Abstract
This paper aims to find the possible relationships between winter precipitation (December, January, February; DJF) in Iran with three oceanic sources through the correlation wavelet analysis by applying the continuous wavelet transform (CWT), the cross–wavelet transform (XWT), and the wavelet transform coherence (WTC). The sources in the North Atlantic Ocean (30°W-70°W, 10°N-30°N), the South Pacific Ocean (80°W-120°W, 20°S-40°S) and the Indian Ocean (50°E-100°E, 10°S-40°S) were selected using Pearson correlation coefficient (PCC > 0.5) that can represent the possible relationships between Iran’s winter precipitations with the oceanic sea surface temperature (SST) anomaly. The monthly gridded precipitation and SST data with a 2.5° × 2.5° resolution were evaluated from 1984 to 2019 to achieve this goal. The XWT results of precipitation and SST anomaly showed that the 8–16 months period is the most effective and predominant period between the South Pacific Ocean and 81% of all the precipitation zones. WTC results for the North Atlantic Ocean and 72% of all the precipitation zones showed periods of 4–8 (36%) and 16–32 (36%) months as the dominant duration. Despite the proximity of the Indian Ocean to the precipitation zones, there is no significant causal relationship between them, based on the XWT results. However, due to Madden–Julian oscillation (MJO), the 4–8 months period (45%) was seen between the Indian Ocean and some precipitation zones, based on WTC results.
Similar content being viewed by others
References
Ahmadi M, Salimi S, Hosseini SA, Poorantiyosh H, Bayat A (2019) Iran's precipitation analysis using synoptic modeling of major teleconnection forces (MTF). Dynam Atmos Ocean 85:41–56. https://doi.org/10.1016/j.dynatmoce.2018.12.001
Amiri MA, Conoscenti C (2017) Landslide susceptibility mapping using precipitation data, Mazandaran Province, north of Iran. Nat Hazards 89(1):255–273. https://doi.org/10.1007/s11069-017-2962-8
Amiri MA, Mesgari MS (2016) Spatial variability analysis of precipitation in Northwest Iran. Arab J Geosci 9(11):1–10. https://doi.org/10.1007/s12517-016-2611-7
Amiri MA, Mesgari MS (2017) Modeling the spatial and temporal variability of precipitation in Northwest Iran. Atmosphere 8(12):1–14. https://doi.org/10.3390/atmos8120254
Amiri MA, Mesgari MS (2018) Analyzing the spatial variability of precipitation extremes along longitude and latitude, Northwest Iran. Kuwait J Sci 45(1):121–127
Amiri MA, Mesgari MS (2019) Spatial variability analysis of precipitation and its concentration in Chaharmahal and Bakhtiari province, Iran. Theor Appl Climatol 137(3–4):2905–2914. https://doi.org/10.1007/s00704-019-02787-y
Amiri MA, Amerian Y, Mesgari MS (2016) Spatial and temporal monthly precipitation forecasting using wavelet transform and neural networks, Qara-Qum catchment, Iran. Arab J Geosci 9(5):421. https://doi.org/10.1007/s12517-016-2446-2
Amiri MA, Mesgari MS, Conoscenti C (2017) Detection of homogeneous precipitation regions at seasonal and annual time scales, Northwest Iran. J Water Clime Change 8(4):701–714. https://doi.org/10.2166/wcc.2017.088
Araghi A, Baygi MM, Adamowski J, Malard J, Nalley D, Hasheminia SM (2015) Using wavelet transforms to estimate surface temperature trends and dominant periodicities in Iran based on gridded reanalysis data. Atmos Res 155:52–72. https://doi.org/10.1016/j.atmosres.2014.11.016
