A Review of Techniques for Diagnosing the Atmospheric Boundary Layer Height (ABLH) Using Aerosol Lidar Data

Round 1

Reviewer 1 Report

General comments

This paper is a review of 6 methods of defining the ABLH and several combinations of those methods. Technically, the discussion of those options is reasonably sound and well referenced. Given that it is a review paper that offers no new approaches or insights to the challenge, it’s “value added” contribution could be increased by providing more challenging ABL examples drawn from “the real world”. As it stands, it is a nice summary of techniques in one place and thus may serve a researcher as a source of references. However, the same can be said for a Google search.

Throughout the paper I kept looking for the definition of the “true” ABLH. The closest the authors come to that is between lines 41 and 44. If this review paper is to be truly useful as a reference, the use of Temp/RH in the definition of the ABLH should be included in each technique’s discussion, not just in Figure 1.

I would recommend publication after the addition of some examples of nocturnal ABLs, fossil or residual layers and cloud topped ABLs. Also, there are numerous misspellings and misuse of English words throughout the document.

Specific comments (reference by line #)

72            First reference to CBL should be spelled out

169-170  This sentence does not make sense as written.

261-275  Since the choice of “a” is so critical, what are some examples and rules for defining it?

536-538  What is truth? Since no method is “perfect” what is the Figure of Merit (FOM) for any technique? The degree of autonomous processing of large data sets?

A few lines with grammar or spelling errors:

74, Table 1, 125,126,130,136,140,316,326,355,356,458,537,570

Author Response

Response to Reviewer #1 (remote-sensing 429292)

We thank the reviewer very much for taking time to handle and review our manuscript. Thank you for your recognition of our work. We have carefully considered and addressed all the valuable comments. Please see our detailed reply below in blue.

This is an interesting paper and I, personally, will explore the use of published technique with data from my airborne Doppler Wind Lidars.

The paper is well written with a few grammar errors and “awkward” word usage.

The figures are readable.

The referenced material is an excellent selection.

Specific comments and suggestions

(1)     33/34: “great concordance” and “great agreement” are not supported by the results. Perhaps “good” or “reasonable” may be better qualitative adjectives.

Reply: Yes, Thanks. The concordance has been quantified and the description has been written as: “While comparing the lidar-determined ABLH by HM (or CFM) and nearby radiosonde measurements of the ABLH, a reasonable concordance is found with a correlation coefficient of 0.94 (or 0.96) and 0.79 (or 0.74), presenting a mean of the relative absolute differences respect to radiosonde measurements of 10.5% (or 12.3%) and 22.3% (or 17.2%) for cloud-free and cloudy situations. The diurnal variations in the ABLH determined from HM and CFM on 4 selected cases show good agreement with mean correlation coefficient higher than 0.99 and a mean absolute bias of 0.22 km.”

See lines 33-39 of the revised version.

The qualitative results in the text are presented in Table 1, Table 2 and described in section 4.1 and 4.2 of the revised manuscript.

Table 1. Correlation coefficients (R), absolute height differences (mean and standard deviation (std) in km) between ABLH determined by theta gradient and by Haar wavelet covariance transform method (HM) or curve fitting method (CFM) in different situations, as well as mean value of relative absolute differences relative to theta-gradient-determined ABLH in average (rd, in 100%).

Table 2. Correlation coefficients (R) and absolute height differences (mean and standard deviation (std) in km) between ABLH retrieved by HM and CFM based on lidar data on 4 selected cases.

(2)     121/123: While the reference to Welton and Campbell (42) is fine, the resulting NRB needs more “in depth” discussion. The NRB is the basic quantity that is being evaluated in this paper.

Reply: Yes, we agree. The NRB are detail introduced in the revised manuscript as below:

The Micro-Pulse Lidar system (MPL-4B) installed at SACOL emits a laser pulse at a wavelength of 527 nm. The optical power measured by a lidar is proportional to the signal backscattered by molecules and particles present in the atmosphere [24]. The lidar signal can be expressed as:

                                                   (1)

where  is the backscatter coefficients.  is a system constant for a given lidar.  is the laser output energy and  is the atmosphere transmission. After range correcting and laser energy normalizing, a resulting signal is called normalized relative backscatter  (NRB) which is defined as:

                                               (2)

The MPL at SACOL records signal up to 20+ km at a vertical resolution of 75 m (or 30 m) for each minute [47]. There, the NRB values are interpolated to a 15 m space range using the Lagrange interpolation. The instrument effect including afterpulse, overlap, pulse energy, detector noise has been corrected, detail information about correcting procedures are given by Welton and Campbell [48]. In the study, the lidar data below 4.3 km is used. In addition, because of the existence of the blind zone caused by the incomplete overlap between the lidar laser beam and its receiving optical axis, the application of the backscattering lidar in near-ground is limited [17,33]. The NRB in lowest few hundred meters are removed.

See section 2.1, lines 137-153 of the revised version.

(3)     143/145: Are the tower instruments sampled every 30 minutes or is there just a 30 minute average value being recorded? If that is the case, how often are the measurements made that go into the average?

Reply: I’m sorry that the original description is confused. The tower instruments are sampled every 30 minutes (not 30 minute average).

 The description in the revised manuscript has been written as: “The 32 m Micrometeorological tower at SACOL can provide wind speed measurements (014A-L, Met One) at 1, 2, 4, 8, 16 and 32 m with a temporal resolution of 30 min”.

See line 174 of the revised version.

(4)     173/174: A figure to illustrate the “idealized backscatter profile” would be helpful.

Reply: Yes, Thanks for your valuable suggestion. A figure illustrating the “idealized backscatter profile” in curve fitting method (Figure 2) as well as a figure presenting the Haar wavelet transform (Figure 1) has been added in the revised manuscript.

Figure 1. (a) A NRB profile (left) and the shape of Haar wavelet, (b) the resulted covariance transform  as .

Figure 2. (a) An idealized backscatter profile, and (b) a real case for curve fitting procedure.

Detail see Figure 1, Figure 2 and related description in line 195, 212 of the revised version.

(5)     188/201: There is frequent mention of the “top of optically thick clouds”. What about clouds that fully attenuate the lidar signal well below cloud tops?

Reply: Thanks. For optically thick cloud, the lidar signal may be fully attenuated by the cloud, thus the top of cloud can’t be identified. However, the signal sharply decreases at the called “upper edge” of the cloud similar to at the top of thin cloud. Therefore, for optically thick cloud, it should be called as upper edge.

In the revised manuscript it has been described as “the strongest negative gradient often appears near the upper edge of clouds”.

See lines 227 of the revised version.

(6)     215: Why 4.3 km?

Reply: Generally, the daytime depth of the continental ABL is on the order of 1 ~ 2 km, the cloud above the ABLH is considered in the study, so the upper altitude is defined to be approximately 4 km. The lidar signal profile below the 4.3 km is used to retrieve the ABLH in the study.

In the revised manuscript it is described as “In the study, the lidar data below 4.3 km is used”.

See line 150 of the revised version.

(7)     219: In Figure 1, should there be a 4.3 km value in the flow chart under “no top limiter”?

Reply: Yes, we agree. For cloud-free situations, the top limiter is 4.3 km and has been changed in the Figure 3 in the revised manuscript.

 Figure 3. Major steps for determining the top limiter to eliminate the cloud effect on atmosphere boundary layer height (ABLH) retrieval in the new technique.

See Figure 3 in the revised version.

(8)     278: “1.0694” km has too many digits after the decimal for this topic. Perhaps  “1.07”  would be more defensible. Care should be taken throughout the paper not to exaggerate on the last significant digit.

Reply: Yes, Thanks. The issues has been carefully checked and revised throughout the paper. For example, “……the height determined from the theta-gradient is 1.07 km (Figure 5a), which is a little higher than the heights retrieved by lidar-based methods, 0.86 km by HM and 0.93 km by CFM…..”.

See lines 326-327 of the revised version.

(9)     297: “.793” is not “great concordance”.

Reply: Yes, we agree. In the revised manuscript, the “great concordance” has been changed to “reasonable concordance” as line 35.

In addition, in cloudy situation, relative to the ABLH determined based on lidar data without top limiter, the ABLH determined with the top limiter is much closer to radiosonde-derived results. The comparison results with a reasonable correlation coefficient can present the improvement of the lidar measurements of the ABLH with the determined top limiter.

Figure 8. Similar to Figure 7, but in cloudy situations. The blue open dots represent the comparison results of ABLH determined by theta gradient (vertical coordinate) and determined by HM (a) or CFM (b) (horizon coordinate) without height limitation, the red stars indicates the comparison results after the top limiter if given for HM and CFM. R represents the correlation coefficients, blue represents no top limiter and red represents with the top limiter.

See Figure 8 and related description as lines 341-349 of the revised manuscript.

(10) Section 4.0 is well done with minor grammar edits.

Reply: Yes, Thanks. Section has been carefully checked and edited. For example, lines 392, 426, 438, 458 …… of the revised version.

