Multi-year ground-based multi-wavelength Raman lidar aerosol dataset over the interior Tibetan Plateau (Yangbajing, 4284 m a.s.l.; 2021&ndash;2024)

Wang, Yinan; Cui, Hongxia; Zhao, Wei; Bi, Yongheng; Wang, Tianqi; Lu, Daren

doi:10.5194/essd-2026-552

Preprints

https://doi.org/10.5194/essd-2026-552

Preprints

17 Aug 2026

| 17 Aug 2026

Status: this preprint is currently under review for the journal ESSD.

Multi-year ground-based multi-wavelength Raman lidar aerosol dataset over the interior Tibetan Plateau (Yangbajing, 4284 m a.s.l.; 2021–2024)

Yinan Wang, Hongxia Cui, Wei Zhao, Yongheng Bi, Tianqi Wang, and Daren Lu

Abstract. The interior of the Tibetan Plateau exerts a first-order influence on the Asian monsoon and regional climate, yet vertically resolved aerosol observations there are scarce, and no openly archived, multi-year, ground-based profile record has existed for this exceptionally clean high-altitude environment. We present such a dataset from a six-channel elastic/Raman/depolarisation lidar (355, 387, 408, 532, 607, 1064 nm) at Yangbajing (30.10° N, 90.52° E, 4284 m a.s.l.), covering September 2021 to December 2024: 437 quality-controlled nighttime profiles on a 75 m grid (157 levels, 0.30 to 12 km a.g.l.) and 279 daytime column-AOD retrievals. The independent products are the nitrogen-Raman extinction at 355 and 532 nm and the Raman-derived lidar ratio. The aerosol backscatter at 355 and 532 nm is retrieved by the elastic (Fernald) inversion with an assumed lidar ratio of 50 sr, and the 1064 nm backscatter is a non-independent colour-ratio transfer. Volume and particle depolarisation ratios (532 nm), water vapour mixing ratio (408/387 nm; radiosonde-calibrated C = 90.4 g kg-1, ~17 % uncertainty), Ångström exponents and column aerosol optical depth (AOD) complete the product set, and a scattering-ratio cloud screen supplemented by a particle-depolarisation ice test separates mineral dust from ice. The site is among the cleanest continental settings sampled by lidar: the nighttime detection-night median column AOD at 532 nm is 0.053 (n = 269) and the daytime detection median is 0.078 (n = 208). The Raman-derived site-mean lidar ratio is 51.6 sr (IQR 41 to 80 sr, n = 85), consistent in the median with the assumed 50 sr and with the CALIPSO clean-continental value, but it varies by a factor of two from night to night. This assumption, not photon noise (median relative σ ~1.7 % for the 532 nm extinction, rising to a 90th percentile of ~24 % in the weak-signal upper troposphere), dominates the column-AOD uncertainty (+60 %/-18 %), for which per-profile S = 41 and 80 sr bounds are provided. Daytime AOD tracks AERONET Nam Co (~85 km) in rank order (Pearson r = 0.61, Spearman ρ = 0.72, both p < 0.001, n = 41). To our knowledge this is the first openly archived, multi-year, ground-based multi-wavelength aerosol profile dataset from the clean interior Tibetan Plateau, a region pivotal for the Asian monsoon and the Third Pole cryosphere where high surface albedo and complex terrain defeat passive retrievals and leave spaceborne lidar the de facto reference. It supplies the vertically resolved ground truth needed to evaluate and correct spaceborne-lidar aerosol detection and typing, to benchmark next-generation missions such as EarthCARE over bright, high terrain, and to constrain reanalysis, model, and aerosol radiative studies of dust transport and monsoon aerosol over the Third Pole.

Received: 12 Jul 2026 – Discussion started: 17 Aug 2026

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.