Araghi A, Mousavi-Baygi M, Adamowski J, Martinez C (2017) Association between three prominent climatic teleconnections and precipitation in Iran using wavelet coherence. Int J Climatol 37(6):2809–2830. https://doi.org/10.1002/joc.4881
Ashraf B, Yazdani R, Mousavi-Baygi M, Bannayan M (2013) Investigation of temporal and spatial climate variability and aridity of Iran. Theor Appl Climatol 118(1):35–46. https://doi.org/10.1007/s00704-013-1040-8
Azad S, Debnath S, Rajeevan M (2015) Analysing predictability in Indian monsoon rainfall: a data analytic approach. Environ Process 2:717–727. https://doi.org/10.1007/s40710-015-0108-0
Baldwin MP, Gray LJ, Dunkerton TJ, Hamilton K, Haynes PH, Randel WJ, Takahashi M (2001) The quasi-biennial oscillation. Rev Geophys 39(2):179–229. https://doi.org/10.1029/1999rg000073
Barbulescu AA (2016) New method for estimation the regional precipitation. Water Resour Manag 30:33–42. https://doi.org/10.1007/s11269-015-1152-2
Bruun JT, Allen JI, Smyth TJ (2017) Heartbeat of the southern oscillation explains ENSO climatic resonances. J Geophys Res Oceans 122(8):6746–6772. https://doi.org/10.1002/2017JC012892
Canchala T, Alfonso-Morales W, Cerón WL, Carvajal-Escobar Y, Caicedo-Bravo E (2020) Teleconnections between monthly rainfall variability and large-scale climate indices in southwestern Colombia. Water 12(7):1863. https://doi.org/10.3390/w12071863
Chandran A, Basha G, Ouarda TBMJ (2016) Influence of climate oscillations on temperature and precipitation over the United Arab Emirates. Int J Climatol 36(1):225–235. https://doi.org/10.1002/joc.4339
Chang X, Wang B, Yan Y, Hao Y, Zhang M (2019) Characterizing effects of monsoons and climate teleconnections on precipitation in China using wavelet coherence and global coherence. Clim Dyn 52:5213–5228. https://doi.org/10.1007/s00382-018-4439-1
Chellali F, Khellaf A, Belouchrani A (2010) Wavelet spectral analysis of the temperature and wind speed data at Adrar, Algeria. Renew Energy 35(6):1214–1219. https://doi.org/10.1016/j.renene.2009.10.010
Chen Y, Guan Y, Shao G, Zhang D (2016) Investigating trends in streamflow and precipitation in Huangfuchuan Basin with wavelet analysis and the Mann-Kendall test. Water 8(3):77. https://doi.org/10.3390/w8030077
Coulibaly P (2006) Spatial and temporal variability of Canadian seasonal precipitation (1900–2000). Adv Water Resour 29(12):1846–1865. https://doi.org/10.1016/j.advwatres.2005.12.013
Coulibaly P, Burn DH (2004) Wavelet analysis of variability in annual Canadian streamflows. Water Resour Res 40(3). https://doi.org/10.1029/2003WR002667
Darand M, Mansouri Daneshvar MR (2014) Regionalization of precipitation regimes in Iran using principal component analysis and hierarchical clustering analysis. Environ Process 1:517–532. https://doi.org/10.1007/s40710-014-0039-1
Das J, Jha S, Goyal MK (2020) On the relationship of climatic and monsoon teleconnections with monthly precipitation over meteorologically homogenous regions in India: wavelet & global coherence approaches. Atmos Res 238:104889. https://doi.org/10.1016/j.atmosres.2020.104889
Dehghani M, Salehi S, Mosavi A, Nabipour N, Shamshirband S, Ghamisi P (2020) Spatial analysis of seasonal precipitation over Iran: Co-variation with climate indices. ISPRS Int J Geoinf 9(2):73. https://doi.org/10.3390/ijgi9020073