(11) 493: What does the last sentence mean? What other lidar is being referenced?

Reply: I’m sorry that the original description is confused. The sentence has been rewritten in the revised manuscript as: “……don’t necessarily apply to other observations sites .…… However, the principle for threshold determination is clear and reasonable, it can be referenced for lidar measurements of ABLH in multiple-layer conditions.”

See lines 515-516 of the revised version.

In addition, the last paragraph of the original manuscript is discussion section, which has been merged into results section described as “4.0. Results and Discussion” in the revised manuscript.

Author Response File: Author Response.docx

Reviewer 2 Report

The paper of Ruijun Dang et al. is a review of atmospheric boundary layer height detection techniques based on aerosol lidar data. Many such techniques have been developed in the last years, so such a review is timely. The authors have done an extended literature review including most relevant references. However, the presentation could be significantly improved. Therefore, I suggest the publication of the paper after some major revisions.

Overall comments

-------------------------

 The introduction is missing detailed definitions of Planetary Boundary Layer, Mixing layer height, Convective boundary layer etc. It is crucial to discuss all these definitions, describe which quantity is estimated from aerosol lidar algorithms, and how this is linked with the quantities measured using other methods e.g. from radiosondes.

In the instrument review section, wind lidars are missing.

I would prefer a definition of theta-gradient method (radiosonde) and the SACOL observatory in the instruction.

 Many algorithms include multiple steps, and it is not easy to follow the relevant text. You should add tables that clearly define key steps of the algorithms. Alternatively, you could include a flowchart for each algorithm.

The comparison of algorithms to real data is an interesting feature of the paper. The authors should include more such cases to highlight the methodology of each algorithm and their potential limitations.

Specific comments

-------------------------

The manuscript could benefit with detailed proofreading.  Some examples are given below:

43: resulted -> resulting

55: overlook -> overlooked

65: Microwave radiometers is not an optical remote sensing method

69: bright -> brightness

69-70: “Even if directly based ….”  I don’t understand why this is a surprise.

89: ACTRI -> ACTRIS

91: AERONET is not a lidar network

92: EARLIENT is part of ACTRIS, you could define it in line 89 as ACTRIS/EARLINET

93: The reference to CALIPSO is not relevant in this paper.

109: Remove “simple”

Table 1: Several typos e.g. “word” instead of “world”, “Aricraft” instead of “aircraft”

120a: Equation symbols are a mess. Lidar constant should be C. You have mixed the r and R (e.g. should be RS(R) and C/R^2)

120b: Why define E_0 outside the lidar constant? It should be omitted (is part of C).

125-126: you mix corrections (background subtraction, range correction) with effects (saturation, overlap, pulse energy). You should change the list to describe one or the other. By the way, what is the issue with pulse energy?

129: receiving optical axis -> receiver field of view

136: Following -> following

149: “By contract” is not the right word here.

162: Threshold methods seem to refer to aerosol backscatter profiles and not lidar range corrected signals. Please verify and correct appropriately. If this is the case, discuss briefly  also available retrieval methods (e.g. after line 135).

171: The equation for this section and forward are not clear. Several closing parentheses are missing. In some cases, it would be clearer to typeset the not as inline but in a separate line.

Figure 1: This is an interesting plot and deserves more space. I would prefer to define the test case and theta gradient method in separate panels. The results are in the left plot are too much overlapping, you could probably separate them similar to Figure 3. The axis labels are inconsistent. The font is the labels of the figure on the left are too large. Figure 2 could act as a guideline for figure presentation throughout the paper.

211: “an idealized backscatter profile” -> “an idealized PBL backscatter profile”

216: give a definition of the erf function

225: “the main robustness of the method”. Please rephrase.

Figure 2: It would be interesting to apply the method on the same data as figure 1.

259: Define the equation at the place where they are used in the text, i.e. after line 254

Figure 3: Apply the algorithms for the same data as Figure 1. Indicate the altitude defined by the Radiosonde. Add also an indication (e.g. a dot) at the altitude where the ABLH would be detected for each value.

301: As before, define the equation after line 295.

313: Including definition of quantities in the parenthesis makes the text hard to follow.

320: Check typesetting of second name.

326-339: This is a good example where a table with all the steps or a flowchart would be very useful.

379: Citation style seems inconsistent (you use both Author, date and bracket formats)

390 -: This should be a different subsection, not part of 3.4.

422: CA -> CAM

424-425: The claim is not very clear.

427: Widely used could be an overstatement.

466: molecular particles -> molecules

465-468: Please specify that this is a local result, or at least valid for specific regions.

538-540: This statement is not true in general.

547: You have already defined this equation, no need to do it again here.

References should be checked again carefully for formatting. E.g. reference 32 is not correctly cited.

Author Response

Response to Reviewer #2(remote-sensing 520086)

We thank the reviewer very much for taking time to handle and review our manuscript. Thank you for your recognition of our work. We have carefully considered and addressed all the valuable comments. Please see our detailed reply below in blue.

The paper of Ruijun Dang et al. is a review of atmospheric boundary layer height detection techniques based on aerosol lidar data. Many such techniques have been developed in the last years, so such a review is timely. The authors have done an extended literature review including most relevant references. However, the presentation could be significantly improved. Therefore, I suggest the publication of the paper after some major revisions.

Overall comments

(1)    The introduction is missing detailed definitions of Planetary Boundary Layer, Mixing layer height, Convective boundary layer etc. It is crucial to discuss all these definitions, describe which quantity is estimated from aerosol lidar algorithms, and how this is linked with the quantities measured using other methods e.g. from radiosondes.

Reply: Yes, Thanks for your valuable suggestions. In the introduction part of the revised manuscript, the Planetary Boundary Layer, Mixing layer height, Convective boundary layer etc. have been detailed defined with two added Figures (Figure 1 and Figure 2 in the revised version).

① The definitions of Planetary Boundary Layer:

“The atmospheric boundary layer (ABL), also called the planetary boundary layer (PBL), is the turbulent layer that is directly influenced by Earth’s surface and responds to surface forcing over a short period of time[1]……”

See Lines 33 to 35 of the revised version.

② The definitions of ABL height, Mixing layer height, Convective boundary layer, the nocturnal boundary layer, the aerosol layer height, and etc.

“A simple scheme of the diurnally varying ABL in clear-sky situation can be divided into four snapshots, the convective boundary layer (CBL) in daytime, more stable nocturnal boundary layer (NBL) at night, the early morning transition (EMT) period and early evening transition (EET) period (Figure 1). The MLH is generally defined as the height up to which the atmospheric properties or substances are dispersed almost uniformly over the entire depth of the mixing layer due to turbulent vertical mixing process [1,3,4] (Figure 2). For the well-mixed CBL, aerosol particles are well mixed by the thermally driven turbulence, the MLH is more or less identical to the ABL height (ABLH) (or CBL height, CBLH) shown as the left frame in Figure 2. At night, shown as the right frame in Figure 2, the nocturnal SBL can be divided into two layers, a near surface mixing layer of continuous turbulence mechanically produced, an upper layer of sporadic or intermittent turbulence, corresponding to two aerosol layers. The MLH is identical with the height of the lower stable surface layer (or ground inversion layer), the ABLH (or, the nocturnal boundary layer height, NBLH) is identical to the height of upper layer, a residual aerosol layer (RL) which is a remnant of the daytime CBL. The EET refers to the period from the sunset to the time when a surface stable layer is formed [5], while the EMT refers to the period from sunrise to the time when the NBL is eroded and the CBL begins to grow rapidly [6]. During EET, the convection is weakening and a ground inversion layer is generating, the strongest aerosol gradient occurs at the RL top, until new aerosol layer generated at the ground provides a renewed strong gradient. During the EMT, the thermal forced turbulence begins to produce, the surface inversion layer is gradually destroyed. The strongest aerosol gradient corresponds to the top of RL or ground aerosol layer. During the periods, high uncertainty and inaccuracy result for the ABLH determination [5-7].”

See Lines 40 to 60 of the revised version.

③ The aerosol determined height and compared to the radiosonde-derived ABLH

“The aerosol lidar derived ABLH is actually a height of surface aerosol layer. Shown as Figure 2, for well-mixed CBL at daytime, the aerosol depth represents the MLH, ideally, the lidar-determined MLH should be equivalent to the radiosonde-derived CBLH with the assumption that the distribution of aerosol concentration is dominated by turbulent mixing. For stable NBL, the height determined by aerosol lidar is either the top of RL (NBLH) or the top of surface mechanical driven ML (MLH, or the height of ground inversion layer). During the transition (EMT and EET) periods, the altitude determined by the lidar is the altitude to which aerosol particles have been mixed in the past, rather than the altitude to which they are currently being mixed.”

See Lines 100 to 107 of the revised version.

