the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 Mar 2024
Multi-scale variability of southeast Australian wind resources
Abstract. There is growing need to understand wind variability in various regions through the world, including in relation to wind energy resources. Here we examine wind variability in southeast Australia in relation to the El Niño-Southern Oscillation (ENSO) as a dominant mode of atmospheric and oceanic variability for this region. The analysis covers variability from seasonal to diurnal time scales for both land and maritime regions of relevance to wind energy generation. Wind speeds were obtained from the 12 km grid-length BARRA reanalysis produced for the Australian region, with focus on wind at a typical hub-height of 100 m above the surface. Results show spatiotemporal variations in how ENSO influences wind speeds, including consistency in these variations over the wind speed distribution. For example, ENSO-related variations in mean winds were mostly similar in sign to ENSO-related variations in weak winds, noting uncertainties for strong winds given available data. Diurnal variability in wind speed was larger for summer than winter and for land than ocean regions, with the diurnal cycle maxima typically occurring in the afternoon and evening rather than morning, plausibly associated with sensible heating of air above land following solar radiation. Localised variations in the diurnal cycle were identified around mountains and coastal regions. The results show some indication of ENSO influences on the diurnal variability. These findings are intended to help enhance scientific understanding on wind variability including in relation to ENSO, as well as contribute information towards practical guidance in planning such as for use in energy sector applications.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(8746 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-228', Anonymous Referee #1, 07 Mar 2024
The article compares predicted windspeeds for Southern EasternAustralia during El Niño and La Niña events, examining the frequency of both low windspeed and high windspeed events, based on data from the Barra dataset.
While the results of the study are interesting there are a few factors that would be worthwhile following up on:
1) The focus of the article is on windspeeds at a height of 100m, which is a little small for offshore wind turbines. It would be instructive to see how the results compare for a more typical offshore turbine hub height (150-200m)
2) While there is some mention of renewable droughts, the article does not discuss the effect on power output.
3) Likewise it would be instructive to understand how variability in windspeed (not just average speeds, and frequency of fast and slow events) change as a result of El Niño/La Niña.
4) It might be worthwhile indicating how diurnal maxima match with peak demand periods from the electricity network in figure 5.
Citation: https://doi.org/10.5194/egusphere-2024-228-RC1 -
RC2: 'Comment on egusphere-2024-228', Anonymous Referee #2, 20 Mar 2024
General comments:
This is a useful and clear study. The scope and discussion are appropriate, the results are novel, all the analyses and interpretation seem reasonable. It’s a nice paper! I have provided quite a few specific and technical comments below but none of them take issue with the science, they are just to help improve the manuscript.
The only thing I feel uneasy about is how the choice of calculating the 100-m wind speeds from winds at other elevations impacts the results, especially for diurnal variability and in regions where the diurnal range in ABL stability is large (e.g., on land far from coasts). Maybe the authors are satisfied with the approach, but it isn’t demonstrated in the manuscript and all the results depend on its veracity.
Specific comments:
Line 32: In Gunn et al (2023) the interannual variability was not formally attributed to ENSO, but reasonably high absolute correlations were found with annual wind power and ENSO in parts of Australia.
Line 45: This sentence about the ENSO-SAM linkage is a bit terse and maybe ambiguous. Maybe I am misinterpreting “zonally symmetric alternating”, but it could be clearer to simply say what El Niño does to SAM and how it’s expressed in pressure and geopotential height.
Line 101: I imagine a logarithmic Law of the Wall is fine with data averaged across a range of atmospheric stabilities temporally, but in detail each hourly wind profile may have very poor fits, especially at night, large absolute stabilities, near topographic obstacles, and near coasts. Of course, some choice must be made about how to interpolate the data for 100-m hub height, but it isn’t demonstrated or explained why this is the best way for the problem at hand rather than an alternative (say, the simplest: linear interpolation between 76.7 m and 130 m). I think this Law of the Wall fit probably ends up dampening the temporal variability in the 100-m wind speeds compared to others (splines, differencing schemes, M-O theory, etc).
