Bruce Harper Andrew Burton

Wind Speed Time Averaging Conversions for Tropical Cyclone Conditions

Wind Speed Time Averaging Conversions for Tropical Cyclone Conditions

Systems Engineering Australia Pty Ltd

IBTrACS Workshop, Asheville, NC, USA, 5-7 May 2009.

Acknowledgements Authors

– Bruce Harper• Systems Engineering Australia

– Jeffrey Kepert• Bureau of Meteorology• Centre for Australian Weather and Climate Research, Melbourne.

– John Ginger• James Cook University• Cyclone Testing Station, Townsville.

WMO Client Representative•Jim Davidson, Bureau of Meteorology, Brisbane.

Internal reviews•James Franklin, Mark Powell, Peter Black, Craig Miller

IBTrACS Workshop, Asheville, NC, USA, 5-7 May 2009.

Questions/Issues– What do we mean by “mean wind”

and “gust”? – How do you compare wind speeds of

different averaging periods?– What does Vmax represent?

(What have we recorded in our Best Tracks?)

– Dvorak

Database Goals– Homogeneity– Transparency

IBTrACS Workshop, Asheville, NC, USA, 5-7 May 2009.

10-min meanHighest 1-min mean in 10-min

Highest 3-sec mean in 10-min

Thin line is the 1-sec averaged wind from a 10Hz sampling of 10 minutes of wind.

Circles are the 3-sec averages.

Thick horizontal bars are the 1-min averages.

Thin horizontal line is the 10-min average.

What do you mean by the “mean” wind?

You cannot convert between any of these estimates of the mean windbut

you can apply a spectral sampling theory to estimate the probability distribution of the variations about the true mean wind and obtain the most likely gust wind speeds

of a given duration within a specific period of observation.

IBTrACS Workshop, Asheville, NC, USA, 5-7 May 2009.

Gust factors• A gust factor is a theoretical conversion between

an estimate of the mean wind speed and the expected highest or “gust” wind speed of a given duration within a stated observation period.– applicable only in a statistical sense – isolated comparisons cannot be expected to match

theoretical values

• Gust factors depend on exposure• To be representative, certain conditions must be

met, many of which may not be exactly satisfied during a specific weather event or at a specific location.

IBTrACS Workshop, Asheville, NC, USA, 5-7 May 2009.

0

1

2

3

4

5

6

0.0010.010.11101001000Hours

Ene

rgy

Den

sity

(m

s-1

)2

5 s

7d 4 d

24 h 12 h

10 min

5 min

1 min

Mesoscale Microscale

"spectral gap"

Schematic energy spectrum of near-ground wind speed after Van der Hoven (1957)

Conflict between the Spectral Gap and the Need for Stationarity

IBTrACS Workshop, Asheville, NC, USA, 5-7 May 2009.

Converting Between Agency Estimates of Vmax

Table E-1 Comparison of recommended and traditional conversion factor approaches.

Conversion At-Sea Off-Sea Off-Land In-Land

Recommended

Method G600,3600/G60,3600

1.03/1.11=0.93

1.05/1.17=0.90

1.06/1.22=0.87

1.08/1.28=0.84

Comparison 1/G60,600 = G600,600/G60,600

0.95 0.90 0.86 0.83

Traditional See text 0.88

IBTrACS Workshop, Asheville, NC, USA, 5-7 May 2009.

Dvorak issues

• Most TC intensity estimates are based on Dvorak

• Dvorak is silent on wind averaging issues

• Dvorak calibration issues

• Generally held that Dvorak Vmax is 1-min average

• Atkinson and Holliday implies V60,300

IBTrACS Workshop, Asheville, NC, USA, 5-7 May 2009.

Dvorak & Transparency

• In most cases CI is the primary metric of intensity.

• For transparency CI must be in BT databases

• What do we do with historical BTs? (Where CI is not included)

IBTrACS Workshop, Asheville, NC, USA, 5-7 May 2009.

Reverse Engineering CIPressure-Wind Relation WA Tropical Cyclones

1985-2003

880

900

920

940

960

980

1000

1020

0 10 20 30 40 50 60 70 80

Vmax (m/s)

Pre

ssu

re (

hP

a)

1985-1992

1993-2002

1987-1989

A&H 10min

Dvorak Atlantic(1984)/A&H 1min

IBTrACS Workshop, Asheville, NC, USA, 5-7 May 2009.

Transparency

• Remove ambiguities, standardise wind definitions and nomenclature

• Rigorously record all metrics and metadata

IBTrACS Workshop, Asheville, NC, USA, 5-7 May 2009.

Summary

• Transparency is critical for future improvement• Improving homogeneity requires transparency• Harper et al study provides:

– a simplified yet consistent relationship for wind averaging conversions

– improved consistency (homogeneity) and recoverability (transparency)

– a strong basis for future work as better data increasingly becomes available

IBTrACS Workshop, Asheville, NC, USA, 5-7 May 2009.

Thank You

(and Bruce and Jeff)