Pith. sign in

REVIEW 4 major objections 4 minor 1 cited by

Five-years Altitude Statistics of Noctilucent Clouds Based on Multi-Site Wide-Field Camera Survey

T0 review · 4 major / 4 minor · reviewed 2026-08-11 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read A five-year, multi-site camera survey finds noctilucent clouds at a mean altitude of 81.4 km and confirms the single-camera umbral method to about 0.5 km.

desk verdict A solid multi-site triangulation study with new five-year NLC altitudes; the unvalidated single-altitude assumption is a real but fixable weakness. read the letter →

arxiv 2412.04951 v1 pith:TW2X4RVU submitted 2024-12-06 physics.ao-ph astro-ph.IM

Oleg S. Ugolnikov , Nikolay N. Pertsev , Vladimir I. Perminov , Ilya S. Yankovsky , Dmitry N. Aleshin , Ekaterina N. Tipikina , Alexander A. Ilyukhin , Egor O. Ugolnikov
show 9 more authors
Stanislav A. Korotkiy Olga Yu. Golubeva Andrey M. Tatarnikov Sergey G. Zheltoukhov Alexey V. Popov Alexey M. Sushkov Egor A. Volkov Natalya S. Krapkina Damir I. Yalyshev
This is my paper · ORCID
classification physics.ao-phastro-ph.IM
keywords noctilucentcloudsmesosphericicetriangulationwide-fieldcameraumbralaltituderadiativetransfercoolingatmosphericshrinking
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper tries to establish that a loose network of ordinary wide-field cameras, separated by 50-100 km, can measure the altitude of noctilucent clouds accurately enough to build statistical maps and to check a simple radiative-transfer model. It processes 14 bright cloud events observed over five summers in central Russia, projecting each camera image onto a fixed a priori layer, co-adding frames with the measured cloud drift, and cross-correlating fields between stations to get a per-fragment parallax altitude. The resulting square-weighted mean NLC altitude is 81.4 km, the brightness-weighted mean is 80.9 km, and the brightest clouds sit at 80.1 km. The independent colorimetric "umbral" altitude exceeds the triangulation altitude by only about 0.5 km on average, which the paper interprets as a small multiple-scattering correction rather than a failure of the model. If the claim holds, long-term monitoring of mesospheric cooling and shrinking becomes possible with inexpensive camera networks rather than lidar or satellite assets.

What carries the argument

The central mechanism is parallax triangulation of NLC brightness patterns across a multi-site camera set. Each image is projected onto an a priori layer at $H_0=81.33$ km, and the projected fields are co-added over two-minute windows using cloud-pattern velocities derived from cross-correlation in time; then the fields from different sites are cross-correlated to find parallax shifts, and a least-squares inversion (Equations 1-4, iterated 3-4 times to include Earth curvature and camera altitudes) converts those shifts into an altitude correction $\Delta H$ for each fragment. The companion "umbral" technique uses all-sky RGB photometry of the same clouds as they pass through the ozone and tropospheric shadow, compared with a single-scattering radiative-transfer model; the $\Delta H$-to-umbral comparison is what tests that model.

What would settle it

Simultaneously observe the same NLC fields with this triangulation network and an independent profiler such as a co-located lidar or a limb-sounding satellite; the claim fails if the triangulation altitudes deviate systematically from the independent altitudes by more than the reported internal errors (~0.1-0.2 km per fragment). The multiple-scattering interpretation of the 0.5 km umbral excess can be settled by checking whether that residual increases as the line of sight through the shadowing atmosphere lengthens.

