Examination of relationship between teleconnection indexes on temperature and precipitation components (Case Study: Karaj Synoptic Stations)

Document Type : Research Article


1 Assistant Professor, Soil Conservation and Watershed Management Research Institute SCWMRI, Tehran

2 PhD Student, Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar

3 PhD, Faculty of Human Science, Mohaghegh Ardabili University, Ardabil


Over the recent decades, human knowledge on earth's climate and his concern about climate change in the future has increased, which has contributed to precise identification of the factors influencing earth's climate. One of the climate phenomena, the change of which causes great anomalies of climate, particularly on temperature and precipitation patterns in many parts of the world, is teleconnection, and it is very important to  reveal the relationship between them and climatic parameters for a better understanding of volatility and climate variability in every area. In this study, the relationship between large-scale and well-known patterns such as the Southern Oscillation Index (SOI), North Atlantic oscillation (NAO), Pacific North America (PNA), Multivariate ENSO Index (MEI) and (PDO) with 9 temperature and precipitation variables in the Karaj synoptic station in a monthly basis were analyzed over the 26-year period (2010-1985). First, the normality of the data series based on the Kolmogorov - Smirnov was confirmed. In order to examine the relationship between large-scale patterns with temperature and precipitation variables, the Pearson correlation coefficient was used. The correlations were assessed on a monthly basis without delay and a delay of one month. The results showed that there is a relationship between the NAO index and the temperature and precipitation variables mostly in autumn and winter months and the impact on the autumn months is higher than the winter months. SOI index is more related with the precipitation variables; this index was clearly shown to play a greater role in autumn and winter months, while the MEI index shows a higher correlation with the temperature variables and not particular relation was shown with precipitation variables for this index. Role and impact of this index, in particular on temperature parameters of April and May in spring and December in late autumn, is stronger. The relationship of PDO index with temperature and precipitation variables in May is observed more in the middle of spring. PNA index is effective only on temperature variables, showing higher relationship in December and February. The obtained results are important for greater understanding of the temperature and precipitation variability.


