Skip to main content

Advertisement

SpringerLink
Log in

Spatiotemporal monthly rainfall forecasts for south-eastern and eastern Australia using climatic indices

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

Knowledge about future rainfall is important for agriculture management and planning in arid and semi-arid regions. Australia has complex variations in rainfall patterns in time and space, arising from the combination of the geographic structure and the dual effects of Indian and Pacific Ocean. This study aims to develop a forecasting model of spatiotemporal monthly rainfall totals using lagged climate indices and historical rainfall data from 1950–2011 for south-eastern and eastern Australia. Data were obtained from the Australian Bureau of Meteorology (BoM) from 136 high-quality weather stations. To reduce spatial complexity, climate regionalization was used to divide the stations in homogenous sub-regions based on similarity of rainfall patterns and intensity using principal component analysis (PCA) and K-means clustering. Subsequently, a fuzzy ranking algorithm (FRA) was applied to the lagged climatic predictors and monthly rainfall in each sub-region to identify the best predictors. Selected predictors by FRA were found to vary by sub-region. After these two stages of pre-processing, an artificial neural network (ANN) model was developed and optimized separately for each sub-region and the entire area. The results indicate that climate regionalization can improve a monthly spatiotemporal rainfall forecast model. The location and number of sub-regions were important for ranking predictors and modeling. This further suggests that the impact of climate variables on Australian rainfall is more variable in both time and space than indicated thus far.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  • Anwar MR, O’Leary G, McNeil D, Hossain H, Nelson R (2007) Climate change impact on rainfed wheat in south-eastern Australia. Field Crop Res 104(1–3):139–147

    Article  Google Scholar 

  • Anwar MR, Rodriguez D, Liu DL, Power S, O’Leary GJ (2008) Quality and potential utility of ENSO-based forecasts of spring rainfall and wheat yield in south-eastern Australia. Aust J Agric Res 59(2):112–126

    Article  Google Scholar 

  • Ashok K, Guan ZY, Yamagata T (2003a) Influence of the Indian Ocean Dipole on the Australian winter rainfall. Geophys Res Lett 30(15)

  • Ashok K, Guan ZY, Yamagata T (2003b) A look at the relationship between the ENSO and the Indian Ocean Dipole. J Meteorol Soc Jpn 81(1):41–56

    Article  Google Scholar 

  • Bannayan M, Lotfabadi SS, Sanjani S, Mohamadian A, Aghaalikhani M (2011) Effects of precipitation and temperature on crop production variability in northeast Iran. Int J Biometeorol 55(3):387–401

    Article  Google Scholar 

  • Cai W, Whetton PH, Pittock AB (2001) Fluctuations of the relationship between ENSO and northeast Australian rainfall. Clim Dyn 17(5-6):421–432

    Article  Google Scholar 

  • Cai W, Cowan T, Sullivan A (2009) Recent unprecedented skewness towards positive Indian Ocean Dipole occurrences and its impact on Australian rainfall. Geophys Res Lett 36(11), L11705

    Article  Google Scholar 

  • Cai W, van Rensch P, Cowan T, Hendon HH (2012) An asymmetry in the IOD and ENSO teleconnection pathway and its impact on Australian climate. J Clim 25(18):6318–6329

    Article  Google Scholar 

  • Chiew FHS, Zhou SL, McMahon TA (2003) Use of seasonal streamflow forecasts in water resources management. J Hydrol 270(1-2):135–144

    Article  Google Scholar 

  • Corte-Real J, Qian BD, Xu H (1998) Regional climate change in Portugal: precipitation variability associated with large-scale atmospheric circulation. Int J Climatol 18(6):619–635

    Article  Google Scholar 

  • Dezfuli AK (2011) Spatio-temporal variability of seasonal rainfall in western equatorial Africa. Theor Appl Climatol 104(1-2):57–69

    Article  Google Scholar 

  • Dezfuli AK, Karamouz M, Araghinejad S (2010) On the relationship of regional meteorological drought with SOI and NAO over southwest Iran. Theor Appl Climatol 100(1-2):57–66

    Article  Google Scholar 

  • Drosdowsky W (1993) An analysis of Australian seasonal rainfall anomalies 1950-1987: spatial patterns. Int J Climatol 13(1):1–30