Watch

Extended reading notes

Core claim

On the paper's own terms, the discovery is a self-consistent altitude climatology of mid-latitude noctilucent clouds built by multi-site triangulation, together with quantitative agreement between two independent ground-based techniques. For each bright NLC fragment, images from several cameras at sites 50-100 km apart are projected onto a spherical shell at the a priori altitude $H_0=81.33$ km, the fields are co-added over a two-minute interval using the pattern velocity found by time-shift correlation, and the residual parallax shifts between stations are inverted by least squares (Equations 1-4) to give one altitude correction per fragment. Averaged over all fragments, the square-weighted mean altitude is 81.4 km, the brightness-weighted (mean optical) altitude is 80.9 km, and the brightest clouds are at 80.1 km. When the all-sky RGB data from the basic site are processed by the colorimetric "umbral" method—watching cloud colors evolve as they sink into ozone and tropospheric shadow, compared with a single-scattering model—the resulting mean altitudes agree with the triangulation values to within about 0.5 km. The paper reads this residual as the contribution of multiple scattering and uses it to support the single-camera technique for future surveys.

Load-bearing premise

The load-bearing premise is that each NLC fragment is an optically thin brightness pattern frozen at a single effective altitude and drifting at constant velocity during the two-minute co-addition interval, with no independent altitude measurement such as lidar or satellite on the same nights to verify that assumption.

Editorial extensions

If this is right

  • An inexpensive network of commodity wide-field cameras can deliver NLC altitude maps with internal errors around 0.1-0.2 km per fragment, without calibrated photometry.
  • Brightness-weighted mean altitude (80.9 km) sits below the square-weighted mean (81.4 km), and the brightest fragments are lower still (80.1 km), so visible-light surveys are systematically biased toward the bottom of the ice layer.
  • The single-camera umbral method, corrected for a ~0.5 km offset, can serve as a proxy for triangulation altitude in surveys without multiple stations.
  • The seasonal pattern—early-season clouds only above 82 km, with the lowest altitudes near the temperature minimum—means future trend analyses must remove seasonal and latitudinal effects before attributing altitude shifts to CO2-driven shrinking.
  • The 0.5 km agreement sets a numerical target that mesospheric radiative-transfer models must meet when describing NLC scattering.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the 0.5 km offset is truly multiple scattering, it should grow with the optical path through the lower atmosphere; binning the umbral-minus-triangulation residual by cloud elevation or solar depression angle within the existing dataset would test that directly.
  • The same pipeline could be applied to historical all-sky or wide-field photographic records from sites with known geometry, extending the NLC altitude time series backward and testing the predicted ~2 km-per-century lowering—an extension the paper does not perform.
  • Because visible NLC detection favors large, low-lying particles, any comparison of these altitudes with lidar or satellite profiles must state which brightness weighting is used; a single "mean altitude" number without that weighting is not physically comparable.
  • If the method is as portable as claimed, a distributed network of citizen-operated RGB cameras could track NLC altitude statistics year after year, turning a mesospheric cooling diagnostic into a low-cost monitoring program.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 4 minor

Summary. This paper presents altitude measurements of noctilucent clouds (NLC) from a multi-site ground-based camera network in central Russia over 2020-2024, based on 14 bright events. The authors update the triangulation procedure to multiple locations, map NLC altitudes for each event, and derive brightness- and square-weighted altitude distributions. They report a square-weighted mean altitude of 81.4 km, a brightness-weighted mean of 80.9 km, and a brightest-cloud height of 80.1 km, and compare these with the "umbral" colorimetric technique, finding a mean difference of about 0.5 km. They also discuss seasonal variation and a possible long-term trend relative to historical values.

Significance. If the method and statistics are reliable, this is a useful contribution: it demonstrates a cost-effective multi-site triangulation network for NLC, provides a five-year altitude distribution at mid-latitudes, and offers a cross-check of the single-camera umbral technique against a geometric method. The per-fragment formal errors of 0.1-0.2 km on the sample night (Figure 4) are encouraging. However, the paper's headline statistics lack uncertainty estimates, and the absolute accuracy of the triangulation is not validated against an independent same-night reference, which limits the strength of the claims. The cross-method comparison is valuable but also needs statistical rigor.

