1. 1 ASAP Turbulence Research at NCAR NASA Applied Science Program Review Session 2B: Turbulence NCAR/RAL Boulder, CO USA Mountain Wave Turbulence Bob Sharman & David Johnson NCAR

2. Background – known turbulence sources Source: P. Lester, “Turbulence – A new perspective for pilots,” Jeppesen, 1994 Clear-air Turbulence (CAT) Mountain wave Turbulence (MWT) Low level Terrain-induced Turbulence (LLT) Convective boundary Layer turbulence In-cloud turbulence Cloud-induced or Convectively-induced Turbulence (CIT)

3. 3 Turbulence Forecast Product: Graphical Turbulence Guidance (GTG) Based on RUC NWP forecasts Uses a combination of turbulence diagnostics, merged and weighted according to current performance (pireps, EDR) ─(Mainly) clear-air sources 10,000 ft MSL-FL450 ─V 1.0 on Operational ADDS since Mar 2003 ─V 2.0 on Experimental ADDS since Nov 2004 Independent QA RT performance evaluations Current work areas –Probabilistic forecasts of moderate-or-greater (MOG) and severe-or-greater (SOG) turbulence –Optimal use of insitu reports –Assimilation of turbulence-related observations –Develop diagnostics for other turbulence sources (MWT, CIT,..) –Transition to WRF … and GTG-N

4. GTG process Ingest full resolution grids Compute & threshold turb. diagnostics Score & combine diagnostics Real-time (RTVS) and post-analysis verification ADDS displays Real-time PIREPs Real-time lightning flash Satellite features wind profilers 88D edr Real-time In-situ data Future In-situ QC GTG3/ITFA core

5. Mountain wave turbulence (MWT) For the past 2 years ASAP work has concentrated on development of a nowcast/forecast system for MWT A major source of severe turbulence encounters Related to topographically generated gravity waves (mountain waves) which may “break” causing turbulence Source: P. Lester, “Turbulence – A new perspective for pilots,” Jeppesen, 1994 MWT

6. 6 Turbulence climatology – increased levels near mountains (15 years of PIREPs) Mog/Total Colorado Rockies Canadian Rockies Wasatch Range Sierra Nevada [SOG/Total] PIREPs 1-60,000 ft 1993 – 2007 Colorado Rockies Canadian Rockies Wasatch Range Sierra Nevada Topography

7. Turbulence levels are significantly higher over mountainous terrain Denver, CO and the Front Range have statistically higher levels of turbulence than almost anywhere in the U. S. “We are gonna get there but it’s going to be a little rocky. It’s sort of like flying into Denver – you know you are going to land, but it’s not fun going over those mountains.” –President-elect Barack Obama in a campaign speech on the economy at Westminster CO, 29 Sep 2008. 7

8. Observations also show high incidence of gravity waves over the Western U. S.

9. ASAP MWT forecasting goal/approach Goal: Develop MWT nowcast/forecast system for aviation use Approach –Develop a system that integrates observations (including satellite) and NWP model data to provide nowcasts/forecasts of MWT CIMSS/UAH provides satellite-based gravity wave feature identifier »But NOTE: waves may or may not be turbulent! NCAR develops semi-empirical MWT forecasting approach based on »PIREPs climatology »Observations »RUC-based (later WRF) diagnostics NCAR develops integrator and implements as a component of the FAA AWRP sponsored GTG3 and GTG-N –GTG and GTG-N will populate the SAS of the NextGen 4D data cube

10. Connection to NextGen 4D data cube 4D Wx SAS 4D Weather Data Cube Insitu data NTDA Mosaic GTGN GTG NWP Model (s) Satellite data Feature extractor 24X7 Processing center PIREPS HOL (MDL?) QC DCIT Indices CoSPA Red  “Single Authoritative Data Source” (SAS) NSSL 3-D DBZ NASA AvWx FAA AWRP Turb RT FAA AWRP other RT NOAA Primary funding source color code EN-2430 Weather Forecasts - Consolidated Turbulence - Level 1. Near-term predictive models and current weather observations are fused to provide a consolidated turbulence forecast that is available to users over a network-enabled infrastructure. This capability will include North America from 10,000 feet to FL450, 0-18 hours, updated hourly, and will forecast clear air and mountain wave turbulence. ASAP Radar