    Article  Google Scholar 

  • Drosdowsky W (2002) SST phases and Australian rainfall. Aust Meteorol Mag 51(1):1–12

    Google Scholar 

  • Drosdowsky W, Chambers LE (2001) Near-global sea surface temperature anomalies as predictors of Australian seasonal rainfall. J Clim 14(7):1677–1687

    Article  Google Scholar 

  • Fawcett RJB, Jones DA, Beard GS (2005) A verification of publicly issued seasonal forecasts issued by the Australian Bureau of Meteorology: 1998-2003. Aust Meteorol Mag 54(1):1–13

    Google Scholar 

  • Gardner MW, Dorling SR (1998) Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences. Atmos Environ 32(14-15):2627–2636

    Article  Google Scholar 

  • Gerstengarbe FW, Werner PC, Fraedrich K (1999) Applying non-hierarchical cluster analysis algorithms to climate classification: some problems and their solution. Theor Appl Climatol 64(3-4):143–150

    Article  Google Scholar 

  • Gong XF, Richman MB (1995) On the application of cluster analysis to growing season precipitation data in north-America east of. Rockies Journal of Climate 8(4):897–931

    Article  Google Scholar 

  • Goovaerts P (2000) Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. J Hydrol 228(1-2):113–129

    Article  Google Scholar 

  • Govindaraju RS (2000a) Artificial neural networks in hydrology. I: preliminary concepts. J Hydrol Eng 5(2):115–123

  • Govindaraju RS (2000b) Artificial neural networks in hydrology. II: hydrologic applications. J Hydrol Eng 5(2):124–137

  • Hagan MT, Menhaj MB (1994) Training feedforward networks with the Marquardt algorithm. IEEE Trans Neural Netw 5(6):989–993

    Article  Google Scholar 

  • Hendon HH, Thompson DWJ, Wheeler MC (2007) Australian rainfall and surface temperature variations associated with the Southern Hemisphere annular mode. J Clim 20(11):2452–2467

    Article  Google Scholar 

  • Hotelling H (1933) Analysis of a complex of statistical variables into principal components. J Educ Psychol 24:417–441

    Article  Google Scholar 

  • Hou Y, Zurada JA, Karwowski W, Marras WS, Davis K (2007) Identification of key variables using fuzzy average with fuzzy cluster distribution. IEEE Trans Fuzzy Syst 15(4):673–685

    Article  Google Scholar 

  • Johnson DE (1998) Applied multivariate methods for data analysts. Duxbury Press

  • Keogh E, Kasetty S (2003) On the need for time series data mining benchmarks: a survey and empirical demonstration. Data Min Knowl Disc 7(4):349–371

    Article  Google Scholar 

  • Kirono DGC, Chiew FHS, Kent DM (2010) Identification of best predictors for forecasting seasonal rainfall and runoff in Australia. Hydrol Process 24(10):1237–1247

    Google Scholar 

  • Kottek M, Grieser J, Beck C, Rudolf B, Rubel F (2006) World map of the Koppen-Geiger climate classification updated. Meteorol Z 15(3):259–263

    Article  Google Scholar 

  • Lin YH, Cunningham GA, Coggeshall SV (1996) Input variable identification—Fuzzy curves and fuzzy surfaces. Fuzzy Sets Syst 82(1):65–71

    Article  Google Scholar 

  • Lund R, Li B (2009) Revisiting climate region definitions via clustering. J Clim 22(7):1787–1800

    Article  Google Scholar 

  • McBride JL, Nicholls N (1983) Seasonal relationships between Australian rainfall and the southern oscillation. Mon Weather Rev 111(10):1998–2004

    Article  Google Scholar 

  • McIntosh PC, Pook MJ, Risbey JS, Lisson SN, Rebbeck M (2007) Seasonal climate forecasts for agriculture: towards better understanding and value. Field Crop Res 104(1-3):130–138

    Article  Google Scholar 

  • Mekanik F, Imteaz MA, Ieee (2012) Forecasting Victorian spring rainfall using ENSO and IOD: a comparison of linear multiple regression and nonlinear ANN. 2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering, 86-89 pp

  • Meneghini B, Simmonds I, Smith IN (2007) Association between Australian rainfall and the Southern Annular Mode. Int J Climatol 27(1):109–121

