General background

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Remote Sensing/Satellite oceanography Pete
Strutton, Burt 356 strutton_at_coas.oregonstate.edu

• General background
• Satellite examples
• SST
• Sea level
• Wind stress
• Ocean color
• New technology

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Why Satellites?

• Oceans are vast and sparsely occupied
• Harsh environment for acquiring measurements
• Satellites can acquire measurements quickly over
  large areas
• BUT
• Cost, risk
• Must measure through intervening atmosphere
• Cant acquire sub-surface measurements

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Components of a remote sensing system
sensor
source
raw data
signal
processing / dissemination
calibration/ validation
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Geostationary Orbit Polar Orbit 36,000km
altitude (for wide view) 850km altitude Stays
over same location Travels over poles Can
document evolving systems Sees whole globe
High temporal resolution Low temporal
resolution Lower spatial resolution Higher
spatial resolution
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Sea Surface Temperature (SST)

• Perhaps the most standard measurement from
  satellites
• Traditionally used infrared (IR) emission
• obscured by clouds
• More recently using Microwave
• can see through clouds
• microwave also provides other data such as water
  vapor, rain, ice
• Temperature important because of its relationship
  to heat budget (global warming) and because its
  diagnostic of currents, upwelling etc

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Advanced Very High ResolutionRadiometer (AVHRR)

• Passive measurement
• Obscured by clouds
• Requires averaging to get good spatial coverage
• Image at right is 8 days, Jul 2006

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Microwave SSTSees through clouds, but obscured
by rain
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Sea Surface Height (SSH)

• Active measurement using microwave
• Pulse sent from satellite to earth, measure
  return time
• With appropriate processing and averaging, it is
  possible to calculate
• Deviations in ocean surface due to bathymetry
• Deviations in ocean surface due to internal
  physical variability
• Discern ocean currents, eddies etc

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Global Map of Seafloor Topography Based on
Altimetry
http//ibis.grdl.noaa.gov/cgi-bin/bathy/bathD.pl
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Wind Stress

• Active measurement, using microwave
• Pulse sent from satellite to ocean surface, then
  scattered depending on surface roughness
• Surface roughness a function of wind stress
• Strength of return to satellite gives wind stress
  and direction

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Scatterometry
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Ocean color (chlorophyll)

• Passive measurement
• Measures light emitted from the ocean - its
  color (careful to distinguish between
  emission and reflection)
• Most of the signal (gt90) at the satellite is NOT
  ocean color - atmospheric interference

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Sea-viewing Wide Field-of-view Sensor
SeaWiFS8-channels, 1km pixel
Main signals Atmosphere,reflection and ocean
color
Lw
Et
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Measuring chlorophyll from space
The Sea-viewing Wide Field of view Sensor SeaWiFS
The satellite
The instrument
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What SeaWiFS sees in one day
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Other remote sensingMoorings, gliders, floats
and AUVs

• Critical problem in oceanography of undersampling
• Large ships are expensive (20K per day)
• Ocean is vast
• Extremely difficult to sample even small areas
• Satellites help, but only sample the surface
• Need more automated subsurface sampling
• Challenges Power, cost and hostile environment
• (salt water, fouling)
• Could potentially make huge advances in global
  coverage

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Ocean observing technology Old school
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Ocean observing technology New school
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Ocean observing technology New school
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Awesome global coverage!
Imagine these floats with bio/chem sensors
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New technology Large Observatories
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New technology Autonomous underwater vehicles
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Gliders
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Summary

• Oceanography has traditionally faced a sampling
  limitation
• Satellites allow us to observe large areas
  quickly, but
• Only surface, and careful calibration/processing
  required
• Careful data handling required for long term
  data sets
• Parameters include SST, altimetry, winds, ice,
  water vapor, rain, chlorophyll, fluorescence
  (productivity)
• Other technologies evolving, both platforms and
  sensors
• Need to get smaller and more power efficient
• Need skilled people to analyze data and advance
  the science