major comments (4)
  1. [Section 5, first paragraph of Discussion] The headline values (square-weighted mean 81.4 km, brightness-weighted mean 80.9 km, brightest clouds 80.1 km) are quoted without any uncertainties. Given that the per-fragment errors in Figure 4 are 0.1-0.2 km and that the statistics come from only 14 independent events, the paper should provide standard errors or confidence intervals for these means and for the seasonal trend points in Figure 7. Without such error bars, the comparison with historical values (Jesse's 82.1 km, 20th-century ~83 km) cannot be meaningfully assessed.
  2. [Section 3, Eqs. (1)-(4) and Figure 4] The quoted per-fragment accuracy is based solely on internal least-squares residuals. The systematic effects of the assumed single effective altitude per fragment, the velocity estimated from the same cloud patterns, and the two-minute co-addition are not quantified. No external altitude reference (lidar, satellite, or independent triangulation) is used for the same nights, so a common bias in the triangulation would shift all reported altitudes and would be absorbed into the reported ~0.5 km umbral-triangulation residual. Please add either a same-event external validation or a sensitivity analysis (e.g., varying H0, testing the velocity estimate, or simulating a multilayer fragment) to bound these systematics.
  3. [Section 4, paragraph after Figure 8] The claim that "the umbral altitude does not significantly exceed the triangulation altitude, the mean difference with account of errors is about 0.5 km" lacks supporting statistics. The number of comparison points, the scatter, the uncertainty on the mean difference, and the error bars on each individual altitude are not reported. I recommend reporting these values, along with a correlation coefficient or a Bland-Altman analysis, so that the agreement can be properly evaluated.
  4. [Section 4, Figure 6 and Section 2] The altitude statistics are based on 14 bright NLC events selected by visibility and structure quality. The paper itself argues that bright visible clouds tend to be lower than the mean lidar profile because of large particles near the cloud bottom (Section 5). This selection effect must be discussed quantitatively in the context of the derived statistical distribution; otherwise the reported mean altitudes (81.4 km and 80.9 km) may reflect the selection criteria rather than the population of NLC at mid-latitudes.
minor comments (4)
  1. [Figure 4] The error bars shown in Figure 4 appear to be formal fit errors; please label them explicitly as such in the caption, since they are central to the accuracy claim.
  2. [References] The reference list contains a typo: "Bronshten, V.A." appears as "Bronsten" in the text; please make the spelling consistent.
  3. [Data availability] The paper does not contain a data availability statement. For reproducibility, please state whether the underlying observations and processing code are publicly available or will be made available upon request.
  4. [Figure 7] In Figure 7, the symbols for triangulation and umbral altitudes are not defined in the available text; please ensure the legend is clear in the final version.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the central altitude statistics are derived from geometric parallax, and the umbral-method comparison is an independent cross-check rather than a fitted input.

full rationale

The paper's load-bearing altitude results come from multi-site triangulation, which is a geometric measurement of parallax shifts between cameras separated by 50-100 km. The a priori altitude H0 = 81.33 km is only an expansion reference; Eqs. (1)-(4) solve for the altitude correction from measured image shifts, and the algebra is independent of H0 in the small-shift limit. No fitted parameter from the altitude statistics is reused to construct the triangulation result. The umbral-altitude comparison in Fig. 8 is a posteriori validation: the colorimetric technique is cited from Ugolnikov (2023a), but its validity is not assumed in the derivation; it is explicitly tested against the independent triangulation measurements. The reported ~0.5 km mean difference is a measured residual, interpreted as a possible multiple-scattering contribution, not a parameter tuned to force agreement. Lidar and satellite comparisons are consistency checks rather than calibration inputs. The absence of same-night lidar/satellite reference is a legitimate systematic-error concern, but it is a correctness risk, not circularity: no equation, fitted value, or derived altitude is equivalent by construction to the inputs of the model being checked.