    Article  Google Scholar 

  • Meyers G, McIntosh P, Pigot L, Pook M (2007) The years of El Nino, La Nina, and interactions with the tropical Indian ocean. J Clim 20(13):2872–2880

    Article  Google Scholar 

  • Munoz-Diaz D, Rodrigo FS (2004) Spatio-temporal patterns of seasonal rainfall in Spain (1912-2000) using cluster and principal component analysis: comparison. Ann Geophys 22(5):1435–1448

    Article  Google Scholar 

  • Murphy BF, Timbal B (2008) A review of recent climate variability and climate change in southeastern Australia. Int J Climatol 28(7):859–879

    Article  Google Scholar 

  • Nicholls N (1983) The southern oscillation and Indonesian sea surface temperature

  • Nicholls N (2010) Local and remote causes of the southern Australian autumn-winter rainfall decline, 1958-2007. Clim Dyn 34(6):835–845

    Article  Google Scholar 

  • Pearson K (1901) On lines and planes of closest fit to systems of points in space. Philos Mag 2(7-12):559–572

    Article  Google Scholar 

  • Peel MC, Finlayson BL, McMahon TA (2007) Updated world map of the Koppen-Geiger climate classification. Hydrol Earth Syst Sci 11(5):1633–1644

    Article  Google Scholar 

  • Piechota TC, Chiew FHS, Dracup JA, McMahon TA (1998) Seasonal streamflow forecasting in eastern Australia and the El Nino Southern Oscillation. Water Resour Res 34(11):3035–3044

    Article  Google Scholar 

  • Power S et al (1998) Australian temperature, Australian rainfall and the Southern Oscillation, 1910-1992: coherent variability and recent changes. Aust Meteorol Mag 47(2):85–101

    Google Scholar 

  • Power S, Casey T, Folland C, Colman A, Mehta V (1999) Inter-decadal modulation of the impact of ENSO on Australia. Clim Dyn 15(5):319–324

    Article  Google Scholar 

  • Reusch DB, Alley RB (2002) Automatic weather stations and artificial neural networks: improving the instrumental record in West Antarctica. Mon Weather Rev 130(12):3037–3053

    Article  Google Scholar 

  • Risbey JS, Pook MJ, McIntosh PC, Wheeler MC, Hendon HH (2009) On the remote drivers of rainfall variability in Australia. Mon Weather Rev 137(10):3233–3253

    Article  Google Scholar 

  • Rogers JC (1990) Pattern of low-frequency monthly sea-level pressure variability (1899-1986) and associated wave cyclone frequencies. J Clim 3(12):1364–1379

    Article  Google Scholar 

  • Rogers JC, McHugh MJ (2002) On the separability of the North Atlantic oscillation and Arctic oscillation. Clim Dyn 19(7):599–608

    Article  Google Scholar 

  • Ropelewski CF, Jones PD (1987) An extension of the Tahaiti-Darwin Southern Oscilation Index. Mon Weather Rev 115(9):2161–2165

    Article  Google Scholar 

  • Ruiz JE, Cordery I, Sharma A (2007) Forecasting streamflows in Australia using the tropical Indo-Pacific thermocline as predictor. J Hydrol 341(3-4):156–164

    Article  Google Scholar 

  • Rumelhart DE, Mcclelland JL (1986) Parallel distributed processing: explorations in the microstructure of cognition. Volume 1. Foundations, Medium: X; Size: Pages: 564pp

  • Saji NH, Yamagata T (2003) Possible impacts of Indian Ocean Dipole mode events on global climate. Clim Res 25(2):151–169

    Article  Google Scholar 

  • Saji NH, Goswami BN, Vinayachandran PN, Yamagata T (1999) A dipole mode in the tropical Indian Ocean. Nature 401(6751):360–363

    Google Scholar 

  • Schepen A, Wang QJ, Robertson D (2012a) Evidence for using lagged climate indices to forecast Australian seasonal rainfall. J Clim 25(4):1230–1246

    Article  Google Scholar 

  • Schepen A, Wang QJ, Robertson DE (2012b) Combining the strengths of statistical and dynamical modeling approaches for forecasting Australian seasonal rainfall. J Geophys Res Atmos 117(D20):20107. doi:10.1029/2012JD018011

