Observational Biases in Aircraft Types at NCEP

1. Discussion of Observational Biases of Some Aircraft Types at NCEPDr. Bradley Ballish NCEP/NCO/PMB7 September 2006 “Where America’s Climate and Weather Services Begin”

2. Overview • Introduction • Sonde/Aircraft temperature biases • Monthly average temperature bias time series plots

3. Overview (Continued) • Aircraft bias factors • Aircraft biases by aircraft types • Monthly average temperature increment plots • Collocation results • Monthly average plots of analysis minus guess • Summary

4. Introduction • Observational data biases are serious in part as they can cause errors in the analysis • Biases can be due to errors in the data or our use that we would like to correct • Biases can be due to forecast model bias that is best corrected in the model • It is helpful to know if the bias is due to problems in the data or the guess • Bias correction looks encouraging but has issues

5. Sonde/Aircraft Temperature Biases • Data monitoring shows that aircraft temperatures as a whole are warmer than the NCEP guess especially around 250 hPa while radiosondes are colder there • Aircraft and radiosonde data are very important for NWP model analyses and forecasts • One objective of this study was to investigate the key reasons for the bias discrepancies and its potential impacts on model analyses and forecasts

6. Monthly Average Temperature Bias Time Series Plots • Biases are global for all data, passing QC from 300 to 200 hPa for GDAS runs • Note that on average, sondes are colder than the guess, while all aircraft types are warmer than guess • We investigated biases for ACARS, AMDAR, AIREPS & SONDES • For more details, see our paper from the AMS annual meeting

7. Monthly Average Temperature Biases 300 to 200 hPa 00Z

8. Monthly Average Temperature Biases 300 to 200 hPa 12Z

9. Aircraft Bias Factors • Many factors affect aircraft biases • These include aircraft type, influence of past data on the guess, airlines, pressure level, software, temperature sensors and Phase of Flight (POF) • Specific aircraft type seems to be most important such as 767-432 versus 767-322

10. Aircraft Temperature Biases by Aircraft Types 300 hPa and up all Times of Day

11. Aircraft Temperature Biases by Aircraft Types 300 hPa and up all Times of Day

16. Aircraft Temperature Biases 250 +/- 25 hPa 00Zon 2.5 by 2.5 degree grid January 2005

17. Radiosonde Temperature Biases 250 +/- 25 hPa 00ZJanuary 2005

18. Average Analysis minus Guess Temperature 250 hPa January 2005

19. Aircraft Temperature Biases 250 +/- 25 hPa 00Zon 2.5 by 2.5 degree grid July 2005

20. Radiosonde Temperature Biases 250 +/- 25 hPa 00ZJuly 2005

21. Average Analysis minus Guess Temperature 250 hPa July 2005

22. Discussion of Temperature Bias Impact • The aircraft bias maps show mostly red dots (warm) while the sonde plots show mostly blue dots (cold) but not always • The analysis minus guess plots often show patterns explainable by the data increments • For 00Z January 2005, huge warming over NE Canada & mixed changes over the CONUS, pattern bears comparison with data increments • For 00Z July 2005, both data types show red dots in the Southern US resulting in a large warming • Wherever both data types show blue dots, there is often cooling in the analysis

25. Summary • The warm aircraft bias versus the cold sonde bias can be explained in part by RADCOR and large variance in aircraft biases for different types • There is evidence of systematic impact on NCEP analyses due to these temperature biases

26. Summary (Continued) • RADCOR needs fundamental improvement and more frequent updates • Bias correction for aircraft biases needs to be performed • Similar studies are planned for AMDAR data