Assumptions & free parameters 1 free parameters · 5 assumptions · 0 invented entities

The core altitude statistics are geometric measurements requiring no fitted constants introduced by this paper; the only chosen reference is the a priori layer H0 = 81.33 km inherited from Ugolnikov (2024), and the final altitudes are corrections to it. The umbral comparison imports the radiative transfer model and its parameters from Ugolnikov (2023a) without re-deriving them. The load-bearing axioms are domain assumptions about cloud structure and motion, namely frozen single-layer patterns with constant velocity over two-minute windows, plus the literature-based assumption that visible NLC are biased to large particles in the lower layer. No new entities are introduced.

free parameters (1)
  • H0 (a priori NLC altitude) = 81.33 km
    Chosen fixed projection altitude following Ugolnikov (2024). All fragments are projected onto this layer and altitudes are derived as corrections to it. It is a coordinate reference inherited from the authors' prior work rather than fitted to the altitude statistics, but the final altitudes are expressed relative to it.
assumptions (5)
  • domain assumption NLC fields can be treated as a frozen brightness pattern moving with constant velocity over the two-minute co-addition interval
    Section 3: fields are co-added 'within the two-minute interval with account of this motion', with velocity found by cross-correlation. If the pattern evolves or the velocity varies, co-addition smears features and biases parallax shifts.
  • domain assumption Each NLC fragment can be assigned a single altitude via parallax shift under projection to the H0 a priori layer
    Section 3, Equations (1) to (4): the whole fragment is projected at constant H0 and the shift yields one altitude correction. Vertically extended or multi-layer clouds would produce brightness-weighted effective altitudes that can differ between techniques.
  • domain assumption The simple radiative transfer model of single scattering with refraction, Rayleigh and aerosol extinction, and O3 and NO2 absorption correctly predicts cloud color versus altitude
    Section 5 and Ugolnikov (2023a): the umbral altitude check assumes the model's color-altitude relation, and the residual of about 0.5 km is attributed to multiple scattering, which is not independently measured or modeled in this paper.
  • domain assumption Visible NLC are dominated by large particles near the bottom of the ice layer, so visible triangulation altitudes lie below lidar and satellite profile means
    Section 5, discussion of the 1 to 1.5 km offset relative to lidar and satellite profiles, imported from Baumgarten et al. (2009), Fiedler et al. (2005), and Gerding et al. (2021). The triangulation altitudes are not cross-calibrated against lidar in this paper.
  • standard math Spherical and ellipsoidal Earth geometry with small-angle approximations in Equations (2) to (4)
    Section 3: curvature corrections and approximations are valid for camera altitudes below 1 km and clouds observed high above the horizon, as the paper states; exact analysis is deferred to future mountain or balloon observations.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Five-years Altitude Statistics of Noctilucent Clouds Based on Multi-Site Wide-Field Camera Survey." pith.science (2026). https://pith.science/paper/TW2X4RVU

@misc{pith2026241204951,
  author       = {Pith},
  title        = {Pith review of: Five-years Altitude Statistics of Noctilucent Clouds Based on Multi-Site Wide-Field Camera Survey},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/TW2X4RVU}},
  note         = {Machine review of arXiv:2412.04951}
}
read the original abstract

The results of simultaneous measurements of noctilucent clouds (NLC) position in a number of ground-based locations are presented. Observational data of 14 bright NLC events over 5 years is used for building the altitude maps of cloud fields using triangulation technique updated for multi-location case. Statistical distribution of NLC altitude and its change during the summer season is considered. Mean NLC altitudes are compared with colorimetric technique based on the same data and simple radiation transfer model. This can be used to check the model and estimate the accuracy of single-camera technique of NLC altitude measurements. Results and methods are suggested for net ground-based survey of noctilucent clouds.

Figures

Figures reproduced from arXiv: 2412.04951 by the authors.

