the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 Mar 2026
TurboMeter: an attribution framework for extreme aviation turbulence events in a changing climate
Abstract. Understanding the influence of climate change on aviation turbulence is critical for ensuring flight safety and developing adaptive strategies. Thus, we present TurboMeter, an attribution framework that combines reanalysis data with a conditional attribution methodology to assess whether the present-day atmosphere, under similar large-scale synoptic configurations, can lead to stronger aviation turbulence than in a cooler historical climate. Turbulence diagnostics – namely the Turbulence Index (TI1) and its two components, vertical wind shear and total deformation – are used to characterize cruise-level turbulence events reported in 2024 over four key flight corridors: the North Atlantic, the North Pacific, East Asia, and the Contiguous United States (CONUS).
Our results highlight enhanced vertical wind shear and deformation in the present period, with increases ranging from 20 % to 50 % relative to historical analogues. Attribution diagnostics indicate that all events are at least partially influenced by anthropogenic climate change, with approximately 68 % (2142 of 3123 reports) classified as being mainly strengthened by anthropogenic forcing, particularly over the North Atlantic, CONUS, and East Asia. A smaller but non-negligible share (about 32 %) is associated with a combination of climate change and natural variability. In contrast, over the North Pacific, the majority of events (81 %) fall into this latter category, highlighting a comparatively stronger role of internal climate variability in that region, consistent with previous studies showing a regionally dependent interplay between anthropogenic forcing and internal climate variability. These findings are further supported by the spatial patterns of increased turbulence-favourable conditions and underscore the growing relevance of climate-informed diagnostics for aviation risk planning by considering both anthropogenic climate change and internal climate variability in projecting future turbulence risk.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2026-1178', Anonymous Referee #1, 02 Jun 2026
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AC1: 'Reply on RC1', Tommaso Alberti, 04 Jun 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-1178/egusphere-2026-1178-AC1-supplement.pdf
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AC1: 'Reply on RC1', Tommaso Alberti, 04 Jun 2026
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RC2: 'Comment on egusphere-2026-1178', Anonymous Referee #2, 06 Jul 2026
Recommendation: Reject / Major Revision
I recommend rejection or, at minimum, major revision. The topic is timely and potentially important, but the present manuscript overstates the interpretation of the aircraft turbulence reports and relies on a synoptic analogue framework that is not sufficient to support the paper’s main attribution claims. The title and conclusions are stronger than what the analysis can justify.
1. Misuse of EDR ≥ 0.2 as “extreme turbulence”
The manuscript defines the event sample using automated in situ aircraft reports with EDR ≥ 0.2 m²/³ s⁻¹, describing these as moderate-or-greater events and using them to frame “extreme aviation turbulence” in the title and throughout the paper. However, EDR values higher than 0.2 from in situ AMDAR/ACARS aircraft data cannot automatically be linked to, or labeled as, “extreme” turbulence. The authors should revise the title and terminology and should more carefully follow previous studies on EDR reporting and intensity classification. The current use of EDR ≥ 0.2 as the basis for “extreme turbulence” is misleading and needs substantial correction.
Relevant references:
Sharman, R., L. B. Cornman, G. Meymaris, J. Pearson, and T. Farrar, 2014: Description and derived climatologies of automated in situ eddy-dissipation-rate reports of atmospheric turbulence. Journal of Applied Meteorology and Climatology, 53, 1416–1432. https://doi.org/10.1175/JAMC-D-13-0329.1Kim, S.-H., H.-Y. Chun, J.-H. Kim, R. D. Sharman, and M. Strahan, 2020: Retrieval of eddy dissipation rate from derived equivalent vertical gust included in Aircraft Meteorological Data Relay (AMDAR). Atmospheric Measurement Techniques, 13, 1373–1385. https://doi.org/10.5194/amt-13-1373-2020.
2. Synoptic analogues cannot guarantee the same turbulence-generation processes
A second major concern is the assumption that similar 500 hPa geopotential-height analogues can meaningfully represent the full downscaling pathway from synoptic flow to small-scale turbulence affecting cruising aircraft. The method identifies historical analogues using Z500 patterns and compares turbulence diagnostics between past and present periods.
This approach may be useful for broad circulation context, but it does not guarantee the same mesoscale or microscale processes responsible for aircraft-scale turbulence. Numerous high-resolution modeling studies have shown that severe aviation turbulence depends on localized mechanisms such as gravity-wave breaking, jet-front interactions, near-cloud processes, and mesoscale convective influences. The authors should substantially weaken or reframe their attribution claims and more fully consider previous high-resolution modeling studies from both U.S. and Korean scientists.
