Evaluation and Impact Factors of Doppler Wind Lidar during Super Typhoon Lekima (2019)
Abstract. Doppler wind lidar (DWL) has been shown to obtain fairly accurate wind speeds in normal wind conditions. However, the evaluation of DWL winds under typhoon conditions is less common. This study evaluated the accuracy of wind data measured by two types of DWLs (WindPrint S4000 and WindCube V2), and investigated the impact of factors (e.g., precipitation and humidity) on the DWL-observed wind speed and direction. Data were collected from joint observations in Baoshan, Zhoushan and Taizhou (China) by the Shanghai Typhoon Institute during the passage of Super Typhoon Lekima in 2019. The DWL observations were compared with measured data from balloon-borne radiosonde released at the same location. The results showed that the 1-min average wind speed and direction of WindPrint S4000 were more consistent with the instantaneous observation data of the sounding balloon than those of WindCube V2. The applicability of DWL was poor when the precipitation intensity was larger than 50 mm · h−1. The DWL wind speed bias significantly increased when the relative humidity exceeded 85 %. When the drift distance of the sounding balloon (ldrift) was less than 1 km, the DWL wind speed bias decreased with an increase of ldrift, whereas it increased with an increase of ldrift when the drift exceeded 1.5 km. Within a radius of 700 km, the root mean square of wind speeds between DWL and sounding balloon measurements showed a trend of increasing as the distance from the typhoon center decreased.
This preprint has been withdrawn.
Xu Wang et al.
Xu Wang et al.
Xu Wang et al.
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The paper Evaluation and Impact Factors of Doppler Wind Lidar during Super Typhoon Lekima (2019) is reviewed with the following comments.
It is an interesting study on Doppler wind lidar data vs. radiosonde data during and near typhoon conditions at three locations in China. The general impression though is that the background for the study, the results and conclusion need much more work to appear in a final form. There appears misinterpretation and lack of focus on the working hypothesis. The fundaments on the theoretical insight is too limited and not presented in a clear and structured way. The paper is rejected.
Lines 16-19 on bias and distance from the typhoon center is not possible to follow in a logical way. This situation also goes for other sections in the paper related such as section 5.3. In case the bias mentioned is shown in Figure 11a and 11b, it does not correspond to the text, and again in lines 472-477 is discrepancy. Overall question is how would you argue that longer distances are giving other results than shorter distances, why and how?
In the introduction several works are cited related to correlation coefficient and RMS but bias is not mentioned. Why is that? It might give a better overview with a table on previous researchers work summarizing their statistics.
Lines 66-74 The text could benefit from more fundamental information on the challenges of Doppler wind lidar and radiosondes in typhoon conditions. It becomes difficult to follow what is the key information and why the measurement techniques is expected to have lower performance than in less windy and rainy conditions. A thought here, is this your hypothesis you are testing? In case so it would be valuable to state this clearly.
Line 81 wording “generally good” is not sufficiently clear
Section 2.1 and 2.2 might be complemented with other auxiliary information if available, e.g. model results of the case and/or local wind speed and direction measurements or from aircraft, to better understand the variability in time and space.
Section 3.1.1. this section would greatly benefit from fundamental knowledge on the two types of lidars. Technical information should appear in the introduction in general terms, so that during the subsequent part of the paper, it is clear what to expect. The specifications on expected accuracy on all the observed parameters from the WindPrint and the WindCubes should be clear. The entire paper is about this topic. Table 2 is included but without further description or explanation (or reference to the values).
Table 1. To clarify, from Bashan there is 43 hours of data, from Zhoushan 24 hours of data and from Taizhou 72 hours of data? It would be valuable to list the number of available valid samples for each. Also in case some samples are invalid, it is relevant to understand this, as it is part of how well given instruments perform.
Section 3.2 is a very basic text and as reader one is left wondering what is the situation when aerosol content, humidity, precipitation, etc. comes into the equations. What effect do you foresee in typhoon conditions. This background would have to be given carefully for both types of lidars, and as well the two radiosonde types. How much more can we expect to trust the various instruments? This remains unclear as is.
Line 191, I do not understand what you mean with “data efficiency”, please clarify
Lines 225-229, this text on aerosol is unclear and not precise. It is difficult to follow what you explain. In case it is fundamental background, it should be presented much earlier in the paper.
Lines 245-250 This text on turbulence and the instruments should be given in background, and corrected, as it is unclear what you are stating. The text is loosely structured, it cause confusion for the reader.
Lines 257-260 This is not correct. Figure 5 shows hardly any DWL data below 100 m height range and in plots a), d) and e) the sonde gives higher values while in plots b) and c) the sonde gives lower values.
Line 285 rephrase “this was due” to e.g. “most likely”. The interpretation of results is not definitive, so you need caution.
Table 3 Would suggestion to include the number of samples and the bias values.
Section 5.1 On precipitation raised a couple of questions. The measurements were taken on the ground (I presume). Do you assume the rain to be homogenous during the entire atmospheric column? Is this valid, or if not always, what may be the case. SNR (signal to noise ratio) explains how good data you have but it appears as you take is as a measure.
Figure 8a and 8b have different scales. Is this intentional, please clarify and note in the text. It would be relevant to related to these plots and at this time revisit why the dB are so different from the two types of lidars, and what we learn from this. If you are comparing the two plots directly between each other (or wish the readers to do so), it is recommended to use the same scale x-axis (rain intensity) and secondary y-axis (sample size) in both plots.
Lines 386-390 on humidity would be place better in the introduction or background section.
Figure 10, why do we hear about bias here for the first time? It is recommended to report on bias throughout the paper, not only for humidity.
Figure 11, would figure b) be a mistake. Is the bias on wind direction around 65 degrees? You have written about a small RMS on wind direction but if there is a very significant bias, that would actually be even more important to report.
Section 5.4 and in particular Figure 12 raises many more question than give answers to the data analysis. Either rework or omit. It is not clear what you wish to present and what can be concluded (also keeping in mind the other uncertainties dealt with earlier).
Line 29, Cot
Line 34 Kopp would be Köpp 1984?
Line 48 carried out by
Line 55 with the height range (several other places you could add height to clarify your text)
Line 61 Korb? Not in your reference list
Line 189 Goit? Not in your reference list
Line 254 Li et al 2018, you have two references of this, so please add a and b to distinguish
Reference list is not in good shape, as the format changes very much. There is several ‘gray literature” please remove.
There are many more technical corrections (but not listed).
Further English editing is necessary.