Download & links

Preprint (PDF, 5464 KB)

Supplement (1251 KB)

Download & links

Yinan Wang, Hongxia Cui, Wei Zhao, Yongheng Bi, Tianqi Wang, and Daren Lu

Status: final response (author comments only)

RC1:
'Comment on essd-2026-552', Anonymous Referee #1, 22 Sep 2026
Review of manuscript entitled “Multi-year ground-based multi-wavelength Raman lidar aerosol dataset over the interior Tibetan Plateau (Yangbajing, 4284 m a.s.l.; 2021-2024)” by Yinan Wang et al.
The manuscript presents and documents an openly archived, multi-year, ground-based multi-wavelength lidar dataset from Yangbajing (30.10°N, 90.52°E, 4284 m a.s.l.) on the interior Tibetan Plateau, covering September 2021–December 2024. The archive contains 437 quality-controlled nighttime profiles (157 levels, 75 m grid, 0.30–12 km a.g.l.) and 279 daytime column-AOD retrievals, with products including elastic backscatter at 355/532/1064 nm, nitrogen-Raman extinction at 355/532 nm, volume and particle depolarisation at 532 nm, water-vapor mixing ratio, Ångström exponents, column AOD, and per-bin uncertainties and quality flags. The paper is framed as a data-description paper and includes instrument description, retrieval methodology, a detailed uncertainty budget, quality control, seasonal characterisation, and independent corroboration against AERONET Nam Co, CALIPSO, and Lhasa radiosondes.
It's acknowledged that huge efforts were made to deploy an advanced atmospheric lidar system at the Third Pole and to maintain the system under difficult logistical conditions. The dataset addresses a genuine and well-justified gap for the research of the Asian monsoon and the Third Pole cryosphere. It should also be mentioned that the authors disclose the current measurement capabilities as well as the problems for the system with many details, making the dataset not similar to those included in the EARLINET. The manuscript bears an honest delimitation of which products are independent (Raman extinction, lidar ratio) versus conditional (elastic backscatter, column AOD). The dataset is likely to be widely used.
However, a big impression is that the manuscript is somewhat too lengthy, with several parts of similar content being present more than once in different sections. Thus, it is suggested that the authors should reorganize the structure of the manuscript, in particular Sections 4, 5, and 6, to avoid repeating similar statements. Also, it would be helpful to polish the English language, since unusual expressions are sometimes shown in the text.
In addition, it would be hard to believe that you have crosstalk in the 607 nm channel, which is rather far from the corresponding elastic channel. What’s more, it is also problematic that the authors insist on providing the particle backscatter coefficient profiles at 1064 nm although they are not independently retrieved from the 1064 Mie backscatter signal, which makes limited sense to my understanding (also see my other major comments regarding this point below).
Therefore, the current form of the manuscript also requires a major revision before it can be considered for publication in ESSD. My comments below are intended to strengthen the documentation and remove several ambiguities that could lead to misuse.

Major comments
Lidar-ratio assumption and the independence boundary

The authors are to be commended for the explicit treatment of the S = 50 sr assumption and for providing per-profile S = 41 and S = 80 sr AOD bounds. However, several points need clarification:
Sect. 3.2 bounds the residual aerosol at the reference altitude to 0.005–0.01 in AOD. This is a useful estimate, but it should be propagated into the archived AOD uncertainty (or at least flagged in the uncertainty_note global attribute) rather than left only in the text. Is it included in the per-bin σ fields? If not, users combining the S-bounds with the photon-noise σ may underestimate the total.
The authors justify a common S = 50 sr at 355 and 532 nm using 30 paired nights with a median 532-minus-355 difference of ~3 sr (IQR −7 to +21 sr, p = 0.16). This is a reasonable argument, but the sample is small, and the IQR is wide. I suggest reporting the 355 and 532 nm lidar ratios separately in Figure 6 or the text, or at least giving the reader the per-wavelength medians so that users can judge whether a common value is appropriate for their application.
Sect. 10.1 reports that the Ansmann et al. (1992) self-calibrated backscatter agrees with the elastic product within 30% on fewer than one night in five. This is an important result and supports the decision to archive the elastic product. However, the text says "the ratio of the two has a median of 1.48 but an interquartile range of 0.79 to 2.27", i.e., a median of 1.48 implies a systematic offset, not just noise. The authors should comment on whether this offset is understood (e.g., calibration of the Raman channel, overlap residual, or the known low-signal bias of the Raman backscatter method) and whether it implies a bias in the elastic product. If the Raman backscatter is systematically higher, this could indicate that the assumed S = 50 sr is biased low for some nights, which would be worth flagging. I also suggest the authors check the SNR at the reference height for Raman retrieval. Usually, it requires a higher standard to achieve a stable aerosol backscatter profile, and even higher when it comes to the short-wavelength band. The authors can do some perturbation analysis to see the effects of SNR at the reference height.

