Study of the Effect of NAO on Precipitation in Iran Using Network Analysis Aproach from November to April of the 1979-2016

Document Type : Research Article

Authors

1 Ph.D. Student, Department of Irrigation and Reclamation Engineering, Natural Resources and Agricultural Campus, University of Tehran, Karaj, Iran

2 Associate Professor, Department of Irrigation and Reclamation Engineering, Natural Resources and Agricultural Campus, University of Tehran, Karaj, Iran

3 Assistant Professor, Department of Irrigation and Reclamation Engineering, Natural Resources and Agricultural Campus, University of Tehran, Karaj, Iran

4 Associate Professor, Department of Space Physics, Institute of Geophysics, University of Tehran, Tehran, Iran

Abstract

Displaying and quantifying how large-scale climatic signals affect the regional and global climate is one of the issues of interest to researchers. New approch of Network Analysis enables us to study a complex system such as the climate more effectively. In this study, the effect of NAO on precipitation in Iran was investigated using the method of Network Analysis. The data used are daily precipitation and NAO daily indices obtained from ERA-Interim data base. The time period covers the cold months (November, December, Jenury, Februry, March, April) of the years 1979-2016. In order to smooth the daily precipitation data, a weekly moving average was applied to data. A modified Pearson’s cross correlation coefficient  was employed for correction of the bias of traditional Pearson correlation due to many zero-precipitation data. The years of the strong NAO negative and positive phases, NAO- and NAO+, were determined by the frequency of the weekly moving avereage NAO index (WMANAOI) greater that 2 standard deviations
( ), where Sd is the standard deviation. The precipitation network was established based on a constant link density of 0.05 for which vertex degree distribution of network is considered. The later statistics is the covariance between precipitation time series at grid points that show indirectly the effect of the variation of precipitation due to large-scale climate signal. Results demonstrated that Network Analysis method can display and quantified the effect of NAO-and NAO+ on the precipitation of Iran. Degree distribution over the whole duration shows that the most degree distribution is in the northwest, west, southwest and east of Iran. The deserts of Iran that are located in the center of the country have the least degree distribution, and so the least similarity with each other, that are clustered in a group. Also, threshold of network, i.e. , is 0.42 and the histogram of all  has the right skewness. The  is a threshold for selecting the statistically significant  between each two griod points over Iran. The degree distribution for noraml years, with less NAO activities, displays that is 0.42 and degree distribution totally is less than those of NAO+ and NAO-phases. During NAO-, degree distribution is increased in the northwest and southwest of Iran. The  in NAO- is 0.46. During NAO+, the degree distribution is increased in the south of Iran while the threshold of network remain 0.43. Also, the histogram of all  has a positive skewness at NAO+ and NAO-that indicate the strong correlations has positive values. Minimum values of  for the whole period, normal years, NAO+ and NAO-are -0.11, -0.14, -0.3 and -.033, respectively.