Relevant references:
Trier, S. B., R. D. Sharman, R. G. Fovell, and R. G. Frehlich, 2010: Numerical simulation of radial cloud bands within the upper-level outflow of an observed mesoscale convective system. Journal of the Atmospheric Sciences, 67, 2990–2999. https://doi.org/10.1175/2010JAS3531.1.Trier, S. B., R. D. Sharman, D. Muñoz-Esparza, and T. P. Lane, 2020: Environment and mechanisms of severe turbulence in a midlatitude cyclone. Journal of the Atmospheric Sciences, 77, 3869–3889. https://doi.org/10.1175/JAS-D-20-0095.1.
Trier, S. B., R. D. Sharman, D. Muñoz-Esparza, and T. L. Keller, 2022: Effects of distant organized convection on forecasts of widespread clear-air turbulence. Monthly Weather Review. https://doi.org/10.1175/MWR-D-22-0077.1.
Kim, S.-H., H.-Y. Chun, D.-B. Lee, J.-H. Kim, and R. D. Sharman, 2021: Improving numerical weather prediction-based near-cloud aviation turbulence forecasts by diagnosing convective gravity wave breaking. Weather and Forecasting, 36, 1735–1757.
3. Convective systems are not sufficiently considered
Third, the manuscript treats many events primarily as clear-air/jet-related turbulence events, but many extreme or severe turbulence encounters are directly or indirectly associated with convective systems, and the separation between natural variability and anthropogenic forcing is not straightforward in such cases. The manuscript itself acknowledges that its framework could be extended in the future to convectively induced turbulence, mountain-wave turbulence, and other turbulence types, which underscores a key limitation of the current analysis. The authors should not present broad attribution conclusions without explicitly addressing convective contamination, near-cloud turbulence, convective outflow, and convectively induced gravity-wave processes.
Relevant references:
Trier, S. B., and R. D. Sharman, 2009: Convection-permitting simulations of the environment supporting widespread turbulence within the upper-level outflow of a mesoscale convective system. Monthly Weather Review, 137, 1972–1990. https://doi.org/10.1175/2008MWR2770.1Baek, S.-H., Kim, J.-H., Kim, S.-H., Lee, Y., Noh, Y.-J., and Lee, S.-M., 2024: Characteristics of convectively induced turbulence in East Asia using geostationary Korea multi-purpose Satellite-2A (GK-2A) and in situ aircraft data. Journal of Geophysical Research: Atmospheres, 129, e2024JD041671. https://doi.org/10.1029/2024JD041671
Kim, J.-H., Park, J.-R., Kim, S.-H., Kim, J., Lee, E., Baek, S., and Lee, G., 2021: A detection of convectively induced turbulence using in situ aircraft and radar spectral width data. Remote Sensing, 13(4), 726. https://doi.org/10.3390/rs13040726
4. Mountain-wave turbulence is insufficiently addressed
Fourth, the treatment of mountain-wave turbulence is inadequate. Mountain-wave turbulence is an important source of upper-tropospheric and lower-stratospheric turbulence, especially over the western United States and other mountainous regions. Such processes cannot be fully captured by ERA5 fields and synoptic analogue matching alone. The CONUS case, for example, includes many reports over North America, but the manuscript does not sufficiently distinguish jet-related CAT from mountain-wave-related turbulence or other terrain-induced processes . The authors should explicitly discuss the limits of ERA5 and Z500-based analogue methods for diagnosing mountain-wave turbulence and should incorporate prior modeling and forecasting studies on this process.
Relevant references:
Shin, Y., J.-H. Kim, R. D. Sharman, T. L. Keller, S. B. Trier, and J. D. Doyle, 2026: Generation mechanisms of a mountain wave turbulence event in the upper troposphere and lower stratosphere over Alaska, USA. Monthly Weather Review. https://doi.org/10.1175/MWR-D-25-0166.1Kim, J.-H., R. D. Sharman, S. Benjamin, J. Brown, S.-H. Park, and J. Klemp, 2019: Improvement of mountain wave turbulence forecast in NOAA’s Rapid Refresh (RAP) model with hybrid vertical coordinate system. Weather and Forecasting, 34(6), 773–780.