The 1064 nm backscatter is explicitly non-independent and accurate only to about a factor of two under strong dust. This is honestly stated. The assumption k = 1 is described as "a rough approximation." Since the site is dust-influenced in spring, and dust has k ~ 0, the 1064 nm product will be most biased exactly when aerosol loading is highest, and the product is most likely to be used. A sentence quantifying the expected seasonal bias (e.g., "in MAM the product may be low by up to a factor of two") would help users.

(This is a tip, not a comment) The crosstalk diagnosis is thorough, and the t > 3 flag is well justified. I'm wondering whether the crosstalk effect can be calibrated and then removed in the preprocessing loop. Because, in theory, crosstalk is only controlled by the optical filters, and the crosstalk ratio should be very stable. If so, the crosstalk ratio can be calibrated using a strong backscatter signal from the cloud. Because cloud backscatter coefficient is wavelength-independent. This property can serve as the standard for crosstalk calibration. I suggest that the authors go to the link below for detailed information.

https://www.tropos.de/fileadmin/user_upload/Institut/Abteilungen/Fernerkundung/Daten_PDF/Bachelorarbeit_Nathan_Skupin.pdf

It seems that section 7 related to “independent corroboration” is not necessary. Only section 7.1 can be somehow considered as “corroboration”, which makes a quantitative comparison with AERONET measurements; this paragraph can also be moved to the previous relevant sections. Section 7.2 is a discussion regarding the reasonability of the measured average lidar ratios by comparing them to the pre-assumed aerosol-type-specific lidar ratio values applied by CALIPSO. Section 7.3 repeats the contents that have already appeared in the previous sections.