Keywords

Main Subjects

References

حجازی­زاده، ز.، فتاحی، ا. و سلیقه، م.، ‎۱۳۹۲‎، بررسی تأثیر سیگنال‌های اقلیمی بر بارش ناحیه مرکزی ایران با استفاده از شبکه عصبی مصنوعی، م. تحقیقات کاربردی علوم جغرافیایی، ۱۳(۲۹)، ۷۵-۸۹. ‎‎
خوش­اخلاق، ف.، قنبری، ن. و معصوم­پور سماکوش، ج.، ۱۳۸۷، مطالعه اثرات نوسان اطلس شمالی بر رژیم بارش و دمای سواحل جنوبی دریای خزر، م. پژوهش­های جغرافیایی طبیعی، ۶۶، ۵۷-۷۰.
ذوالجودی، م.، صناعی، ب. و غفاریان، پ.، ۱۳۹۶، بررسی ارتباط بین دوره‌های خشک‌سالی و ترسالی حوضه آب‌ریز دریاچه ارومیه با الگوی پیوند از دور نوسان اطلس شمالی، فصلنامه تحقیقات جغرافیایی، ۳۲ (۲)، ۱۰۶-۱۱۹.
رضیئی، ط. و ستوده، ف.، ۱۳۹۶، بررسی دقت مرکز اروپایی پیش‌بینی‌های میان­مدت جوی (ECMWF) در پیش بینی بارش مناطق گوناگون اقلیمی ایران، م. فیزیک، زمین و فضا، ۴۳(۱)، ۱۳۳-۱۴۷.
سیدنژادگل‌خطمی، ن.، ۱۳۹۸، کاربست تحلیل شبکه در بررسی تأثیر دو سیگنال بزرگ-مقیاس اقلیمی (MJO، NAO) بر الگوهای زمانی- مکانی خشک‌سالی‌های ایران با روش تحلیل شبکه، رساله دکتری، دانشگاه تهران، پردیس کشاورزی و منابع طبیعی کرج.
لشکری، ح.، ۱۳۸۱، مسیریابی سامانه‌های کم‌فشار سودانی ورودی به ایران، فصلنامه مدرس علوم انسانی، ۶ (۲)، ۱۳۳-۱۵۶.
محمدنژاد، ع.، احمدی‌گیوی، ف. و ایران‌نژاد، پ.، ۱۳۹۲، اثر سامانه‌های مدیترانه‌ای بر خشک‌سالی غرب ایران، م. فیزیک زمین و فضا، ۳۹ (۳)، ۹۷-۱۱۰.‎
نوغانی‌دخت‌بهمنی، م. و صادقی‌نژاد، م.، ۱۳۹۳، روش تحلیل شبکه (رویکردهای نظری و تکنیک‌ها)، دومین کنفرانس ملی جامعه­شناسی و علوم اجتماعی، سالن همایش‌ها دانشگاه تهران.
یاراحمدی، د. و عزیزی، ق.، ۱۳۸۶، تحلیل چند متغیره ارتباط میزان بارش فصلی ایران و شاخص‌های اقلیمی، م. پژوهش‌های جغرافیایی، ۶۲، ۱۷۴-۱۶۱.‎‎
Ahrens, C. D., 2008, Meteorology Today, An introduction to weather, climate and the environment (Babaei, M.R. Trans.). Cengage Learning: Toronto, Canada.
Barlow, M., Lyon, B. and Cullen, H., 2005, Modulation of daily precipitation over Soutwest Asia by Madden-Julian Oscillation, Monthly Weather Review, 133, 3579-3594.
‎Boers, N.‎, ‎Bookhagen, B.‎, ‎Marwan, N.‎, ‎Kurths, J‎. ‎and Marengo, J‎., ‎2013, ‎Complex networks identify spatial patterns of extreme rainfall events‎ ‎of the South American Monsoon System‎. ‎Geophysical research letters‎, ‎40‎(16), ‎4386-4392.‎
Boers, N.‎, ‎Donner, R. V.‎, ‎Bookhagen, B‎. ‎and Kurths, J.‎, ‎2014, ‎Complex network analysis helps to identify impacts of the El Niño Southern Oscillation on moisture divergence in South America‎. ‎Climate Dynamics, 45(3-4), 619-632.
Ciemer, C., Boers, N., Henrique, M. J. B., Kurths, J., Rammig, A, 2018, Temporal evolution of the spatial covariability of rainfall in South America. Climate Dynamics, 51, 371-382.
Dezfuli, A. K., Karamouz, M. and Araghinejad, S., 2010, On the relationship of regional meteorological drought with SOI and NAO over southwest Iran. Theoretical and Applied Climatology, 100(1), 57–66.
Donges, J. F.‎, ‎Zou, Y.‎, ‎Marwan, N‎. ‎and Kurths, J.‎, ‎2009‎, ‎The backbone of the climate network‎, ‎ Europhysics Letters ‎, ‎87 (4), 48007.
Elsner, J.B.‎, ‎Jagger, T. H‎. ‎and Fogarty, E. A.‎, ‎2009, ‎Visibility network of United States hurricanes‎. ‎Geophysical Research Letters‎, ‎36(16), 1-5.
Filippi, L., Palazzi, E., Von Hardenberg, J. and Provenzale, A., 2014, Multidecadal variations in the relationship between the NAO and winter precipitation in the Hindu Kush-Karakoram. Journal of Climate, 27(20), 7890–7902.
Gozolchiani, A.‎, ‎Havlin, S‎. ‎and Yamasaki, K.‎, ‎2011, ‎Emergence of El Nin˜o as an autonomous component in the Climate Network‎. ‎Physical review letters‎, ‎107‎, ‎148501‎.
Higgins, R. W., Schemm, J. K. E., Shi, W. and Leetmaa, A., 2000, Extreme precipitation events in the western United States related to tropical forcing. Journal of Climate. 13, 793-820.
Hosseinzadeh Talaee, P., Tabari, H. and SobhanArdakani, S., 2014, Hydrological drought in the west of Iran and possible association with large-scale atmospheric circulation patterns. Hydrological Processes, 28(3), 764–773.
Hurrell, J. W., 1995, Decadal trends in the North Atlantic Oscillation: regional temperatures and precipitation. Science, 269, 676–679.
Kawale, J.‎, ‎Liess, S.‎, ‎Kumar, A.‎, ‎Steinbach, M.‎, ‎Ganguly, A.‎, ‎Samatova, N. F.‎, ‎Semazzi, F.‎, ‎Snyder, P‎. ‎and Kumar, V.‎, ‎2011‎, ‎Data guided discovery of dynamic climate dipoles‎, ‎Conference on Intelligent Data Understanding‎. ‎October 19-21‎, ‎Mountain View‎, ‎California, ‎30-44.