Figure 1. A simplified scheme of diurnal cycle of ABL in clear-sky situations (adapted from Stull [1]). Solid line marks the height of ABL (ABLH), the dashed line marks the top of residual layer (RL). The entrainment process near the top of ABL is marked by the dashed arrows. SBL, stable boundary layer; CBL, convective boundary layer; EZ, entrainment zone; RL, residual layer; EMT, early morning transition; EET, early evening transition.

Figure 2. Principle vertical profiles of the some variables for the well mixed boundary layer during daytime (left), and the more stable nocturnal boundary layer with shallow surface mixing layer, residual aerosol layer and the above free atmosphere layer (right) (adapted from Stull [1]).

See Figure 1 and Figure 2 in the revised version.

References:

1.             Stull, R.B. An Introduction to Boundary Layer Meteorology. Atmospheric Sciences Library 1988, 8 (8), 89.

2.             Seibert, P.; Beyrich, F.; Gryning, S.-E.; Joffre, S.; Rasmussen, A.; Tercier, P. Review and intercomparison of operational methods for the determination of the mixing height. Atmospheric Environment 2000, 34 (7), 1001-1027.

3.             Garratt, J.R. The atmospheric boundary layer. Cambridge University Press 1992.

4.             Beyrich, F.; Gryning, S.E.; Joffre, S.; Rasmussen, A.; Seibert, P.; Tercier, P. Mixing Height Determination for Dispersion Modelling - A Test of Meteorological Pre-Processors. Air Pollution Modeling and Its Application XII. Springer US. 1998.

5.             Haman, C.L.; Lefer, B.; Morris, G.A. Seasonal variability in the diurnal evolution of the boundary layer in a near-coastal urban environment. Journal of Atmospheric & Oceanic Technology 2012, 29 (5), 697-710.

6.             Granados‐Muñoz M. J., N.G.F., Bravo‐Aranda J. A. . Automatic determination of the planetary boundary layer height using lidar: One‐year analysis over southeastern Spain[J]. Journal of Geophysical Research: Atmospheres 2012, 117.

7.             Pal, S.; Haeffelin, M.; Batchvarova, E. Exploring a geophysical process-based attribution technique for the determination of the atmospheric boundary layer depth using aerosol lidar and near-surface meteorological measurements. Journal of Geophysical Research-Atmospheres 2013, 118 (16), 9277-9295.

(2)    In the instrument review section, wind lidars are missing.

Reply: Yes, Thanks a lot for your valuable suggestion, the wind lidar has been considered and introduced as:

“Lidar is a powerful active remote sensing instrument measuring vertical profile of aerosol, wind speed or trace gas such as water vapor.……The wind lidar measures wind speed and direction starting above the ground and reaching up to a height depending on the aerosol content of atmosphere [40]. Presently, using the wind lidar to estimate the ABLH is less widely than the aerosol lidar but it is a promising way.…….”

See Lines 94 to 99 of the revised version.

References:

40.          Floors, R.; Vincent, C.L.; Gryning, S.E.; Peña, A.; Batchvarova, E. The Wind Profile in the Coastal Boundary Layer: Wind Lidar Measurements;and Numerical Modelling. Boundary-Layer Meteorology 2013, 147 (3), 469-491.

(3)    I would prefer a definition of theta-gradient method (radiosonde) and the SACOL observatory in the instruction.

Reply: Yes, Thanks for your valuable suggestion. The theta-gradient method, radiosonde, and SACOL (Semi-Arid Climate observatory and Laboratory) has been introduced in the Introduction section of the revised manuscript.

“……based on the MPL (Micro-Pulse Lidar) profiles over SACOL (Semi-Arid Climate observatory and Laboratory) in China. The SACOL (35.57°N, 104.08°E; 1965.8 m above sea level) is located at the top of Tsuiying Mountain in the Yuzhong campus of Lanzhou University. The reference ABLH is defined by the theta-gradient method (the altitude where the maximum of the theta gradient occurs [42,55]) based on the potential temperature profiles provided by a nearby radiosonde site (35.87°N, 104.15°E; 1875 m above sea level (90.8 m lower than SACOL)), which is approximately 8.83 km from SACOL (detail descriptions about lidar system over SACOL, and the radiosonde-provided profiles of atmospheric variables see Dang et al. [56]).”

See Lines 130 to 137 of the revised version.

References:

42.          Hennemuth, B.; Lammert, A. Determination of the Atmospheric Boundary Layer Height from Radiosonde and Lidar Backscatter. Boundary-Layer Meteorology 2006, 120 (1), 181-200.

55.          Li, H.; Yang, Y.; Hu, X.M.; Huang, Z.; Wang, G.; Zhang, B.; Zhang, T. Evaluation of retrieval methods of daytime convective boundary layer height based on Lidar data. Journal of Geophysical Research-atmospheres 2017, 122 (8), 4578-4593.

56.          Dang, R.; Yang, Y.; Li, H.; Hu, X.-M.; Wang, Z.; Huang, Z.; Zhou, T.; Zhang, T. Atmosphere Boundary Layer Height (ABLH) Determination under Multiple-Layer Conditions Using Micro-Pulse Lidar. Remote Sens 2019, 11, 263.

(4)    Many algorithms include multiple steps, and it is not easy to follow the relevant text. You should add tables that clearly define key steps of the algorithms. Alternatively, you could include a flowchart for each algorithm.

Reply: Yes, Thanks for your valuable suggestions very much. In the revised version, simple flowcharts or schemes for some algorithms have been added. Some examples are as follows:

① Flowchart for the combination of the VAR (variance analysis) and GM (gradient method) in Hennemuth and Lammert [42].

Figure 9. Flowchart for the combination of the VAR and GM in Hennemuth and Lammert [42].

See Lines 370 to 379 and Figure 9 in the revised version.

② A simple scheme for THT (temporal-height-tracking) algorithm in Martucci et al. [119]

Figure 10. Synopsis of the THT algorithm in Martucci et al. [119] The profiles of the  and  are averaged over the interval 30 min, for , profile of the  is the single signal gradient profile at  step,  is calculated by the moving variance within the temporal interval ,.

See Lines 380 to 394 and Figure 10 in the revised version.

③ Flowchart for the combination of the VAR (variance analysis) and STRST-2D (structure of the atmosphere, 2D version) in Pal et al. [7]

Figure 11. Flowchart for the combination of the STRAT-2D and variance analysis in Pal et al.[7]

See Lines 441 to 450 and Figure 11 in the revised version.

References:

42.          Hennemuth, B.; Lammert, A. Determination of the Atmospheric Boundary Layer Height from Radiosonde and Lidar Backscatter. Boundary-Layer Meteorology 2006, 120 (1), 181-200.

119.        Martucci, G.; Matthey, R.; Mitev, V.; Richner, H. Frequency of Boundary-Layer-Top Fluctuations in Convective and Stable Conditions Using Laser Remote Sensing. Boundary-Layer Meteorology 2010, 135 (2), 313-331.

7.             Pal, S.; Haeffelin, M.; Batchvarova, E. Exploring a geophysical process-based attribution technique for the determination of the atmospheric boundary layer depth using aerosol lidar and near-surface meteorological measurements. Journal of Geophysical Research-atmospheres 2013, 118 (16), 9277-9295.

(5)    The comparison of algorithms to real data is an interesting feature of the paper. The authors should include more such cases to highlight the methodology of each algorithm and their potential limitations.

Reply: Yes, Thanks. In the revised manuscript, for classical methodologies, real cases are selected to show the algorithms. Meanwhile, the difference between the determined ABLH and the radiosonde-derived ABLH has been demonstrated.

Based on the MPL-provided RSCS (range-corrected lidar signal) profile, besides the real cases in Figures 3-6 (Figures 1-4 in the original manuscript), a case showing the variance analysis is added in the revised version (Figure 7). Meanwhile, two cases showing the interference of the residual layer (RL) and cloud layers on ABLH determination are presented as Figure 8 and Figure 12 in the revised manuscript.

Figure 7. (a) 31 vertical RSCS profiles between 05:15-05:45 UTC (1 min interval) on 10 September 2010 over SACOL, (b) vertical profile of temporal variance (VAR).

See Lines 335 to 346 and Figure 7 in the revised version.

Figure 8. Time-height cross-section of the RSCS provided by the MPL over SACOL, with height directly determined from first-order gradient method (GM), HAAR/MHAT wavelet covariance transform, and ideal profile fitting (CFM) on 28 July 2007 and on 12 June 2007.

See Lines 356 to 359 and Figure 8 in the revised version.

Figure 12. Same as in Figure 8, the top limiter in (a) and (c) represents the upper altitude defined in Dang et al. [56], the ABLH in (b) and (d) determined from the HM, HAAR, MHAT and CFM below the top limiter.

See Lines 469 to 473 and Figure 12 in the revised version.

We are regret that for some improved versions of the classical methods and new developed techniques, parameters selection or local characteristics are usually the key for the algorithm (e.g., the threshold selection for threshold method), it is difficult for us to present the real cases utilizing these algorithms.