Main Subjects

[1].      Rodriguez-Puebla, C, Encinas, A H. Nieto, S, Garmendia, J, 1998, Spatial and temporal patterns of annual precipitation variability over the Iberian Peninsula. International Journal of Climatology, 18(3): 299-316.
[2].      GhvidelRahimi, Y, Farajzadeh, M, Hatami, D, 2015, Analysis of the relationship between the North Sea - Caspian pattern and minimum temperatures in Iran, Journal of geographical space 5: 137 -159. [Persian]
[3].      Ahmadi. M, 2014, Analyzing on the relationship among Teleconnection Patterns (TP) and Iran’s Precipitation Characteristics (IPC). PhD Thesis, Geographical and Remote sensing Department, Faculty of Humanities, Tarbiat Modares University. [Persian]
[4].      GhvidelRahimi, Y, Farajzadeh, M, Kakapour, S, 2014, Study the affecting of North Sea - Caspian pattern on autumn rainfall fluctuations in the West and Northwest regions of Iran. Journal of Geography and Planning, 49: 217 -230. [Persian]
[5].      Kkosravi, M, ,2004, Study of relationship between atmospheric circulation macro-scale patterns of Northern Hemisphere with drought in Sistan and Baluchestan, geography and development, 3: 167-188. [Persian]
[6].      Karamouz M., Ramezani, F., Razavi, S, 2007, Forecasting the long-term of rainfall through meteorological signals: Application of Artificial Neural Networks, Seventh International Congress on Civil Engineering. Tehran, 11 p. [Persian]
[7].      Hazrati, SH, Abrishamchi, A, Tajrishi, M, 2004, Investigating the Effects of north and south Atlantic Oscillation on temperature and precipitation in Urmia Lake basin, First National Congress of Civil Engineering, 8p. [Persian]
[8].      Walker, 1924, Correlation in seasonal variations of weather, Mem. India Meteorological department, 24: 75-131.
[9].      Bhutiyani, M. R. Kale, V S, Pawar, N. J, 2010, Climate change and the precipitation variations in the northwestern Himalaya: 1866–2006. International Journal of Climatology, 30(4): 535-548.
[10].   Tremblay, L., Larocque, M., Anctil, F., Rivard, C, 2011, Teleconnections and interannual variability in Canadian groundwater levels. Journal of Hydrology, 410(3): 178-188.
[11].   Rampelotto P.H. Rigozo N.R. da Rosa M.B. Prestes A. Frigo E. Souza Echer M.P. Nordemann D.J.R, 2012, Variability of rainfall and temperature (1912–2008) parameters measured from Santa Maria (29°41′S, 53°48′W) and their connections with ENSO and solar activity, Journal of Atmospheric and Solar-Terrestrial Physics, 77: 152-160.
[12].   Rasanen, T A, Kummu, M, 2013, Spatiotemporal influences of ENSO on precipitation and flood pulse in the Mekong River Basin, Journal of Hydrology, 476: 154-168.
[13].   Hamedani Azmoodehfar, M. Azarmsa, S.A, 2013, Assessment the Effect of ENSO on Weather Temperature Changes Using Fuzzy Analysis (Case Study: Chabahar). PCBEE Procedia, 5: 508 – 513.
[14].   Daneshmand, H., Tavousi, T., Khosravi, M., Tavakoli, S, 2015, Modeling minimum temperature using adaptive neuro-fuzzy inference system based on spectral analysis of climate indices: A case study in Iran. Journal of the Saudi Society of Agricultural Sciences, 14(1): 33-40.
[16].   Beck, F., Bárdossy, A., Seidel, J., Müller, T., Sanchis, E. F., Hauser, A, 2015, Statistical analysis of sub-daily precipitation extremes in Singapore. Journal of Hydrology: Regional Studies, 3: 337-358.
[17].   Salahi, B, KhorshidDoust, A M, Ghavidel, Y, 2004, The Relationship of North Atlantic Oscillation with drought in East Azerbaijan, Geographical Research, 60: 147 -156. [Persian]
[18].   Alizade, A, Erfaniyan, M, Ansari, H, 2001, Study the affecting of Telecanection patterns on temperature and precipitation parameters (Case Study: Mashhad synoptic station). Journal of Irrigation and Drainage, 2: 176-185. [Persian]
[19].   Hosseini, SA., Failiyan, KH., Rahmani, S., Amiri, A., Yaghoubi, F, 2013, Relationship between signals meteorological with winter precipitation and temperature of Saqez and Sanandaj synoptic stations, the second conference on the role of geography in environmental planning of the third millennium, PNU center of Saghez, 6p.[Persian]
[20].   Salahi, B, Hajizadeh, Z, 2013, Analysis of the relationship North Atlantic Oscillation and surface temperatures variability of the Atlantic with rainfall and temperature of Lorestan province, Geographical Research, 28(3):119-130. [Persian]
[21].   FatehiMerej, A, Tajdini, M, Salajegheh, A, 2015, The relationship between climatic signals (SOI, MEI, NINO, NAO) and drought in Kerman province, Journal of Agricultural Meteorology, 3(1): 25-39. [Persian]
[22].   Javari, M, 2010 Methods of quantitative analysis in climatology (with an emphasis on seasonal models), first edition, Payamrasan press, p 17. [Persian]
[23].   Alijani, B, 2009, Synoptic climatology, Samt, Tehran. [Persian]
[24].   Asakereh, H, 2007, Climate change, first edition, Zanjan University Press, Zanjan. [Persian]
[25].   Masoudian, S A, 2005, Study of Iran rainfall associated with ENSO, geography and regional development, (4): 73-82.[Persian]
Volume 4, Issue 3
September 2017
Pages 641-651
  • Receive Date: 01 October 2016
  • Revise Date: 25 July 2017
  • Accept Date: 24 May 2017
  • First Publish Date: 23 September 2017