Assessing the impact of cold and warm ENSO on drought over Iran

Document Type: Original Article


1 Department of Geomatics Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran

2 Babol Noshirvani University of Technology, Civil Engineering Department, P.O.Box 484, Shariati Ave, Babol,Mazandaran 47148-71167, Iran


The impacts of El Niño Southern Oscillation (ENSO) on climate change and in the global scale are well
known, and have attracted the attention of researchers since the twentieth century. The study of ENSO
impact on climate using precipitation and near surface temperature data from re-analysis products makes
global and long-term analyses of this phenomenon possible. The common method to analyze the ENSO
impact is to quantify the probability of extreme drought occurrences when the surface temperatures of
central-east equatorial Pacific sea are abnormal. Although the results are always uncertain due to the
complexity of atmospheric teleconnections, application of the recently available gridded datasets helps one
to conduct more precise modeling and predictions. Spatiotemporal patterns of ENSO impact from 1980 to
the end of 2013 for four ENSO indices (e.g. Nino 3.4, MEI, ONI, SOI) over Iran was investigated in this
study. Spatial maps of the Pearson correlation coefficients and a composite analysis were obtained between
the GPCC precipitation and temperature dataset with ENSO states. In addition, the frequency maps of
extreme drought conditions during ENSO states were acquired. The results show that the western (along the
range of Zagros Mountain) and northern (along the Alborz Mountain and the coastlines of the Caspian Sea
to Khorasan Province) regions are more affected by ENSO events. The Pearson correlation coefficient for
all four ENSO indices over the mentioned regions was determined to be about 0.70 for precipitation datasets
and -0.70 for temperature datasets. The frequency analysis of extreme drought based and CZI (Chinese Z
Index) and ENSO phases shows that the western and northeast parts of Iran are more affected by centraleast equatorial Pacific teleconnections. Composite analysis for all four ENSO indices shows the precipitation
(over the rainy months)/temperature (over the summer months) anomalies, for the El Niño states about +25
(mm)/ -0.5˚ (C) and for the La Niña states about -25 (mm)/+0.6˚ to 1˚ (C).


