Global aviation turbulence forecasting using the Graphical Turbulence Guidance (GTG) for

the WAFS Block UpgradesR. Sharman1, J.-H. Kim2, and C. Bartholomew3

National Center for Atmospheric Research, Boulder, CO, USA 1

NOAA/Aviation Weather Center, Kansas City, MO, USA 2

The Met Office, Exeter, UK 3

Aviation Turbulence: Background

• Aircraft scale turbulence from all sources is too smallto directly predict (~100m-1 km)

• Must infer its presence from larger scales

• Many sources

From Lester 1994

Turbulence forecasting for the World Area Forecast System (WAFS)

• Provides global forecasts of significant weather for strategic flight planning

• Based on forecasts from 2 WAFCs (World Area Forecast Centers) in London UK and Washington DC USA

• Established and administered by ICAO and WMO• ICAO requested upgrades provided at regular intervals to

accommodate new technologies in aviation weather forecasting

• Implemented in Aviation System Block Upgrade (ABSU)– Current: 6-36 hr forecasts updated every 6-hr on 1.25°x1.25°

grid– ABSU 0 (~2019): Same forecasts but on 0.5 °x 0.5° grid– ABSU 1 (~2024): Probabilistic forecasts on 0.25°x 0.25° grid– ABSU 2 (~2030): Integrated flight planning

Introduction to WAFS

Significant Weather (SIGWX) charts (Prog charts)

- World Area Forecast

Center (WAFC) Washington

(US; AWC) and London

(UK; MO)

● Man-made Progchart

● Jet, CAT, and Cb

● Issues 4 times a day at 00,

06, 12, 18 UTC

● 24-hr forecast snapshot

● Layer and Freq. info.

Introduction to WAFS

WAFS grids for Jet, CAT, and Cb top

- WAFS Blended Max

between two WAFCs.

● Automated grid forecasts

● 06 - 36 hr fcsts with 3-hr

interval

● Issues at 00, 06, 12, 18 UTC

● Potentials for Clear-Air

Turbulence using Ellrod

index

WAFS Upgrade for turbulence forecasting• WAFS upgrade plan until 2019 (ICAO ASBU 0):

– Use the Graphical Turbulence Guidance (GTG) – Forecasts energy dissipation rate (ε)^1/3 (EDR)

» ICAO reporting standard for turbulence measurements» metric for atmospheric turbulence intensity (aircraft

independent)» Directly related to aircraft loads» convenient 0-1 scale (m2/3 s-1)» For mid-sized aircraft: “light”~0.15, “moderate’~0.22,

“severe”~0.35– Provides explicit forecasts of clear-air turbulence (CAT) and

mountain wave turbulence (MWT) both EDR– Based on NWP models from London and Washington WAFCs

» Unified model (UM) ~10 km» Global forecast system (GFS) ~ 13 km

– Final product is a blend of the two

Graphical Turbulence Guidance (GTG)*

• Use NWP model (global or regional) to compute a suite of “turbulence diagnostics” typically related to large scale spatial variations

• Multiple causes require multiple forecasting strategies →

– Ds depend on source (“CAT”, MWT, CIT) and altitude region (high, middle, low)

– D*s are calibrated Ds to EDR assuming a log-normal distribution of EDR in upper troposphere and lower stratosphere (UTLS)

– Ws from turbulence measurements – GTG (or G-GTG) is weighted ensemble mean– Verified against 1000s of PIREPs and in situ EDR data

GTG = W1D1* + W2D2* + W3D3* + ….

*Ref: Sharman et al. Wea Fcsting 2006,Sharman and Pearson JAMC 2017

Some Traditional Turbulence Diagnostics

• Richardson Number

• Frontogenesis function (good at upper levels)

• Divergence tendency

• Deformation x shear (“Ellrod index”)

( )22 units2 ( , ) st

J u v f uζ β −∂∆=

∂−∇ Φ+ + −

( )1/22 2 2,

(Ellrod and Knox . 2010)

(units )

" 3": 0

SH ST

SH ST

vDEF D D

zv u u v

D Dx y x y

Wea Forecasting

I DEF r st

Ellrod r

−∂= +

∂

∂ ∂ ∂ ∂= + = −∂ ∂ ∂ ∂

∂∆ = + = ∂

≠

13 u v w u v w u v wF D x x x y x z x y x y y y z y z x z y z z zθ θ θ θ θ θ θ θ θ θ θ θ

θ

∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂=− + + + + + + +∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂∇

+

2

2(nondimensional)c

vz

NRi Ri<∂∂

=

G-GTG schematic

MO UM

Compute CAT, MWT diagnostics (typically

10-15)

Remap diagnostics

to EDR

Combine diagnostics (ensemble mean or

probabilistic)

NOAA GFS

Compute CAT, MWT diagnostics (typically

10-15)

Remap diagnostics

to EDR

Combine diagnostics (ensemble mean or

probabilistic)

} Blended GTG

Example remapping case: GFS

GTG CAT, MWT, MAX

GTG from NOAA GFS, UK UMCAT MWT MAX

GFS

diff

UM

GFS/UM Blend

Verification: Case study of MWT over Greenland

Statistical verification against automated EDR reports from DAL aircraft

Use GTG diagnostics as ensemble to produce probabilities of exceeding a

certain EDR

Ensemble mean vs probability of EDR>0.22

Ensemble mean Probability

Can use G-GTG Ds computed with different NWP ensembles to produce probabilities: GEFS

Ensemble Prob. > 0.2 EDR

5 CAT/5 MWT diagnostics

x21 GEFS ensemblemembers

=EnsembleProbability> 0.2 EDR

12-h fcst

18-h fcst

Need for more observations• In the GTG approach performance depends on large dataset of

observations to form reliable statistical performance metrics• Observations of EDR are preferred since they correspond to what is

being predicted and EDR is the ICAO standard for reporting• In particular need more observations in the S. Hemisphere• In situ EDR measurements are being expanded

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– Boeing offers EDR package on new aircraft with AIMS-2 avionics

– EDR software package is free to interested air lines from NCAR

– DAL 767s and 777s currently implemented

– International carriers may soon implement this (Xiamen, Air France, Lufthansa, Qantas…)

– Private vendors (accessibility, standard?)

Courtesy Tim Rahmes, BoeingCourtesy Tim Rahmes, Boeing

Summary and future work• G-GTG has been developed for use with several regional and global NWP

models: (NOAA GFS, UK UM, ECMWF, NOAA RAP, NOAA HRRR) • G-GTG will become turbulence forecast product provided by the World

Area Forecast System (WAFS)– Washington: Uses NOAA GFS at EMC– London: Uses UKMO UM at Exeter– Grids merged at EMC

• Performing case studies• Gathering more global observations• Developing CIT diagnostics• Testing with ensembles using GEFS and MOGREPS-G to predict

probabilities of exceeding certain EDR level

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This research is in response to requirements and fundingby the Federal Aviation Administration (FAA). The views expressed arethose of the authors and do not necessarily represent the official policy

or position of the FAA.

Ref: Kim et al., Aviation Turbulence Forecast Technique for the World Area Forecast System (WAFS) Submitted to Bull. Amer. Meteror. Soc.

Thank you