the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Lidar depolarization characterization using a reference system
Alkistis Papetta
Franco Marenco
Rodanthi-Elisavet Mamouri
Argyro Nisantzi
Ioana Elisabeta Popovici
Philippe Goloub
Maria Kezoudi
Stephane Victori
Jean Sciare
Abstract. In this study, we will present a new approach for the determination of depolarization parameters of the Nicosia CIMEL CE376 lidar system, using the PollyXT in Limassol as a reference instrument. The method is applied retrospectively to the valuable measurements obtained during the 2021 Cyprus Fall campaign. Lidar depolarization measurements represent valuable information for aerosol typing and for the quantification of some specific aerosol types such as dust and volcanic ash. An accurate characterization is required for quality measurements and to remove instrumental artefacts. This article uses the PollyXT reference calibrated depolarization lidar to evaluate our system's gain ratio and channel cross-talk. This approach uses observations of transported dust from desert regions, with layers in the free troposphere. Above the boundary layer and the highest terrain elevation of the region, we can expect that for long transport aerosols local effects should not affect the aerosol mixture so that we can expect similar depolarization properties at the two stations (separated by ∼60 km). Algebraic equations are used to derive depolarization parameters from the comparison of the volume depolarization ratio measured by the two systems. The applied methodology offers a promising opportunity to evaluate the depolarization parameters of a lidar system, in cases where a priori knowledge of the cross-talk parameters is not available.
- Preprint
(15211 KB) - Metadata XML
- BibTeX
- EndNote
Alkistis Papetta et al.
Status: open (until 04 Oct 2023)
-
RC1: 'Comment on egusphere-2023-1338', Anonymous Referee #1, 13 Sep 2023
reply
The manuscript deals with the potential of a CIMEL lidar to measure height profiles of the depolarization ratio. It needs improvements, major revisions are required. In addition, the text (language) can be significantly improved. I attached a PDF with suggestions for text improvements.
Let me start with some general remarks:
One should follow the notation (letters for parameters, definitions, etc.) as used in Freudenthaler (Atmos. Meas. Tech., 9, 4181–4255, https://doi.org/10.5194/amt-9-4181-2016, 2016), Belegante et al. (2018), and Bravo-Aranda (2016). All these papers are given in the reference list. It is confusing for lidar experts, familiar with these fundamental papers, when gamma and epsilon is used here in a different way as in these standard papers. Another example, D is used in the three mentioned papers in the context of diattenuation (consideration, corrections), here, in this manuscript D1, D2, Dref and Dm are used for very different parameters. When the same notation as in Freudenthaler (2016) is used, reading and comparisons are facilitated. Furthermore, it is then much more easy to discuss gaps in the approach presented in this manuscript under review.
The +/-45 deg calibration is now commonly denoted as delta 90 deg calibration. All in all, please follow the way (and notations) given by Freudenthaler (2016) as much as possible. Freudenthaler et al (2009) is no longer a good guide. Meanwhile , the number of influencing quantities and parameters has significantly increased.
I have the feeling, it would be good if the authors study again these fundamental papers of Freudenthaler, Belegante et al., and Bravo-Aranada et al., and consider the main messages in the introduction or later in the discussion section. Even in case of a quite poor depolarization lidar (as this CIMEL lidar of the Cyprus Institute) one should at least discuss the full framework of a properly designed and properly working depolarization lidar, i.e., one should not ignore the state of the art. For example, have a look into the Belegante et al paper in which diattenuation of the receiver optics is nicely described. Please do not omit all these features in your manuscript with the argument: It is not really necessary to mention that in case of observations with the ‘black box’ CIMEL lidar. The approach presented here is quite simple (basic) and describes the way to handle a poor and simple lidar with many unknown features so that the lidar cannot be characterized properly. One could ask, do we need a manuscript that describes the status of depolarization ratio observations performed 20 years ago?
The figures are not just in a good quality. E.g., many text parts (x-axis and y-axis) are almost not readable (rather small).
Concerning the Polly lidar, a reference to the basic PollyNET paper of Baars et al. (ACP, 2016) is recommended. The lidar is described by Engelmann et al. (2016), but also by Jimenez et al. (ACP, 2020, part 2). Hofer et al. (ACP, 2017, 2020a, 2020b) used this lidar type for dust studies in Tajikistan.
Polly seems to be used for dust studies at Cyprus since almost 10 years (since 2015), besides the Raymetrics lidar since 2011-2012, if I follow the literature of Mamouri and Nisantzi. It should be mentioned that there is already expertise in this field of atmospheric science since more than 10 years, respective papers should be cited to corroborate that.