Dinpashoh Y (2006) Study of reference crop evapotranspiration in IR of Iran. Agric Water Manag 84(1–2):123–129. https://doi.org/10.1016/j.agwat.2006.02.011
Domroes M, Kaviani M, Schaefer D (1998) An analysis of regional and intra-annual precipitation variability over Iran using multivariate statistical methods. Theor Appl Climatol 61(3–4):151–159. https://doi.org/10.1007/s007040050060
Farajzadeh J, Alizadeh F (2018) A hybrid linear–nonlinear approach to predict the monthly rainfall over the Urmia Lake watershed using wavelet-SARIMAX-LSSVM conjugated model. J Hydroinf 20(1):246–262. https://doi.org/10.2166/hydro.2017.013
Fritier N, Massei N, Laignel B, Durand A, Dieppois B, Deloffre J (2012) Links between NAO fluctuations and inter-annual variability of winter-months precipitation in the Seine River watershed (northwestern France). Compt Rendus Geosci 344(8):396–405. https://doi.org/10.1016/j.crte.2012.07.004
Gan TY, Gobena AK, Wang Q (2007) Precipitation of southwestern Canada: wavelet, scaling, multifractal analysis, and teleconnection to climate anomalies. J Geophys Res Atmos 112(D10). https://doi.org/10.1029/2006JD007157
Grinsted A, Moore JC, Jevrejeva S (2004) Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Process Geophys 11:561–566. https://doi.org/10.5194/npg-11-561-2004
Guntu RK, Yeditha PK, Rathinasamy M, Perc M, Marwan N, Kurths J, Agarwal A (2020) Wavelet entropy-based evaluation of intrinsic predictability of time series. Chaos 30(3):033117. https://doi.org/10.1063/1.5145005
Hauke J, Kossowski T (2011) Comparison of values of Pearson's and Spearman's correlation coefficients on the same sets of data. Quaest Geogr 30(2):87–93. https://doi.org/10.2478/v10117011-0021-1
Helali J, Salimi S, Lotfi M, Hosseini SA, Bayat A, Ahmadi M, Naderizarneh S (2020) Investigation of the effect of large-scale atmospheric signals at different time lags on the autumn precipitation of Iran’s watersheds. Arab J Geosci 13(18):1–24. https://doi.org/10.1007/s12517-020-05840-7
Hermida L, López L, Merino A, Berthet C, García-Ortega E, Sánchez JL, Dessens J (2015) Hailfall in Southwest France: relationship with precipitation, trends and wavelet analysis. Atmos Res 156:174–188. https://doi.org/10.1016/j.atmosres.2015.01.00
Jiang R, Gan TY, Xie J, Wang N (2014) Spatiotemporal variability of Alberta's seasonal precipitation, their teleconnection with large-scale climate anomalies and sea surface temperature. Int J Climatol 34(9):2899–2917. https://doi.org/10.1002/joc.3883
Kalimeris A, Ranieri E, Founda D, Norrant C (2017) Variability modes of precipitation along a Central Mediterranean area and their relations with ENSO, NAO, and other climatic patterns. Atmos Res 198:56–80. https://doi.org/10.1016/j.atmosres.2017.07.031
Kaplan A, Cane MA, Kushnir Y, Clement AC, Blumenthal MB, Rajagopalan B (1998) Analyses of global sea surface temperature 1856–1991. J Geophys Res Oceans 103(C9):18567–18589. https://doi.org/10.1029/97JC01736
Khalili K, Tahoudi MN, Mirabbasi R, Ahmadi F (2016) Investigation of spatial and temporal variability of precipitation in Iran over the last half century. Stoch Env Res Risk A 30(4):1205–1221. https://doi.org/10.1007/s00477-015-1095-4
Kim S (2004) Wavelet analysis of precipitation variability in northern California, USA. KSCE J Civ Eng 8(4):471–477. https://doi.org/10.1007/BF02829169
Kisi O, Shiri J (2011) Precipitation forecasting using wavelet-genetic programming and wavelet-neuro-fuzzy conjunction models. Water Resour Manag 25(13):3135–3152. https://doi.org/10.1007/s11269-011-9849-3