Ludescher, J.‎, ‎Gozolchiani, A.‎, ‎Bogachev, M. I.‎, ‎Bunde, A.‎, ‎Havlin, Sh‎. ‎and Schellnhuber, H. S.‎, ‎2014‎, ‎Very early warning of next El Niño‎. ‎Spring barrier‎, ‎111 (6), ‎264-2066‎. ‎
Malik, N.‎, ‎Marwan, N‎. ‎and Kurths, J.‎, ‎2010‎, ‎Spatial structures and directionalities in Monsoonal precipitation over South Asia, Nonlinear Processes in Geophysics, 17 (5), 371-381.
Mo, K. C. and Higgins, R. W., 1998, Tropical convection and precipitation regimes in the Western United States, Journal of Climate. 11, 2404-2423.
Molavi-Arabshahi, M., Arpe, K. and Leroy, S. A. G., 2016, Precipitation and temperature of the southwest Caspian Sea region during the last 55 years: their trends and teleconnections with large-scale atmospheric phenomena. Interna-tional Journal of Climatology, 36(5), 2156–2172. 
Onnela, J. P., Saramäki, J., Kertész, J., Kaski, K., 2005, Intensity and coherence of motifs in weighted complex networks, Physical Review E-Statistical, Nonlinear and Soft Matter Physics, 71(6),1-4.
Radebach A.‎, ‎Donner, R. V.‎, ‎Runge, J.‎, ‎Donges, J. F.‎, ‎and Kurths, J.‎, ‎2013‎, ‎Disentangling different types of ElNino episodes by evolving climate network analysis‎, ‎Physical review E, 88(5)‎, ‎052807‎.
Shabbar, A., Huang, j. and Higuchi, K., 2001, The relationship between the wintertime north atlantic oscillation and blocking episodes in the north atlantic, International journal of climatology, 21, 355–369.
Steinhaeuser, K.‎, ‎Chawla, N‎.‎ V‎. ‎‎and Ganguly‎, A‎.‎ R.‎, ‎2010‎, ‎Complex networks as a unified framework for descriptive analysis and predictive modeling in climate‎. ‎Article in review, Science and Technology, 4(5), 497-511.
Steinhaeuser, K.‎, ‎Chawla, N. V.‎ ‎and Ganguly, A. R.‎, ‎2010, ‎Complex networks in climate science‎: ‎progress‎, ‎opportunities and challenges, Conference on Intelligent Data Understandi ‎, 2005-2008‎.
Tsonis, A. A‎. ‎and Roebber, P. J‎., ‎2004, ‎The architecture of the climate network‎. ‎Physica A‎, ‎333, 497-504.
‎Tsonis, A. A‎. ‎and Swanson K. L.‎, ‎2008‎, ‎Topology and Predictability of El Nin˜o and La Nin˜a Networks‎, ‎Physical review letters‎, ‎100(22)‎, ‎228502‎.
‎Tsonis, A. A.‎, ‎Swanson, K. L‎. ‎and Roebber, P.J.‎, ‎2006‎, ‎What do networks have to do with climate‎? ‎American Meteorological Society‎, ‎87(5), 585-595.
‎Tsonis, A. A.‎, ‎Wang, G.‎, ‎Swanson, K. L.‎, ‎Rodrigues, F. A‎. ‎and Costa, L. F‎., ‎2011‎, ‎Community structure and dynamics in climate networks‎, ‎Springer‎, ‎‎Climate Dynamics‎, ‎37(5), 933–940‎.
Uetz, P., Giot, L., Cagney, G., Mansfield, T. A., Judson, R. S., Knight, J. R., Lockshon, D., Narayan, V., Srinivasan, M., Pochart, P., Qureshi-Emili, A., Li, Y., Godwin, B., Conover, D., Kalbfleisch, T., Vijayadamodar, G., Yang M., Johnston, M., Fields, S., Rothberg, J. M., 2000, ‎A comprehensive analysis of protein-protein interactions in saccharomyces cerevisiae‎. ‎Nature‎, ‎403, 623-627.
Vazifehkhah, S., Kahya, E., 2018. Hydrological drought associations with extreme phases of the North Atlantic and Arctic Oscillations over Turkey and northern Iran, International Journal of Climatology, April, 1-17.
Wallace, J. M., Gutzler, D. S., 1981, Teleconnections in the geopotential height field during the northern hemisphere winter. Monthly Weather Review, 109, 784–812.
Wang, Y.‎, ‎Gozolchiani, A.‎, ‎Ashkenazy, Y.‎, ‎Berezin, Y.‎, ‎Guez, O.‎, ‎and Havlin, Sh.‎, ‎2013‎, ‎Dominant Imprint of Rossby Waves in the Climate Network‎, ‎Physical Review Letters‎, ‎111‎, ‎138501‎.
Wasserman, S. and ‎Faust, K‎., 1994, ‎Social Network Analysis‎. ‎Cambridge University Press‎.
Xavier, P., Rahmat, R., Cheong, W. K. and Wallace, E., 2014, Influence of Madden-Julian ocillation on Southeast Asia rainfall extremes: observations and predictability, Geophysical Research Letters., 41(12), 4406-4412.
Yamasaki, K.‎, ‎Gozolchiani, A‎. ‎and Havlin, S., ‎2008‎, ‎Climate Networks around the Globe are Significantly Affected by El Ni˜no‎, ‎Physical Review Letters‎, ‎100(22), ‎157–179.
Journal of the Earth and Space Physics
Volume 46, Issue 2
July 2020
Pages 313-329

Files

Share

How to cite

Statistics