Minor comments
Line 10: Is it really a "six-channel" lidar? Should the 532 nm cross-channel be included?
Line 13: Insert "vertical" before "grid".
Line 27-29: similar content has already been provided in the first sentence of the paragraph.
Line 30: “ground truth” is overselling
Line 35-39: please add the scientific significance of conducting height-resolved aerosol observations over the plateau interior, especially considering the low aerosol loading there.
Line 45: add previous studies if possible.
Line 47: "to our knowledge, none has been released as an openly archived, multi-year, multi-wavelength record". It should be made clear what the scientific value is of having this record.
Line 53-54: It would be better to reorganize this sentence
Line 63: mention the wavelength for the lidar ratio
Line 68: “climate” -> “climatology”
Line 81 and 82: please specify the “northern deserts” and “local dust emissions” (what kinds?)
In section 2.2, it would be better to provide the pulse energy of the laser employed
Table 1: "Backscatter" -> "Elastic".
Line 147: "~90 km distant" -> "~90 km in distance".
Line 171: "Raman lidar ratio" is an awkward expression. Use "lidar ratio" instead.
Line 188-189: Why not derive the 1064 nm aerosol backscatter from the 1064 nm elastic signal?
In section 3.3: please discuss why this lidar system cannot provide an independent measurement of backscatter at 1064 nm. The solution for the backscatter coefficient at 1064 nm will bring large uncertainties due to the roughly assumed Ångström exponent. It would be even a bit better to apply any possible values from the AERONET measurements of the nearest station.
Line 231-232: it's suggested to add the statistics of the lidar ratio in the supplementary material, which is very informative for dataset users.
Line 242-246: This sentence is too long and should be divided.
Line 243-246: did you consider using the simultaneous and quasi-collocated CALIPSO measurements overflying to calibrate the gain ratio for the depolarization ratio.
Line 247-248: it's suggested to add some details to explain "high-voltage-versus-gain LUT for each photomultiplier".
Line 290-296: This C is an average value for different nights. Did you make any changes to the lidar system during these several years’ measurements, which may influence the values of C. Is it in general stable over long-term operation?
Line 297: do you mean that the overlap functions at low heights are the same for both 408-nm and 387-nm channels?
Line 300: please explain “bin-level availability”
Line 305: insert "ratio" after "depolarisation".
Line 308: "By day" -> "At daytime".
Line 311: It's not clear how "a near-surface reference" is determined, considering that there are always non-negligible aerosols from the surface.
Line 323-324: "volume linear depolarisation ratio" should be used consistently in the manuscript.
Line 327: what is the value of the molecular depolarization ratio applied in the lidar system?
Line 341: "aerosol night" -> "nighttime aerosol profile".
Line 349: "molecular temperature profile" -> "US Standard Atmosphere 1976".
Line 368: "spherical layer (a liquid water cloud)" -> "liquid water cloud".
Line 380-381: remove ", rather than through telescope chromatic". This is somehow misleading, as the overlap difference was not only caused by telescope chromatic aberration.
Line 404-407 and 597-600: it is strange that you have crosstalk between 532 nm and 607 nm, which are rather far from each other in the optical spectrum. And this is not even the case for 355 nm and 387 nm. Are you sure that this problem is caused by the interference filter centered at 607 nm? Because of this issue, you lost almost 25% of the valid data as seen in Fig. 4a, which is really a pity, especially considering that you collected the data from a location difficult to reach.
Line 418-421: It should be noted that Ångström exponents for some dust layers can be negative; see Veselovskii et al. (2020)
Veselovskii, I., Hu, Q., Goloub, P., Podvin, T., Korenskiy, M., Derimian, Y., Legrand, M., and Castellanos, P.: Variability in lidar-derived particle properties over West Africa due to changes in absorption: towards an understanding, Atmos. Chem. Phys., 20, 6563–6581, https://doi.org/10.5194/acp-20-6563-2020, 2020.
Line 434-439: the contents of this paragraph have already been provided in previous sections.
Line 488-491: the contents of this paragraph have already been provided in previous sections.
Line 526-528: it would be better to have some references here
Figure 6c: use British spelling for “depolarization” for the sake of consistency
Section 6.2, distinguishing dust and ice clouds can also involve the backscatter ratio together with the particle linear depolarization ratio. In addition, clouds can only show up for a while rather than the entire night; thus, is it problematic to use night-average profiles for identifying dust nights and ice-carry nights?
Line 575-585: the contents of this paragraph have already been provided in previous sections (similarly, section 7.3).
Line 627: "near-overpass" -> "closest".
Line 688-691: The contents of this paragraph have already been provided in previous sections.
Section 7.4: This section is redundant with previous sections (sections 5.4, 6.3, and 9). I highly suggest that the authors go through the manuscript to remove the replicated content. The same applies to section 8.3.
Line 744: "Users should cite both this paper and the Zenodo dataset DOI", I think this claim should be more relevant to the dataset.
Line 784: insert "range" before gate.
Line 795: "The dataset provides the vertically resolved aerosol ground reference that is missing for the plateau interior".
Line 800: remove "forthcoming".
Table 4: it's suggested to add the China Aerosol Raman Lidar Network (CARLNET) for comparison; see Shao et al. (2025) and Bu et al. (2026). The dataset is only accessible within the China Meteorological Administration.
In the reference, there are many incorrect characters that should be checked. To name a few, "Munoz-Porcar" -> "Muñoz-Porcar"; "Muller" -> "Müller".
Line 847: “staff” -> “staffs”
Citation: https://doi.org/10.5194/essd-2026-552-RC1
RC2: 'Comment on essd-2026-552', Anonymous Referee #2, 02 Oct 2026

Is the article itself appropriate to support the publication of a data set?
Yes.
But it doesn’t contain all necessary information => see below.