Komasi M, Sharghi S, Safavi HR (2018) Wavelet and cuckoo search-support vector machine conjugation for drought forecasting using standardized precipitation index (case study: Urmia Lake, Iran). J Hydroinf 20(4):975–988. https://doi.org/10.2166/hydro.2018.115
Kuo CC, Gan TY, Yu PS (2010) Wavelet analysis on the variability, teleconnectivity, and predictability of the seasonal rainfall of Taiwan. Mon Weather Rev 138(1):162–175. https://doi.org/10.1175/2009MWR2718.1
Lee JH, Lee J, Julien PY (2018) Global climate teleconnection with rainfall erosivity in South Korea. Catena 167:28–43. https://doi.org/10.1016/j.catena.2018.03.008
Li F, He L (2017) The effects of dominant driving forces on summer precipitation during different periods in Beijing. Atmosphere 8(3):44. https://doi.org/10.3390/atmos8030044
Mechoso CR, Lyons SW, Spahr JA (1990) The impact of sea surface temperature anomalies on the rainfall over Northeast Brazil. J Clim 3(8):812–826. https://doi.org/10.1175/1520-0442(1990)003<0812:TIOSST>2.0.CO;2
Moazenzadeh R, Mohammadi B, Shamshirband S, Chau KW (2018) Coupling a firefly algorithm with support vector regression to predict evaporation in northern Iran. Eng Appl Comput Fluid Mech 12(1):584–597. https://doi.org/10.1080/19942060.2018.1482476
Moron V, Ward MN, Navarra A (2001) Observed and SST-forced seasonal rainfall variability across tropical America. Int J Climatol 21(12):1467–1501
Muhati FD, Ininda JM, Opijah FJ (2007) Relationship between ENSO parameters and the trends and periodic fluctuations in east African rainfall. J Kenya Meteorol Soc 1(1):20–43
Mwale D, Gan TY, Shen SS, Shu TT, Kim KM (2007) Wavelet empirical orthogonal functions of space-time-frequency regimes and predictability of southern Africa summer rainfall. J Hydrol Eng 12(5):513–523. https://doi.org/10.1061/(ASCE)1084-0699(2007)12:5(513)
Nalley D, Adamowski J, Khalil B, Biswas A (2016) Inter-annual to inter-decadal streamflow variability in Quebec and Ontario in relation to dominant large-scale climate indices. J Hydrol 536:426–446. https://doi.org/10.1016/j.jhydrol.2016.02.049
Nazari-Sharabian M, Karakouzian M (2020) Relationship between sunspot numbers and mean annual precipitation: application of cross-wavelet transform-a case study. J 3(1):67–78. https://doi.org/10.3390/j3010007
Nicholls N (1989) Sea surface temperatures and Australian winter rainfall. J Clim 2(9):965–973. https://doi.org/10.1175/1520-0442(1989)002<0965:SSTAAW>2.0.CO;2
Nourani V, Alami MT, Aminfar MH (2009) A combined neural-wavelet model for prediction of Ligvanchai watershed precipitation. Eng Appl Artif Intell 22(3):466–472. https://doi.org/10.1016/j.engappai.2008.09.003
Obilor EI, Amadi EC (2018) Test for significance of Pearson’s correlation coefficient. IJMSS 6(1):11–23
Partal T, Cigizoglu HK (2009) Prediction of daily precipitation using wavelet—neural networks. Hydrol Sci J 54(2):234–246. https://doi.org/10.1623/hysj.54.2.234
Partal T, Kisi O (2007) Wavelet and neuro-fuzzy conjunction model for precipitation forecasting. J Hydrol 342(1–2):199–212. https://doi.org/10.1016/j.jhydrol.2007.05.026
Pathak P, Kalra A, Ahmad S, Bernardez M (2016) Wavelet-aided analysis to estimate seasonal variability and dominant periodicities in temperature, precipitation, and streamflow in the Midwestern United States. Water Resour Manag 30(13):4649–4665. https://doi.org/10.1007/s11269-016-1445-0
