Mitigating the Impact of Adverse Weather on Aviation

Chapter
Part of the Research Topics in Aerospace book series (RTA)

Abstract

Weather has a significant impact on the safety and efficiency of air traffic during all phases of flight. Especially information on adverse weather must be tailored to the user’s needs, easy to understand, self-explaining and clear in its message. DLR-IPA has developed a concept and tools to detect, track and predict hazardous weather elements and provide this information in simple unambiguous form to controllers and pilots. It has been demonstrated that these products make a significant contribution to raising the safety and efficiency of the air transport system.

Keywords

Situational Awareness Thunderstorm Activity Winter Weather False Alarm Ratio Weather Hazard 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Eurocontrol Performance Review Commission (2011) Performance Review Report 2010. Available at http://www.eurocontrol.int/prc/public/standard_page/doc_prr.html
  2. Forster C, Tafferner A (2009) An integrated user-oriented weather forecast system for air traffic using real-time observations and model data. In: Proceedings of the European Air and Space Conference (CEAS), Manchester, UK, 26–29 October 2009Google Scholar
  3. Forster, C., and A. Tafferner, 2012: Nowcasting thunderstorms for Munich airport. The DLR Project Wetter & Fliegen. In: Gerz T, Schwarz C (eds.) Final research report DLR-FB 2012-02, pp 32–45Google Scholar
  4. Gerz T, Schwarz C (eds.) (2012) The DLR Project Wetter & Fliegen. Final research report DLR-FB, vol 2012-02, p 280Google Scholar
  5. GoP (2001) European Aeronautics: a vision for 2020–Meeting society’s needs and winning global leadership. Report of the group of personalities, European Commission, January 2001, p 26Google Scholar
  6. Hauf T, Leykauf H, Schumann U (eds) (2004) Luftverkehr und Wetter, Statuspapier, DLR-Mitteilungen, vol 2004-02, p 57Google Scholar
  7. Kober, K., Tafferner, A.: Tracking and nowcasting of convective cells using remote sensing data from radar and satellite. Meteorol. Z. 1(18), 75–84 (2009). doi: 10.1127/0941-2948/2009/359 CrossRefGoogle Scholar
  8. Leifeld C (2004) Weiterentwicklung des nowcastingsystems ADWICE zur Erkennung vereisungsgefährdeter Lufträume, Berichte des Deutschen Wetterdienstes, Offenbach am Main, vol 224, p 118Google Scholar
  9. Leighton Q (2006) Modeling and simulation needs for next generation air transportation system research. AIAA modeling and simulation technologies conference and exhibit, Keystone, Colorado, 21–24 August 2006. AIAA 2006-6109, pp 1–8Google Scholar
  10. Pradier, S., Forster, C., Heesbeen, W.W.M., Pagé, C., Sénési, S., Tafferner, A., Bernard-Bouissières, I., Caumont, O., Drouin, A., Ducroq, V., et al.: Description of convective-scale numerical weather simulation use in a flight simulator within the Flysafe project. Meteorol Atmos Phys (2009). doi: 10.1007/s00703-008-0317-4 Google Scholar
  11. Schraff C, Reich H, Rhodin A, Potthast R, Blahak U, Stephan K, Zeng Y, Epperlein D, Leuenberger D, Weusthoff T et al. (2011) COSMO priority project KENDA for Km-scale ensemble-based data assimilation. 9th SRNWP workshop on non-hydrostatic modelling, Bad Orb, 16–18 May 2011Google Scholar
  12. Sénési S, Guillou Y, Tafferner A, Forster C (2009) Cb nowcasting in FLYSAFE: improving flight safety regarding thunderstorm hazards. WMO symposium on nowcasting, Whistler, BC, Canada, 30 August–4 September 2009Google Scholar
  13. Tafferner, A., Hauf, T., Leifeld, C., Hafner, T., Leykauf, H., Voigt, U.: ADWICE–advanced diagnosis and warning system for aircraft icing environments. Weather. Forecast 18(2), 184–203 (2003)ADSCrossRefGoogle Scholar
  14. Tafferner, A., Forster, C., Hagen, M., Keil, C., Zinner, T., Volkert, H.: Development and propagation of severe thunderstorms in the upper Danube catchment area: towards an integrated nowcasting and forecasting system using real-time data and high-resolution simulations. Meteorol. Atmos. Phys. 101, 211–227 (2008a). doi: 10.1007/s00703-008-0322-7 ADSCrossRefGoogle Scholar
  15. Tafferner A, Forster C, Sénési S, Guillou Y, Tabary P, Laroche P, Delannoy A, Lunnon B, Turb D, Hauf T et al. (2008b) Nowcasting thunderstorm hazards for flight operations: the CB WIMS approach in FLYSAFE. 26th Congress of the International Council of the Aeronautical Sciences, Anchorge, AK (USA), 14 September 2008, pp 1–10Google Scholar
  16. Tafferner A, Forster C, Hagen M, Hauf T, Lunnon B, Mirza A, Guillou Y, Zinner T (2010) Improved thunderstorm weather information for pilots through ground and satellite based observing systems. 14th conference on aviation, range, and aerospace meteorology, 90th AMS annual meeting, 17–21 January 2010, AtlantaGoogle Scholar
  17. Tafferner A, Keis F (2012) Nowcasting winter weather at Munich airport. In: The DLR Project Wetter & Fliegen, Final research report DLR-FB 2012-02, pp 46–57Google Scholar
  18. Zinner, T., Mannstein, H., Tafferner, A.: Cb-TRAM: tracking and monitoring severe convection from onset over rapid development to mature phase using multi-channel Meteosat-8 SEVIRI data. Meteorol. Atmos. Phys. 101,   (2008). doi: 10.1007/s00703-008-0290-y CrossRefGoogle Scholar
  19. Zinner T, Betz H-D (2009) Validation of Meteosat storm detection and nowcasting based on lightning network data. In: Proceedings of the EUMETSAT meteorological satellite conference 2009, Bath, United Kingdom, EUMETSAT P. vol 55, p 8Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Thomas Gerz
    • 1
  • Caroline Forster
    • 1
  • Arnold Tafferner
    • 1
  1. 1.DLR, Institute of Atmospheric Physics (IPA)OberpfaffenhofenGermany

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