Park, S.-H., J. Klemp, and J.-H. Kim, 2019: Hybrid mass coordinate in WRF-ARW and its impact on upper-level turbulence forecasting. Monthly Weather Review, 147(3), 971–985. https://doi.org/10.1175/MWR-D-18-0334.1
5. East Asia and Pacific turbulence mechanisms are oversimplified
Fifth, the interpretation of East Asia and the Pacific is too simplified. The manuscript links East Asian turbulence mainly to jet-stream intensification and deformation/shear along the East Asian jet . However, in East Asia and the western Pacific, high turbulence-index values in ERA5 are not simply related to the jet stream alone. They often result from complicated combinations of typhoons, tropical cyclone outflow, upper-level frontogenesis, vertical shear, deformation, and convective or near-cloud processes. Therefore, the manuscript should avoid attributing high TI, VWS, and DEF values only to jet-stream changes and should consider previous regional studies on East Asian and western Pacific turbulence mechanisms.
Relevant references:
Lee, J. H., J.-H. Kim, S. B. Trier, R. D. Sharman, and J. D. Doyle, 2025: Generation mechanisms of near-cloud turbulence events in the upper-level outflow of Tropical Cyclone Hagibis. Monthly Weather Review, 153, 521–542. https://doi.org/10.1175/MWR-D-24-0116.1Kim, J.-H., H.-Y. Chun, R. D. Sharman, and S. B. Trier, 2014: The role of vertical shear on aviation turbulence within cirrus bands of a simulated western Pacific cyclone. Monthly Weather Review, 142(8), 2794–2813.
Kim, J.-H., and H.-Y. Chun, 2012: A numerical simulation of convectively induced turbulence above deep convection. Journal of Applied Meteorology and Climatology, 51, 1180–1200.
Kim, J.-H., and H.-Y. Chun, 2010: A numerical study of clear-air turbulence encounters over South Korea on 2 April 2007. Journal of Applied Meteorology and Climatology, 49, 2381–2403.
6. Main methodological limitation: Z500 cannot represent the full turbulence pathway
The central methodological issue is that 500 hPa geopotential-height fields cannot represent the full synoptic-to-mesoscale story linking atmospheric circulation to turbulence reports. The paper’s framework may identify broad circulation analogues, but it cannot by itself establish the physical pathway to aircraft-scale turbulence. This limitation is especially important because the paper makes strong claims that approximately 68% of events were mainly strengthened by anthropogenic forcing . These claims require much stronger validation against observed EDR intensity, turbulence type, convective proximity, cloud environment, mountain-wave environments, and high-resolution model diagnostics.
Overall, the manuscript addresses an important topic, but the current analysis is not sufficient to support the strong wording in the title, abstract, and conclusions. I recommend reject or major revision, with substantial revision required in the event definition, terminology, physical interpretation, literature review, and attribution methodology.
Citation: https://doi.org/10.5194/egusphere-2026-1178-RC2
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“TurboMeter: an attribution framework for extreme aviation turbulence events in a changing climate” by Tommaso Alberti, Davide Faranda, Mohamed Foudad, Erika Coppola, Lia Rapella, Rachel Burbidge, Miguel A.C. Teixeira, and Paul Williams
Recommendation: Reject
General comments
This manuscript introduced an analogue-based attribution framework, TurboMeter, which had been developed to assess relative contributions of anthropogenic climate change and natural variability on aviation turbulence in changing climate. The key procedures to the framework are, first, select turbulence-prone days in an independent time frame (a one year period of 2024 in this study) using automated in-situ turbulence observations from commercial aircraft; second, characterize the synoptic-scale patterns of the selected turbulence days using the 500-hPa geopotential height in ERA5 as a single metric; third, for each of the selected turbulence days, identify analogues in both past (1950–1986) and present (1987–2023) climates that have similar 500-hPa geopotential height patterns with the selected turbulence event; and then last, compute and compare a single turbulence index (TI1) and its components (vertical wind shear (VWS) and deformation (DEF)) to assess if there are any changes between the past- and present-climate analogues despite the similar 500-hPa geopotential height patterns.
I agree to the necessity of assessing the attribution of anthropogenic climate change to aviation turbulence, separately from the attribution of natural variability. However, I have several major concerns about the algorithms on which the TurboMeter framework is built on, i.e., the characterization of the synoptic-scale patterns and the case selection, in particular. In brief, I doubt if using the 500-hPa geopotential height alone is sufficient to characterize synoptic-scale patterns and identify analogues, especially characterizing the synoptic conditions that are critical to generation, maintenance, and intensification of aviation turbulence; in addition, the case selection was made based on the EDR threshold only, without separating sources of turbulence (e.g., clear-air turbulence, mountain-wave turbulence, convectively induced turbulence), which seems to make it even harder to justify using the 500-hPa geopotential height alone as a single metric to identify synoptic-scale patterns responsible for the selected turbulent days.