References:

56.          Dang, R.; Yang, Y.; Li, H.; Hu, X.-M.; Wang, Z.; Huang, Z.; Zhou, T.; Zhang, T. Atmosphere Boundary Layer Height (ABLH) Determination under Multiple-Layer Conditions Using Micro-Pulse Lidar. Remote Sens 2019, 11, 263.

Specific comments

The manuscript could benefit with detailed proofreading. Some examples are given below:

(1)    43: resulted -> resulting

Reply: Yes, We agree. the “resulted” has been changed to “resulting”:

“The resulting ABLH are often used as a reference for estimating the modeled results s….”

See Line 68 of the revised version.

(2)    55: overlook -> overlooked

Reply: Yes, We agree. The original description is “the meteorological model errors caused by imperfect parameterizations cannot be completely overlooked”, the sentence aims to introduce the advantages and shortcomings of the numerical model.

In the revised manuscript, the introduction structure has been changed, mainly introduces the ABLH determination from measurement profiles, the ABLH calculated from numerical models are mainly discussed in the Summary part. Therefore, the original sentence in the introduction section has been removed.

(3)    65: Microwave radiometers is not an optical remote sensing method

Reply: Yes, Thanks. Microwave radiometers is a passive microwave remote sensing instrument rather than an optical remote sensing method.

The description has been changed to “The microwave radiometer is a passive microwave remote sensing instrument……”

See Line 90 of the revised version.

(4)    69: bright -> brightness

Reply: Yes, Thanks. The “bright” has been changed to “brightness”:

“……it provides brightness temperature profiles……”

See Line 90 of the revised version.

(5)    69-70: “Even if directly based ….” I don’t understand why this is a surprise.

Reply: I’m very sorry that the original description is confused.

The sentences has been rewritten as: “The disadvantage is that the vertical resolution of the profiles decreases with altitude, meanwhile, the retrieved vertical profiles are generally of poor quality under cloudy or rainy conditions”

See Lines 91 to 93 of the revised version.

(6)    89: ACTRI -> ACTRIS

Reply: Yes, Thanks. The “ACTRI” has been changed to “ACTRIS”:

“……a great number of aerosol lidars have been deployed and have established networks including both ground-based systems such as ACTRIS……”

See Line 112 of the revised version.

(7)    91: AERONET is not a lidar network

Reply: Yes, Thanks a lot. The introduction of AERONET has been removed.

See Line 115 of the revised version.

(8)    92: EARLIENT is part of ACTRIS, you could define it in line 89 as ACTRIS/EARLINET

Reply: Yes, We agree. The description has been rewritten as: “such as ACTRIS/EARLINET (Aerosols, Clouds, and Trace gases Research Infrastructure, http://www.actris.net/, or the European Aerosol Research Lidar Network, http://www.earlinet.org/)......”

See Lines 112 to 114 of the revised version.

(9)    93: The reference to CALIPSO is not relevant in this paper.

Reply: Yes, Thanks. In the revised manuscript, a literature by Leventidou et al. [50] which introduced Factors affecting the comparisons of planetary boundary layer height retrievals from CALIPSO, ecmwf and radiosondes is referenced here.

See Line 117 of the revised version.

References:

50.          Leventidou, E.; Zanis, P.; Balis, D.; Giannakaki, E.; Pytharoulis, I.; Amiridis, V. Factors affecting the comparisons of planetary boundary layer height retrievals from calipso, ecmwf and radiosondes over thessaloniki, greece. Atmospheric Environment 2013, 74 (360-366).

(10)109: Remove “simple”

Reply: Yes, We agree. The “simple” has been removed:

” Section 5 presents summary and conclusions with brief discussion and prospect”.

See Line 139 of the revised version.

(11)Table 1: Several typos e.g. “word” instead of “world”, “Aricraft” instead of “aircraft”

Reply: Yes, Thanks. In Table 1, some errors has been corrected as follows:

① signal noise ratio -> signal-to-noise ratio

② all over the word -> all over the world

③ suited for ABLH climatology study -> suited for ABLH climatology studying

④ aircraft -> Aircraft

⑤ high sample rate -> high sampling rate

⑥ operated continuously -> continuous operation

See Table 1 in the revised version.

(12)120a: Equation symbols are a mess. Lidar constant should be C. You have mixed the r and R (e.g. should be RS(R) and C/R^2)

Reply: Yes, Thanks. The Equations (1) and (2) have been corrected as follows:

  ,                          (1)

,                      (2)

where  is a constant for a given lidar system,  and  represent the total backscatter coefficient (sum of molecular and particulate contributions, ) and total extinction coefficient (),  is the range to the target, respectively.

See Lines 160 to 165 of the revised version.

(13)120b: Why define E_0 outside the lidar constant? It should be omitted (is part of C)

Reply: Yes, We agree. For RSCS profiles used in the study, the laser pulse energy (E) has been emitted, the constant showed be represented by.

See Equations (1)-(2) and lines 160 to 165 of the revised version.

(14)125-126: you mix corrections (background subtraction, range correction) with effects (saturation, overlap, pulse energy). You should change the list to describe one or the other. By the way, what is the issue with pulse energy?

Reply: Yes, Thanks. For raw lidar data, there are several procedures for correction including dark count (or Dead time), afterpulsing, background, range correction, overlap correction and emitting laser pulse energy. The resulted data is the RSCS profiles. The laser pulse energy is real-time recorded although the temporal variation is small. In the correction processes, the last procedure is to emit laser pulse energy.

The description has been rewritten as: “Welton and Campbell [60] discussed the uncertainties and the factors that affect the MPL measured data. The raw lidar data are corrected in terms of dead-time, afterpulsing, background, overlap, and pulse energy, the detail procedures were depicted elaborately by Campbell et al. [61] and Kotthaus et al. [62].”

See Lines 157 to 160 of the revised version.

References:

60.          Welton, E.J.; Campbell, J.R. Micropulse Lidar Signals: Uncertainty Analysis. Journal of Atmospheric and Oceanic Technology 2002, 19 (19), 2089-2094.

61.          Campbell, J.R.; Hlavka, D.L.; Welton, E.J.; Flynn, C.J.; Turner, D.D.; Spinhirne, J.D. Full-time, eye-safe cloud and aerosol lidar observation at atmospheric radiation measurement program sites: instruments and data processing. Journal of Atmospheric and Oceanic Technology 2002, 19 (4), 431-442.

62.          Kotthaus, S.; O'Connor, E.; Münkel, C.; Charlton-Perez, C.; Grimmond, C.S.B. Recommendations for processing atmospheric attenuated backscatter profiles from Vaisala CL31 ceilometers. Atmospheric Measurement Techniques 2016, 9 (8), 1-32.

(15)129: receiving optical axis -> receiver field of view

Reply: Yes, Thanks. The “receiving optical axis” has been changed to “receiver field of view”:

“……the blind zone caused by the overlap between the lidar laser beam and its receiver field of view has to be taken into consideration”

See Lines 168 to 170 of the revised version.

(16)136: Following -> following

Reply: Yes, Thanks. “Following” has been changed to “following”:

“In the following subsection……”

See Line 171 of the revised version.

(17)149: “By contract” is not the right word here.

Reply: Yes, We agree. “By contract” has been changed to “In comparison”:

“In comparison, the signal-gradient-based methods yield instantaneous ABLH with the temporal resolution of the observation system whereas the variance analysis yields the mean CBLH over about one hour”

See Line 183 of the revised version.

(18)162: Threshold methods seem to refer to aerosol backscatter profiles and not lidar range corrected signals. Please verify and correct appropriately. If this is the case, discuss briefly also available retrieval methods (e.g. after line 135).

Reply: Yes, We agree, the threshold methods refer to aerosol backscatter profiles rather than the lidar range corrected signals.

The descriptions have been corrected as: ” The threshold method generally defines the ABLH as the altitude where the backscatter intensity or the intensity gradient exceeds a preset threshold [71,72].……”

See Lines 195 to 200 of the revised version.

References:

71.          Dupont, E.; Pelon, J.; Flamant, C. Study of the moist Convective Boundary Layer structure by backscattering lidar. Boundary-Layer Meteorology 1994, 69 (1-2), 1-25.

72.          Strawbridge, K.B.; Snyder, B.J. Planetary boundary layer height determination during Pacific 2001 using the advantage of a scanning lidar instrument. Atmospheric Environment 2004, 38 (34), 5861-5871.

(19)171: The equation for this section and forward are not clear. Several closing parentheses are missing. In some cases, it would be clearer to typeset the not as inline but in a separate line.

Reply: Yes, Thanks. The equations are presented in a separate line in the revised version as follows:

“……GM defines the ABLH as the position of largest negative peak of the first derivative of RSCS…..”

                                (3)

“…… IPM, as well as ……. LGM were proposed, which determine the ABLH through looking for the absolute minimum value of the second-order derivative or the gradient of the logarithm of RSCS with respect to the altitude:”

                                (4)

                                (5)

“……proposed the cubic root gradient method (CRGM), which defines the ABLH as the height where the minimum of the cubic root gradient of the RSCS occurs [81]:”

                               (6)

See Lines 204 to 218 of the revised version.

