A Network of Mode-S Receivers for Routine Acquisition of Aircraft-Derived Meteorological Data

Edmund Keith Stone Met Office, Exeter, United Kingdom

Search for other papers by Edmund Keith Stone in
Current site
Google Scholar
PubMed
Close
and
Gary Pearce Met Office, Exeter, United Kingdom

Search for other papers by Gary Pearce in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Aircraft are an important source of meteorological observations for both numerical weather models and aviation weather forecasting. There has been increasing interest in novel methods for gathering aircraft-based observations, especially mode-selective (Mode-S) enhanced surveillance (EHS)-derived data. This paper reports on the progress made in the United Kingdom at the Met Office on receiving and processing these data. Five receivers have been deployed, providing up to 5.7 million observations of horizontal wind and temperatures per day over the United Kingdom. The receivers are relatively low cost and deploying them at existing operational weather radar sites has been shown to be an ideal choice. Heading corrections are required to improve the quality of the wind observations. When corrected the Mode-S EHS wind data have similar observations-minus-background (o−b) statistics as Aircraft Meteorological Data Relay [AMDAR; using a Met Office version of the Unified Model over the United Kingdom (UKV)]. For the u wind component, the average per model run o−b root-mean-square value for the Mode-S EHS–derived data was 2.45 and 2.12 m s−1 for AMDAR. The AMDAR data are assimilated into the model.

Corresponding author address: Ed Stone, Met Office, FitzRoy Road, Exeter, Devon EX1 3PB, United Kingdom. E-mail: ed.stone@metoffice.gov.uk

Abstract

Aircraft are an important source of meteorological observations for both numerical weather models and aviation weather forecasting. There has been increasing interest in novel methods for gathering aircraft-based observations, especially mode-selective (Mode-S) enhanced surveillance (EHS)-derived data. This paper reports on the progress made in the United Kingdom at the Met Office on receiving and processing these data. Five receivers have been deployed, providing up to 5.7 million observations of horizontal wind and temperatures per day over the United Kingdom. The receivers are relatively low cost and deploying them at existing operational weather radar sites has been shown to be an ideal choice. Heading corrections are required to improve the quality of the wind observations. When corrected the Mode-S EHS wind data have similar observations-minus-background (o−b) statistics as Aircraft Meteorological Data Relay [AMDAR; using a Met Office version of the Unified Model over the United Kingdom (UKV)]. For the u wind component, the average per model run o−b root-mean-square value for the Mode-S EHS–derived data was 2.45 and 2.12 m s−1 for AMDAR. The AMDAR data are assimilated into the model.

Corresponding author address: Ed Stone, Met Office, FitzRoy Road, Exeter, Devon EX1 3PB, United Kingdom. E-mail: ed.stone@metoffice.gov.uk
Save
  • Cardinali, C., Isaksen L. , and Andersson E. , 2003: Use and impact of automated aircraft data in a global 4DVAR data assimilation system. Mon. Wea. Rev., 131, 18651877, doi:10.1175//2569.1.

    • Search Google Scholar
    • Export Citation
  • Collinson, R. P. G., 2011: Introduction to Avionics Systems. 3rd ed. Springer, 530 pp., doi:10.1007/978-94-007-0708-5.

  • Cress, A., and Wergen W. , 2001: Impact of profile observations on the German Weather Service’s NWP system. Meteor. Z., 10, 91101, doi:10.1127/0941-2948/2001/0010-0091.

    • Search Google Scholar
    • Export Citation
  • de Haan, S., 2010: Quality assessment of high resolution wind and temperature observations from ModeS. Rev. ed. KNMI Scientific Rep. WR 2009-07, 31 pp.

  • de Haan, S., 2011: High-resolution wind and temperature observations from aircraft tracked by Mode-S air traffic control radar. J. Geophys. Res., 116, D10111, doi:10.1029/2010JD015264.

