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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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
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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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- 1
“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.