(20)Figure 1: This is an interesting plot and deserves more space. I would prefer to define the test case and theta gradient method in separate panels. The results are in the left plot are too much overlapping, you could probably separate them similar to Figure 3. The axis labels are inconsistent. The font is the labels of the figure on the left are too large. Figure 2 could act as a guideline for figure presentation throughout the paper.

Reply: Yes, Thanks for your valuable suggestions.

① The theta gradient method is defined in introduction section as: ”The reference ABLH is defined by the theta-gradient method (the altitude where the maximum of the theta gradient occurs [42,55]) based on the potential temperature profiles provided by a nearby radiosonde site……”

See Lines 132 to 136 of the revised version.

② The test case is defined described as: “An example RSCS profile is observed by the MPL over SACOL at 12:00 UTC on 10 September 2010. The potential temperature and the specific humidity profiles at the same time are provided by a nearby radiosonde site”

See Lines 219 to 221 of the revised version.

③ The Figure 1 has been plotted (Figure 3 in the revised version), the text font and size, etc. are set following Figure 2 (Figure 4 in the revised version).

Figure 3. A case at 12:00 UTC on 10 September 2010 over SACOL (Semi-Arid Climate observatory and Laboratory, in China). The profiles of lidar range-squared-corrected signal (RSCS, black solid line), first derivative (red solid line), second derivative (blue solid line), the logarithm gradient (orange solid line) and the cubic root gradient (green solid line) of RSCS provided by a micro-pulse lidar (MPL), the respectively determined ABLH are named as h(GM), h(IPM), h(LGM), h(CRGM) (left), the profiles of potential temperature (red profile) and the specific humidity (black profile) at a nearby radiosonde site with the CBLH determined by the theta-gradient method (h(PT)) (right).

See Figure 3 in the revised version.

References:

42.          Hennemuth, B.; Lammert, A. Determination of the Atmospheric Boundary Layer Height from Radiosonde and Lidar Backscatter. Boundary-Layer Meteorology 2006, 120 (1), 181-200.

55.          Li, H.; Yang, Y.; Hu, X.M.; Huang, Z.; Wang, G.; Zhang, B.; Zhang, T. Evaluation of retrieval methods of daytime convective boundary layer height based on Lidar data. Journal of Geophysical Research-atmospheres 2017, 122 (8), 4578-4593.

(21)211: “an idealized backscatter profile” -> “an idealized PBL backscatter profile”

Reply: Yes, Thanks. “an idealized backscatter profile” has been changed to “an idealized ABL backscatter profile”:

“…..the ABLH is derived from fitting an idealized ABL backscatter profile (, Equation (7))……”

See Line 247 of the revised version.

(22)216: give a definition of the erf function

Reply: Yes, erf function has been defined in Equation (8) in the revised manuscript：

where the error function () is defined as:

                            (8)

See Lines 253 to 254 of the revised version.

(23)225: “the main robustness of the method”. Please rephrase.

Reply: Yes, Thanks.

The sentence has been rewritten as: “The robustness of the technique is based on utilizing the whole backscatter profile rather than the profile surrounding the top of ML”

See Lines 262 to 263 of the revised version.

(24)Figure 2: It would be interesting to apply the method on the same data as figure 1.

Reply: Thanks. In fact, in the original manuscript, the same case is presented in Figure 1 and Figure 2 (Figure 3 and Figure 4 in the revised version). In Figure 1, to show the profiles of RSCS, first derivative, second derivative, the logarithm gradient and the cubic root gradient of RSCS simultaneously (the profiles are with different magnitudes), the profiles are multiplied by some constants.

To highlight that the same case is used, the observation time of data is demonstrated for every Figure.

Figure 3. A case at 12:00 UTC on 10 September 2010 over SACOL (Semi-Arid Climate observatory and Laboratory, in China). The profiles of lidar range-squared-corrected signal (RSCS, black solid line), first derivative (red solid line), second derivative (blue solid line), the logarithm gradient (orange solid line) and the cubic root gradient (green solid line) of RSCS provided by a micro-pulse lidar (MPL), the respectively determined ABLH are named as h(GM), h(IPM), h(LGM), h(CRGM) (left), the profiles of potential temperature (red profile) and the specific humidity (black profile) from a nearby radiosoundings with the CBLH determined by the theta-gradient method (h(PT)) (right).

Figure 4. (a) An idealized ABL backscatter profile, (b) the curve fitting procedure for a case at 12:00 UTC on 10 September 2010 over SACOL (the same case in Figure (3)) (adapted from the Figure 2 in Dang et al. [56])

See Figure 3 and Figure 4 in the revised version.

References:

56.          Dang, R.; Yang, Y.; Li, H.; Hu, X.-M.; Wang, Z.; Huang, Z.; Zhou, T.; Zhang, T. Atmosphere Boundary Layer Height (ABLH) Determination under Multiple-Layer Conditions Using Micro-Pulse Lidar. Remote Sens 2019, 11, 263.

(25)259: Define the equation at the place where they are used in the text, i.e. after line 254

Reply: Yes, Thanks. The Equations (6) and (7) (Equations (11) and (12) in the revised manuscript) have been defined at the place where are used in the text:

 “The wavelet  and the covariance transform  are defined by Equations (11) and (12)……”

           ,                      (11)

            ,                           (12)

See Line 291 and Equations (11)-(12) in the revised version.

(26)Figure 3: Apply the algorithms for the same data as Figure 1. Indicate the altitude defined by the Radiosonde. Add also an indication (e.g. a dot) at the altitude where the ABLH would be detected for each value.

Reply: Thanks. We have tried to applying the WCT method (Figure 3) (Figure 5 in the revised version) for the same data as Figure 1 (Figure 3 in the revised version), and the Figure is shown as follows:

(a)       RSCS profile with the shapes of HAAR wavelet (HAAR) and the Mexican-Hat wavelet (MHAT), the resulting covariance transform for (b) HAAR and (c) MHAT at various values of the dilation at 12:00 UTC on 10 September 2010 over SACOL. The dashed lines represent the retrieved MLH.

The selection of an appropriate dilation  is the key for WCT, the example at 12:00 UTC on 10 September 2010 over SACOL (the same case as Figure 1 in the original version) shows that when different dilations are selected, different ABLH (the dot lines in (b) and (c)) can be obtained. However, the case can’t clearly show the interference of the local structures of RSCS on ABLH determination.

The case at 06:00 UTC on 10 September 2010 over SACOL (Figure 3 in the original version, named Figure 5 in the revised version) as follows can more clearly show the fact that “in complex situations where there are several significant variations in signal profile, if  is too small, the covariance transform identifies local structures in signal, while  is too large, only the biggest structures are identified and adjacent signal structures may cause interference”

Figure 5. (a) RSCS profile with the shapes of HAAR wavelet (HAAR) and the Mexican-Hat wavelet (MHAT), the resulting covariance transform for (b) HAAR and (c) MHAT at various values of the dilation at 06:00 UTC on 10 September 2010 over SACOL. The dashed lines represent the retrieved MLH.

Therefore, the RSCS profile at 06:00 UTC on 10 September 2010 over SACOL is still selected to present WCT method in the revised manuscript.

See Lines 300 to 304 and Figure 5 in the revised version.

(27)301: As before, define the equation after line 295.

Reply: Yes, Thanks. In the revised manuscript, the Equation has been defined at the place where are used in the text as:

“……the variance (VAR in Equation (14)) or standard deviation (STD in Equation (15)) analyzes……”

See Line 337 of the revised version.

(28)313: Including definition of quantities in the parenthesis makes the text hard to follow.

Reply: Yes, Thanks. In the original manuscript, the sentence introduces the STRAT-2D algorithm, the quantities are defined in the place where detailed introduce the algorithm:

“……a called STRAT-2D (2D version of structure of the atmosphere) algorithm [116], which includes an edge detection method [117] based on both vertical and temporal gradients in the attenuated backscatter signal.”

“……an algorithm called STRAT-2D which includes an edge detection method [117] based on both vertical and temporal gradients in the backscatter signal. Using Sobel 2-D derivation operators [122], the algorithm retrieves MLH by deriving gradients in two directions , vertical  and horizontal .”

See Lines 361 to 363, 433 to 435 of the revised version.

References:

116.        Haeffelin, M.; Angelini, F.; Morille, Y.; Martucci, G.; Frey, S.; Gobbi, G.P.; Lolli, S.; O’Dowd, C.D.; Sauvage, L.; Xueref-Rémy, I.; Wastine, B.; Feist, D.G. Evaluation of Mixing-Height Retrievals from Automatic Profiling Lidars and Ceilometers in View of Future Integrated Networks in Europe. Boundary-Layer Meteorology 2012, 143 (1), 49-75.