Sections 3.1 & 3.2: It would be useful to provide up front what the absolute values for wind speed and frequency of <5 and >25 m/s winds are so that the anomalies can be contextualised. I recognise that average wind speed is given in Figure 8, and Figures 2 & 3 are normalised, but it would be useful for the reader if it was known a priori. Even a frequency distribution of wind speeds could be nice – this would help put the mean and tails in context, and verify the distribution looks Weibull.
Figure 3: The 5 hours/season definition on Line 217 is inconsistent with the 10 hours/year in the caption. Masking out low frequency locations seems appropriate, but it should probably be done with a colour not on the colour map (e.g., grey, not white).
Figure 6: Is it possible to do the stippling and neutral conditions like Figures 1-3 here too?
Line 338: I don’t know if the “continuous ridge” apparent in Figure 9 during El Niño isn’t apparent in La Niña simply because of which contour lines have been chosen – the shape (not magnitude) of the pattern looks very similar across both modes.
Line 348: This is interesting but should be qualified by noting there’s no stippling for this relationship.
Line 376: I don’t think the results suggest that ENSO influences the timing of the diurnal wind speed cycle. I believe that only the top row of Figure 8 is presented for ENSO-dependent diurnal cycle: there’s no phase shift there.
Line 413: Maybe this should be qualified by noting only regions where amplitudes are >0.5 m/s.
Line 422: How much is the timing related to low-level nocturnal jets? I would have guessed the flip from day to night peaks between boxes 1 and 2, respectively, was due to them being more prevalent over regions with lower relief and heat capacity. On the other hand, the amplitude of the relationship is lower in box 2. In any case, fitting a logarithmic profile to the data ensures this phenomenon isn’t captured appropriately.
Technical corrections:
Line 53: missing “s” on “mode”.
Line 56: parenthesis on reference missing, capitalised “Anomalies” (or maybe a full stop missing beforehand?).
Line 89: this was only RMSE within Australia, yet the word “global” (for the other reanalyses coverage) make this ambiguous.
Line 121: a reference for precedent of this definition of ENSO states would be useful.
Line 150: “et al” missing for Gunn et al (2023) reference.
Line 298: I think there’s an erroneous “including” in this sentence.
Line 318: I think the “that” should be a “than”.
Figure 8: Could the boxes in the figure be labelled?
Line 341: The tildes on ENSO mode “n” characters are missing.
Line 386: I think it’s supposed to say “weak winds occur more frequently” for La Niña SON over the continent (as per Figure 2).
Citation: https://doi.org/10.5194/egusphere-2024-228-RC2 - AC1: 'Comment on egusphere-2024-228', Claire Vincent, 04 Jun 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-228', Anonymous Referee #1, 07 Mar 2024
The article compares predicted windspeeds for Southern EasternAustralia during El Niño and La Niña events, examining the frequency of both low windspeed and high windspeed events, based on data from the Barra dataset.
While the results of the study are interesting there are a few factors that would be worthwhile following up on:
1) The focus of the article is on windspeeds at a height of 100m, which is a little small for offshore wind turbines. It would be instructive to see how the results compare for a more typical offshore turbine hub height (150-200m)
2) While there is some mention of renewable droughts, the article does not discuss the effect on power output.
3) Likewise it would be instructive to understand how variability in windspeed (not just average speeds, and frequency of fast and slow events) change as a result of El Niño/La Niña.
4) It might be worthwhile indicating how diurnal maxima match with peak demand periods from the electricity network in figure 5.
Citation: https://doi.org/10.5194/egusphere-2024-228-RC1 -
RC2: 'Comment on egusphere-2024-228', Anonymous Referee #2, 20 Mar 2024
General comments:
This is a useful and clear study. The scope and discussion are appropriate, the results are novel, all the analyses and interpretation seem reasonable. It’s a nice paper! I have provided quite a few specific and technical comments below but none of them take issue with the science, they are just to help improve the manuscript.
