Multi‐diagnostic multi‐model ensemble forecasts of aviation turbulence

Storer, Luke N.; Gill, Philip G.; Williams, Paul D.

doi:10.1002/met.1885

Cited by 6 publications

(2 citation statements)

References 28 publications

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“…Note that TI1 is widely used in many forecast weather centers (e.g., Météo-France, KNMI). The two World Area Forecast Centers (WAFC; London and Washington) also use TI1 as a single diagnostic to provide a global turbulence forecast on a 1.25°× 1.25°grid (Gill, 2014;J.-H. Kim et al, 2018;Storer et al, 2020), and TI1 has been implemented in the graphical turbulence guidance algorithm (Sharman et al, 2006).…”

Section: Choice Of Cat Diagnosticsmentioning

confidence: 99%

Past and Future Trends in Clear‐Air Turbulence Over the Northern Hemisphere

Foudad,

Sanchez‐Gomez,

Jaravel

et al. 2024

JGR Atmospheres

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Clear‐Air Turbulence (CAT) is associated with wind shear in the vicinity of jet streams in upper atmospheric levels. This turbulence occurs in cloudless regions and causes most weather‐related aircraft accidents. Recent studies have shown that in response to climate change, CAT could significantly increase over certain regions as a consequence of strengthening of jet streams. In this study we use several atmospheric reanalyses and coupled model experiments database to evaluate CAT recent and future changes in the Northern Hemisphere. Several CAT diagnostics are computed to assess the sensitivity of the results to different turbulence representations. A significant positive trend in CAT frequency is found in the reanalyses in different Northern Hemisphere regions over the period 1980–2021. The signal‐to‐noise analysis shows that over North Africa, East Asia and Middle East the increase of CAT occurrence in the last decades is likely attributed to the response to anthropogenic forcing. In contrast, over the North Atlantic and North Pacific the response to external forcing is not detectable due to a weak signal to noise ratio related to large internal variability. Future climate projections show that over several Northern Hemisphere regions, CAT is projected to increase with a high model agreement and independently of the CAT diagnostic used. The largest increase in CAT is projected to occur over East Asia. In the North Atlantic, large uncertainty remains due to lack of model agreement and different results between the various CAT diagnostics.

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Section: Choice Of Cat Diagnosticsmentioning

confidence: 99%

Past and Future Trends in Clear‐Air Turbulence Over the Northern Hemisphere

Foudad,

Sanchez‐Gomez,

Jaravel

et al. 2024

JGR Atmospheres

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“…GTG has now been updated to forecast MWT in addition to CAT (Sharman and Pearson, 2017). Recently, probabilistic forecasts of aviation turbulence, generated using ensemble prediction systems, have been tested as a potentially more informative alternative to traditional deterministic forecasts (Gill and Buchanan, 2014; Storer et al ., 2019a; 2020).…”

Section: Introductionmentioning

confidence: 99%

Can a climate model successfully diagnose clear‐air turbulence and its response to climate change?

Williams

Storer

2022

Quart J Royal Meteoro Soc

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Atmospheric turbulence causes the majority of weather-related aircraft accidents. Climate models project large increases in clear-air turbulence as the jet streams become more sheared in response to climate change. However, climate models have coarser resolutions than the numerical weather prediction models that are used to forecast clear-air turbulence operationally, raising questions about their suitability for this purpose. Here we provide the first rigorous demonstration that climate models are capable of successfully diagnosing clear-air turbulence and its response to climate change. We use an ensemble of seven clear-air turbulence diagnostics to compare 38 years of historic turbulence diagnosed from climate model simulations and high-resolution reanalysis data. We find that the differences in turbulence between the climate model and reanalysis data are much smaller than the spread between the diagnostics. When using a climate model to calculate the probabilities (and their temporal trends) of encountering clear-air turbulence of any strength, at any flight cruising level, and in any season, we find that most of the uncertainty stems from the turbulence diagnostics rather than the climate model. These results confirm the suitability of climate models for the task of producing future clear-air turbulence projections. The turbulence increases are generally larger when diagnosed from the reanalysis data than the climate model, suggesting that previous quantifications from climate models of the response of clear-air turbulence to climate change may be underestimates. Our results show that the key to reducing uncertainty in projections of future clear-air turbulence lies in improving the clear-air turbulence diagnostics rather than the climate models.

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