# Presentation: 102400

## ASAP Turbulence Research at NCAR

**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**

## 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)

## 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

## 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

## 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

## Turbulence climatology – increased levels near mountains (15 years of PIREPs) 

- Turbulence climatology – increased levels near mountains (15 years of PIREPs)

- Mog/Total

- Topography

## 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.

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

## 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**

## Connection to NextGen 4D 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**

## 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

## 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!!

## MWT pireps climatology

**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

## 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

## +

- Mountain Wave GTG3 is
- Combination of GTG+ MWT diagnostic (CWEDR)

**GTG3**

**Current experimental  GTG2**

- CASE STUDY

## CASE STUDY Example: Severe Turbulence encounter 15 Mar 2006  GTG2 did NOT capture event

**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)

## 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

## 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

## 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!_