    • Search Google Scholar
    • Export Citation
  • de Haan, S., 2013: An improved correction method for high quality wind and temperature observations derived from Mode-S EHS. KNMI Tech. Rep. TR-338, 43 pp.

  • de Haan, S., and Stoffelen A. , 2012: Assimilation of high-resolution Mode-S wind and temperature observations in a regional NWP model for nowcasting applications. Wea. Forecasting, 27, 918937, doi:10.1175/WAF-D-11-00088.1.

    • Search Google Scholar
    • Export Citation
  • de Haan, S., de Haij M. , and Sondij J. , 2013: The use of a commercial ADS-B receiver to derive upper air wind and temperature observations from Mode-S EHS information in The Netherlands. KNMI Tech. Rep. TR-336, 44 pp.

  • de Leege, A., van Paassen M. , and Mulder M. , 2013: Using automatic dependent surveillance-broadcast for meteorological monitoring. J. Aircr., 50, 249261, doi:10.2514/1.C031901.

    • Search Google Scholar
    • Export Citation
  • EUMETNET, 2015: E-AMDAR. Accessed 7 July 2015. [Available online at http://www.eumetnet.eu/e-amdar.]

  • Eyre, J., and Reid R. , 2014: Cost-benefit studies for observing systems. Met Office Forecasting Research Tech. Rep. 593, 11 pp.

  • Finlay, C. C., and Coauthors, 2010: International geomagnetic reference field: The eleventh generation. Geophys. J. Int., 183, 12161230, doi:10.1111/j.1365-246X.2010.04804.x.

    • Search Google Scholar
    • Export Citation
  • Graham, R. J., Anderson S. R. , and Bader M. J. , 2000: The relative utility of current observation systems to global-scale NWP forecasts. Quart. J. Roy. Meteor. Soc., 126, 24352460, doi:10.1002/qj.49712656805.

    • Search Google Scholar
    • Export Citation
  • ICAO, 2012: Technical provisions for Mode S services and extended squitter. 2nd ed. International Civil Aviation Organization Doc. 9871, AN/460, 326 pp.

  • Jacobs, N. A., Mulally D. J. , and Anderson A. K. , 2014: Correction of flux valve–based heading for improvement of aircraft wind observations. J. Atmos. Oceanic Technol., 31, 17331747, doi:10.1175/JTECH-D-13-00175.1.

    • Search Google Scholar
    • Export Citation
  • KNMI, 2014: QEvC info. Accessed 10 June 2015. [Available online at http://www.knmi.nl/samenw/geoss/eumetnet/E-Amdar/QEvC/.]

  • Köllner, G., 2013: Mode-S Beast. Accessed 8 July 2014. [Available online at http://www.modesbeast.com/.]

  • Lorenc, A. C., and Marriott R. T. , 2014: Forecast sensitivity to observations in the Met Office global numerical weather prediction system. Quart. J. Roy. Meteor. Soc., 140, 209224, doi:10.1002/qj.2122.

    • Search Google Scholar
    • Export Citation
  • Maus, S., Macmillan S. , McLean S. , Hamilton B. , Thomson A. , Nair M. , and Rollins C. , 2010: The US/UK World Magnetic Model for 2010-2015. British Geological Survey, NOAA Tech. Rep. NESDIS/NGDC, 98 pp.

  • Petersen, R. A., 2016: On the impact and benefits of AMDAR observations in operational forecasting. Part I: A review of the impact of automated aircraft wind and temperature reports. Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-14-00055.1, in press.

  • Stone, E. K., and Kitchen M. , 2015: Introducing an approach for extracting temperature from aircraft GNSS and pressure altitude reports in ADS-B messages. J. Atmos. Oceanic Technol., 32, 736743, doi:10.1175/JTECH-D-14-00192.1.

    • Search Google Scholar
    • Export Citation
  • Strajnar, B., 2012: Validation of Mode-S Meteorological Routine Air Report aircraft observations. J. Geophys. Res., 117, D23110, doi:10.1029/2012JD018315.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1998 569 49
PDF Downloads 997 184 18