Is the data set significant – unique, useful, and complete?
Unique: yes
Useful: no

Is the data set itself of high quality?
No.
Please, compare Fig._by_reviewer 1 (attached by supplyment) with particle linear depolarization ratios larger than 0.6.
(Figure_by_reviewer 1: particle_depolarization_532_in_Yangbajing_lidar_multiwavelength_2021-2024.png)

Is the data set usable in its current format and size?
No.
Are the formal metadata appropriate?
There is no separate metadata file.

Is the length of the article appropriate?
No, it contains a lot of repetition. The article could be shortened.

Is the overall structure of the article well-structured and clear?
Sections could be combined, and repetition could be avoided.

Is the language consistent and precise?
The language has to be improved.

Are mathematical formulae, symbols, abbreviations, and units correctly defined and used?
There are only 3 equations. The findings can only be understood by a scientist familiar with lidar technology. As a result, the data can only be evaluated by such scientists and should only be used by them, respectively.
For example, the very large value of the calibration constant of the water vapor mixing ratio shows that the SNR in the water vapor channel is very low and, consequently, the relative error of the water vapor mixing ratio is very large. Unfortunately, the SNR or the relative error of the water vapor mixing ratio based on the SNR of the two used channels, especially of the 408-channel, is not specified anywhere.

Are figures and tables correct and of high quality?
Yes.

The data set contains the quantities which are characterizing the atmosphere and are not only system-dependent:
angstrom_backscatter, angstrom_extinction, backscatter_1064, backscatter_355, backscatter_532, cloud_base_km, cloud_detected, cloud_free_night, cloud_top_km, column_aod_532_day , column_aod_532_day_qc, column_aod_532_day_S41, column_aod_532_day_S80, column_aod_532_night, column_aod_532_night_qc, column_aod_532_night_S80, extinction_355, extinction_532, leak607_crosstalk_flag, particle_depolarization_532, sigma_backscatter_355, sigma_backscatter_532, sigma_extinction_355, sigma_extinction_355, volume_depolarization_532, water_vapour_mixing_ratio

The NC-data file size of the data with approximately 1 MB
is very small for
lidar data characterizing the atmosphere during a period between September 2021 to December 2024 (more than 3 years!).

The data set itself does not contain
- height of the station,
- SNR of the channels,
- tilt angle of the system,
- uncertainties of the retrieved quantities,
- relative errors of the retrieved quantities, and
- absolute errors of the retrieved quantities

Some general remarks:

Introduction / frame of work / paper layout (general remarks):
I’m missing the discussion of already published results of vertically resolved measured data in Tibet, for instance https://doi.org/10.1051/epjconf/201611906016.
There is no paragraph to the structure of the paper.

Instrumental (general remarks):
The measurement system is not described in sufficient detail (for example: purification of the emitted polarization by a polarizer after the laser?; divergence of the emitted radiation; FOV of the receiver?). As a result, questions remain unanswered regarding the analysis of errors, and the errors cited cannot be adequately verified. The data file does not contain any errors.
Why is the leakage of the 607-channel existing only for/at strong aerosol backscatter at 532 nm? That doesn't make sense.

Atmospheric (general remarks):
Smoothing:
Usually there are aerosol layers in the atmosphere. Hence it makes no sense to average vertically just with an increasing smoothing length with height. By this, its highly likely that values from inside a layer are averaged together with values from below or/and above a layer. Therefore, the values within an aerosol layer are distorted and smaller than they would be if they were calculated by averaging only the values within the layer.
I see a layering in Fig. 7a during the spring time but I don’t see this layering in Fig. 7c.

Averaging over months makes no sense. Please, compare the red highlighted period in Fig._by_reviewer 2 (attached by supplyment) and other periods.
(Figure_by_reviewer 2: extinction_532_in_Yangbajing_lidar_multiwavelength_2021-2024.png)

In addition, there are some comments regarding specific passages in the text. However, I will not list them here, as a general revision of the dataset and the text is required.