Pourasghar F, Tozuka T, Jahanbakhsh S, Sarraf BS, Ghaemi H, Yamagata T (2012) The inter annual precipitation variability in the southern part of Iran as linked to large-scale climate modes. Clim Dyn 39(9–10):2329–2341. https://doi.org/10.1007/s00382-012-1357-5
Qi P, Zhang G, Xu YJ, Wang L, Ding C, Cheng C (2018) Assessing the influence of precipitation on shallow groundwater table response using a combination of singular value decomposition and cross-wavelet approaches. Water 10(5):598. https://doi.org/10.3390/w10050598
Randel WJ, Wu F, Swinbank R, Nash J, O’Neill A (1999) Global QBO circulation derived from UKMO stratospheric analyses. J Atmos Sci 56(4):457–474. https://doi.org/10.1175/1520-0469(1999)056<0457:GQCDFU>2.0.CO;2
Raziei T, Saghafian B, Paulo AA, Pereira LS, Bordi I (2009) Spatial patterns and temporal variability of drought in western Iran. Water Resour Manag 23:439–455. https://doi.org/10.1007/s11269-008-9282-4
Rehman SU, Usmani BA, Khan K, Khan AJ, Ali M, Ahmed A, Ali S (2019) Wavelet analysis for precipitation attributes. IJCSNS 19(4):279
Roushangar K, Alizadeh F (2018) Identifying complexity of annual precipitation variation in Iran during 1960–2010 based on information theory and discrete wavelet transform. Stoch Environ Res Risk Assess 32(5):1205–1223. https://doi.org/10.1007/s00477-017-1430-z
Roushangar K, Alizadeh F, Adamowski J (2018) Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach. Environ Res 165:176–192. https://doi.org/10.1016/j.envres.2018.04.017
Rousta I, Soltani M, Zhou W, Cheung HH (2016) Analysis of extreme precipitation events over central plateau of Iran. Am J Clim Chang 5:297–313. https://doi.org/10.4236/ajcc.2016.53024
Santos CAG, Galvao CO, Trigo RM, Servat E (2003) Rainfall data analysis using wavelet transform. International Association of Hydrological Sciences Publication 278:195–201
Sattari MT, Apaydin H, Shamshirband S (2020) Performance evaluation of deep learning-based gated recurrent units (GRUs) and tree-based models for estimating ETo by using limited meteorological variables. Mathematics 8(6):972. https://doi.org/10.3390/math8060972
Schneider U, Becker A, Finger P, Rustemeier E, Ziese M (2020) GPCC full data monthly product version 2020 at 0.25°: monthly land-surface precipitation from rain-gauges built on GTS-based and historical data. https://doi.org/10.5676/DWD_GPCC/FD_M_V2020_025. Accessed 1 Mar 2021
Schober P, Boer C, Schwarte LA (2018) Correlation coefficients: appropriate use and interpretation. Anesth Analg 126(5):1763–1768. https://doi.org/10.1213/ANE.0000000000002864
Sezen C, Partal T (2020) Wavelet combined innovative trend analysis for precipitation data in the Euphrates-Tigris basin, Turkey. Hydrol Sci J 65(11):1909–1927. https://doi.org/10.1080/02626667.2020.1784422
Shafaei M, Adamowski J, Fakheri-Fard A, Dinpashoh Y, Adamowski K (2016) A wavelet-SARIMA-ANN hybrid model for precipitation forecasting. J Water Land Dev 28(1):27–36
Shamshirband S, Hashemi S, Salimi H, Samadianfard S, Asadi E, Shadkani S, Kargar K, Mosavi A, Nabipour N, Chau KW (2020) Predicting standardized streamflow index for hydrological drought using machine learning models. Eng Appl Comput Fluid Mech 14(1):339–350. https://doi.org/10.1080/19942060.2020.1715844