Figure 1
Figure 1. shows the distribution of the pattern velocity of the fragments of noctilucent clouds recorded by central camera set. We see that NLC patterns are moving south-westwards, the velocity can reach 100 m/s. While westward motion is typical for summer upper mesosphere, southward velocity component appears in NLC cases, when cold air masses are transported from the polar regions (Fiedler et al., 2011, Gerding et al., 2021… view at source ↗
Figure 2
Figure 2. Graphical scheme of the altitude estimation. [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. NLC field in the evening, July 3, 2023, 19:48 [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Displacement of the NLC field on a priori surface compared the first camera in basic [PITH_FULL_IMAGE:figures/full_fig_p007_4.png]
Figure 5
Figure 5. Figure 5: Altitude maps of NLC for different observ [PITH_FULL_IMAGE:figures/full_fig_p008_5.png]
Figure 6
Figure 6. Figure 6: Brightness- and square-weighted distribution of measured NLC altitudes in 2020-2024. Altitudes of noctilucent clouds are further averaged over the space and time for each twilight. These mean altitudes change during the summer cold mesosphere season, as we can see in …
Figure 8
Figure 8. Figure 8: Comparison of mean triangulation and umbral altitudes of NLC by the data of observations in 2020-2024. Possible problem in long-term trend study of NLC is related with change of measuring techniques and difference of altitudes depending on the method. It is known that …

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Winter Noctilucent Clouds Following Sudden Stratospheric Warming: First Observations

    physics.ao-ph 2025-01 conditional novelty 7.0 of 10

    First reported winter noctilucent clouds at about 70 km altitude appeared over Siberia in December 2024, apparently formed by mesospheric cooling during a sudden stratospheric warming.

Reference graph

Works this paper leans on

34 extracted references · 23 canonical work pages · cited by 1 Pith paper

  1. [1]

    Methods and observa tions. J. Geophys. Res. Atmos. 119, 9324–9337. https://doi.org/10.1002/2014JD021832. Berger, U., Lübken, F.-J.,

    work page doi:10.1002/2014jd021832

  2. [12]

    Updated PMC tr ends derived from SB UV data. J. Geophys. Res. 120, 2140-2166. https://doi.org/10.1002/2014JD022253. Dubietis, A., Dalin, P., Balciunas, R., Černis, K., Pertsev, N., Sukhodoev, V., Perminov, V., Zalcik, M., Zadorozhny, A., Connors, M., Sc hofield, I., McEwan, T., McEachran, I., Frandsen, S., Hansen, O., Andersen, H., Grønne, J., Melnikov, D...

    work page doi:10.1002/2014jd022253

  3. [13]

    Appl Opt

    Noctilucent clouds: modern ground-based photographic observations by a digital camera network. Appl Opt. 50, F72- F79. https://doi.org/10.1364/AO.50.000F72. Fiedler, J., Baumgarten, G., von Cossart, F.,

    work page doi:10.1364/ao.50.000f72

  4. [16]

    NLC and the background atmosphere above ALOMAR. Atm. Chem. Phys. 11, 5701-5717. http://doi.org/10.5194/acp-11-5701-2011. Gadsden, M., Schröder, W.,

    work page doi:10.5194/acp-11-5701-2011 2011

  5. [17]

    On the unusually bright and frequent noc tilucent clouds in summer 2019 ab ove Northern Germany. J. Atmos. Sol. Terr. Phys. 217, 105577. https://doi.org/10.1016/j.jastp.2021.105577. Jesse O.,

    arXiv 2019

  6. [18]

    Microphysical parameters of mesospheric ice clouds derived from calibrated observations of polar mesosphere summ er echoes at Bragg wave lengths of 2.8 m and 30 cm. J. Geophys. Res. 115, D00I13. https://doi.org/10.1029/2009JD012271,

    doi:10.1029/2009jd012271

  7. [21]

    Seasonal and latitudinal variation of noctilucent cloud altitudes. Geophys. Res. Lett. 35, L06801, http://dx.doi.org/10.1029/2007GL032281. Lübken, F.-J., Berger, U., Baumgarten, G.,

    work page doi:10.1029/2007gl032281

  8. [24]

    J. Geophys. Res. Atmos. 127, D036767. https://doi.org/10.1029/2022JD036767. 13 Pertsev, N., Dalin, P., Perminov, V. , Romejko, V., Dubietis, A., Bal čiunas, R., Černis, K., Zalcik, M.,

    doi:10.1029/2022jd036767

Show all 34 references
  1. [28]