The three-parameter approach (and also the two-parameter approach) partly leads to negative results (depolarization ratios). Too much co-polarized signal is obviously subtracted from the cross-polarized channel output (signal), because your gamma is obviously too large. The minimum should be the Rayleigh depolarization ratio after all corrections. That sounds trivial but this needs to be mentioned. Please comment on this point! The negative results are not discussed yet. Yes, we know, that is a fundamental problem in case of such lidars (when subsequent corrections need to be made without a clear knowledge or idea about system details). However, in AMT these problems need to be discussed to tell the readers that a proper design of the receiver optics and well described and characterized receiver elements are a prerequisite for proper depolarization observations.
Did you use the Polly Rayleigh depolarization ratios to correct the CIMEL lidar observations? I have the impression, that is the case. The Polly Rayleigh depolarization ratios are too my opinion very high. The 532 nm values should be around 1.1% when I check other papers with Polly data.
In addition, the Polly description is too short. Meanwhile, to my knowledge (from several workshops with Polly presentations) they use diod-pumped lasers with 100 Hz rep rate (Cabo Verde, Tajikistan, Cyprus). It should also be mentioned that the total signal and the cross-polarized signal (Engelmann et al., 2016, Jimenez et al., 2020) are measured, and not the co and cross polarized signal components. It is not needed to explain the way to obtain the depol ratio, one may cite Engelmann et al. (2016), but the reader should know.
However, one needs more details to the Polly data analysis (towards depolarization ratios) used in this study: Polly has automated delta 90 deg calibration units, right? How often (per day? per week?) What is explicitly done in the two shown measurement cases? What v-star is used? As mentioned, the Rayleigh depol value seems to be very high with 2.2%! How was this Rayleigh value obtained (for what v-star, derived from how many delta 90 deg observations)? What about the used transmissivity ratios in the case of the Polly data analysis? Where the TROPOS lidar experts (with their long-term experience) involved in the data analysis?
If possible, please provide absolute values for D1, D2, Dref, and Dm, not just differences. It would be good to have more absolute values! And this not only for dust layers, but also for Rayleigh height zones.
Some detailed comments:
Introduction:
There are many Limassol lidar papers (lidar/photmeter CUT team) on dust observations that could be cited to provide the reader with background information about the long-term experience of Cyprus lidar scientists in this field of dust research.
Line 20: There were several field campaigns (CyCARE, ALIFE) with strong contributions by depol lidars. That should be emphasized. Floutsi et al. (Atmos. Meas. Tech., 16, 2353–2379, https://doi.org/10.5194/amt-16-2353-2023) uses CyCARE and ALIFE data and mention the campaigns. If there is no better reference…. then use Floutsi et al.
Lines 24-25: Measurements were not only conducted within the troposphere, even in the stratosphere over Cyprus (Baars et al., ACP, 2019, Canadian wildfire smoke). Should be mentioned to corroborate the importance of the location of Cyprus in the Eastern Mediterranean.
Figure 2: I am surprised that such a bad lidar can deliver still useful results…! Well and carefully performed analysis, the authors did!
Lines 100-105: I have trouble to get Eq.(7) from Eq.(6). The jump is too large for me. I recommend to provide more details to the mathematical treatment…., some more words (not equations…) may be sufficient.
Section 3.2.: As already mentioned, the Polly system needs to be better described along the general comments above.
Section 4:
Please keep in mind that there is always some pollution (from all the northern African states at the coast) mixed into the dust plumes reaching Cyprus. Pollution leads to a decrease of the particle depolarization ratio. Furthermore, keep in mind, the contribution of pollution can be rather inhomogeneous so that Nicosia and Limassol observations can be quite different.
Figure 4 is confusing: What is the arrival height? Different colors for different stations, different colors for different heights, no color scales…. The request of ACP is: (a), (b), (c), (d) ….. if there are 2,3,4 panels… Please improve all figures regarding (a), (b), (c)… if there are more than one panel.
Figure 5: Please show the same color plots for Limassol in addition: left panels (a), (c), Nicosia observations, right panels (b), (d), Limassol observations! Then we can better see to what extent the different observations can be compared.
Figure 6 and 8 (and 10): Polly Rayleigh values of 2% seem to be too high, CIMEL lidar delivers negative depolarization ratios (16 Feb.). Please check the Polly data analysis.
Figures 7 and 9: text of (x-axis and y-axis) must be larger.
Line 390: There is no TROPOS co-author (although they probably need to take care of the Polly lidar all the time), and there is even no word about the TROPOS guys in the acknowledgement.
Alkistis Papetta et al.
Alkistis Papetta et al.
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 147 | 48 | 9 | 204 | 7 | 6 |
- HTML: 147
- PDF: 48
- XML: 9
- Total: 204
- BibTeX: 7
- EndNote: 6
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1