# Presentation: 102420

## 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**

## 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)

## 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

## Flow Chart for Global GTG

**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 GTG Demonstration at NCAR

**Global GTG Demonstration at NCAR**

- Global GTG

- World Wide Web

- Synthetic
- SIGMETs

- Pilots

- ATM / Dispatchers

## Future NEXTGen Use of Global GTG

**Future NEXTGen Use of Global GTG**

- Global GTG

**NEXTGen**
**4-D**
**Data Cube**

- World Wide Web

- SIGMETs

- Pilots

- ATM / Dispatchers

- SWIM

## Cockpit Uplink Demo

**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

- ASCII display  via cockpit printer

- _>_40kft

- 30-39kft

**Notes:**
The aircraft is flying from north to south, along the path indicated by the red arrow in the left panel. The ascii display that was sent to the cockpit (right panel) is aircraft-relative, such that their current position is at the bottom of the display and future positions (a maximum of about 2 hours into the future) are shown at the middle and top of the display. The latitude and longitude positions are indicated. The flight path (indicated by ‘*’) is where the aircraft is expected to be and assumes the pilot does not deviate. The uplink display is sent to the aircraft each time a position report is submitted, approximately once per hour. 
The uplink display is not an official FAA product yet and the pilot cannot use this display to make tactical decisions. But it is a means for the pilot to receive longer-range weather information than can be obtained from onboard radars. 
The common situational awareness enables both the pilot and dispatcher to have the same information such that better decisions can be made, for example if flight path deviations are needed due to approaching weather. Further, the pilot can request that the flight crew and passengers be belted in their seats if significant weather is expected , lessening the chance for injuries.  
Because the uplink display is sent without the pilot’s request (i.e., unsolicited information), their interest is piqued and it gets their attention. This product is the first to be sent to the cockpit in this manner. 
Gary Blackburn, software engineer in RAL, lead the effort with contributions from Jason Craig and Kay Levesque. 
The FAA Aviation Weather Research Program and the NASA Aviation Safety Program were funding agencies for this effort. 

## Empirical Turbulence Data: UAL EDR

**United EDR above 10,000 ft MSL, 07-01-2008 to 07-15-2008**

**Empirical Turbulence Data: UAL EDR**

## Empirical Turbulence Data: Delta EDR

**Delta EDR above 10,000 ft MSL, 07-01-2008 to 10-31-2008**

**Empirical Turbulence Data: Delta EDR**

## Empirical Turbulence Data: Ude

**U****de****, various airlines, 11-1-2008 to 11-5-2008**

## Empirical Turbulence Data: AIREPs

**Empirical Turbulence Data: AIREPs**

## 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

## 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)**

## GFS-GTG 6-hr forecasts valid 18Z 4 Nov2008 (election day)

- GFS-based diagnostic

- RUC-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)**

## 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

## (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

## 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

## 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

## 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

## Tropopause Fold Turbulence Prediction(Tony Wimmers, UW/CIMSS)

**Tropopause Fold Turbulence Prediction*****(Tony Wimmers, UW/CIMSS)***

- Background
- Algorithm basics
- Adapting the algorithm to aircraft hazard awareness
- Latest developments

## Background

## Background: Tropopause folding and Clear Air Turbulence (CAT)

**Background: Tropopause folding and ****Clear Air Turbulence (CAT)**

*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

## Background: GOES Layer-Average Specific Humidity (GLASH)

**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.

## Background: Synoptic-scale UTH

## Background: Synoptic-scale UTH

**300 hPa Potential **
**Vorticity**

## Background: Validation with aircraft ozone lidar

**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.

## Algorithm basics

## 1. Humidity product(cloud masked)

**longitude**

**latitude**

- decreasing specific humidity

## 2. Smoothed gradient of humidity product

**longitude**

**latitude**

- decreasing specific humidity

**longitude**

**latitude**

## 3. Contour along boundaries

**3. Contour along boundaries**

**longitude**

**latitude**

- decreasing specific humidity

**longitude**

**latitude**

## 4. Extend polygons out from boundaries

**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.

## Adapting the algorithm to aircraft hazard awareness

## Adapting to aircraft hazard awareness

**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

## Adapting to aircraft hazard awareness

- decreasing specific humidity

**longitude**

**latitude **

**2. Assign a vertical height to the trop. folds**

## Filtering cases of tropopause folding

**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)

## 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

## Recent developments

## Algorithm Development - Adaptation for operational use

**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

## Algorithm Development - Adaptation for operational use

**Algorithm Development - ****Adaptation for operational use**

- Test case output: Tropopause Fold minimum/maximum heights

## Algorithm Development - Adaptation for operational use

**Algorithm Development - ****Adaptation for operational use**

- Test case output: Tropopause Fold exposed flight directions

## Algorithm Development - Future objectives

**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)**

## 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

**Integrated System Solution (ISS) Diagram**