  • Shi G et al (2008) Variability and trend of North West Australia rainfall: observations and coupled climate modeling. J Clim 21(12):2938–2959

    Article  Google Scholar 

  • Sivakumar MVK, Hansen J (2007) Climate prediction and agriculture: summary and the way forward. Climate Prediction and Agriculture 1–13. doi:10.1007/978-3-540-44650-7_1

  • Smith TM, Reynolds RW, Peterson TC, Lawrimore J (2008) Improvements to NOAA’s historical merged land-ocean surface temperature analysis (1880-2006). J Clim 21(10):2283–2296

    Article  Google Scholar 

  • Stanski HR, Wilson LJ, Burrows WR (1989) Survey of common verification methods in meteorology. World weather watch tech. Rep. 8, WMO/TD No. 358

  • Stone R, Auliciems A (1992) SOI phase relationships with rainfall in eastern Australia. Int J Climatol 12(6):625–636

    Article  Google Scholar 

  • Stone RC, Hammer GL, Marcussen T (1996) Prediction of global rainfall probabilities using phases of the southern oscillation index. Nature 384(6606):252–255

    Article  Google Scholar 

  • Tasadduq M, Rehman S, Bubshait K (2002) Application of neural networks for the prediction of hourly mean surface temperatures in Saudi Arabia. Renew Energy 25(4):545–554

    Article  Google Scholar 

  • Valle S, Li WH, Qin SJ (1999) Selection of the number of principal components: the variance of the reconstruction error criterion with a comparison to other methods. Ind Eng Chem Res 38(11):4389–4401

    Article  Google Scholar 

  • van Ogtrop FF, Vervoort RW, Heller GZ, Stasinopoulos DM, Rigby RA (2011) Long-range forecasting of intermittent streamflow. Hydrol Earth Syst Sci 15(11):3343–3354

    Article  Google Scholar 

  • Verdon DC, Franks SW (2005) Indian Ocean sea surface temperature variability and winter rainfall: Eastern Australia. Water Resour Res 41(9). doi:10.1029/2004WR003845

  • Villar JCE et al (2009) Spatio-temporal rainfall variability in the Amazon basin countries (Brazil, Peru, Bolivia, Colombia, and Ecuador). Int J Climatol 29(11):1574–1594

    Article  Google Scholar 

  • Wang G, Hendon HH (2007) Sensitivity of Australian rainfall to inter-El Nino variations. J Clim 20(16):4211–4226

    Article  Google Scholar 

  • Wang QJ, Schepen A, Robertson DE (2012) Merging seasonal rainfall forecasts from multiple statistical models through Bayesian model averaging. J Clim 25(16):5524–5537

    Article  Google Scholar 

  • Wilson LL, Lettenmaier DP, Skyllingstad E (1992) A hierarchical stochastic-model of large-scale atmospheric circulation patterns and multiple station daily precipitation. J Geophys Res-Atmos 97(D3):2791–2809

    Article  Google Scholar 

  • Zhao M, Hendon HH (2009) Representation and prediction of the Indian Ocean dipole in the POAMA seasonal forecast model. Q J R Meteorol Soc 135(639):337–352

    Article  Google Scholar 

Download references

Acknowledgments

The authors gratefully acknowledge funding for project provided by the Australian Research Council and Grain Growers Limited. The authors would like to thank to Dr. Floris Van Ogtrop for valuable discussions and advice.

Author information

Authors and Affiliations

  1. Department of Environmental Sciences, Faculty of Agriculture and Environment, The University of Sydney, Sydney, Australia

    Maryam Montazerolghaem, Willem Vervoort, Budiman Minasny & Alex McBratney

Authors
  1. Maryam Montazerolghaem
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Willem Vervoort
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Budiman Minasny
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Alex McBratney
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Maryam Montazerolghaem.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Montazerolghaem, M., Vervoort, W., Minasny, B. et al. Spatiotemporal monthly rainfall forecasts for south-eastern and eastern Australia using climatic indices. Theor Appl Climatol 124, 1045–1063 (2016). https://doi.org/10.1007/s00704-015-1457-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-015-1457-3

Keywords

Search

Navigation