of variance accounted for by trend, significant periodicities, and random component show that the pattern is similar for the percent of variance accounted for periodicities, and random component contribute dominantly for the four temperature variables and frost free days (FFD) for all three regions. Overall, the study reveals that the extreme minimum temperature is increasing annually and seasonally, with statistically significant at many stations.
Cite this paper
Ahmed, S. , Rudra, R. , Dickinson, T. and Ahmed, M. (2014) Trend and Periodicity of Temperature Time Series in Ontario. American Journal of Climate Change, 3, 272-288. doi: 10.4236/ajcc.2014.33026.
Ahmed, S. , Rudra, R. , Dickinson, T. and Ahmed, M. (2014) Trend and Periodicity of Temperature Time Series in Ontario. American Journal of Climate Change, 3, 272-288. doi: 10.4236/ajcc.2014.33026.
References
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http://dx.doi.org/10.1623/hysj.48.1.51.43478 [20] Feidas, H., Makrogiannis, T. and Bora-Senta, E. (2004) Trend Analysis of Air Temperature Time Series in Greece and Their Relationship with Circulation Using Surface and Satellite Data: 1955-2001. Theoretical and Applied Climatology, 79, 185-208.
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http://dx.doi.org/10.1623/hysj.49.1.21.53996 [22] Kottegoda, N.T., Natale, L. and Raiteri, E. (2008) Stochastic Modelling of Periodicity and Trend for Multisite Daily Rainfall Simulation. Journal of Hydrology, 361, 319-329.
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http://dx.doi.org/10.1109/TGRS.1981.350324 [26] Friedlander, B. (1982) A Recursive Maximum Likelihood Algorithm for ARMA Spectral Estimation. IEEE Transactions on Information Theory, 28, 639-646.
http://dx.doi.org/10.1109/TIT.1982.1056531 [27] Friedlander, B. (1982) Systematic Identification Technique for Adaptive Signal Processing. Circuits, Systems and Signal Processing, 1, 3-41.
http://dx.doi.org/10.1007/BF01600032 [28] Kay, S.M. and Marple, S.L. (1981) Spectrum Analysis: A Modern Perspective. Proceedings of the Institute of Electrical and Electronic Engineering, 69, 1380-1419. [29] Rao, A.R., Jeong, G.D. and Chang, F.J. (1992) Estimation of Periodicities in Hydrological Data. Stochastic Hydrology and Hydraulics, 6, 270-288.
http://dx.doi.org/10.1007/BF01581621 [30] Chen, Z., Grasby, S.E., and Osadetz, K.G. (2004) Relation between Climate Variability and Groundwater Levels in the Upper Carbonate Aquifer, Southern Manitoba, Canada. Journal of Hydrology, 290, 43-62.
http://dx.doi.org/10.1016/j.jhydrol.2003.11.029 [31] Omidvari, M., Hassanzadeh, S. and Hosseinibalam, F. (2007) Time Series Analysis of Ozone Data in Isfahan. Journal of Physics A, 387, 4393-4403. [32] Easterling, D.R., Horton, B., Jones, P.D., Peterson, T.C., Karl, T.R., Parker, D.E., Salinger, M.J., Razuvayev, V., Plummer, N., Jamason, P. and Folland, C.K. (1997) Maximum and Minimum Temperature Trends for the Globe. Science, 277, 364-367.
http://dx.doi.org/10.1126/science.277.5324.364 [33] Machiwal, D. and Jha, M.K. (2008) Comparative Evaluation of Statistical Tests for Time Series Analysis: Application to Hydrological Time Series. Hydrological Sciences Journal, 53, 353-366.
http://dx.doi.org/10.1623/hysj.53.2.353 [34] Goosens, C. and Berger, A. (1986) Annual and Seasonal Climatic Variations over the Northern Hemisphere and Europe during the Last Century. Annales Geophysicae, Series B, 4, 385-400. [35] Onoz, B. and Bayazit, M. (2003) The Power of Statistical Tests for Trend Detection. Turkish Journal of Engineering and Environmental Sciences, 27, 247-251. [36] Sneyers, R. (1990) On the Statistical Analysis of Series of Observations. Technical Note No. 143, WMO No. 415, World Meteorological Organization, Geneva, 192 p. [37] Zhang, X., Vincent, L., Hogg, W.D. and Niitsoo, A. (2000) Temperature and Precipitation Trends in Canada during the 20th Century. Atmosphere-Ocean, 38, 395-429.
http://dx.doi.org/10.1080/07055900.2000.9649654 [38] Vincent, L.A., Zhang, X., Bonsal, B.R. and Hogg, W.D. (2002) Homogenization of Daily Temperatures over Canada. Journal of Climate, 15, 1322-1334.
