Investigation of the relationship of NINO4 and NAO indices with meteorological drought in synoptic stations in northern Iran

Authors

1 PhD Student of Watershed Management, Dept. of Watershed & Rangland, Gorgan University of Agriculture and Natural Resources, Gorgan, Iran

2 Prof. of Rangland and Watershed, Dept. of Natural Resources, Isfahan University of Technology, Isfahan. Iran

3 Assoc. Prof. of Rangland and Watershed, Dept. of Natural Resources, Isfahan University of Technology, Isfahan, Iran

Abstract

Background and Objectives: Water shortages in a defined area and in a certain period are called drought. This phenomenon is time dependent rather than aridity, and it is quitely temporary. drought in various regions of Iran in arid, semi-arid and even humid areas shows different forms and causes great damage. Drought is calculated using indices such as precipitation and evapotranspiration. The teleconnection is also a new branch of synoptic climatology, which recognizes the relationships between phenomena and climatic elements such as rainfall, drought, and temperature in remote locations. In other words, teleconnection patterns are the occurrence and continuation of large scale models of circulation abnormalities and air pressure that extend over a wide geographical range. These patterns are also oscillatory behavior of low frequencies. Teleconnection mechanisms are one of the important issues in justifying the behavior of the climate, and its effects do not always appear in the same form everywhere (Khosravi, 2004). In worldwide, many studies have been done on climate signals in variety ways. Iran is also affected by rainfall systems, which affects the pattern of rainfall and drought in it.
Methodology: The purpose of this study was to investigate the relationship between NINO4 and NAO indices with meteorological droughts in synoptic stations in the southern part of the Caspian Sea. For this purpose, data of rainfall were obtained monthly from the Meteorological Organization of Iran. Then, SPI was calculated for different time scales of months including 1, 3, 6, 9, 12, 15, 18, 24, 48. The next step was to obtain the values of the Ocean Atmospheric indices, including NINO4 and NAO, at the monthly scale from the Australian Meteorological Organization. For analysis, the MINITAB16, SPSS16 was used. In this case, the simultaneous and asynchronous relationship between the time series of SPI and the NAO and NINO4 indices was determined. In this stage, Spearman's correlation test and cross-correlation function were determined. In the next step, regression modeling was done. In this way, regression models for the time series of SPI were calculated taking into the simultaneous and asynchronous state of the NAO and NINO4 indices. The lag times were 1-6, 12, 24, 48 months. Finally, errors for regression models were determined at all stations to select the best model.
Findings: The results showed relationships between NAO with SPI different series at Ardabil and Babolsar stations in January, April, August and December; the NINO4 with SPI at Ardebil station in all months except October and December. Also, the results of regression equations showed that in SPI time series of NINO4 with the highest coefficient, the highest and NAO with lowest coefficient, had the lowest effect on drought in studied areas. In this case, the Ardabil has the highest coefficient in SPI24 months. At the end, the error statistics including RMSE, R, R2, CE were calculated for model reliability and calculation of errors.
Conclusion: In this case, the best model was found at the Gorgan station by calculating the error statistics. The result suggests that these stations are neighbor to the Caspian Sea, which has affected the rainfall and drought pattern of the regions. This can also be the result of the universality of the Enso phenomenon that affects the world's climate. In order to obtain better results, it is recommended to study the precipitation and temperature pattern of these areas with other Ocean Atmospheric indices such as SOI and AO. Regarding the fact that the distant teleconnection indices do not occur in all directions in one way, it is suggested to study rainfall and temperature pattern of other parts of Iran in relation to climate signals. This study is also in line with another study by researchers who through statistical and synoptic methods have investigated the relationship between climatic factors such as rainfall and temperature with climatic signals. Study of other researchers determine that there is a significant relationship between the annual rainfall of Iran and the South Oscillation Index.
temperature pattern of these areas with other Ocean Atmospheric indices such as SOI and AO. Regarding the fact that the distant teleconnection indices do not occur in all directions in one way, it is suggested to study rainfall and temperature pattern of other parts of Iran in relation to climate signals. This study is also in line with another study by researchers who through statistical and synoptic methods have investigated the relationship between climatic factors such as rainfall and temperature with climatic signals. Study of other researchers determine that there is a significant relationship between the annual rainfall of Iran and the South Oscillation Index.

