the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
On predicting offshore hub-height wind speed and wind power density in the Northeast US coast using high-resolution WRF model configurations during anticyclones coinciding with wind drought
Abstract. We investigated the predictive capability of various configurations of the Weather Research and Forecasting (WRF) model version 4.4, to predict hub-height offshore wind speed and wind power density in the Northeast US wind farm lease areas. The selected atmospheric conditions were high-pressure systems (anticyclones) coinciding with wind speed below the cut-in wind turbine threshold. There are many factors affecting the potential of offshore wind power generation, one of them being low winds, namely wind droughts, that have been present in future climate change scenarios. The efficiency of high-resolution hub-height wind prediction for such events has not been extensively investigated, even though the anticipation of such events will be important in our increased reliance on wind and solar power resources in the near future. We used offshore wind observations from the Woods Hole Oceanographic Institution's (WHOI) Air-Sea Interaction Tower (ASIT) tower located south of Martha’s Vineyard to assess the impact of initial and boundary conditions, number of model vertical levels, and inclusion of high-resolution sea surface temperature (SST) fields. Our findings showed that the initial and boundary conditions exhibited the strongest influence on hub height wind predictions above all other factors, such as SST and model vertical layers. NAM/WRF and HRRR/WRF were able to capture the decreased wind speed, and there was no single configuration that systematically produced better results. However, when using the predicted wind speed to estimate wind power density, HRRR/WRF had statistically improved results, with lower errors than NAM/WRF. Our work underscored that for predicting offshore wind resources, it is important to evaluate not only the WRF predictive wind speed, but also the connection of wind speed to wind power.
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Interactive discussion
Status: closed
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RC1: 'Comment on wes-2023-148', Anonymous Referee #1, 27 Jan 2024
The authors conducted different combinations of the WRF model configurations in forecasting wind speed/WPD for offshore wind farm. They focused on using different initial and boundary conditions, SST input, and number of vertical layers to investigate the sensitivity of the modeled wind to the different configurations at high-resolution grid spacing (dx = 600m). The paper is within the scope of Wind Energy Science Discussions. However, according to the reviewer, this manuscript needs to be revised to become clear and suitable for publication.
There are main comments:
- Novelty of the idea and contributions need to be added to the introduction as bullet points.
- The limitations of the proposed approach (if any) should be mentioned in the conclusion, given the vague results/conclusions in the manuscript.
- The author assumes that three components (initial and boundary components, SST, and vertical layers) have impacts on the WRF model. Are there other components which can significantly or potentially impact modeled wind from NWP models (e.g., PBL parameterizations, data assimilation, nesting, spin-up time, convection schemes, etc.)?
- 600-m grid spacing is still under “Grey Zone”. Any rationales why the authors have not tested different PBL schemes? For example, there is a WRF PBL scheme (e.g., Shin-Hong PBL) specialized for the sub-kilometer transition scale.
- What is the advantage of using the 600-m grid when compared to using lower spatial resolutions, e.g., dx > 1-km? Basically, running WRF model with the sub-kilometer grid is computationally expensive, and the authors still use the parameterizations for their wind forecasts. Do you think the proposed approach can be usable/applicable for actual wind energy applications?
- Lack of analysis in different scales: The authors focused on analyzing the sensitivity of WRF experiments to the wind prediction with error/bias for point locations. They could see and analyze wind shear or 2D maps of modeled hub-height wind from different WRF experiments.
- Do the authors think if their WRF experiments tested for only 4 events would be enough to represent the proposed sensitivity analysis?
- It would be good if the authors could increase font size a little on Figures 5-11 (on x,y axis and legend).
- Is it possible to add plots including an analysis of statistical metrics for “All events” in sections 3.1-3.3, so that readers can comfortably understand the overall result for each sensitivity analysis, even if the sample size of WRF experiments is small?
Citation: https://doi.org/10.5194/wes-2023-148-RC1 -
AC1: 'Reply on RC1', Marina Astitha, 19 Mar 2024
Dear reviewer,
We greatly appreciate your time and effort to review our manuscript. Your questions and comments will help us improve the quality and presentation of the paper.
Unfortunately, we have decided to withdraw the paper from Wind Energy Science, due to inaction and no response from the editorial office for a second reviewer to continue with the review process. It has been 5 months since submission.
Again, we greatly value the time you spent for this review, and we will use your comments to revise the manuscript accordingly.
Sincerely,
Prof. Marina Astitha (corresponding author)
Citation: https://doi.org/10.5194/wes-2023-148-AC1
Interactive discussion
Status: closed
-
RC1: 'Comment on wes-2023-148', Anonymous Referee #1, 27 Jan 2024
The authors conducted different combinations of the WRF model configurations in forecasting wind speed/WPD for offshore wind farm. They focused on using different initial and boundary conditions, SST input, and number of vertical layers to investigate the sensitivity of the modeled wind to the different configurations at high-resolution grid spacing (dx = 600m). The paper is within the scope of Wind Energy Science Discussions. However, according to the reviewer, this manuscript needs to be revised to become clear and suitable for publication.
There are main comments:
- Novelty of the idea and contributions need to be added to the introduction as bullet points.
- The limitations of the proposed approach (if any) should be mentioned in the conclusion, given the vague results/conclusions in the manuscript.
- The author assumes that three components (initial and boundary components, SST, and vertical layers) have impacts on the WRF model. Are there other components which can significantly or potentially impact modeled wind from NWP models (e.g., PBL parameterizations, data assimilation, nesting, spin-up time, convection schemes, etc.)?
- 600-m grid spacing is still under “Grey Zone”. Any rationales why the authors have not tested different PBL schemes? For example, there is a WRF PBL scheme (e.g., Shin-Hong PBL) specialized for the sub-kilometer transition scale.
- What is the advantage of using the 600-m grid when compared to using lower spatial resolutions, e.g., dx > 1-km? Basically, running WRF model with the sub-kilometer grid is computationally expensive, and the authors still use the parameterizations for their wind forecasts. Do you think the proposed approach can be usable/applicable for actual wind energy applications?
- Lack of analysis in different scales: The authors focused on analyzing the sensitivity of WRF experiments to the wind prediction with error/bias for point locations. They could see and analyze wind shear or 2D maps of modeled hub-height wind from different WRF experiments.
- Do the authors think if their WRF experiments tested for only 4 events would be enough to represent the proposed sensitivity analysis?
- It would be good if the authors could increase font size a little on Figures 5-11 (on x,y axis and legend).
- Is it possible to add plots including an analysis of statistical metrics for “All events” in sections 3.1-3.3, so that readers can comfortably understand the overall result for each sensitivity analysis, even if the sample size of WRF experiments is small?
Citation: https://doi.org/10.5194/wes-2023-148-RC1 -
AC1: 'Reply on RC1', Marina Astitha, 19 Mar 2024
Dear reviewer,
We greatly appreciate your time and effort to review our manuscript. Your questions and comments will help us improve the quality and presentation of the paper.
Unfortunately, we have decided to withdraw the paper from Wind Energy Science, due to inaction and no response from the editorial office for a second reviewer to continue with the review process. It has been 5 months since submission.
Again, we greatly value the time you spent for this review, and we will use your comments to revise the manuscript accordingly.
Sincerely,
Prof. Marina Astitha (corresponding author)
Citation: https://doi.org/10.5194/wes-2023-148-AC1
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