1. Global Atmospheric Turbulence Decision Support System for Aviation John Williams, Bob Sharman, and Cathy Kessinger (NCAR); Tony Wimmers and Wayne Feltz (UW/CIMSS) NASA Applied Sciences Weather Program Review Boulder, CO November 18, 2008 and UW-Madison SSEC/CIMSS

2. Global Turbulence project goals Develop global probabilistic turbulence nowcasts and forecasts and supporting global convective nowcasts –Address clear-air turbulence (CAT), convectively-induced turbulence (CIT), and mountain-wave turbulence (MWT) –0-3 hour nowcasts of convection –0-36 hour forecasts of turbulence, 10,000 – 45,000 ft. Support World Area Forecast System (WAFS) –Provide improved accuracy and timeliness over current SIGMETs and SIGWX charts Support NextGen SWIM 4-D data cube Leverage and provide outlet for previous FAA and NASA-funded work (e.g., Oceanic Weather)

3. Approach Develop a database of global turbulence reports for empirical model development, tuning and verification Adapt CONUS GTG (AWRP-funded) diagnostics for use with Global Forecast System (GFS) model data Adapt Oceanic Nowcast (AWRP/NASA) for global application on GOES East and West, MTSAT, and Meteosat Adapt satellite-based turbulence algorithms (NASA/GOES-R) including tropopause folding, CIT and MWT features Adapt CIT diagnostics (AWRP/NASA) for use with GFS model and satellite convection diagnoses and nowcasts Develop nowcast/forecast data fusion system Verify and benchmark the forecasts vs. SIGMETs Run real-time demonstration over GOES East/West domain –Adapt CONUS Experimental ADDS display (AWRP/NOAA) –Cockpit uplink messages (prev. AWRP-funded) –Web-based pilot/forecaster feedback

4. Flow Chart for Global GTG Geo-, Leo- Satellites In Situ Observations (tuning) Convection Diag. & Now. Turb. Detection (trop. folding) Mountain Wave GFS Model CIT/CAT Diagnoses Global Graphical Turbulence Guidance

5. Global GTG Demonstration at NCAR Global GTG World Wide Web Synthetic SIGMETs Pilots ATM / Dispatchers

6. Future NEXTGen Use of Global GTG Global GTG NEXTGen 4-D Data Cube World Wide Web WAFC SIGMETs Human over the Loop Pilots ATM / Dispatchers

7. Cockpit Uplink Demo Aircraft-relative display of cloud top height Pilot and dispatcher receive a “heads up” for approaching weather (common situational awareness) United Airlines test on oceanic flights Cloud Top Height Current Position Future Positions Flight Path ASCII display via cockpit printer >40kft 30-39kft

8. United EDR above 10,000 ft MSL, 07-01-2008 to 07-15-2008 Empirical Turbulence Data: UAL EDR

9. Delta EDR above 10,000 ft MSL, 07-01-2008 to 10-31-2008 Empirical Turbulence Data: Delta EDR

10. Empirical Turbulence Data: U de U de, various airlines, 11-1-2008 to 11-5-2008

11. Empirical Turbulence Data: AIREPs

12. Turbulence data collection status Most data are available from NCAR archives –NCDC archive data may also be used Quality control development is underway Database design is underway

13. Adapting GTG diagnostics for GFS Challenges of global model –Cycle boundaries in longitude –Poles are singular points –Constant lat-lon grid, therefore Δx (long.) nonuniform in spatial distance, much smaller near poles –Different vertical coordinates –Some diagnostics break down at equator GFS (sigma coordinates) RUC (hybridB coordinates)

14. GFS-based diagnosticRUC-based diagnostic Ellrod index FL350 EDR index FL350 Ri from thermal wind FL200 Note: breaks down at equator GFS-GTG 6-hr forecasts valid 18Z 4 Nov2008 (election day)

15. GFS-GTG status Initial implementation of common GTG core software (supports RUC, WRF, and GFS models) Still testing GFS-based diagnostics –Need to refine based on turbulence reports for particular cases –Then perform statistical evaluations over extended time period GFS data are being ingested and converted in real-time –0.5 degree GFS 00-, 03-, 06-, 09-, and 12-hour pressure coordinate files (will switch to 1/3 degree) Real-time system monitoring tools have been set up

16. (Near-) Global Convection Nowcasting Geostationary satellite-based methodologies cover +70 degrees latitude Could expand coverage using polar-orbiting satellites –Northern latitudes benefit (over-the-pole aviation routes) –Few (no?) commercial aviation routes over Antarctica MTSAT-1R Courtesy of David Johnson

17. Geo-Satellite Methodology Fuzzy logic data fusion of two methods –Cloud Top Height from longwave infrared (10 micron) & GFS model –Global Convective Diagnosis [TB(6.5 micron) – TB(10 micron)] Convective Diagnosis Oceanic (CDO) Interest Field (0 to 2) –Final, binary product will have a threshold applied Cloud Top Height Global Convective Diagnosis Convective Diagnosis Oceanic Interest

18. Challenges for Convection Nowcasting Varying, full-disk satellite scanning strategies –3 hourly: GOES-E and GOES-W –1 hourly: MTSAT-1R –15 minutes: Meteosat-9 GOES satellites have partial scans that could be merged –Discontinuities across scanning boundaries make extrapolation difficult Planning for 3-hourly updates for Global Turbulence –Provides an analysis and 3-hr nowcast Will examine Meteosat-9 imagery in anticipation of future rapid-update GOES-R capability