    Small-scale structures in noctilucent clouds observed by lidar. J. Atm. Sol. Terr. Phys. 208, 105384. https://doi.org/10.1016/j.jastp.2020.105384. Suzuki, H., Sakanoi, K., Nishitani, N., Ogawa, T., Ejiri, M.K., Kubota, M., Kinoshita, T., Murayama, Y., Fujiyoshi, Y.,

    2020

  2. [30]

    Retrieval of particle size distribution of polar stratospheric clouds based on wide-angle color and polarization analysis. Plan. Space Sci. 200, 105213. https://doi.org/10.1016/j.pss.2021.105213. Ugolnikov, O.S., 2023a. Altitude and particle size measurements of noctilucent cl...

    2021

  3. [32]

    Is thermospheric long-term cooling due to CO 2 or O 3? Ann. Geophys. 29, 1779–1782. https://www.ann-geophys.net/29/1779/2011/. Von Savigny, C., Petelina, S.V., Karlsson, B., Ll ewellyn, E.J., Degens tein, D.A., Lloyd, N.D., Burrows, J.P.,

    2011

  4. [33]

    Vertical variation of NLC part icle sizes retrieved fr om Odin/OSIRIS limb scattering observations. Geophys. Res. Lett. 32, L07806. https://doi.org/10.1029/2004GL021982. Von Zahn, U. ,

    doi

  5. [34]

    Are noctilucent clouds truly a «miner’s canary» for global change? EOS. Trans. AGU. 84, 261-264. https://doi.org/10.1029/2003EO280001. Von Zahn, U., Baumgarten, G., Berger, U., Fied ler, J., Hartogh, P.,

    doi

  6. [98]

    Rapp, M., Thomas, G.E.,

    https://doi.org/10.1186/1880-5981-66-98. Rapp, M., Thomas, G.E.,

    doi

  7. [182]

    Thomas, G.E., Olivero J.,

    https://doi.org/10.1186/s40623-016-0562-6. Thomas, G.E., Olivero J.,

    doi

  8. [1149]

    Lübken, F.-J., Rapp, M., Strelnikova, I.,

    https://doi.org/10.3390/atmos15101149. Lübken, F.-J., Rapp, M., Strelnikova, I.,

    doi

  9. [1989]

    How will cha nges in carbon dioxide and methane modify the mean structure of the mesosphere and th ermosphere? Geophys. Res. Lett. 16, 1441-1444. https://doi.org/10.1029/GL016i012p01441. Schäfer, B., Baumgarten, G., Fiedler, J.,

    doi

  10. [2003]

    Noctilucent clouds above ALOMAR between 1997 and 2001: Occurrence and properti es. J. Geophys. Res. 108, D8, 8453, https://doi.org/:10.1029/2002JD002419. Fiedler, J., Baumgarten, G., von Cossart, F.,

    1997 doi

  11. [2005]

    Mean diurnal va riations of noctilucent clouds during 7 years of lidar observations at ALOMAR. Ann. Geophys. 23, 1175-1181. https://angeo.copernicus.org/articles/23/1175/2005/angeo-23-1175-2005.pdf. Fiedler, J., Baumgarten, G., Berger, U., Hoffmann, P., Kaifle r, N., Lübken, F.-J.,

    2005

  12. [2007]

    The sensitivity of mesospheric ice layers to atmospheric background temperatures and water vapor. Adv. Space Res. 40, 794-801. https://doi.org/10.1016/j.asr.2007.01.014. Lübken, F.-J., Baumgarten, G., Fiedler, J., Gerding, M., H ӧffner, J., Berger, U.,

    2007 doi

  13. [2008]

    Influence of stratos pheric ozone changes on long-term trends in the meso- and lower thermosphere. J. Atm. Sol-Terr. Phys. 70, 1473-1481. https://doi.org/10.1016/j.jastp.2008.03.024. Bronshten, V.A., Grishin, N.I.,

