Comparison of aircraft‐derived observations with in situ research aircraft measurements

Mode Selective Enhanced Surveillance (Mode-S EHS) reports are aircraft-based observations that have value in numerical weather prediction (NWP). These reports contain the aircraft's state vector in terms of its speed, direction, altitude and Mach number. Using the state vector, meteorological observations of temperature and horizontal wind can be derived. However, Mode-S EHS processing reduces the precision of the state vector from 16-bit to 10-bit binary representation. We use full precision data from research grade instruments, on-board the United Kingdom's Facility for Atmospheric Airborne Measurements, to emulate Mode-S EHS reports and to compare with derived observations. We aim to understand the observation errors due to the reduced precision of Mode-S EHS reports. We derive error models to estimate these observation errors. The temperature error increases from 1.25 K to 2.5 K between an altitude of 10 km and the surface due to its dependency on Mach number and also Mode-S EHS precision. For the cases studied, the zonal wind error is around 0.50 ms− 1 and the meridional wind error is 0.25 ms− 1. The wind is also subject to systematic errors that are directionally dependent. We conclude that Mode-S EHS derived horizontal winds are suitable for data assimilation in high-resolution NWP. Temperature reports may be usable when aggregated from multiple aircraft. While these reduced precision, high frequency data provide useful, albeit noisy, observations; direct reports of the higher precision data would be preferable.

[1]  Lars Isaksen,et al.  Use and impact of automated aircraft data in a global 4DVAR data assimilation system , 2003 .

[2]  M. Mulder,et al.  Using Automatic Dependent Surveillance-Broadcast for Meteorological Monitoring , 2012 .

[3]  S. Dance.  Issues in high resolution limited area data assimilation for quantitative precipitation forecasting , 2004 .

[4]  E. R. Cohen.  An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements , 1998 .

[5]  B. Strajnar,et al.  Validation of Mode‐S Meteorological Routine Air Report aircraft observations , 2012 .

[6]  M. Mulder,et al.  Using Automatic Dependent Surveillance-Broadcast for Meteorological Monitoring , 2013 .

[7]  I. Jolliffe,et al.  Forecast verification : a practitioner's guide in atmospheric science , 2011 .

[8]  Cary R. Spitzer.  Avionics: Elements, Software and Functions , 2006 .

[9]  A. Anderson,et al.  Correction of Flux Valve–Based Heading for Improvement of Aircraft Wind Observations , 2014 .

[10]  W. Briggs.  Statistical Methods in the Atmospheric Sciences , 2007 .

[11]  Tijana Janjić,et al.  Assimilation of Mode-S EHS Aircraft Observations in COSMO-KENDA , 2016 .

[12]  Barry E. Schwartz,et al.  A Comparison of Temperature and Wind Measurements from ACARS-Equipped Aircraft and Rawinsondes , 1995 .

[13]  Sarah L. Dance,et al.  3D-Var Assimilation of Insect-Derived Doppler Radar Radial Winds in Convective Cases Using a High-Resolution Model , 2011 .

[14]  R. P. G. Collinson,et al.  Introduction to Avionics Systems , 2003 .

[15]  D. Dallet,et al.  High-Speed A/D & D/A conversion: A survey , 2008, 2008 IEEE Bipolar/BiCMOS Circuits and Technology Meeting.

[16]  Sula Systems.  A SUB-MILLIMETRE WAVE AIRBORNE DEMONSTRATOR FOR THE OBSERVATION OF PRECIPITATION AND ICE CLOUDS , 2009 .

[17]  R. Lawson,et al.  Performance of Some Airborne Thermometers in Clouds , 1990 .

[18]  M. Kitchen,et al.  Introducing an Approach for Extracting Temperature from Aircraft GNSS and Pressure Altitude Reports in ADS-B Messages , 2015 .

[19]  Thomas Hauf,et al.  Aircraft type‐specific errors in AMDAR weather reports from commercial aircraft , 2008 .

[20]  C. Drüe,et al.  Comparison of Boundary-Layer Profiles and Layer Detection by AMDAR and WTR/RASS at Frankfurt Airport , 2010 .

[21]  S. Haan.  Mode-S Enhanced Surveillance derived observations from multiple Air Traffic Control Radars and the impact in hourly HIRLAM , 2013 .

[22]  B. Widrow,et al.  Statistical theory of quantization , 1996 .

[23]  A. A. Woodfield,et al.  Measurement of air temperature on an aircraft traveling at high subsonic and supersonic speeds , 1963 .

[24]  Nedjeljka Žagar,et al.  Impact of new aircraft observations Mode‐S MRAR in a mesoscale NWP model , 2015 .

[25]  Juanzhen Sun,et al.  Use of NWP for Nowcasting Convective Precipitation: Recent Progress and Challenges , 2014 .

[26]  David Simonin,et al.  Performance of 4D‐Var NWP‐based nowcasting of precipitation at the Met Office for summer 2012 , 2016 .

[27]  Preprint Mps,et al.  Representativity error for temperature and humidity using the Met Office high resolution model , 2012 .

[28]  S. Haan,et al.  High‐resolution wind and temperature observations from aircraft tracked by Mode‐S air traffic control radar , 2011 .

[29]  A. Anderson,et al.  5.6 Correction of Aircraft Flux Valve Based Heading for Two-Dimensional Winds Aloft Calculations Using Weather Model Comparisons , 2011 .

[30]  M. Pedder,et al.  Atmospheric data analysis: by Roger Daley, Cambridge University Press. Cambridge atmospheric and space science series, 2. 457 pages. Published 1991. Price: £55,-/U.S. $79.50 ISBN 0 521 382157. , 1992 .

[31]  Carl A. Friehe,et al.  Analysis of a Radome Air-Motion System on a Twin-Jet Aircraft for Boundary-Layer Research , 1991 .

[32]  S. Benjamin,et al.  Accuracy of ACARS Wind and Temperature Observations Determined by Collocation , 1999 .

[33]  Ad Stoffelen,et al.  Assimilation of High-Resolution Mode-S Wind and Temperature Observations in a Regional NWP Model for Nowcasting Applications , 2012 .

[34]  Lindsay J. Bennett,et al.  The Convective Precipitation Experiment (COPE): Investigating the Origins of Heavy Precipitation in the Southwestern United Kingdom , 2016 .

[35]  Brian Hamilton,et al.  The US/UK World Magnetic Model for 2010-2015 , 2010 .

[36]  V. Kumar,et al.  Systematic Differences in Aircraft and Radiosonde Temperatures , 2008 .

[37]  Siebren de Haan,et al.  Estimates of Mode-S EHS aircraft-derived wind observation errors using triple collocation , 2015 .

[38]  David Simonin,et al.  Doppler radar radial wind assimilation using an hourly cycling 3D‐Var with a 1.5 km resolution version of the Met Office Unified Model for nowcasting , 2014 .