Besides my concerns on the TurboMeter framework, the analysis of the TurboMeter output needs to be improved to provide more in-depth explanation of physical mechanisms supporting the output. The result plots in the manuscript focused on 500-hPa geopotential height, TI1, VWS and DEF. However, the main texts mentioned and relied heavily on changes in and patterns of the jet stream in explaining the TurboMeter output, while the jet stream and other synoptic-scale patterns were never shown or compared in the manuscript. I think the analysis needs to be improved by explicitly showing the differences and similarities in jets, troughs, and other possible sources of turbulence between the past and current climate analogues.
While I agree to the motivation, objective, and necessity of this study, I have major concerns about the methodology that would need significant revisions and could lead to significant changes in the results, as well as lack of in-depth analysis on physical mechanisms explaining the TurboMeter output. Therefore, my recommendation is to reject this manuscript to allow the authors sufficient time to work on their revisions but strongly encourage to re-submit the manuscript.
Major comments
1. This study used a single metric of 500-hPa geopotential height to characterize synoptic-scale patterns of turbulence-prone days in 2024 and then to identify analogues (i.e. days with similar synoptic-scale patterns) in past (1950–1986) and present (1987–2023) climates. Then, based on the comparison between the past and present climate analogues, the contribution of anthropogenic climate change was determined; that is, if the characteristics of TI1 are found differently between the past- and present-climate analogues despite similar synoptic-scale patterns, their differences can be attributed to anthropogenic climate change.
For this analogue-based attribution framework works, it should be validated that the 500-hPa geopotential height is a good metric to characterize synoptic-scale patterns that generate, maintain, and intensity turbulence in the selected turbulent days. However, this study does not provide that critical validation of the metric (500-hPa geopotential height). This validation can be done by comparing the weather patterns between the analogues for each case. Do the past and climate analogues selected based on the 500-hPa geopotential height have similar synoptic weather patterns (i.e., jet, trough, baroclinicity, convection, etc.)? Or do they just happen to have similar 500-hPa geopotential height patterns but show very different weather conditions among the analogues? Without such a validation of the use of 500-hPa geopotential height as a metric to characterize synoptic-scale patterns, it is hard to justify the outcomes of the attribution method based on the metric.
2. In this study, turbulence-prone days were selected based on automated in-flight turbulence reports using an EDR threshold (EDR ≥ 0.2), without distinguishing the primary mechanisms and/or sources of turbulence. Turbulence can be generated by diverse sources, which include but are not limited to clear-air turbulence in the vicinity of jet, trough, tropopause etc. in the absence of clouds; mountain-wave turbulence due to breaking waves; convectively induced turbulence associated with moist instabilities, intense updrafts/downdrafts, outflows etc. This can be especially problematic as relative contributions of turbulence sources may differ among the four flight corridors (i.e., North Atlantic, North Pacific, East Asia, and CONUS), therefore may impact the differences in the TurboMeter outcomes among them. I think it is needed to validate that the selected turbulence days in 2024 and their past and present analogues are associated with the same source of turbulence; for example, if a selected case in 2024 is clear air turbulence, their analogues should be clear-air turbulence days as well. Also, the turbulence index TI1 and its components seem more appropriate for clear-air turbulence than for mountain-wave turbulence or convectively induced turbulence.
Such complexity in the possible source of turbulence is another reason why I don’t think the 500-hPa geopotential height alone is a good metric to identify similar synoptic patterns and analogues. Do the analogies have similar synoptic patterns in terms of jets and troughs, background atmospheric conditions for wave breaking, and initiation and development of convection, which all are synoptic conditions for turbulence generation?
3. Overall, I think the result section needs revisions in terms of plots and texts both.
The plots presented focused on the TurboMeter outputs, including 500-hPa geopotential height, TI1, VWS, and DEF. However, neither the main text nor the figure caption mentioned what vertical levels the TI1, VWS, and DEF plots are for. If those turbulence parameters are presented for a 500-hPa level, I think it needs to be updated to an upper level, for example 300 hPa, which is in typical cursing altitude range and is of great interest in aviation turbulence.
For the main texts, the differences in turbulence between the past and present climates, as well as their difference among the four flight corridors, were mainly explained in terms of the jet dynamics. However, this manuscript never showed how the actual synoptic-scale patterns look like including jets, temperature patterns, etc., to support their arguments. I think the analysis needs to be improved by explicitly showing the differences and similarities in jets, troughs, and other possible sources of turbulence between the past and current climate analogues.