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Changing patterns in rainfall extremes in South Australia

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Abstract

Daily rainfall records from seven stations in South Australia, with record lengths from 50 to 137 years and a common period of 36 years, are investigated for evidence of changes in the statistical distribution of annual total and annual average of monthly daily maxima. In addition, the monthly time series of monthly totals and monthly daily maxima are analysed for three stations for which records exceed 100 years. The monthly series show seasonality and provide evidence of a reduction in rainfall when the Southern Oscillation Index (SOI) is negative, which is modulated by the Pacific Decadal Oscillation (PDO). However, the monthly series do not provide any evidence of a consistent trend or of any changes in the seasonal pattern. Multivariate analyses, typically used in statistical quality control (SQC), are applied to time series of yearly totals and of averages of the 12 monthly daily maxima, during the common 36-year period. Although there are some outlying points in the charts, there is no evidence of any trend or step changes. However, some supplementary permutation tests do provide weak evidence of an increase of variability of rainfall measures. Furthermore, a factor analysis does provide some evidence of a change in the spatial structure of extremes. The variability of a factor which represents the difference between extremes in the Adelaide Hills and the plains increases in the second 18 years relative to the first 18 years. There is also some evidence that the mean of this factor has increased in absolute magnitude.

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Acknowledgments

This study was funded by the Goyder Institute for Water Research under their Climate Change program. The researchers are grateful to the developers of the R project for software code and to the Australian Bureau of Meteorology for providing meteorological data.

Author information

Authors and Affiliations

  1. Centre for Water Management and Reuse, School of Natural and Built Environments, University of South Australia, Mawson Lakes, SA, 5095, Australia

    Mohammad Kamruzzaman & Simon Beecham

  2. School of Mathematical Sciences, University of Adelaide, Adelaide, SA, 5005, Australia

    Andrew V. Metcalfe

Authors
  1. Mohammad Kamruzzaman
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  2. Simon Beecham
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  3. Andrew V. Metcalfe
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Corresponding author

Correspondence to Mohammad Kamruzzaman.

Appendices

Appendix 1

Fig. 14
figure 14

Line plot representation of data quality in observed stations

Full size image

Appendix 2: Estimated coefficients of linear and quadratic terms t, SOI, PDO and their interaction effects on monthly daily maximum and monthly total rainfall using regression analysis

i Glen Osmond

 

Glen Osmond

Monthly daily maximum rainfall

Month total rainfall

Estimate

Std. error

t value

P-value

Estimate

Std. error

t value

P-value

Average

12.2400

1.228

9.967

0.000

24.2900

3.066

7.924

0.000

Linear t

0.0028

0.003

0.931

0.352

−0.0069

0.007

−0.925

0.355

Quad. t

0.0000

0.000

0.816

0.415

0.0000

0.000

1.682

0.093

Feb

−1.2900

1.652

−0.780

0.435

−3.7510

4.126

−0.909

0.363

Mar

−0.2284

1.650

−0.138

0.890

4.0720

4.120

0.988

0.323

Apr

4.9260

1.652

2.982

0.003

25.7700

4.124

6.248

0.000

May

8.5170

1.652

5.157

0.000

49.1600

4.124

11.919

0.000

June

7.3240

1.650

4.437

0.000

56.1300

4.121

13.621

0.000

July

5.5560

1.650

3.367

0.001

57.5900

4.120

13.978

0.000

Aug

5.2430

1.652

3.174

0.002

50.9600

4.124

12.358

0.000

Sep

3.7610

1.650

2.279

0.023

36.9800

4.121

8.975

0.000

Oct

3.0330

1.651

1.837

0.066

26.6600

4.122

6.468

0.000

Nov

2.3540

1.650

1.427

0.154

14.3300

4.119

3.479

0.001

Dec

2.3160

1.650

1.404

0.161

7.8500

4.120

1.906

0.057

PDO

0.3737

0.351

1.064

0.287

1.6830

0.877

1.920

0.055

SOI

0.1162

0.034

3.390

0.001

0.4815

0.086

5.626

0.000

PDOxSOI

−0.0470

0.030

−1.565

0.118

−0.1434

0.075

−1.912

0.056

ii Salisbury Bowling Club

 

Salisbury

Monthly daily maximum rainfall

Month total rainfall

Estimate

Std. error

t value

P-value

Estimate

Std. error

t value

P-value

Average

11.0000

1.117

9.848

0.000

18.8600

2.609

7.229

0.000

Linear t

0.0001

0.003

0.026

0.979

0.0029

0.006

0.461

0.645

Quad. t

0.0000

0.000

0.496

0.620

0.0000

0.000

0.305

0.761

Feb

0.1940

1.503

0.129

0.897

−0.0642

3.512

−0.018

0.985

Mar

1.1930

1.501

0.795

0.427

4.2700

3.507

1.218

0.224

Apr

3.6490

1.502

2.429

0.015

18.5700

3.510

5.291

0.000

May

5.8730

1.502

3.909

0.000

37.1100

3.510

10.573

0.000

June

7.1290

1.501

4.749

0.000

44.6000

3.508

12.716

0.000

July

2.6720

1.501

1.781

0.075

38.4100

3.507

10.952

0.000

Aug

4.1140

1.502

2.738

0.006

39.2000

3.510

11.168

0.000

Sep

3.7030

1.501

2.467

0.014

31.0800

3.507

8.861

0.000

Oct

4.0470

1.502

2.695

0.007

21.9200

3.509

6.246

0.000

Nov

2.2030

1.500

1.468

0.142

9.9220

3.506

2.830

0.005

Dec

2.6210

1.501

1.747

0.081

7.0280

3.506

2.004

0.045

PDO

0.6256

0.319

1.959

0.050

1.3750

0.746

1.842

0.066

SOI

0.0989

0.031

3.172

0.002

0.4033

0.073

5.536

0.000

PDOxSOI

−0.0584

0.027

−2.137

0.033

−0.0943

0.064

−1.478

0.140

Appendix 3

Fig. 15
figure 15

Residual from best fitted regression model for annual average monthly maximum rainfall. a Residuals against t (upper left), b histogram (upper right) and c normal quantile-quantile plot (lower left), d autocorrelation plots (lower right) for Glen Osmond

Full size image
Fig. 16
figure 16

Residual from best fitted regression model for annual total rainfall. a Residuals against t (upper left), b histogram (upper right) and c normal quantile-quantile plot (lower left), d autocorrelation plots (lower right) for Glen Osmond

Full size image
Fig. 17
figure 17

Residual from best fitted regression model for annual average monthly maximum rainfall. a Residuals against t (upper left), b histogram (upper right) and c normal quantile-quantile plot (lower left), d autocorrelation plots (lower right) for Salisbury

Full size image
Fig. 18
figure 18

Residual from best fitted regression model for annual total rainfall. a Residuals against t (upper left), b histogram (upper right) and c normal quantile-quantile plot (lower left), d autocorrelation plots (lower right) for Salisbury

Full size image

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Kamruzzaman, M., Beecham, S. & Metcalfe, A.V. Changing patterns in rainfall extremes in South Australia. Theor Appl Climatol 127, 793–813 (2017). https://doi.org/10.1007/s00704-015-1667-8

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  • DOI: https://doi.org/10.1007/s00704-015-1667-8

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