Singh A, Thakur S, Adhikary NC (2020) Influence of climatic indices (AMO, PDO, and ENSO) and temperature on rainfall in the northeast region of India. SN Appl Sci 2(10):1–15. https://doi.org/10.1007/s42452-020-03527-y
Smith LC, Turcotte DL, Isacks B (1998) Stream flow characterization and feature detection using a discrete wavelet transform. Hydrol Process 12:233–249. https://doi.org/10.1002/(SICI)1099-1085(199802)12:2<233::AID-HYP573>3.0.CO;2-3
Streten NA (1983) Extreme distributions of Australian annual rainfall in relation to sea surface temperature. Int J Climatol 3(2):143–153. https://doi.org/10.1002/joc.3370030204
Tabari H, Talaee PH (2011) Temporal variability of precipitation over Iran: 1966–2005. J Hydrol 396(3–4):313–320. https://doi.org/10.1016/j.jhydrol.2010.11.034
Tan X, Gan TY, Shao D (2016) Wavelet analysis of precipitation extremes over Canadian ecoregions and teleconnections to large-scale climate anomalies. J Geophys Res Atmos 121(24):14–469. https://doi.org/10.1002/2016JD025533
Torrence C, Compo GP (1998) A practical guide to wavelet analysis. Bull Am Meteorol Soc 79(1):61–78. https://doi.org/10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2
Torrence C, Webster PJ (1999) Interdecadal changes in the ENSO–monsoon system. J Clim 12(8):2679–2690. https://doi.org/10.1175/1520-0442(1999)012<2679:ICITEM>2.0.CO;2
Uvo CB, Repelli CA, Zebiak SE, Kushnir Y (1998) The relationships between tropical Pacific and Atlantic SST and Northeast Brazil monthly precipitation. J Clim 11(4):551–562. https://doi.org/10.1175/1520-0442(1998)011<0551:TRBTPA>2.0.CO;2
van der Ent RJ, Savenije HHG (2013) Oceanic sources of continental precipitation and the correlation with sea surface temperature. Water Resour Res 49:3993–4004. https://doi.org/10.1002/wrcr.20296
Xu Y, Li S, Cai Y (2005) Wavelet analysis of rainfall variation in the Hebei plain. Sci China Ser D-Earth Sci 48(12):2241–2250. https://doi.org/10.1360/04yd0215
Acknowledgments
To apply the WTC and XWT methods in this paper, the MATLAB codes used were provided by A. Grinsted (http://noc.ac.uk/using-science/crosswavelet-wavelet-coherence) and C. Torrence and G. P. Compo (http://paos.colorado.edu/research/wavelets/software.html).
Research Data Policy and Data Availability Statements
The authors declare that data supporting the findings of this study are available and were cited within the article.
Funding
The research is part of the Ph.D. thesis of Atefe Ebrahimi and was supported by the University of Isfahan.
Author information
Authors and Affiliations
Contributions
Mohammad Joghataei contributed to the study’s conception and design. Atefe Ebrahimi performed material preparation, data collection, and analysis. Atefe Ebrahimi and Mohammad Joghataei wrote the first draft of the manuscript, and Dariush Rahimi and Saeed Movahedi commented on the previous versions of the manuscript. All authors read and approved the final manuscript.
Corresponding authors
Ethics declarations
Conflict of Interest
The authors declare that they have no conflict of interest.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
ESM 1
(DOCX 6876 kb)
Rights and permissions
About this article
Cite this article
Ebrahimi, A., Rahimi, D., Joghataei, M. et al. Correlation Wavelet Analysis for Linkage between Winter Precipitation and Three Oceanic Sources in Iran. Environ. Process. 8, 1027–1045 (2021). https://doi.org/10.1007/s40710-021-00524-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40710-021-00524-0