1. Comparison of Radiosonde and Profiler Data with ACARS Data for Describing the Great Plains Low-Level Jet Ross W. Bradshaw Meteorology Program, Dept. of Geological and Atmospheric Sciences, Iowa State University, Ames, IA Mentor: Daryl Herzmann Dept. of Agronomy, Iowa State University, Ames, IA

2. Motivation: General interest in aviation Possible decommissioning of radiosondes in favor of ACARS in near future Wanted to test data on a feature normally difficult to observe

3. ACARS: Aircraft Communications, Addressing, and Reporting System American Airlines, United Airlines, Delta Airlines, Northwest Airlines, FedEx, and UPS have sensors on all their aircraft, as well as some business jets and other airlines Sensors record temperature, onboard computers calculate wind speed and direction Used in most numerical models already - RUC heavily dependant on ACARS observations

4. David Helms – NOAA’s Office of Science and Technology FY08 – Start elimination of redundant soundings Example: Southwest Airlines –450 Boeing 737’s –8 destinations daily (16 soundings daily) –Total of 7,200 soundings per day Expand sensors to record water vapor, turbulence, icing, and air quality Available to public in near real-time NWS cost reduction of 4 million dollars per year

5. Radiosonde (purple) and WVSSII (black) Comparison April 26, 2005

6. 12 Hour time-lapse of United States ACARS measurements 68,000 Observations/Day

7. ACARS Sensor

8. Methods: Checked climatological data from Southeast Nebraska for nocturnal thunderstorm occurrences Used Iowa State’s meteorology data archive to acquire wind profiler data Found ten cases with low-level jet occurrence in great plains for 2005 and 2006 warm seasons

9. 24 June 2005 - Haviland, KS profiler as viewed through Gempak Altitude (m) Time (UTC)

10. Low-level jet instances evaluated during warm seasons of 2005 and 2006 DateLocationTime (UTC)Time (LST) 24 June 2005Haviland, KS0300 – 15002100 – 900 28 June 2005Haviland, KS0300 – 15002100 – 900 17 July 2005McCook, NE0300 – 15002100 – 900 25 July 2005Haviland, KS0300 – 15002100 – 900 26 July 2005Vici, OK0000 – 15001900 – 900 27 May 2006Vici, OK0000 – 12001800 – 600 31 July 2006Haviland, KS0000 – 18001800 – 1200 01 August 2006Haviland, KS0000 – 15001800 – 900 02 August 2006Haviland, KS0000 – 12001800 – 600 10 August 2006Hillsboro, KS0000 – 18001800 – 1200

11. Methods: Wichita Mid- Continent Airport in Wichita, KS chosen as the ACARS reference point ACARS data acquired from Earth Systems Research Lab, Global Systems Division (ESRL, GSD) Wichita, KS Airport Hillsboro, KS Profiler Haviland, KS Profiler McCook, NE Profiler Vici, OK Profiler

12. Data and Analysis: Radiosonde and profiler data collocated with ACARS by altitude Comparisons made with data separation, altitude of airplane, and wind speeds for each observation source

13. Data Point Separation Schwartz and Benjamin (1995) found that distance separation of 60 km or more create too much difference in wind speeds The overall average distance separation of this study was 187 km with a standard deviation of 48 km This is outside of what Schwartz and Benjamin consider acceptable

14. 24 June 2005 – Distance separation between Haviland, KS profiler and ACARS observation

15. Airplane Altitude In overall study, the airplane altitude: –Mean was 8,770 m (~325 hPa) –Median was 10,556 m (~240 hPa) –Standard deviation was 3,530 m Most low-level jets exist below 2,500 m In a comparison of altitude vs. observed wind from the ACARS data, near surface observations showed sharp increase in wind speed

16. 31 July 2006 – ACARS reported altitude and ACARS observed wind speed

17. Observed Winds Wind direction was consistent with all observations which agrees with the findings of Lord et al. (1984) The wind speed measurements are the most inconsistent with the radiosondes –Inconsistency most likely due to difference in amount of observations

18. Scatter plot for all cases combined of ACARS wind speed against profiler wind speed

19. Case with least correlation: 10 August 2006 – ACARS wind speed against profiler wind speed

20. Case with most correlation: 31 July 2006 – ACARS wind speed against profiler wind speed

21. Conclusions: Radiosondes only provide observations at 00 UTC and 12 UTC, missing most of the low-level jet occurrence Radiosonde network too sparse –Only 2 year-round radiosonde sites in Kansas

22. Conclusions: ACARS system failed to accurately locate and diagnose the low-level jet –Most ACARS data restricted to upper atmosphere, fails to produce sufficient near-surface observations –Too much separation between sources to make accurate data comparison Profiler network sufficient in locating the Great Plains low-level jet –3 to 4 profilers in each Great Plains state –Observation times only separated by 6 min –Makes observation every 250 m –Proven accurate

23. Future Studies: More airports could be used in a larger study Wider range of data including more cases Study other mesoscale phenomena

24. Acknowledgements: Daryl Herzmann (Iowa State University) –For helping acquire and organize data Dr. Eugene Takle (Iowa State University) –For guidance in completing the project Thank you both very much!

25. Thank you for coming! Any questions? Contact Info: rwbradshaw@gmail.com rwb@iastate.edu