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Impact of climate change on clear air turbulence for aviation

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Required Education : Master ou Ecole d'ingénieur
Start date : 1 September 2020
Mission duration : 3 ans
Deadline for applications : 28 August 2020
Salary : 2475 Euros brut mensuel

Context:

In the context of the CERFACS / AIRBUS / Météo-France collaboration and the “Climate and aviation” application axis, the impact of climate change on atmospheric turbulence at altitude (in other words, clear air turbulence or CAT) has been established as a priority topic. Indeed, turbulence at altitude is responsible for a large number of incidents on an airplane in flight (Clark et al. 2000). Commercial flights around the world record hundreds of CAT incidents every year, which can result in passenger injuries and aircraft damage, and consequently in economic loss. In addition, areas of turbulence in clear air cannot be detected by measuring instruments (satellites and / or radars), and therefore they are very difficult to avoid by airplanes. In general, the areas characterized by a higher probability of occurrence of CAT are located at mid-latitudes, at the level of strong zonal currents from West to East located at altitude (about 10 km), called “jet stream” (Reiter and Nania, 1964). Jet currents are characterized by very strong winds at altitude associated with significant wind shear. From observational data and simulations with climate models, recent studies have shown that in response to global warming, the jet current could intensify and move towards the poles in both hemispheres (Shaw et al. 2016 ). However, strong uncertainties persist, due in particular to the high internal variability of the climate at mid latitudes. Recently, studies have shown that the global warming induced by the increase in greenhouse gases (notably CO2) would induce changes in the CAT in the transatlantic corridor. These changes would result in an intensification of the CAT in winter between 10 and 40%, with an increase in extreme cases (Williams and Joshie, 2013; Williams 2016). These results could have strong implications for aviation, including aircraft safety in commercial flights.

However, the standard resolution of global climate models, of around 100 km, does not allow a correct representation of the atmospheric turbulence of the mesoscale and the changes in intensity of the extreme CAT episodes could be underestimated. The main objective of this proposal, in collaboration with Météo-France and AIRBUS, is to estimate turbulence change projections in clear air (CAT) using the set of simulations carried out with the new generation of climate models (CMIP6) and a dynamic downscaling (nested models of the large scale – mesh of the order of 100 km – up to the meso-scale (kilometric mesh) or even to the micro-scale (scale from simulation to large scales / LES – mesh of the order of 10 m).

Program:

The PhD will be carried out in two phases. The first phase will consist in analyzing recent climate scenarios resulting from the CMIP6 climate models in order to provide a global vision of CAT changes. The second phase will tackle the problem of downscaling by selecting case studies of high CAT and by extrapolating them in future climatic conditions.

  • Phase 1) Study of CAT changes with climate models and evaluation of uncertainties

First, we will make a selection of the most relevant indicators to characterize the CAT using climatic simulations and atmospheric reanalyses. Some of these indicators are proposed in the work of Williams and Joshie (2013). This will allow us to assess climate models in terms of performance to represent the CAT in different regions of the globe. To reduce the uncertainty associated with climate models, it is envisaged to use techniques similar to those developed in Sanderson et al. (2017) to make a selection of the most efficient models, which will allow a more relevant representation of the uncertainty envelope of all the CMIP6 models. Using climate projections and taking into account several scenarios, we will be able to assess the evolution of CAT phenomena on a global scale, in terms of change in frequency and intensity of CAT events.

  • Phase 2) Study of the impact on the aircraft and “futurization” of the case studies

In a second step, we will focus on a selection of episodes of strong CAT made in the previous step. The choice of study cases will be made togeher with AIRBUS in order to choose the most relevant ones. Then we will carry out the “futurization” of these episodes, in other words, the extrapolation of an episode that marked in the past in a future climate background, in order to quantify whether future climatic conditions have an impact on these cases. To better assess the impacts at the aircraft scale, we will develop a downscaling approach, to go from the 100 km scale to the mesoscale (1 km) or even to the micro-scale (10 m) (Moeng et al. 2007, Wiersema et al. 2020). This will consist in performing nested simulations with different atmosphere models (Figure 1) to gradually reach the desired spatial scale: as the scales decrease, the models will have finer and finer spatio-temporal resolution and an increasingly accurate modeling of the physical processes involved (this nesting of models will allow in particular to move from turbulence indicators to an explicit resolution of turbulence in “large scale simulation” mode).
In close collaboration with Météo-France, we will set up a modeling chain using several atmosphere models: ARPEGE (100 km), ALADIN-Climat (12 km), AROME-Climat or Méso-NH (about 1.3 km). Then we will be able to reach the micro-scale with the Meso-NH model (Lac et al. 2018, Joulain et al. 2020). This will require an important modeling effort and several researchers from CERFACS and CNRM will be involved.

Figure 1: Descending approach to reach LES resolution (10 m) from the spatial resolution of standard climate models.

Bibliography:

  1. Clark, T. L. et al. Origins of aircraft-damaging clear-air turbulence during the 9 December 1992 Colorado downslope windstorm: Numerical simulations and comparison with observations. J. Atmos. Sci. 57, 1105–1131 (2000).
  2. Joulin, P.-A., M. L. Mayol, V. Masson, F. Blondel, Q. Rodier, M. Cathelain, and C. Lac, The Actuator Line Method in the meteorological LES model Meso-NH to analyze the Horns Rev 1 wind farm photo case, Front. Earth Sci., 7, 350, 2020.
  3. Lac, C. et al. Overview of the Meso-NH model version 5.4 and its applications, Geosci. Model Dev., 11, 1929–1969 (2018).
  4. Moeng, C.-H., J. Dudhia, J. Klemp, and P. Sullivan. Examining two-way grid nesting for large eddy simulation of the PBL using the WRF Model. Mon. Wea. Rev., 135, 2295–2311 (2017).
  5. Reiter, E. R. & Nania, A. Jet-stream structure and clear-air turbulence (CAT). J. Appl. Meteorol. 3, 247–260 (1964)
  6. Sanderson, B. M., Wehner, M., and Knutti, R. Skill and independence weighting for multi-model assessments, Geosci. Model Dev., 10, 2379–2395 (2017).
  7. Shaw, T. A., Barpanda, P., & Donohoe, A. A moist static energy framework for zonal‐mean storm‐track intensity. Journal of the Atmospheric Sciences, 75(6), 1979–1994 (2018).
  8. Williams P. D. and Joshi M. M. Intensification of winter transatlantic aviation turbulence in response to climate change. Nat. Clim. Change, 3, 644–8 (2013)
  9. Williams P. Transatlantic flight times and climatic change, Environmental Research Letters (2016)
  10. Wiersema, D.J., K.A. Lundquist, and F.K. Chow. Mesoscale to Microscale Simulations over Complex Terrain with the Immersed Boundary Method in the Weather Research and Forecasting Model. Mon. Wea. Rev., 148, 577–595 (2020).

Contacts: