Weather Nowcasting and Short Term Forecasting

  • Arnold Tafferner
  • Caroline Forster
Part of the Research Topics in Aerospace book series (RTA)


This article is about present weather and its immediate development, on the challenge of how to observe it, and how to forecast it in the short term. It touches on the problems meteorologists have in delivering reliable estimates of, e.g., which path a thunderstorm will take during its track, whether it will bring hail or just rain, or when there will be freezing conditions at an airport with subsequent problems for air traffic on ground, arrival and departure. Some illustrative examples are given, showing how the problems are tackled and how integrated forecasting systems, in particular, can be successful in meeting the challenge.


Numerical Weather Prediction Model Short Term Forecast Weather Phenomenon Gust Front Weather Feature 
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.



The work presented here was funded by the DLR project Wetter & Fliegen (2008–2012) and benefited from the EU projects RISK-AWARE, FLYSAFE. Thanks are due to nowcast GmbH for providing lightning observations, and to the Department of Meteorology at Vienna University for the VERA system.


  1. Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., Reinhardt, T.: Operational convective-scale numerical Weather prediction with the COSMO model: description and sensitivities. Mon. Weather Rev. 139, 3887–3905 (2011)ADSCrossRefGoogle Scholar
  2. Bretl, S.: Untersuchung des lebenszyklus von gewittern in mitteleuropa mit hilfe von fernerkundungs- und modelldaten. Diplomarbeit, Ludwig-Maximilians-Universität München, München (2010)Google Scholar
  3. Browning, K. A.: Nowcasting, p. 256. Academic Press, London (1982)Google Scholar
  4. Conway, B. J.: An overview of nowcasting techniques. In: SAF Training Workshop—Nowcasting and Very Short Range Forecasting, EUMETSAT (1998)Google Scholar
  5. COST 722, 2004: WWRP/NWP Expert Meeting, FMI, Helsinki, 9–11 June 2004Google Scholar
  6. Dengler, K., Anger, J., Keil, C.: Validation of time-lagged ensemble forecasts relevant for predicting aircraft wake vortices. Meteorol. Z. 20, 625–634 (2011)CrossRefGoogle Scholar
  7. Evans, J., Ducot, E.: The integrated terminal weather system (ITWS). MIT Lincoln Laboratory J. 7(2), 449 (1994)Google Scholar
  8. Forster, C., Tafferner, A.: 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
  9. Heimann, D., Kurz, M.: The Munich Hailstorm of July 12, 1984–a discussion of the synoptic situation. Beitr. Phys. Atmos. 58, 528–544 (1985)Google Scholar
  10. Höller, H., Reinhardt, M.E.: The Munich Hailstorm of July 12, 1984–convective development and preliminary hailstone analysis. Beitr. Phys. Atmos. 59(1), 1–12 (1986)Google Scholar
  11. Kober, K., Tafferner, A.: Tracking and nowcasting of convective cells using remote sensing data from radar and satellite. Meteorol. Z. 1(18), 075–084 (2009). doi: 10.1127/0941-2948/2009/359 CrossRefGoogle Scholar
  12. Köhler, M.: Untersuchung der Auslösung von Gewittern während der “Wetter und Fliegen” Sommerkampagne 2010. Masterarbeit, DLR/IPA (2011)Google Scholar
  13. Leifeld, C.: Weiterentwicklung des Nowcastingsystems ADWICE zur Erkennung vereisungsgefährdeter Lufträume, Berichte des Deutschen Wetterdienstes, Offenbach am Main, vol. 224, pp. 118 (2004)Google Scholar
  14. Mannstein, H., Meyer, R., Wendling, P.: Operational detection of contrails from NOAA-AVHRR-Data. Int. J. Rem. Sensing 20, 1641–1660 (1999)ADSCrossRefGoogle Scholar
  15. Meyer, V.: Thunderstorm tracking and monitoring on the basis of three dimensional lightning data and conventional and polarimetric radar data. Dissertation, Ludwig-Maximilians-Universität München, Mai (2010)Google Scholar
  16. Mueller, C., Saxen, T., Roberts, R., Wilson, J., Betancourt, T., Dettling, S., Oien, N., Yee, J.: NCAR auto-nowcast system. Weather Forecast 18(4), 545–561 (2003)ADSCrossRefGoogle Scholar
  17. Steinacker, R., Pöttschacher, W., Dorninger, M.: Enhanced resolution analysis of the atmosphere over the Alps using the fingerprint technique. Annalen der Meteorologie 35, 235–237 (1997)Google Scholar
  18. Stich, D., Forster, C., Zinner, T., Tafferner, A.: Convection initiation—nowcasting by data fusion and its verification.In: European Conferences on Severe Storms (ECSS 2011), Palma de Mallorca, Balearic Islands, Spain, 3–7 October 2011Google Scholar
  19. 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
  20. 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 (2008). doi: 10.1007/s00703-008-0322-7 ADSCrossRefGoogle Scholar
  21. Tafferner, A., Forster, C., Hagen, M., Hauf, T., Lunnon, B., Mirza, A., Guillou, Y., Zinner, T.: Improved thunderstorm weather information for pilots through ground and satellite based observing systems. In: 14th conference on Aviation, Range, and Aerospace Meteorology, 90th AMS Annual Meeting, Atlanta, 17–21 January 2010Google Scholar
  22. Tafferner, A., Forster, C., Gerz, T.: Concatenating weather monitoring and forecast: the WxFUSION concept. In: Gerz, T., Schwarz, C. (eds.) The DLR Project Wetter & Fliegen. Final Report DLR-FB 2012-02, pp. 25–30, 2012Google Scholar
  23. Wilson, J.W., Crook, N.A., Mueller, C.K., Sun, J., Dixon, M.: Nowcasting thunderstorms: a status report. Bull. Am. Meteorol. Soc. 79(10), 2079–2093 (1998)ADSCrossRefGoogle Scholar
  24. 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

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.DLR, Institute of Atmospheric Physics (IPA)OberpfaffenhofenGermany

Personalised recommendations