http://dx.doi.org/10.1175/1520-0442(2002)015<1322:HODTOC>2.0.CO;2
[1] US Environmental Protection Agency (2013) Temperature.
http://www.epa.gov/climatechange/science/indicators/weather-climate/temperature.html [2] Mirza, M.Q., Warrick, R.A., Ericksen, N.J. and Kenny, G.J. (1998) Trends and Persistence in Precipitation in the Ganges, Brahmaputra and Meghna River Basins. Hydrological Sciences Journal, 43, 845-858.
http://dx.doi.org/10.1080/02626669809492182 [3] Astel, A., Mazerski, J., Polkowska, Z. and Namiesnik, J. (2004) Application of PCA and Time Series Analysis in Studies of Precipitation in Tricity (Poland). Advances in Environmental Research, 8, 337-349.
http://dx.doi.org/10.1016/S1093-0191(02)00107-7 [4] Costain, J.K. and Bollinger, G.A. (1996) Climatic Changes, Streamflow, and Long-Term Forecasting of Intraplate Seismicity. Journal of Geodynamics, 22, 97-117. [5] Milhous, R.T. (2003) Mixing Physical Habitat and Streamflow Time Series Analysis. Colorado State University, Office of Conference Services, Fort Collins, 21 p. [6] Yildirim, Y.E., Turkes, M. and Tekiner, M. (2004) Time-Series Analysis of Long-Term Variations in Stream-Flow Data of Some Stream-Flow Stations over the Gediz Basin and in Precipitation of the Akhisar Station. Pakistan Journal of Biological Sciences, 7, 17-24.
http://dx.doi.org/10.3923/pjbs.2004.17.24 [7] Chen, C.S., Liu, C.H. and Su, H.C. (2008) A Nonlinear Time Series Analysis Using Two-Stage Genetic Algorithms for Streamflow Forecasting. Hydrological Processes, 22, 3697-3711.
http://dx.doi.org/10.1002/hyp.6973 [8] Shao, Q., Wong, H., Li, M. and Ip, W.C. (2009) Streamflow Forecasting Using Functional-Coefficient Time Series Model with Periodic Variation. Journal of Hydrology, 368, 88-95.
http://dx.doi.org/10.1016/j.jhydrol.2009.01.029 [9] Kite, G. (1989) Use of Time Series Analyses to Detect Climatic Change. Journal of Hydrology, 111, 259-279.
http://dx.doi.org/10.1016/0022-1694(89)90264-3 [10] Khan, A.R. (2001) Analysis of Hydro-Mateorological Time Series in the Upper Indus Basin: Searching Evidence for Climatic Change. International Water Management Institute, Working Paper 23, Pakistan Country Series Number 7, Colombo. [11] Bani-Domi, M. (2005) Trend Analysis of Temperatures and Precipitation in Jordan. Umm Al-Qura University Journal of Educational, Social Sciences & Humanities, 17, 1-36. [12] Gan, T.Y. (2007) Trends in Air Temperature and Precipitation for Canada and North-Eastern USA. International Journal of Climatology, 15, 1115-1134.
http://dx.doi.org/10.1002/joc.3370151005 [13] Mann, H.B. (1945) Non-Parametric Tests against Trend. Econometrica, 13, 245-259. [14] Kendall, M.G. (1975) Rank Correlation Measures. Charles Griffin, London. [15] ven Belle, G. and Hughes, J.P. (1984) Nonparametric Tests for Trend in Water Quality. Water Resources Research, 20, 127-136. [16] Cailas, M.D., Cavadias, G. and Gehr, R. (1986) Application of a Nonparametric Approach for Monitoring and Detecting Trends in Water Quality Data of the St. Lawrence River. Water Pollution Research Journal of Canada, 21, 153-167. [17] Hipel, K.W., McLeod, A.I. and Weiler, R.R. (1988) Data Analysis of Water Quality Time Series in Lake Erie. JAWRA: Journal of the American Water Resources Association, 24, 533-544.
http://dx.doi.org/10.1111/j.1752-1688.1988.tb00903.x [18] Chiew, F.H.S. and McMohan, T.A. (1993) Detection of Trend or Change in Annual Flow of Australian Rivers. International Journal of Climatology, 13, 643-653.
http://dx.doi.org/10.1002/joc.3370130605 [19] Yue, S., Pilon, P.J., and Phinney, B. (2003) Canadian Streamflow Trend Detection: Impacts of Serial and Cross-Correlation. Hydrological Sciences Journal, 48, 51-63.
