Satellite Derived Mid Upper Level Winds

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Satellite Derived Mid- Upper Level Winds
Cegeon Chan
MET 315 Remote Sensing
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Outline

• Importance
• Instruments
• Location Tracking
• Height Assignment
• Quality Control

http//apollo.lsc.vsc.edu/classes/remote/index.htm
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• Accuracy
• Summary

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Importance

• Over oceanic regions
• Dvorak Technique
• Wind vectors
• Numerical Weather Prediction

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Different Types

• cloud-drift
• 2) Water Vapor
• 3) Sounder WV
• 4) Visible

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What does it look like?

• Capable of gathering water vapor fields
• Measure infrared energy

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Imager
Sounder

• Responsible for NH and SH
• Low Frequency

• Responsible for the tropics
• High Frequency

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Tracking Background

• Similar to cloud tracking
• Algorithm is housed within McIdas!
• Very sensitive
• Rule at least 3 images to derive winds to
  produce 2 vectors
• Measures consistency between successive images

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Tracking Procedure

• Take a small area
• Isolate the lowest cloud brightness temperature
  within a pixel array

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Tracking Procedure (cont.)

• Compute bi-directional gradients are computed
• Cloud-free environments
• Generally in moist regimes

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Height Assignment

• Goal is to ascertain the height level of the
  feature you tracked
• Can be complicated if there are multiple moist
  layers

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Height Assignment (more)

• Convert measured radiance into Brightness
  Temperature
• This value is collocated with a model guess
  temperature

S. Velden, Christopher, Christopher M. Hayden,
Steven J. Nieman, W. Paul Menzel, Steven Wanzong,
James S. Goerss, 1997 Upper-Tropospheric Winds
Derived from Geostationary Satellite Water Vapor
Observations. Bulletin of the American
Meteorological Society Vol. 78, No. 2, pp.
173173
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Quality Control Algorithm

• Slow using cloud drift winds
• Add 8 for 10m/s
• Incorporate satellite winds into analysis
• Remove those differing significantly from analysis

• Yellow minus satellite
• Red Plus satellite

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Accuracy how good is it?

• A particular single level does not represent a
  layer
• Generally good for 50 mb

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Sources of Errors

• Assumption of clouds and water vapor
• Image registration errors
• Target identification and tracking errors
• Inaccurate height assignment

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Summary

• Great applications oceanic analysis, tropical
  cyclones
• Improved numerical weather analysis and
  prediction systems
• Similar to cloud tracking method
• Tendency to be slow

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