the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Interdecadal Cycles in Australian Annual Rainfall
Abstract. The extremes of Australian rainfall have profound economic, ecological and societal impacts; however, the current forecast horizon is limited to a few months. This study investigates interdecadal periodicity in annual rainfall records across eastern Australia. Wavelet analysis was conducted on rainfall data from 347 sites covering 130 years (1890–2020). Prominent cycles were extracted from each site and clustered using a Gaussian Mixture Model. This revealed three principal cycles centred around 12.9, 20.4 and 29.1 years that were highly significant over red noise by t-test (p<0.0001). Overall, the three cycles combined had a mean contribution to total rainfall variance (R2) of 13 % across all sites, but this was up to 29 % at individual sites. Both the 12.9-yr and 20.4-yr cycles were detected at over 95 % of sites. The strength of each cycle varied over time and this amplitude modulation of the signal showed a systematic movement across the area investigated. 86 % of extremely wet years fell within the positive phase of the combined reconstruction, with 80 % of extremely dry years falling in the negative phase. These results indicate underlying periodicity in annual rainfall across eastern Australia, with the potential to build this into long-term forecasts. This concept has been suggested in the past, but not rigorously tested. These findings open new paths for research into rainfall patterns in Australia and internationally. They also have broad implications for the management of water resources across all sectors.
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Status: open (until 24 Jan 2025)
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RC1: 'Comment on egusphere-2024-3149', Anonymous Referee #1, 08 Dec 2024
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The manuscript is clearly written and presented. The methods used are standard and clear. The results are appropriately analyzed. The main shortcoming is that there is no effort to explain the results or to add insight to them. For instance, I assume that there are distinct seasons for rainfall in at least part of the region of Australia that was analyzed
Would it make sense to look for composites of atmospheric and oceanic state variables for the +ve and -ve phases of the 3 oscillations and/or to do a similar wavelet-clustering analysis of those variables and/or look for the wavelet coherence of some of those variables with the precipitation time series?
I think doing something like that would help make the paper more convincing
Some similar work is reported in https://www.mdpi.com/2306-5338/10/3/67
Citation: https://doi.org/10.5194/egusphere-2024-3149-RC1 -
RC2: 'Comment on egusphere-2024-3149', Anonymous Referee #2, 03 Jan 2025
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In this study, the authors investigate interdecadal periodicity in annual rainfall records across eastern Australia. They employ wavelet analysis and a Gaussian Mixture Model to extract and cluster prominent cycles from rainfall data collected at 347 sites covering 130 years (1890-2020). The results confirm the existence of an underlying periodicity in annual rainfall across eastern Australia, with three dominant cycles identified in the rainfall records. This analysis aims at explaining some of the disparate earlier findings and provides the basis for building long-term forecasts. This could open new paths for research into rainfall patterns in Australia and internationally, with broad implications for the management of water resources across all sectors.
The scientific contribution of this paper falls within the scope of Hydrology and Earth System Sciences. The paper is well-written with a clear and well-organized structure. The findings are appropriately discussed and related to previous works on the same topic. The discussion is efficiently supported by figures.
I suggest considering just some minor revisions:
- While the concept of periodicity of rainfall events in Australia is widely and carefully explored, citing a number of previous studies, the choice of using wavelet analysis in this work is not adequately motivated. Is this the first application of wavelet analysis to a hydrological dataset? What are the advantages? Please provide a wider explanation and eventually cite previous papers using this technique to support your choice.
- The visualization of the results is crucial and I found all the figures suitable to convey the different messages about dominant cycles. The only figure that needs some substantial changes is the first. I suggest improving Fig.1 to make it easier to interpret. Furthermore, it appears to have a very low definition, I suggest improving the visualization quality.
- In Fig.5, the letters that indicate the different panels do not correspond to the letters in the caption and in the text where the results are discussed.
- In Fig.4 and 6, I suggest changing the colormap to help the reader distinguish the cycle families and I also recommend making more evident the sites with significant cycles over red noise (I have difficulties in the identification of the points circled in white as it is now).
- Page 5 line 102: possible typo “p”lane.
- Page 15 line 311: typo "20.4-yrcyclecan".
- Page 22 line 427: possible typo “the allowed”.
Citation: https://doi.org/10.5194/egusphere-2024-3149-RC2
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