Citation: https://doi.org/10.5194/essd-2026-552-RC2
RC3: 'Comment on essd-2026-552', Anonymous Referee #3, 15 Oct 2026

The manuscript presents and documents a new, multi-year ground-based lidar dataset from Yangbajing (30.10°N, 90.52°E, 4284 m a.s.l.), a pristine site on the interior Tibetan Plateau. The dataset spans September 2021 to December 2024 and contains 437 quality-controlled nighttime profiles and 279 daytime column-AOD retrievals on a 75 m vertical grid (157 levels, 0.30–12 km a.g.l.). The products include aerosol optical properties and water vapor mixing ratio. The paper describes the instrument, the processing chain, quality control (cloud screening, overlap correction, SNR/detection limits, 607 nm crosstalk diagnosis, and depolarisation calibration epochs), the uncertainty budget, dataset characterisation, independent corroboration (AERONET Nam Co, CALIPSO, and Lhasa radiosondes), and a discussion of the independence boundary and applications.
This is the first openly archived, multi-year, multi-wavelength ground-based aerosol profile dataset from the clean interior Tibetan Plateau—a region of first-order importance for the Asian monsoon and the Third Pole cryosphere, although profiles of aerosol components have been recorded by other instruments and reported previously (see Wang et al., 2019). Nevertheless, this study still introduces a highly valuable dataset with continuous coverage over a longer period, which is essential for detailed case studies. The retrieval methods follow established community practice (EARLINET SCC-style, D'Amico, 2015), the uncertainty budget is carefully investigated and quantitative, and the quality control is transparently documented. The manuscript merits publication; however, several issues should be carefully addressed to improve readability and especially dataset quality.
Having reviewed the previous review report, I believe sufficient technical comments have already been raised by the other two reviewers. My main concerns therefore focus on data quality, which I ask the authors to address or clarify.
1. The aerosol backscatter coefficient at 1064 nm is not derived directly from the 1064 nm elastic signal but rather from a conversion of the aerosol backscatter coefficient at 532 nm. This means that the 1064 nm backscatter imposes invalid constraints on aerosol microphysical properties, which is usually what one expects from a 3β+2α configuration (Müller et al., 2016; Veselovskii et al., 2004). I strongly suggest that the authors regenerate the 1064 nm aerosol backscatter based on the 1064 nm elastic signal. If that is not feasible, it may be reasonable to remove the 1064 nm aerosol backscatter from the dataset.
2. The crosstalk at the 607 nm Raman channel is a very unusual case for a modern Raman lidar, given the very large spectral gap from the elastic signal at 532 nm. I therefore strongly suggest that the authors verify this effect. If it is indeed real, a crosstalk correction is necessary. The authors may follow the method suggested by Reviewer 1.
3. In Sect. 10.3, the authors note that near the surface, fog, low stratus, and blowing dust can produce comparable scattering ratios, and that they did not perform a dedicated near-surface sensitivity test. They advise users working in the lowest ~2 km to treat cloud flags conservatively, which is appropriate. However, given that the boundary layer is precisely where aerosol radiative effects and surface–aerosol interactions are most important, I would encourage the authors to add a brief quantitative statement about the expected frequency of ambiguous cases. For example, how many nights have a cloud base below 2 km? How many have cloud_phase = 3 (undetermined)? The archived cloud_base_km, cloud_top_km, and cloud_phase variables provide this information, but a summary statistic in the paper would help users assess the practical impact. This could be added as a short paragraph in Sect. 6 or 10.3, or as a note in the dataset description.
4. The authors claim that this is "the first openly archived, multi-year, ground-based multi-wavelength aerosol profile dataset from the clean interior Tibetan Plateau." They support this with a comparison table (Table 4) showing that EARLINET/ACTRIS, MPLNET, AD-Net, NDACC, and PollyNET have no interior Tibetan Plateau station. This is a strong and potentially contentious claim. However, I would suggest adding a sentence acknowledging that there may be non-English-language or non-openly-archived datasets from Chinese institutions that are not captured by these networks, and that the claim is made to the best of the authors' knowledge based on publicly available information. This is a minor point but would strengthen the credibility of the claim.
References
Wang, M., Xu, B. Q., Yang, S., et al.: Black carbon profiles from tethered balloon flights over the southeastern Tibetan Plateau (in Chinese), Chin. Sci. Bull., 64, 2949–2958, https://doi.org/10.1360/TB-2019-0101, 2019.
D'Amico, G., Amodeo, A., Baars, H., Binietoglou, I., Freudenthaler, V., Mattis, I., Wandinger, U., and Pappalardo, G.: EARLINET Single Calculus Chain, overview on methodology and strategy, Atmos. Meas. Tech., 8, 4891–4916, https://doi.org/10.5194/amt-8-4891-2015, 2015.
Müller, D., Böckmann, C., Kolgotin, A., Schneidenbach, L., Chemyakin, E., Rosemann, J., Znak, P., and Romanov, A.: Microphysical particle properties derived from inversion algorithms developed in the framework of EARLINET, Atmos. Meas. Tech., 9, 5007–5035, https://doi.org/10.5194/amt-9-5007-2016, 2016.
Veselovskii, I., Kolgotin, A., Griaznov, V., Müller, D., Franke, K., and Whiteman, D. N.: Inversion of multiwavelength Raman lidar data for retrieval of bimodal aerosol size distribution, Appl. Opt., 43, 1180–1195, https://doi.org/10.1364/AO.43.001180, 2004.