11. MWT diagnostics Provide Identify preferred regions from climatology of MWT PIREPs (15 years) –Develop MWT/total ratios by month, 5000 ft altitude band, CONUS domain Develop model-based (currently RUC20) diagnostics to compare to MWT pireps [2 years of historical data] –Need to be altitude dependent, so traditional 2d indicators developed by airlines are insufficient: Strong wind component normal to ridge Terrain characteristics (mean height, variance, etc.) –Thus requires 3D discriminators 11

12. Semi-empirical MWT forecasting approach Identify mountain wave related turbulence events from PIREPs: –Use only records that mention turbulence level and waves, e.g., UA /OV RLG/TM 1418/FL150/TP C172/WV 30050KT/TB NEG/RM TREMENDOUS MTN WAVE UA /OV SUN360035/TM 1837/FL125/TP PA31/TA M10/TB MOD/RM MTN WAVE UUA /OV MVA 085050/TM 1835/FL400/TP B737/TB SEV/RM SEV MTN WAVE/FULL TILT ON THROTTLES. +/- 40KTS –Don’t use “light” reports – attempt to discriminate only between null and moderate-or-greater (MOG) –For now restrict to 10,000 ft to 60,0000 ft –Note turbulence ≠ waves!! – Not trying to predict wave amplitude!!

13. MWT pireps climatology # MWT MOG PIREPs sfc-60,000 ft 1993 – 2007 (15 yrs) % MWT MOG/Total PIREPs 30,000-35,000 ft February 1993 – 2007 (15 yrs) MWT POLYGON h=1km Evaluate over Western U.S.: Example

14. ROC null-MOG performance of 47 diagnostics evaluated against MWT PIREPs 0-hr fcst Ellrod TI1 Wmaxt Standard GTG MWTClimo x wmax x EDRLL [ CWEDR ] DIV + DIVT + SIGWX + wmax + climo + EDRLL Low threshold High threshold Jun 2005-Jun 2007 15Z,18Z 0,6 hr forecasts 2985 pireps 2393 nulls 592 MOG MWT No skill line

15. + Mountain Wave GTG3 is Combination of GTG+ MWT diagnostic (CWEDR) CWEDR GTG3 Current experimental GTG2 CASE STUDY

16. Location turbulence encounter (black circle with red center) CASE STUDY Example: Severe Turbulence encounter 15 Mar 2006 GTG2 did NOT capture event initialized 18 UTC; 3 hr forecast GTG forecast moderate turbulence (yellow regions)

17. Turbulence encounter (black circle with red center) initialized 18 UTC; 3 hr forecast Mountain wave turbulence - enhanced GTG3: Did capture 15 Mar 2006 severe turbulence event!! Severe turbulence predicted in red regions

18. Another possible MOG discriminator: Wave pattern complexity? Simple wave pattern 3 Sep 2004 2010 UTC Complex wave pattern 6 Mar 2004 1950 UTC Some evidence that turbulence may be related to complexity of lee wave pattern as observed in satellite imagery (Uhlenbrock et al.,2007) MODIS WV (6.7 u) imagery Courtesy Wayne Feltz, CIMSS/SSEC, UW Madison

19. Summary/Future work Have developed a MWT diagnostic that seems to be fairly reliable in discriminating between smooth conditions (with or without waves) and MOG turbulence due to wave breaking Extra discrimination may be possible by Using random forest or other artificial intelligence techniques to come up with a better set of NWP- based diagnostics Incorporate UAH/CIMSS wave feature detector –Can be used to identify wave and nonwave days and possibly to infer amplitudes –Wave patterns could possibly be used to identify conditions conducive to turbulence Then incorporate the new algorithm into GTG3!