117.        Canny, J.F. Computational Approach to Edge Detection. IEEE Trans. Pattern Anal. Mach. Intell. 1986, 6, 679-698.

122.        Sobel, I.; Feldman, G. A 3 × 3 isotropic gradient operator for image processing presentation for stanford artificial project. 2008.

(29)320: Check typesetting of second name.

Reply: Yes, Thanks. “B¨osenberg” has been changed to “Bösenberg”.

See Line 374 in the revised version.

(30)326-339: This is a good example where a table with all the steps or a flowchart would be very useful.

Reply: Yes, Thanks. For the THT (temporal-height- tracking) algorithm, a simple scheme is presented.

Figure 10. Synopsis of the THT algorithm in Martucci et al. [119] The profiles of the  and  are averaged over the interval 30 min, for , profile of the  is the single signal gradient profile at  step, is calculated by the moving variance within the temporal interval , .

See Lines 380 to 394 and Figure 10 in the revised version.

References:

119.        Martucci, G.; Matthey, R.; Mitev, V.; Richner, H. Frequency of Boundary-Layer-Top Fluctuations in Convective and Stable Conditions Using Laser Remote Sensing. Boundary-Layer Meteorology 2010, 135 (2), 313-331.

(31)379: Citation style seems inconsistent (you use both Author, date and bracket formats)

Reply: Yes, Thanks. The citation style has been checked throughout the text, the uniform style in the revised manuscript is only bract or Author and bracket. For example,……[1], or Seibert [2] found that…….

References:

1.             Stull, R.B. An Introduction to Boundary Layer Meteorology. Atmospheric Sciences Library 1988, 8 (8), 89.

2.             Seibert, P.; Beyrich, F.; Gryning, S.-E.; Joffre, S.; Rasmussen, A.; Tercier, P. Review and intercomparison of operational methods for the determination of the mixing height. Atmospheric Environment 2000, 34 (7), 1001-1027.

(32)390 -: This should be a different subsection, not part of 3.4.

Reply: Yes, Thanks, we agree. In the revised version, providing height restriction to the classical methodologies is introduced in a subsection 3.5:

“3.5. Height restriction for some classical methodologies”

See Line 453 of the revised version.

(33)422: CA -> CAM

Reply: Yes, Thanks. The “CA” has been changed to “CAM”:

“CAM is used to determine the ABLH……”

See Line 492 of the revised version.

(34) 424-425: The claim is not very clear.

Reply: Yes, Thanks. The original description is confused and has been rewritten as: “Thus, the technique makes available a single result when the gradient-based techniques and the variance analysis methods provide different ones”

See Lines 494 to 495 of the revised version.

(35)427: Widely used could be an overstatement.

Reply: Thanks. We agree. The “widely used” has been removed and the sentence has been rewritten as: “A solution utilizing an extended Kalman filter (EKF) to trace the evolution of the ABLH from a ground-based lidar has been recently tested and developed”

See Lines 496 to 497 of the revised version.

(36)466: molecular particles -> molecules

Reply: Yes, Thanks. “molecular particles” has been changed to “molecules”:

“…..most of the particles in the upper atmosphere (above 1500 m) are molecules with……”

See Line 535 of the revised version.

(37)465-468: Please specify that this is a local result, or at least valid for specific regions.

Reply: Yes, Thanks. The localization of the result has been stated and the sentence has been rewritten as: “Liu et al. [138] found that locally, most of the particles in the upper atmosphere (above 1500 m) are molecules ……”

See Line 534 of the revised version.

References:

138.        Liu, B.; Ma, Y.; Gong, W.; Yang, J.; Zhang, M. Two-wavelength Lidar inversion algorithm for determining planetary boundary layer height. Journal of Quantitative Spectroscopy Radiative Transfer 2018a, 206, 117-124.

(38)538-540: This statement is not true in general.

Reply: Yes, Thanks. The statement makes no sense and has been removed in the revised manuscript.

See Lines 585 to 586 of the revised version.

(39)547: You have already defined this equation, no need to do it again here.

Reply: Yes, Thanks. The Equation has been removed and the sentence has been written as:” A technique called START-2D (structure of the atmosphere, 2D version) performs well under multiple layer situations by using a temporal-vertical gradient.”

See Line 592 of the revised version.

(40)References should be checked again carefully for formatting. E.g. reference 32 is not correctly cited.

Reply: Yes, Thanks. The formatting of the references has been carefully checked and corrected.

References:

39.          Saeed, U.; Rocadenbosch, F.; Crewell, S. Synergetic use of LiDAR and microwave radiometer observations for boundary-layer height detection. IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 2015 IEEE international. 26-31 July; 2015; 3945-3948.

See Lines 744 to 746 of the revised version.

Author Response File: Author Response.docx

Reviewer 3 Report

The manuscript by Dang et al. is an overview paper, which in general is not easy to be well written. In this case, it seems that the authors made a good job, however some improvements would be beneficial to the readers. The structure of paper is strait forward and clear. Although I would suggest to rather rephrase in title of sections 2: 'traditional techniques' to 'classical methodology'. I appreciate the maths, tables and figures.

Introductory is in my opinion the weakest part. (It is in fact to a great extent repetition after already published paper in Rem. Sens. (ABL-SI) by the same authors: Dong et al. 2019.) Reading the Introduction,  I had a feeling that this all is well known facts that every 1-2 year PhD student working in boundary-layer research must know. This may discourage some experienced scientists from reading the paper further. The review of methods by writing a few equations is somewhat weak for a really good scientific review paper.

The main missing topic to be dicscussed (or at least to comment on) is that actually lidars/ceilometers do measure the aerosol boundary layer heigt and not the meteorological atmospheric boundary layer height. Important questions that could be carefully revised in the literature are, e.g.: What is the offset of the measured values of aerosol vs atmospheric height? Does this depend on season? What is the role of clouds? Is there (and in which kind of measurements) the good-weather bias affecting the results? What clear advantages there are for using the classical vs improved vs new methods? If at one measurements site different methodology is used, then what is the accuracy/uncertainty of each approach? If one compares the results, to what extend one can use the different methodologies as providing the same result? Are there any (and which) methods complementing the others? Finally, is there a perfect set of instruments that is recomended by authors as crucial for high-quality boundary layer sensing?

I can see that some answers to these questions are hidden in the Figures/Tables but it would be good to have then discussed as a few bottom-line statements.

Coming to that, I reckon that the discussion/prospect & conclusion chapters... should be combined to one. Then bottom-line alone stressing that there is no perfect method for retherieval of ABLH is somewhat weak - and gere authors could add more compact discussions on the questions posed above. In a review paper, I expect them also to highlight where to the research on boundary layer should/would head to in the nearest future.

As for the reference list is practically completed, I would add few more important: Baars et al ACP 2008, Tsanknakis et al AMT 2011, Stachlewska et al. Acta Geophys. 2012, Kotthaus et l. AMT 2016... (Pls check carefully all citations listed in Bibliography for typos, e.g. ref.41 mistake in name: Ca3Rdoba; or ref. 73 small-case for name of journal: remote sening).

Author Response

Response to Reviewer #3(remote-sensing 520086)

We thank the reviewer very much for taking time to handle and review our manuscript. Thank you for your recognition of our work. We have carefully considered and addressed all the valuable comments. Please see our detailed reply below in blue.

The manuscript by Dang et al. is an overview paper, which in general is not easy to be well written. In this case, it seems that the authors made a good job, however some improvements would be beneficial to the readers. The structure of paper is strait forward and clear. Although I would suggest to rather rephrase in title of sections 2: 'traditional techniques' to 'classical methodology'. I appreciate the maths, tables and figures.

Reply: Yes, Thanks for your valuable suggestions. The “traditional techniques” has been changed to “classical methodologies” in the revised manuscript.

For each method, the Equation has been added. Meanwhile, to show the algorithm clearly, some figures or flowcharts have been added in the revised manuscript.

For example:

① The added Equations:

First-order gradient method (GM):

                                (3)

The inflection point method (IPM) adn the logarithm gradient method (LGM):

                                (4)

                                (5)

Cubic root gradient method (CRGM):

                               (6)

See lines 206 to 214 of the revised manuscript.

② The added Figures:

For variance analysis (VAR), an example is added, the vertical RSCS (range-corrected signal) profiles are between 05:15-05:45 UTC (1 min interval) on 10 September 2010, obtained from SACOL (Semi-Arid Climate observatory and Laboratory) in China

Figure 7. (a) 31 vertical RSCS profiles between 05:15-05:45 UTC (1 min interval) on 10 September 2010 over SACOL, (b) vertical profile of temporal variance (VAR).

See lines 355 to 346 and Figure 7 in the revised manuscript.

A flowchart for the combination of the VAR and GM in Hennemuth and Lammert [42]:

Figure 9. Flowchart for the combination of the VAR and GM in Hennemuth and Lammert [42].

See lines 374 to 379 and Figure 9 in the revised manuscript.