    2008 doi

  14. [2009]

    The noctilucent cloud (NLC) display during the ECOMA/MASS sounding rocket flights on 3 August 2007: morphology on global to local scales. Ann. Geophys. 27, 953-965. www.ann-geophys.net/27/953/2009/. Baumgarten, G., Fiedler, J., Rapp, M

    2007

  15. [2010]

    On microphysical processes of noctilucent clouds (NLC): observations and modeling of mean and width of the particle size-distribution. Atm. Chem. Phys. 10, 6661-6668. https://doi.org/10.5194/acp-10-6661-2010. Baumgarten, G., Fritts, D.C.,

    2010 doi

  16. [2011]

    Mesospheric temper ature trends at mid-latitudes in summer. Geophys. Res. Lett. 38, L22804. https://doi.org/10.1029/2011GL049528. Berger, U., Lübken, F.-J.,

    doi

  17. [2012]

    Notes on historical aspects on the earliest known observations of noctilucent clouds. Hist. Geo Space Sci. 3, 87-97. https://doi.org/10.5194/hgss-3- 87-2012. Dalin, P., Connors, M., Schofield, I., Dubietis , A., Pertsev, N., Perminov, V., Zalcik, M., Zadorozhny, A., McEwan, T....

    2012 doi

  18. [2013]

    First common volume ground-based and space 12 measurements of the mesosphe ric front in noctilu cent clouds. Geophys. Res. Lett. 40, 6399-6404. https://doi.org/10.1002/2013GL058553. Dalin, P., Perminov, V., Pertsev, N., Romejko, V.,

    doi

  19. [2015]

    Trends in mesosphe ric ice layers in the Northern Hemisphere during 1961-2013. J. Geophys. Res. Atmos. 120, 11277-11298. https://doi.org/10.1002/2015JD023355. Bremer, J., Peters, D.,

    1961 doi

  20. [2016]

    The relationship between polar mesospheric clouds and their background atmo sphere as observed by Odin-SMR and Odin-OSIRIS. Atm. Chem. Phys. 16, 12587-12600. https://doi.org/10.5194/acp-16- 12587-2016. Dalin, P., Pertsev, N., Romejko, V.,

    2016 doi

  21. [2017]

    Analysis of small-scale structures in lidar observations of noctilucent clouds using a patte rn recognition method. J. Atmos. Sol. Terr. Phys. 162, 48-56. http://dx.doi.org/10.1016/j.jastp.2017.04.005. Roble, R.G., Dickinson, R.E.,

    2017 doi

  22. [2018]

    On the anthropoge nic impact on long-term evolution of noctilucent clouds

    On the anthropogenic impact on long-term evolution of noctilucent clouds. On the anthropoge nic impact on long-term evolution of noctilucent clouds. Geophys. Res. Lett. 45, 6681-6689. https://doi.org/10.1029/2018GL077719. Mlynczak, M.G., Hunt, L.A., Garcia, R.R., Harvey, V.L.,...

    doi

  23. [2020]

    Updated long -term trends in mesopause temperature, airglow emissions, and noctilu cent clouds. J. Geophys. Res. Atmos. 125, e2019JD030814. https://doi.org/10.1029/2019JD030814. DeLand, M.T., Thomas, G.E.,

    doi

  24. [2021]

    Trends in the polar summer mesosphere temper ature and pressure altitude from satellite observations. J. Atm. Sol-Terr. Phys. 220, 105650. https://doi.org/10.1016/j.jastp.2021.105650. Baumgarten, G., et al.,

    2021

  25. [2022]

    Cooling and contraction of the mesosphe re and lower thermosphere from 2002 to

    2002

  26. [2024]

    Noctilucent clouds altitude and particle size mapping based on spread observations by ground-based all-sky cameras. J. Atm. Sol. Terr. Phys. 259, 106242. https://doi.org/ 10.1016/j.jastp.2024.106242. Walsh, P.L., Oliver, W.L.,

    2024

Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.