the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Sep 2024
Evolution of Wind Field in the Atmospheric Boundary Layer with using of Multiple Sources Observations during the Transit of Super Typhoon Doksuri (2305)
Abstract. The accurate wind field observation of tropical cyclone (TC) boundary layer is of great significance to improve the TC track and intensity forecasting. To investigate the vertical structure of TC boundary layer during the landfall process of Super Typhoon Doksuri, three kinds of instruments including the coherent Doppler lidar (CDL), radar wind profiler (RWP) and automatic weather station (AWS) are deployed at two sites in Xiamen, Fujian province. A data fusion method is developed to obtain the complete wind speed profiles covering the whole Atmospheric Boundary Layer (ABL) based on the above instruments. The wind speeds in the near field blind zones of CDL observation are interpolated by combining the AWS measurements at 10 m. The CDL provides high temporal-spatial resolution wind speed profiles from tens of meters to its highest detection height. The wind speeds above the highest detection height of the CDL would be supplemented with the RWP measurements. The hourly mean wind speed profiles are compared with traditional models. Generally, the wind speed profiles fit well with the power law in the lower part of the ABL, before wind speed changes rapidly. However, it would cause a large error (up to 73 %) to describe the exact wind speed profiles with traditional models during and after the typhoon’s passage, especially when the wind speed is almost constant with height or when wind shear exists. Then fine structures and evolutionary processes of the wind field in the ABL during the typhoon landfall are investigated. In addition, the wind field distribution and wind speed variation with distance from the typhoon center are statistical analyzed. The joint wind field measurements of CDL, RWP and AWS have the broad application prospects on the dynamics study of the TC boundary layer and the improvement of the boundary layer parameterization scheme in numerical forecast models.
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Status: open (until 19 Mar 2025)
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CC1: 'Comment on amt-2024-156', Chong Wang, 06 Nov 2024
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The tropical cyclone is the most severe meteorological disasters in southeastern of china, the background in the introduction is described in detail. This work is co-operated with China Meteorological Administration (CMA)，combining with other observation methods, no-blind zone wind speed profiles is achieved.
Here are some suggestions
1) Cloud information is important during the tropical cyclone, so, the CNRs are necessarily in the figures.
2) More evolution of wind field during the tropical cyclone should be discussed.Citation: https://doi.org/10.5194/amt-2024-156-CC1 -
RC1: 'Comment on amt-2024-156', Anonymous Referee #1, 03 Jan 2025
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The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2024-156/amt-2024-156-RC1-supplement.pdf
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RC2: 'Comment on amt-2024-156', Anonymous Referee #2, 21 Feb 2025
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General comments：
This manuscript presents a data fusion method to obtain the complete wind speed profiles with the combination observation of the CDL, RWP and AWS. And this method was applied and showed good performance during the landfall process of Super Typhoon Doksuri. As CDL, RWP and AWS are widely deployed in the southeastern coastal areas of China, I think this method has practical value and broad application prospects in the wind field observation within the typhoon boundary layer. The main topic of this manuscript is of interest to the readership of AMT. I recommend this manuscript for publication after addressing the following comments.1. The core of this paper lies in the data fusion of CDL and RWP. How is the wind profile retrieved in the transition zone (or the overlapping data region) of the data? Has an assessment been conducted to evaluate the consistency of wind speed and direction observations between the two instruments?
2. In section 4.3, you mentioned that the traditional models cause a large error (up to 73%) to describe the exact wind speed profiles during and after the typhoon’s passage, especially when the wind speed is almost constant with height or when wind shear exists. How was the 73% error calculated? It would be better to give a more detailed error analysis.
3. In Line 271 to line 272, you mention that the detection range of the CDL decreased sharply affected by the high precipitation. Have you tried to utilize other techniques, such as raindrop size distribution measurements, to mitigate the impact of precipitation on the performance of CDL?
4. In this manuscript, the evolution characteristics of the vertical profiles of horizontal wind speed and direction at two stations were analyzed. Have you attempted to utilize multi-station observations to investigate the three-dimensional structure of the typhoon, such as vortex characteristics?
5. Is it possible to give a a further discussion for conclusion (4) in the manuscript regarding on the findings on wind speeds of “15 m/s to 25 m/s on 28 July..maximum wind speed values of 51.25 m/s and 52.34 m/s..” An explanation of the such findings’ significance would be more interesting for the readerships instead of list the information.Specific comments：
1. Line 106, change “labeled” to “labelled”.
2. Line 196, it would be better that “980” and “hPa” list in the same line.
3. Line 220, remove “of two instruments”.
4. Line 240, change “wind shear layers appeared at 600 m during 11:00 LST ~ 13:00 LST and 1100 m during 12:00 LST ~ 13:00 LST” to “wind shear layers appeared at 600 m and 1100 m during 11:00 LST ~ 13:00 LST and 12:00 LST ~ 13:00 LST, respectively”.
5. Figure 6: please explain why not to set the intercept to be zero in the linear regression model since two exact same physical quantities are compared? What are the physical significance of these two intercept individually?Citation: https://doi.org/10.5194/amt-2024-156-RC2
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