19. Global convective nowcasting status Real-time ingest and processing of GOES full disc scans (Terrascan) implemented Initial (uncalibrated) CDO field produced in real-time Archived data from MTSAT has been transmitted from CIMSS to NCAR for analysis Real-time system monitoring tools have been set up

20. 20 Tropopause Fold Turbulence Prediction (Tony Wimmers, UW/CIMSS) Background Algorithm basics Adapting the algorithm to aircraft hazard awareness Latest developments

21. Background

22. Background: Tropopause folding and Clear Air Turbulence (CAT) 14 12 10 8 6 4 150 200 300 400 500 600 700 (~100 km) subtropical air mass polar air mass stratosphere Pressure (hPa) Height (km) tropopause front From Shapiro, M. A. (1980): Turbulent mixing within tropopause folds as a mechanism for the exchange of chemical constituents between the stratosphere and the troposphere, J. Atmos. Sci., 37, 994-1004. Upper-air front

23. Background: GOES Layer-Average Specific Humidity (GLASH) (WV channel) (GLASH product) Wimmers, A. J., and J.L. Moody, A fixed-layer estimation of upper tropospheric specific humidity from the GOES water vapor channel: Parameterization and validation of the altered brightness temperature product, Journal of Geophysical Research-Atmospheres 106 (D15), 17115-17132, 2001.

24. Background: Synoptic-scale UTH

25. 300 hPa Potential Vorticity

26. Background: Validation with aircraft ozone lidar Tropopause folds were measured at crossings of upper-troposphere air mass boundaries Wimmers, A. J., J.L. Moody, E.V. Browell, J.W. Hair, W.B. Grant, C.F. Butler, M.A. Fenn, C.C. Schmidt, J. Li, and B.A. Ridley, Signatures of tropopause folding in satellite imagery, Journal of Geophysical Research - Atmospheres, 109, art. no. 8360, 2003.

27. Algorithm basics

28. 1. Humidity product (cloud masked) longitude latitude decreasing specific humidity

29. 2. Smoothed gradient of humidity product longitude latitude decreasing specific humidity longitude latitude

30. longitude latitude 3. Contour along boundaries longitude latitude decreasing specific humidity longitude latitude

31. longitude latitude 4. Extend polygons out from boundaries longitude latitude decreasing specific humidity longitude latitude Wimmers, A. J. and J. L. Moody, Tropopause folding at satellite-observed spatial gradients: 2. Development of an empirical model, Journal of Geophysical Research – Atmospheres, 109, art. no. D19307, 2004.

32. Adapting the algorithm to aircraft hazard awareness

33. 33 Adapting to aircraft hazard awareness  Validation data - Eddy Diffusion Rate  Automated reporting of inertial disturbance on commercial aircraft  3-minute integration time per measurement (short). This indicates several measurements through any single turbulent region.  Collected and quality-checked by NCAR  ~ 1 month latency

34. Adapting to aircraft hazard awareness decreasing specific humidity longitude latitude 2. Assign a vertical height to the trop. folds 1. Filter for the trop. folds associated with turbulence x x x x

35. Filtering cases of tropopause folding Measurements of turbulence are limited to near-orthogonal crossings of the aircraft with the direction of flow “20º” “75º” Also limiting factors: - Direction of flow - WV gradient strength - Time of year (possibly)

36. Height assignment (validation with EDR data) EDR reports conform to the expected cross-section of turbulence in a tropopause fold Potential temperature difference from the lower tropopause Distance from tropopause break probability of turbulence Predicted area of turbulence

37. Recent developments

38. 38 Algorithm Development - Adaptation for operational use  In 2007, the Tropopause Folding Turbulence Product was adapted as an algorithm for the GOES Algorithm Working Group (AWG)  AWG is a multi-year project to prepare end-user products to be optimized and online at the very start of the GOES-R operations  The t ransition of this algorithm to the GOES-R platfor m includes the following:  Port original Matlab code to Fortran (  )  Incorporate products into GEOCAT environment (  )  Apply to synthetic GOES-R 6.19um channel data  Validation of the adapted product with EDR data

39. Algorithm Development - Adaptation for operational use Test case output: Tropopause Fold minimum/maximum heights

40. Algorithm Development - Adaptation for operational use Test case output: Tropopause Fold exposed flight directions

41. 41 Algorithm Development - Future objectives –Adapt the algorithm for use with MTSAT and Meteosat imagery  Makes the product truly global  Gradients will be intercalibrated with MODIS data and tropopause features can be confirmed with the Aqua Ozone Mapping Instrument (OMI)

42. Summary (John Williams) The Global Turbulence DSS project aims to produce global probabilistic turbulence nowcasts and forecasts supported by global convective nowcasts –Improve WAFS SIGMET and SIGWX charts –Provide turbulence information for pilots and air- traffic management via the NextGen 4-D data cube Leverages existing CONUS systems and NASA- and FAA-funded turbulence and convection R&D Progress made on empirical turbulence database, GFS-GTG, global convection diagnosis, and tropopause fold detection. An example of a comprehensive, end-to-end, collaborative product development project NextGen transition to operations needs to be defined

44. Integrated System Solution (ISS) Diagram