A simple scheme for THT (temporal-height-tracking) algorithm in Martucci et al. [119,120]:

Figure 10. Synopsis of the THT algorithm in Martucci et al. [119] The profiles of the  and  are averaged over the interval 30 min, for , profile of the  is the single signal gradient profile at  step, is calculated by the moving variance within the temporal interval ,.

See lines 380 to 394 and Figure 10 in the revised manuscript.

A flowchart for STRAR-2D (structure of the atmosphere, 2D version) in Pal et al [7]:

Figure 11. Flowchart for the combination of the STRAT-2D and variance anaylsis in Pal et al. [7]

See lines 441 to 446 and Figure 11 in the revised manuscript.

References:

42.          Hennemuth, B.; Lammert, A. Determination of the Atmospheric Boundary Layer Height from Radiosonde and Lidar Backscatter. Boundary-Layer Meteorology 2006, 120 (1), 181-200.

119.        Martucci, G.; Matthey, R.; Mitev, V.; Richner, H. Frequency of Boundary-Layer-Top Fluctuations in Convective and Stable Conditions Using Laser Remote Sensing. Boundary-Layer Meteorology 2010, 135 (2), 313-331.

120.        Martucci, G.; Milroy, C.; Dowd, O.; Colin, D. Detection of Cloud-Base Height Using Jenoptik CHM15K and Vaisala CL31 Ceilometers. Journal of Atmospheric Oceanic Technology 2010, 27 (2), 305.

7.             Pal, S.; Haeffelin, M.; Batchvarova, E. Exploring a geophysical process-based attribution technique for the determination of the atmospheric boundary layer depth using aerosol lidar and near-surface meteorological measurements. Journal of Geophysical Research-Atmospheres 2013, 118 (16), 9277-9295.

(1)    Introductory is in my opinion the weakest part. (It is in fact to a great extent repetition after already published paper in Rem. Sens. (ABL-SI) by the same authors: Dong et al. 2019.) Reading the Introduction, I had a feeling that this all is well known facts that every 1-2 year PhD student working in boundary-layer research must know. This may discourage some experienced scientists from reading the paper further. The review of methods by writing a few equations is somewhat weak for a really good scientific review paper.

Reply: Yes, Thanks for your valuable suggestions. The introduction part has been rewritten completely. In the revised manuscript, a great improvement is the definition of the Atmospheric boundary layer height (ABLH), mixing layer height (MLH), lidar-derived height and radiosonde-defined height in detail with the help of two added Figures (Figure 1 and Figure 2 in the revised manuscript).

Figure 1. A simplified scheme of diurnal cycle of ABL in clear-sky situations (adapted from Stull [1]). Solid line marks the height of ABL (ABLH), the dashed line marks the top of residual layer (RL). The entrainment process near the top of ABL is marked by the dashed arrows. SBL, stable boundary layer; CBL, convective boundary layer; EZ, entrainment zone; RL, residual layer; EMT, early morning transition; EET, early evening transition.

Figure 2. Principle vertical profiles of the some variables for the well mixed boundary layer during daytime (left), and the more stable nocturnal boundary layer with shallow surface mixing layer, residual aerosol layer and the above free atmosphere layer (right) (adapted from Stull [1]).

See lines 40 to 60, 99 to 107 and Figures 1-2 in the revised manuscript.

Reference:

1.             Stull, R.B. An Introduction to Boundary Layer Meteorology. Atmospheric Sciences Library 1988, 8 (8), 89.

(2)    The main missing topic to be dicscussed (or at least to comment on) is that actually lidars/ceilometers do measure the aerosol boundary layer height and not the meteorological atmospheric boundary layer height. Important questions that could be carefully revised in the literature are, e.g.: What is the offset of the measured values of aerosol vs atmospheric height? Does this depend on season? What is the role of clouds? Is there (and in which kind of measurements) the good-weather bias affecting the results? What clear advantages there are for using the classical vs improved vs new methods? If at one measurements site different methodology is used, then what is the accuracy/uncertainty of each approach? If one compares the results, to what extend one can use the different methodologies as providing the same result? Are there any (and which) methods complementing the others? Finally, is there a perfect set of instruments that is recomended by authors as crucial for high-quality boundary layer sensing?

I can see that some answers to these questions are hidden in the Figures/Tables but it would be good to have then discussed as a few bottom-line statements.

Reply: Yes, Thanks a lot for your valuable suggestions, the questions will be replied in detail as follows.

① What is the offset of the measured values of aerosol vs atmospheric height? Does this depend on season?

Reply: In the introduction part of the revised manuscript, the Planetary Boundary Layer, Mixing layer height, lidar defined aerosol height and radiosonde-derived height from temperature have been detailed defined. Relative to season, the influence of daily variation may be more significant and the difference is introduced in terms of diurnal variation.

“The aerosol lidar derived ABLH is actually a height of surface aerosol layer. Shown as Figure 2, for well-mixed CBL at daytime, the aerosol depth represents the MLH, ideally, the lidar-determined MLH should be equivalent to the radiosonde-derived CBLH with the assumption that the distribution of aerosol concentration is dominated by turbulent mixing. For stable NBL, the height determined by an aerosol lidar is either the top of RL (NBLH) or the top of surface mechanical driven ML (MLH, or the height of ground inversion layer). During the early morning transition (EMT) and early evening transition (EET) periods, the altitude determined by the lidar is the altitude to which aerosol particles have been mixed in the past, rather than the altitude to which they are currently being mixed.”

Figure 2. Principle vertical profiles of the some variables for the well mixed boundary layer during daytime (left), and the more stable nocturnal boundary layer with shallow surface

See lines 99 to 107 and Figures 1-2 in the revised manuscript.

② What is the role of clouds? Is there (and in which kind of measurements) the good weather bias affecting the results?

Reply: The study mainly concentrates on the ABLH determination from aerosol lidar. The cloud layers as well as weather conditions can cause serious effect on lidar determination of ABLH.

In the revised manuscript, to explain the interference of cloud and weather condition on ABLH determination from aerosol lidar, a real case with significant residual layer (RL) in clear-sky situation and a cloudy case with cloud layers whole day are added (Figure 8 and Figure 12 in the revised manuscript).

“……For example, most of the methods are susceptible to clouds and multiple aerosol layers, shown as Figure 8, in the morning on 28 July 2007 over SACOL, the height retrieved from FIT is the top of RL, while the GM, HAAR and MHT capture the top of ground aerosol layer and the growing CBL. For the cloudy day 12 June 2007, the upper edges of the cloud layers are retrieved, the methods are not able to define the ABLH.”

Figure 8. Time-height cross-section of the RSCS provided by the MPL over SACOL, with height directly determined from first-order gradient method (GM), HAAR/MHAT wavelet covariance transform, and ideal profile fitting (CFM) on 28 July 2007 and on 12 June 2007.

See lines 356 to 359 and Figures 8 in the revised manuscript.

“……The top limiter and the ABLH determined below the height restriction on 28 July and 12 June 2007 over SACOL are shown as Figure 12. With the top limiter, the diurnal variations of ABLH on two day are successfully retrieved although the local structures of the signal affect the temporal continuity of the resulted ABLH especially from GM……”

Figure 12. Same as in Figure 8, the top limiter in (a) and (c) represents the upper altitude defined in Dang et al. [56], the ABLH in (b) and (d) determined from the HM, HAAR, MHAT and CFM below the top limiter.

See lines 469 to 473 and Figures 12 in the revised manuscript.

In the conclusion part, the effects of cloud layers and weather condition are also discussed: “……Most of them perform great when the signal structure is simple in clear-sky conditions and shows the characteristics of ABL clearly. The main challenge is under complex signal structure conditions caused by multiple-layer aerosol layers (advected or elevated), cloud layers as well as noise. Because of the interferences caused by them, many of the lidar-based techniques are unable to process the large data set automatically. To overcome the shortcomings……However, ABLH determination in cloudy situations is still changeling and there are so far some unresolved issues. For example, when the cloud is within the ABL but not at the ABL top, the lidar estimation of ABLH is quite difficult. To reduce the cloud interference on ABLH determination, the identification of cloud layer should be further studied and the location of the cloud layer should be determined more accurately. Meanwhile, the influence of cloud layers on the diurnal development of ABL is necessary to be further studied”

See lines 580 to 600 of the revised manuscript.

③ What clear advantages there are for using the classical vs improved vs new methods?

Reply: When the methods are introduced in the revised manuscript, advantages and limitations of each method have been stated, shown as some Tables and Figures.

For example,

“The combination of the GM (first-order gradient method) and the VAR (variance analysis) theoretically should perform better than the GM when there are several local minima in RSCS gradient profile -either atmosphere -or noise-induced. Meanwhile, it can yield instantaneous MLH with the resolution of observation system compared to the VAR being used alone. Similar to VAR, the combined method is also only applicable to daytime CBL.”

See Lines 395 to 399 of the revised manuscript.