Citation: https://doi.org/10.5194/essd-2026-552-RC3
EC1: 'Comment on essd-2026-552', Montserrat Costa Surós, 19 Oct 2026

Note from the editor: Please include the DOI and the appropriate reference/citation to the dataset in the abstract, in accordance with ESSD requirements.

Citation: https://doi.org/10.5194/essd-2026-552-EC1

Yinan Wang, Hongxia Cui, Wei Zhao, Yongheng Bi, Tianqi Wang, and Daren Lu

Supplement

https://doi.org/10.5194/essd-2026-552-supplement

Data sets

Multi-year ground-based multi-wavelength Raman lidar aerosol dataset over the interior Tibetan Plateau (Yangbajing, 4284 m a.s.l.; 2021–2024) Yinan Wang, Hongxia Cui, Wei Zhao, Yongheng Bi, Tianqi Wang and Daren Lu https://doi.org/10.5281/zenodo.21317571

Yinan Wang, Hongxia Cui, Wei Zhao, Yongheng Bi, Tianqi Wang, and Daren Lu

Viewed

Total article views: 444 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	Supplement	BibTeX	EndNote
243	84	117	444	52	152	120

HTML: 243
PDF: 84
XML: 117
Total: 444
Supplement: 52
BibTeX: 152
EndNote: 120

Views and downloads (calculated since 17 Aug 2026)

Month	HTML	PDF	XML	Total
Aug 2026	51	12	4	67
Sep 2026	135	46	91	272
Oct 2026	57	26	22	105

Cumulative views and downloads (calculated since 17 Aug 2026)

Month	HTML	PDF	XML	Total
Aug 2026	51	12	4	67
Sep 2026	135	46	91	272
Oct 2026	57	26	22	105

Viewed (geographical distribution)

Total article views: 405 (including HTML, PDF, and XML) Thereof 405 with geography defined and 0 with unknown origin.

Country	#	Views	%

Latest update: 23 Oct 2026

Download

Preprint (5464 KB)
Metadata XML

Short summary

We present the first openly archived multi-year, multi-wavelength Raman-lidar aerosol dataset from the clean interior Tibetan Plateau (Yangbajing, 4284 m; 2021–2024): quality-controlled profiles of backscatter, extinction, depolarisation and water vapour, with uncertainties and flags. The pristine site makes aerosol largely detection-limited. It gives a ground-truth reference for spaceborne-lidar evaluation, reanalysis and model assessment, and dust and radiative studies over the Third Pole.


Total:	0
HTML:	0
PDF:	0
XML:	0