The only thing I feel uneasy about is how the choice of calculating the 100-m wind speeds from winds at other elevations impacts the results, especially for diurnal variability and in regions where the diurnal range in ABL stability is large (e.g., on land far from coasts). Maybe the authors are satisfied with the approach, but it isn’t demonstrated in the manuscript and all the results depend on its veracity.
Specific comments:
Line 32: In Gunn et al (2023) the interannual variability was not formally attributed to ENSO, but reasonably high absolute correlations were found with annual wind power and ENSO in parts of Australia.
Line 45: This sentence about the ENSO-SAM linkage is a bit terse and maybe ambiguous. Maybe I am misinterpreting “zonally symmetric alternating”, but it could be clearer to simply say what El Niño does to SAM and how it’s expressed in pressure and geopotential height.
Line 101: I imagine a logarithmic Law of the Wall is fine with data averaged across a range of atmospheric stabilities temporally, but in detail each hourly wind profile may have very poor fits, especially at night, large absolute stabilities, near topographic obstacles, and near coasts. Of course, some choice must be made about how to interpolate the data for 100-m hub height, but it isn’t demonstrated or explained why this is the best way for the problem at hand rather than an alternative (say, the simplest: linear interpolation between 76.7 m and 130 m). I think this Law of the Wall fit probably ends up dampening the temporal variability in the 100-m wind speeds compared to others (splines, differencing schemes, M-O theory, etc).
Sections 3.1 & 3.2: It would be useful to provide up front what the absolute values for wind speed and frequency of <5 and >25 m/s winds are so that the anomalies can be contextualised. I recognise that average wind speed is given in Figure 8, and Figures 2 & 3 are normalised, but it would be useful for the reader if it was known a priori. Even a frequency distribution of wind speeds could be nice – this would help put the mean and tails in context, and verify the distribution looks Weibull.
Figure 3: The 5 hours/season definition on Line 217 is inconsistent with the 10 hours/year in the caption. Masking out low frequency locations seems appropriate, but it should probably be done with a colour not on the colour map (e.g., grey, not white).
Figure 6: Is it possible to do the stippling and neutral conditions like Figures 1-3 here too?
Line 338: I don’t know if the “continuous ridge” apparent in Figure 9 during El Niño isn’t apparent in La Niña simply because of which contour lines have been chosen – the shape (not magnitude) of the pattern looks very similar across both modes.
Line 348: This is interesting but should be qualified by noting there’s no stippling for this relationship.
Line 376: I don’t think the results suggest that ENSO influences the timing of the diurnal wind speed cycle. I believe that only the top row of Figure 8 is presented for ENSO-dependent diurnal cycle: there’s no phase shift there.
Line 413: Maybe this should be qualified by noting only regions where amplitudes are >0.5 m/s.
Line 422: How much is the timing related to low-level nocturnal jets? I would have guessed the flip from day to night peaks between boxes 1 and 2, respectively, was due to them being more prevalent over regions with lower relief and heat capacity. On the other hand, the amplitude of the relationship is lower in box 2. In any case, fitting a logarithmic profile to the data ensures this phenomenon isn’t captured appropriately.
Technical corrections:
Line 53: missing “s” on “mode”.
Line 56: parenthesis on reference missing, capitalised “Anomalies” (or maybe a full stop missing beforehand?).
Line 89: this was only RMSE within Australia, yet the word “global” (for the other reanalyses coverage) make this ambiguous.
Line 121: a reference for precedent of this definition of ENSO states would be useful.
Line 150: “et al” missing for Gunn et al (2023) reference.
Line 298: I think there’s an erroneous “including” in this sentence.
Line 318: I think the “that” should be a “than”.
Figure 8: Could the boxes in the figure be labelled?
Line 341: The tildes on ENSO mode “n” characters are missing.
Line 386: I think it’s supposed to say “weak winds occur more frequently” for La Niña SON over the continent (as per Figure 2).
Citation: https://doi.org/10.5194/egusphere-2024-228-RC2 - AC1: 'Comment on egusphere-2024-228', Claire Vincent, 04 Jun 2024
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Claire Louise Vincent
Andrew J. Dowdy
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(8746 KB) - Metadata XML