andrew burton bureau of meteorology, perth, australia use of scatterometer winds in tc forecasting...
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![Page 1: Andrew Burton Bureau of Meteorology, Perth, Australia Use of Scatterometer Winds in TC Forecasting Tropical Cyclone Warning Centre Perth](https://reader033.vdocuments.us/reader033/viewer/2022042702/56649d6c5503460f94a4c3e6/html5/thumbnails/1.jpg)
Andrew BurtonBureau of Meteorology, Perth, Australia
Use of Scatterometer Winds in TC Forecasting
Tropical Cyclone Warning Centre Perth
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Application of Scatterometer to Tropical Cyclone Forecasting
• Formation• Size (radius of gales)• Wind distribution• Not for absolute intensity (winds saturate at >60 90? knots)
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Where to Get Scatterometer Data
• NRL Monterey http://www.nrlmry.navy.mil/tc_pages/tc_home.html
• NOAA/NESDIS QuikSCAT http://manati.wwb.noaa.gov/quikscat
Storms page – includes ambiguities: http://manati.wwb.noaa.gov/cgi-bin/
qscat_storm.pl Alternative NOAA site, with SSMI wind speeds:
http://polar.wwb.noaa.gov/winds/globdata.html• FNMOC
http://152.80.49.210/PUBLIC/SCAT or http://www.fnmoc.navy.mil/PUBLIC/SCAT• Remote Sensing Systems
http://www.ssmi.com
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NRL Monterey http://www.nrlmry.navy.mil/tc_pages/tc_home.html
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NOAA/NESDIS QuikSCAT http://manati.wwb.noaa.gov/quikscat
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FNMOChttp://152.80.49.210/PUBLIC/SCAT/
Near Real-Time Ambiguity Removal
FNMOC Ambiguity Removal over SSMI
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Remote Sensing Systemshttp://www.ssmi.com
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Scatterometer Coverage
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QuikSCAT: SeaWinds Measurements
From Dr. M. Freilich, Oregon State University
V-pol H-pol
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SeaWinds: Swath Geometry
From Dr. M. Freilich, Oregon State University
Red = V-polBlue = H-polEdge
View (2 solns) V-pol only
Subtrack View (4 solns,but small angle var)
Ideal View(4 solns, 90
deg var)
Forward Look
Backward Look
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Scatterometry: 2-Look Solutions
From Dr. M. Freilich, Oregon State University
1 2 3 4
Solution: wind ~10m/s at ?? degFrom Dr. M. Freilich, Oregon State University
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Scatterometry: 4-Look Solution(s)
From Dr. M. Freilich, Oregon State University
1 2
3 4
Most-likely solution: 10m/s at 40deg
From Dr. M. Freilich, Oregon State University
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Ambiguities: The Chicken-Scratch Diagram
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Location, Intensity, Wind Distribution
Source: Tropical storms discussion group
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25 Jan 1800Z 26 Jan 0517Z 26 Jan 1800Z
27 Jan 1712Z 28 Jan 0427Z
XX
X
X
O O
O
O
O
20S170W170W
170W170W
160W 160W
Small system (X) analysed for 3 days --no help from NWP model
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• Edge of swath (~ 7 wind vector cells)
• Rain effects
• Sensitivity to errors in NWP• Practical wind regime 3-45? m/s
(problems with both very light and very strong winds)
• Resolution (25km) – impact in tight gradients
• Ambiguity Removal Process and rain flag process can affect final solution
Interpretation Challenges
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Edge Problems
Along the whole edge… or small portion…
FNMOC DISPLAY
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•Position using the curvature outside ‘rain block’ region.
•Look for good north-south winds.
Rain Effects – “tear drop”
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Streamlines
X
Look for non-rain flagged winds
Beware of winds perpendicular to the swath, even when they are not flagged
TC Chris 03/02/02 0914Z
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Isotachs
X
Look for min speed near centreTC Chris 04/02/02 1002Z
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Errors in NWP
Wrong Model
Position?
TC Guillaume
19/02/02 1341Z
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Where is TC HUDAH?No circulation!
?
Max Winds 95 knots
Try to fix in trough equator-ward of the strongest winds
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?
? cc
Max Wind 55 KTS
(Light winds?) -----low skill
AVN 19/12Z tau 2420/2356Z
10S10S
20S
20S
In this case, poor model initialization combined with a lower skill nadir position, picks proper wind speed, but NO circulation center
TC Paul
Model initialization errors
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Comparing Different Solutions
FNMOC-NOGAPSFNMOC-NRT
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NRCS imageryNormalised Radar Cross Section
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14 S
10 S
18 S
92 E 88 E 84 E 92 E 88 E 84 E
Scatterometer winds give wrong estimate for centre
Comparison between Quikscat solution from NESDIS 30/11/2001 at 0023Z and fair LLCC seen in SSMI near 14.4S 89.1E 30/11/2001 at 0218Z
Microwave Imagery vs Quikscat
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Analysis Methods - Summary
• Ignore the bad - streamline the good
• Tear-drop – curved end
• TC’s – equatorward side of max wind
• Compare different solutions
• Isotach method – ignore direction
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Conclusions
• Provides coverage over data sparse areas
• Wind speeds generally good – useful for areas of gales etc
• Use the data if it makes sense
• Be aware of low skill areas and different ambiguity removal processes (compare!)
• Do not use in isolation