Main Subjects

Agnew, C.T. & Chappel, A. (1999). Drought in the Sahel, Geo J., 48, 299-311.
Allan, R.J. & Pariwono, J.I. (1990). Ocean-atmosphere interactions in low-latitude Australia. Int. J. Climatol., 10, 145–178.
Alexander, L. V., Zhang, X., Peterson, T. C., et al., (2006). Global observed changes in daily climate extremes of temperature and precipitation,” Journal of Geophysical Research Atmospheres, vol. 111, no. 5, Article ID D05109, pp. 1–22.
Ashok, K., Behera, S. K., Rao, S. A., Weng, H., & Yamagata, T. (2007). El Niño Modoki and its possible teleconnection. Journal of Geophysical Research: Oceans, 112(C11).
Boschat, G., Simmonds, I., Purich, A., Cowan, T., & Pezza, A. B. (2016). On the use of composite analyses to form physical hypotheses: An example from heat wave–SST associations. Scientific reports, 6, 29599.
Brönnimann, S. (2007). Impact of El Niño–Southern Oscillation on European climate. Rev. Geophys. 45, RG3003.
Davey, M.K., Brookshaw, A. & Ineson, S. (2014). The probability of the impact of ENSO on precipitation and near-surface temperature. Clim. Risk Manag. 1, 5–24. (doi:10.1016/j.crm.2013.12.002).
Dore, M. H. I. (2005). Climate change and changes in global precipitation patterns: what do we know? Environment International, vol. 31, no. 8, pp. 1167–1181
Frederiksen, C.S. & Balgovind, R.C. (1994). The influence of the Indian Ocean: Indonesian SST gradient on the Australian winter rainfall and circulation in an atmospheric GCM. Q. J. R. Meteorol. Soc., 120, 923–952.
Harrison, D. E. & Larkin, N. K. (1998). Seasonal U.S. temperature and precipitation anomalies associated with El Niño: Historical results and comparison with 1997–98. Geophys. Res. Lett., 25(21), 3959–3962.
Kahya, E. & Dracup, J.A. (1993). US streamflow patterns in relation to the El Niho: Southern Oscillation. Water Resour. Res., 29, 2491–2503.
Kang, I.-S., & Kug, J.-S. (2002). El Nin˜o and La Nin˜ a sea surface temperature anomalies: Asymmetry characteristics associated with their wind stress anomalies. J. Geophys. Res., 107, 4372, doi:10.1029/2001JD000393.
Kao, H. Y., & Yu, J. Y. (2009). Contrasting eastern-Pacific and central-Pacific types of ENSO. Journal of Climate, 22(3), 615-632.
Kendall, M., & Stuart, A. (1977). The advanced theory of statistics. Vol. 1: Distribution theory. London: Griffin, 1977, 4th ed.
Kug, J. S., Sooraj, K. P., Kim, D., et al. (2009). Simulation of state-dependent high-frequency atmospheric variability associated with ENSO. Clim Dyn 32:635–48.
Kug, J. S., Jin, F. F., & An, S. I. (2009). Two types of El Niño events: cold tongue El Niño and warm pool El Niño. Journal of Climate, 22(6), 1499-1515.
Larkin, N. K., & Harrison, D. E. (2005). On the definition of El Niño and associated seasonal average US weather anomalies. Geophysical Research Letters, 32(13).
Li, W., Zhai, P. & Cai, J. (2011). Researeh on the Relationship of ENSO and the Frequeney of Extreme Precipitation Events in China. Advances in Climate Change Research 2, 101–107
Mo, K. C. (2010). Inter decadal modulation of the impact of ENSO on precipitation and temperature over the United States. J Climate 23: 3639–56.
Nazemosadat, M. J., & Cordery, I. (2000). On the relationships between ENSO and autumn rainfall in Iran. International Journal of Climatology, 20(1), 47-61.
New, M., Todd, M., Hulme, M. & Jones, P. (2001). Precipitation measurements and trends in the twentieth century. International Journal of Climatology, vol. 21, no. 15, pp. 1899–1922.
Salehnia, N., Alizadeh, A., Sanaeinejad, H., Bannayan, M., Zarrin, A., & Hoogenboom, G. (2017). Estimation of meteorological drought indices based on AgMERRA precipitation data and station-observed precipitation data. Journal of Arid Land, 9(6), 797-809.
Schneider, U., Fuchs, T., Meyer-Christoffer, A., & Rudolf, B. (2008). Global precipitation analysis products of the GPCC. Global Precipitation Climatology Centre (GPCC), DWD, Internet Publikation, 112.
Shimola, K. &Krishnaveni, M. (2014). A study on rainfall variability and its pattern in a semi-arid basin, Tamil Nadu, India, Disaster Advances.
Sivakumar, M., Gommes, R. & Baier, W. (2000). Agrometeorology and sustainable agriculture. Agric. Forest Meteorol, 103, 11–26.
Wu, G.-X. & Zhang, X.-H. (1996). Research in China on climate and its variability. Theor. Appl. Climatol., 55, 3–17.
Yeh, S. W., Kug, J. S., Dewitte, B., Kwon, M. H., Kirtman, B. P., & Jin, F. F. (2009). El Niño in a changing climate. Nature, 461(7263), 511.
Yu, J., Kao, H, & Lee T (2010). Subtropics-related inter annual sea surfacetemperature variability in the central equatorial Pacific. J Climate23:2869–84.
Zoljoodi, M., & Didevarasl, A. (2013). Evaluation of spatial–temporal variability of drought events in Iran using palmer drought severity index and its principal factors (through 1951–2005). Atmos Clim Sci, 3, 193-207.