http://dx.doi.org/10.1623/hysj.48.1.51.43478 [20] Feidas, H., Makrogiannis, T. and Bora-Senta, E. (2004) Trend Analysis of Air Temperature Time Series in Greece and Their Relationship with Circulation Using Surface and Satellite Data: 1955-2001. Theoretical and Applied Climatology, 79, 185-208.
http://dx.doi.org/10.1007/s00704-004-0064-5 [21] Yue, S. and Pilon, P. (2004) A Comparison of the Power of the t Test, Mann-Kendall and Bootstrap Tests for Trend Detection. Hydrological Sciences Journal, 49, 21-37.
http://dx.doi.org/10.1623/hysj.49.1.21.53996 [22] Kottegoda, N.T., Natale, L. and Raiteri, E. (2008) Stochastic Modelling of Periodicity and Trend for Multisite Daily Rainfall Simulation. Journal of Hydrology, 361, 319-329.
http://dx.doi.org/10.1016/j.jhydrol.2008.08.008 [23] Burg, J.P. (1967) Maximum Entropy Spectral Analysis. Proceedings of 37th Meeting, Society of Exploration Geophysics, Oklahoma City. [24] Marple, L. (1980) A New Autoregressive Spectrum Analysis Algorithm. IEEE Transactions on Acoustics, Speech and Signal Processing, 28, 441-454. [25] Cadzow, J.A. (1981) Autoregressive Moving Average Spectral Estimation: A Model Equation Error Procedure. IEEE Transactions on Geoscience and Remote Sensing, 19, 24-28.
http://dx.doi.org/10.1109/TGRS.1981.350324 [26] Friedlander, B. (1982) A Recursive Maximum Likelihood Algorithm for ARMA Spectral Estimation. IEEE Transactions on Information Theory, 28, 639-646.
http://dx.doi.org/10.1109/TIT.1982.1056531 [27] Friedlander, B. (1982) Systematic Identification Technique for Adaptive Signal Processing. Circuits, Systems and Signal Processing, 1, 3-41.
http://dx.doi.org/10.1007/BF01600032 [28] Kay, S.M. and Marple, S.L. (1981) Spectrum Analysis: A Modern Perspective. Proceedings of the Institute of Electrical and Electronic Engineering, 69, 1380-1419. [29] Rao, A.R., Jeong, G.D. and Chang, F.J. (1992) Estimation of Periodicities in Hydrological Data. Stochastic Hydrology and Hydraulics, 6, 270-288.
http://dx.doi.org/10.1007/BF01581621 [30] Chen, Z., Grasby, S.E., and Osadetz, K.G. (2004) Relation between Climate Variability and Groundwater Levels in the Upper Carbonate Aquifer, Southern Manitoba, Canada. Journal of Hydrology, 290, 43-62.
http://dx.doi.org/10.1016/j.jhydrol.2003.11.029 [31] Omidvari, M., Hassanzadeh, S. and Hosseinibalam, F. (2007) Time Series Analysis of Ozone Data in Isfahan. Journal of Physics A, 387, 4393-4403. [32] Easterling, D.R., Horton, B., Jones, P.D., Peterson, T.C., Karl, T.R., Parker, D.E., Salinger, M.J., Razuvayev, V., Plummer, N., Jamason, P. and Folland, C.K. (1997) Maximum and Minimum Temperature Trends for the Globe. Science, 277, 364-367.
http://dx.doi.org/10.1126/science.277.5324.364 [33] Machiwal, D. and Jha, M.K. (2008) Comparative Evaluation of Statistical Tests for Time Series Analysis: Application to Hydrological Time Series. Hydrological Sciences Journal, 53, 353-366.
http://dx.doi.org/10.1623/hysj.53.2.353 [34] Goosens, C. and Berger, A. (1986) Annual and Seasonal Climatic Variations over the Northern Hemisphere and Europe during the Last Century. Annales Geophysicae, Series B, 4, 385-400. [35] Onoz, B. and Bayazit, M. (2003) The Power of Statistical Tests for Trend Detection. Turkish Journal of Engineering and Environmental Sciences, 27, 247-251. [36] Sneyers, R. (1990) On the Statistical Analysis of Series of Observations. Technical Note No. 143, WMO No. 415, World Meteorological Organization, Geneva, 192 p. [37] Zhang, X., Vincent, L., Hogg, W.D. and Niitsoo, A. (2000) Temperature and Precipitation Trends in Canada during the 20th Century. Atmosphere-Ocean, 38, 395-429.
http://dx.doi.org/10.1080/07055900.2000.9649654 [38] Vincent, L.A., Zhang, X., Bonsal, B.R. and Hogg, W.D. (2002) Homogenization of Daily Temperatures over Canada. Journal of Climate, 15, 1322-1334.
http://dx.doi.org/10.1175/1520-0442(2002)015<1322:HODTOC>2.0.CO;2