Keywords


Ahmadigivi F and Parhizgar D, 2008. Investigating the effect of Enso on the distribution of seasonal rainfall in Iran in the period 1971-2000. Journal of Earth and Space Physics 35 (4): 25-37 (In Persian with English abstract).
Baqerzadehchehreh K, 2004. Evaluation of meteorological signals in drought prediction using artificial neural networks in Tehran province. Master Thesis. Faculty of Agriculture. Tarbiat Modares University (In Persian with English abstract).
Bayatvarkashi M and Shirmohammadi N, 2019. Investigation of the effect of drought and Enso on changes in surface water flow in Hamedan and Zanjan provinces. Earth Knowledge Research 10 (40): 1-17 (In Persian with English abstract).
Ghavidelrahimi Y, Farajzadeh M and Kakapour S, 2014. Investigation of the effect of teleconnection pattern from the North-Caspian Sea on the oscillations of autumn rainfall in the western and northwestern regions of Iran. Journal of Geography and Planning 18 (49): 217-230 (In Persian with English abstract).
Ildromi A, Nouri H and Bayatvarkashi M, 2017. Investigating the relationship between Enso and the occurrence of drought in Iran. Journal of Soil and Water Science 27 (2): 143-156 (In Persian with English abstract).
Karimi A and Bazrafshan A, 2016. Investigating the effect of Enso on droughts and wetlands in Hormozgan province. First International Conference on Water, Environment and Sustainable Development. September 27-29. University of Mohaghegh Ardabili, Ardabil (In Persian with English abstract).
Khanitemeliyeh Z, Rezaei H and Mirabbasi Najafabadi R, 2020. Bivariate analysis of drought risk in west and northwest of Iran using PSO algorithm and copula functions. Journal of Water and Soil Conservation 27(3): 125-144 (In Persian with English abstract).
Khoshakhlaq F, Ghanbari N and Masoom Poursamakoush J, 2008. Study of the effects of North Atlantic oscillation on precipitation regime and temperature of the southern shores of the Caspian Sea. Quarterly Journal of Geographical Research 66: 70-57 (In Persian with English abstract).
Lamb PJ and Peppler RA, 1987. North Atlantic Oscillation: Concept and an application. Bulletin of the American Meteorological Society 68: 1218 – 1225.
Mckee TB, Doesken NJ and Kleist J, 1993.The relationship of drought frequency and duration to time scales. Pp.176-184. 8th conference on Applied Climatology. January 17- 22, Anaheim, California.
Modarres R, 2006. Regional precipitation climates of Iran. Journal of Hydrology 45: 13-27.
Mokhtari A, Islamian SS and Mousavi SF, 2011. Study of drought indices and fluctuations in Iran with the help of ocean fluctuation indices. Master Thesis in Irrigation and Drainage. School of Agriculture. Isfahan University of Technology (In Persian with English abstract).
Moradi H, 2004. North Atlantic Oscillation Index and its impact on Iran's climate. Journal of Geographical Research 48: 30-17 (In Persian with English abstract).
Nasiri B, Naserzadeh MH, Toulabi Nejad M and Zarei Choghablaki Z, 2016. Effect of Enso Atmospheric-Large-Scale pattern on discharge of Kashkanrod. Journal of Hydrogeomophology 2(5): 141-166 (In Persian with English abstract).
NazemoSadat MJ and Ghasemi A, 2004. The effect of water temperature fluctuations in the Caspian Sea on winter and spring rainfall in the northwestern regions of southwestern Iran. Journal of Agricultural Science and Technology and Natural Resources 4: 14-17 (In Persian with English abstract).
Rahimi D, Abdullahi Kh and Hashemi Nasab S, 2016. Identification of teleconnection pattern on precipitation in Karun basin. Journal of Eco Hydrology 3 (1): 95-105 (In Persian with English abstract).
Roughani R, Sultani S and bashari H, 2010. Study of rainfall changes in Iran with the help of atmospheric oceanic indicators. Master Thesis in Watershed Management. Faculty of Natural Resources. Isfahan University of Technology (In Persian with English abstract).
Samali R, Bazrafshan O, Biniaz M and Musliemi H, 2018. Review the relationship between Enso on droughts and wetlands in the southern coastal provinces of Iran. Iranian Journal of Irrigation and Drainage 1(13): 217-231.
Sedaghat Kerdar A and Fatahi E, 2008. Drought precautionary indicators in Iran. Journal of Geography and Development (11): 76-59 (In Persian with English abstract).
Schongart J and Junk WJ, 2007. Forecasting the flood-pulse in central Amazonia by ENSO indices. Journal of Hydrology 335:124-132.
Shoyokhi Soghanloo S, 2019. The effect of remote linking patterns (large-scale climatic signals) on rainfall in Mazandaran province, The Third National Conference on Water Resources Management in Coastal Areas. October 10 .Sari (In Persian with English abstract).
Syed FS, Giorgi F, Pal JS and King MP, 2006. Effect of remote forcing on the winter precipitation of central Southwest Asia part1: observation. Theoretical and Applied Climatology 86:147-160.
Thom HCS, 1958. A note on gamma distribution. Monthly Weather Review 86: 117–122.
Turkes M and Erlat E, 2005. Climatological responses of winter precipitation in Turky to variability of the North Atlantic Oscillation during the period 1930-2001. Theoretical and Applied Climatology 78: 33-46.
Rodo X and Baert E, 1997. Variation in seasonal rainfall in Southern Europe during the
present century: Relationships with the North Atlantic Oscillation an the El Nino- SouthernOscillation. Climate Dynamics 13:275-28.
Walker GT, 1923. Correlation in seasonal variations of weather, part VIII: A preliminary study of world weather. Memoirs of the India Meteorological Department 24(4): 75-131.
Yar Ahmadi D and Azizi Q, 2007. Multivariate analysis of the relationship between seasonal rainfall in Iran and climatic indicators. Journal of Geographical Research 62: 174-161(In Persian with English abstract).
Zareabyaneh H, 2014. The effect of Enso on the variability of surface water resources in Hamadan province. Journal of Soil and Water Science 24 (4): 153-167(In Persian with English abstract).