1. Analysis of Select Data Biases in North America Dr. Bradley Ballish NCEP/NCO/PMB October 2008 JAG/ODAA Meeting “Where America’s Climate and Weather Services Begin”

2. Overview Introduction Temperature observation count comparison Temperature bias comparison Wind speed bias comparison Profiler wind speed bias after using GSI determined pressures Proposed aircraft temperature bias corrections Temperature bias vs Phase of Flight (POF) for Canadian AMDAR data Speed bias vs POF for Canadian AMDAR data Relative humidity bias comparison Future work Summary

3. Introduction There are large numbers of new aircraft observations (temperatures, winds and moisture) over the North American (NA) continent, but these data exhibit considerable biases (observation minus NCEP background (guess)) that need to be corrected Ballish and Kumar (BAMS, Dec. 2008) show the need for aircraft temperature bias corrections and analyze different methods and issues Temperature and speed biases can vary with the aircraft POF as well as with aircraft type As far as known, no center is applying aircraft bias corrections Impact tests adding TAMDAR and Canadian AMDAR data did not show positive impact, but some of these new data types have large biases that need correction

4. Temperature Observation Count Comparison The next slide compares the average number of different types of temperature counts to the nearest mandatory pressure level per GDAS model run in June 2008 Counts for Radiosondes, ACARS, TAMDAR and two types of Canadian AMDAR are compared Wind observation counts (not shown) were found to be nearly identical to temperature counts Clearly the aircraft counts out number those from sondes

5. Sondes have low counts relative to large ACARS counts

6. Temperature Bias Comparison The next slide compares the average temperature bias of different types of observations to the nearest mandatory pressure level per GDAS model run in June 2008 Biases for sondes, ACARS, TAMDAR and two types of Canadian AMDAR are shown Clearly the aircraft temperatures are generally warmer than those from sondes (as found for ACARS and AMDAR, BK(2008)) The DHC-8 aircraft have the warmest bias

7. Sondes are cold compared to aircraft

8. Wind Speed Bias Comparison The next slide compares the average wind speed bias of different types of observations to the nearest mandatory pressure level per GDAS model run in June 2008 Biases for sondes, profilers, ACARS, TAMDAR and two types of Canadian AMDAR are shown The profilers show negative speed biases due to using a standard atmosphere to obtain their pressures – this is corrected in the GSI For some aircraft, the speed biases vary much with the POF, see later slides

9. Profiler low speed bias is fixed in GSI

10. Profiler Wind Speed Bias After Using GSI Determined Pressures The next slide compares the average wind speed bias of profiler data versus the guess using a standard atmosphere to derive pressure versus GSI derived pressures The GSI derived pressures are clearly better The profilers with GSI derived pressures show some small bias due to attempts at ground clutter and bird migration removal at the sites

12. Proposed Aircraft Temperature Bias Corrections BK(2008) studied aircraft temperature biases and has proposed bias corrections shown in the next slide for January 2007 for the 15 aircraft types with the largest counts In the following slide, the same is shown for non US AMDAR types This study did not include TAMDAR or Canadian AMDAR types

13. Most corrections are negative

15. Temperature Bias vs POF for Canadian AMDAR Data In the following slide, the temperature biases for Canadian AMDAR type CRJ are shown vs the POF This aircraft type has generally warm biases that vary with the POF In the following slide, the same is shown for Canadian aircraft type DHC-8 Here the biases vary considerably with the POF

17. Ascent vs descent is large

18. Speed Bias vs POF for Canadian AMDAR Data In the following slide, the wind speed biases for Canadian AMDAR type CRJ are shown vs the POF This aircraft type has speed biases that vary considerably with the POF In the following slide, the same is shown for Canadian aircraft type DHC-8 Here the speed biases vary even more with the POF

19. Ascent vs descent is large

20. Ascent vs descent is very large

21. Relative Humidity Bias Comparison The next three slides show counts of moisture observations, relative humidity biases and RMS differences versus the guess for the North American area in June 2008 for sondes, ACARS and TAMDAR data The TAMDAR data (at this time) is mainly in the mid west, yet have higher counts and very good stats versus the guess

22. TAMDAR has large counts, but are just in mid-west only

23. TAMDAR biases may be better than sondes

24. Aircraft RMS values would be lower with time interpolation of background

25. Future Work An algorithm needs to be developed, refined, tested and made operational to make bias corrections of aircraft data BK(2008) point out that there are problems to address such as large background temperature errors around the tropopause and inadequate time interpolation of the background International cooperation is needed to have the aircraft type as part of the raw aircraft data

26. Summary The aircraft data over the North American continent need temperature and wind bias corrections More work in this area and testing (impact studies) are needed to be able to make such corrections operational The TAMDAR data have excellent moisture stats and the UPS ACARS data are almost as good Care must be taken on how observational data are used, quality controlled and bias corrected to use them optimally