“The STRAT-2D algorithm takes both temporal and spatial gradients of backscatter signal into account and provides three to five (including cloud base) height candidates for ABLH. The technique is a fairly good choice for retrieving ABLH in multiple-layer conditions although other additional assistant method such as threshold method or variance analysis is necessary”

See Lines 447 to 450 of the revised manuscript.

……

In the Summary and Conclusions part, the advantages and limitations have been summarized as follows:

“Most of them perform great when the signal structure is simple in clear-sky conditions and shows the stratification of ABL clearly. The main challenge is under complex signal structures conditions caused by multiple-layer aerosol layers (advected or elevated), cloud layers as well as noise. Because of the interferences caused by them, many of the lidar-based techniques are unable to process the large data set automatically. To overcome the shortcomings, on the one hand, some of the traditional techniques were improved…….A technique called START-2D (structure of the atmosphere, 2D version) perform well under multiple layer situations by using a temporal-vertical gradient. On the other hand, some studies imposed height constraints to the techniques, defining an upper altitude to omit the noise signal generated by multiple layers……Most of the new techniques have been tested and showed perform well, however, the application of them is currently limited.”

See Lines 584 to 600 of the revised manuscript.

④ If at one measurements site different methodology is used, then what is the accuracy/uncertainty of each approach? If one compares the results, to what extend one can use the different methodologies as providing the same result? Are there any (and which) methods complementing the others?

Reply: In the review, some practical cases are selected based on the Micro-Pulse lidar (MPL) profiles over SACOL (Semi-Arid Climate observatory and Laboratory) in China. For the same real case, the differences between the ABLH determined from different lidar-based methods and the radiosonde-derived ABLH have been stated in the revised manuscript.

“……over SACOL at 12:00 UTC on 10 September 2010……In this clear-sky case with simple RSCS profile, the gradient-methods-determined ABLH are 0.095 km, 0.036 km, 0.186 km and 0.186 km higher than the theta-gradient-determined thermodynamic CBLH…….”

See Lines 221 to 225 of the revised manuscript.

“The small difference between the FIT-determined ABLH and the theta-gradient-determined CBLH is 0.004 km……. The robustness of the technique is based on utilizing the whole backscatter profile rather than the profile surrounding the top of ML [50]. Relatively, the FIT is less sensitivity to local signal structures than the methods directly based on the gradient……”

See Lines 261 to 265 of the revised manuscript.

“At 12:00 UTC on 10 September 2010 over SACOL (the same case as Figure 3), when the dilation  is selected as 300 m, the HAAR-determined (or MHAT-determined) ABLH is 0.201 km (or 0.287 km) higher than the theta-gradient-determined CBLH (Figure is not shown). For this case, the difference between lidar-defined ABLH by gradient methods, FIT and WCT are within 0.3 km. Meanwhile, the ABLH determined by all above lidar-based algorithms are a little higher than the radiosonde-derived ABLH. This is actually a reasonable phenomenon [103]. The most energetic convective plumes could penetrate into the stable or inversion layer above the ML, which thereby transport aerosols up to levels higher than the bottom of the stable or inversion layer.”

See Lines 313 to 320 of the revised manuscript.

⑤ Finally, is there a perfect set of instruments that is recommended by authors as crucial for high-quality boundary layer sensing?

Reply: This review concentrates on the ABLH determination from aerosol lidar, and focuses on methodologies (only based on aerosol lidar) rather than the instruments. Therefore, no perfect set of instruments can be recommended based on this review.

Reference:

56.          Dang, R.; Yang, Y.; Li, H.; Hu, X.-M.; Wang, Z.; Huang, Z.; Zhou, T.; Zhang, T. Atmosphere Boundary Layer Height (ABLH) Determination under Multiple-Layer Conditions Using Micro-Pulse Lidar. Remote Sensing 2019, 11, 263.

50.          Leventidou, E.; Zanis, P.; Balis, D.; Giannakaki, E.; Pytharoulis, I.; Amiridis, V. Factors affecting the comparisons of planetary boundary layer height retrievals from calipso, ecmwf and radiosondes over thessaloniki, greece. Atmospheric Environment 2013, 74, 360-366.

103.        Coulter, R.L. Comparison of three methods for measuring mixing-layer height. Journal of Applied Meteorology 1979, 18:11 (11), 1495-1499.

(3)    Coming to that, I reckon that the discussion/prospect & conclusion chapters... should be combined to one. Then bottom-line alone stressing that there is no perfect method for retrieval of ABLH is somewhat weak - and here authors could add more compact discussions on the questions posed above. In a review paper, I expect them also to highlight where to the research on boundary layer should/would head to in the nearest future.

Reply: Yes, Thanks for your valuable suggestions.

In the revised version, the discussion/prospect and conclusion chapters have been combined to one section “5. Summary and Conclusions”. Combined with the above questions, the section has been rewritten completely including summary, brief discussion and prospect. Details can refer to the replies to above comments (2) (① to ④), and the “summary and conclusions“ section of the revised manuscript.

For prospect on ABLH determination in the future, we mainly concentrate on service of the lidar data to numerical weather prediction (NWP) models and environment models:

“Lidar estimation is one of the profile measurements of ABLH or MLH, the other possibility for ABLH estimation is the application of the simple PBL parameterizations or numerical models. The profile measurement is generally the first option if data is available. However, continuous profile measurements for the operational determination of the ABLH are not generally available, meanwhile, the spatial and temporal representativeness of ABLH derived from profile measurements need further studies. Numerical weather predication (NWP) models have been used in the practice of the meteorological and environmental service. In the NWP models, PBL schemes are used to parameterize the unresolved turbulent vertical fluxes of heat, momentum, and constituents such as moisture within the PBL and throughout the atmosphere. For different schemes, different assumptions are used, which may be the root causes of models performance difference. One of the promising applications of the lidar-determined instantaneous ABLH is to estimate the simulated results from the NWP models and to continuously improve the PBL parameterizations in the models. Meanwhile, what the most important for NWP models are the initial and boundary conditions, assimilating the lidar derived ABLH into the models is expected to provide more accurate meteorological initials and boundaries for NWP models, which will be a very attractive approach to let the lidar data serve numerical models when there are numerous lidar observations at present. Thus, it is possible to substitute NWP model output for profiles measurements of ABLH in the future. The output from NWP models are expected to provide more accurate meteorological fields for dispersion models or environmental models, the air quality simulation is expected to improve.”

See Lines 613 to 631 of the revised version.

(4)    As for the reference list is practically completed, I would add few more important: Baars et al ACP 2008, Tsanknakis et al AMT 2011, Stachlewska et al. Acta Geophys. 2012, Kotthaus et l. AMT 2016... (Pls check carefully all citations listed in Bibliography for typos, e.g. ref.41 mistake in name: Ca3Rdoba; or ref. 73 small-case for name of journal: remote sening).

Reply: Yes, Thanks a lot. The recommended literatures have been referenced.

See line 408, 207,353, 160, 110, 110 of the revised manuscript

The reference formatting and spelling has been carefully checked and revised throughout the text.

References:

121.        Baars, H.; Ansmann, A.; Engelmann, R.; Althausen, D. Continuous monitoring of the boundary-layer top with lidar. Atmos. Chem. Phys. 2008, 8 (23), 7281-7296.

77.          Tsaknakis, G.; Papayannis, A.; Kokkalis, P.; Amiridis, V.; Kambezidis, H.D.; Mamouri, R.E.; Georgoussis, G.; Avdikos, G. Inter-comparison of lidar and ceilometer retrievals for aerosol and Planetary Boundary Layer profiling over Athens, Greece. Atmos. Meas. Tech. Discuss 2011, 4, 73-99.

115.        Stachlewska, I.S.; Migacz, S.; Szkop, A.; Zielińska, A.J.; Swaczyna, P.L. Ceilometer observations of the boundary layer over Warsaw, Poland. Acta Geophysica 2012, 60 (5), 1386-1412.

62.          Kotthaus, S.; O'Connor, E.; Münkel, C.; Charlton-Perez, C.; Grimmond, C.S.B. Recommendations for processing atmospheric attenuated backscatter profiles from Vaisala CL31 ceilometers. Atmospheric Measurement Techniques 2016, 9 (8), 1-32.

43.          Toledo, D.; Córdoba-Jabonero, C.; Adame, J.A.; Benito, D.L.M.; Gil-Ojeda, M. Estimation of the atmospheric boundary layer height during different atmospheric conditions: a comparison on reliability of several methods applied to lidar measurements. International Journal of Remote Sensing 2017, 38 (11), 3203-3218.

56.          Dang, R.; Yang, Y.; Li, H.; Hu, X.-M.; Wang, Z.; Huang, Z.; Zhou, T.; Zhang, T. Atmosphere Boundary Layer Height (ABLH) Determination under Multiple-Layer Conditions Using Micro-Pulse Lidar. Remote Sensing 2019, 11, 263.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

The article presentation is much improved. It can be published as is.