Coupling between air travel and climate

Abstract

The airline industry closely monitors the midlatitude jet stream for short-term planning of flight paths and arrival times. In addition to passenger safety and on-time metrics, this is due to the acute sensitivity of airline profits to fuel cost. US carriers spent US$47 billion on jet fuel in 2011, compared with a total industry operating revenue of US$192 billion. Beyond the timescale of synoptic weather, the El Niño/Southern Oscillation (ENSO), Arctic Oscillation (AO) and other modes of variability modulate the strength and position of the Aleutian low and Pacific high on interannual timescales, which influence the tendency of the exit region of the midlatitude Pacific jet stream to extend, retract and meander poleward and equatorward1,2,3. The impact of global aviation on climate change has been studied for decades owing to the radiative forcing of emitted greenhouse gases, contrails and other effects4,5. The impact of climate variability on air travel, however, has only recently come into focus, primarily in terms of turbulence6,7. Shifting attention to flight durations, here we show that 88% of the interannual variance in domestic flight times between Hawaii and the continental US is explained by a linear combination of ENSO and the AO. Further, we extend our analysis to CMIP5 model projections to explore potential feedbacks between anthropogenic climate change and air travel.

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Figure 1: Overview map and flight-time variability.
Figure 2: Atmospheric correlations.
Figure 3: Flight time, wind and climate.
Figure 4: Round-trip flying time residual.
Figure 5: Projected trends in mean flight-level winds.

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Acknowledgements

The authors thank B. Carmichael and B. Sharman of the National Center for Atmospheric Research Aviation Applications Program, G. Compo of the Cooperative Institute for Research in the Environmental Sciences, and D. Battisti of the University of Washington Department of Atmospheric Sciences for helpful discussions. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP5, and we thank the climate modelling groups for producing and making available their model output. For CMIP5, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. CMIP5 model output data were acquired from the WHOI CMIP5 Community Storage Server, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA. NCEP/NCAR Reanalysis data were provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, and acquired from their website at http://www.esrl.noaa.gov/psd. Domestic flight data were acquired from the TranStats website, maintained by the Bureau of Transportation Statistics, Research and Innovative Technology Administration (RITA), US Department of Transportation (http://www.transtats.bts.gov). Airline industry and business statistics were gathered from the MIT Global Airline Industry Program, Airline Data Project (http://web.mit.edu/airlinedata/www/Revenue&Related.html), Air Transport Action Group (http://aviationbenefits.org/media/26786/ATAG__AviationBenefits2014_FULL_LowRes.pdf), and National Air Traffic Controllers Association (NATCA). Emissions coefficients were gathered from the US Energy Information Administration (http://eia.gov/environment/emissions/co2_vol_mass.cfm). K.B.K. acknowledges support from the Strategic Environmental Research and Development Program, the WHOI Oceans and Climate Change Institute, the Alfred P. Sloan Foundation, and Microsoft Research.

Author information

K.B.K. and H.C.B. jointly conceived the study. K.B.K. conducted the analyses and wrote the paper with input from all authors.

Correspondence to Kristopher B. Karnauskas.

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The authors declare no competing financial interests.

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Karnauskas, K., Donnelly, J., Barkley, H. et al. Coupling between air travel and climate. Nature Clim Change 5, 1068–1073 (2015). https://doi.org/10.1038/nclimate2715

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