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Envisat: Near Real Time Processing and Oceanography

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Envisat: Near Real Time Processing and Oceanography. Envisat CCVT Meeting. Kirk Whitmer Gregg Jacobs JE Sverdrup/NRL Stennis Space Center, MS, USA. ALPS and ODDITIES. ALPS : Near real time data processing system Data is quality checked at each step and suspect data is flagged

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Presentation Transcript
slide1
Envisat: Near Real Time Processing

and Oceanography

Envisat CCVT Meeting

Kirk Whitmer

Gregg Jacobs

JE Sverdrup/NRL

Stennis Space Center, MS, USA

slide2
ALPS and ODDITIES
  • ALPS: Near real time data processing system
  • Data is quality checked at each step
  • and suspect data is flagged
  • Must err on the side of caution because of
  • subsequent subsystems
  • Run daily at NRL and NAVO
  • ODDITIES: Graphical data analysis system
  • Results displayed on

The Real Time Ocean Environment website

  • www.ocean.nrlssc.navy.mil/altimetry
  • Run daily at NRL

Envisat imar data fed into the systems…

slide3
read: data is read from gdrs

into ALPS format

  • Smooth electromagnetic bias and
  • wet troposphere along track
  • Apply correction terms to height:
  • Wet troposphere, Dry troposphere
  • Inverse barometer, Solid tide
  • Ionosphere, Electromagnetic bias
  • Check for minimum number of high rate values (>15)
  • Check flag for water (sea ice?)
slide4
Ionosphere drop plot

Ku band correction only

Doris Ku band correction only

All ionosphere corrections applied:

Ku band correction

Doris Ku band correction

Model Ku band correction

slide5
interp: data is interpolated to

reference ground tracks

  • Minimum number of points needed to interpolate
  • Interpolation incorporates the geoid gradient
  • Along track smoothing
slide6
Data too sparse to interpolate to ground tracks
  • Single largest contributor to “dropped” data points
slide7
aptide:tides are removed
  • got00.2 tide model applied
  • No points are dropped
slide8
orbgem:orbit correction calculated

and applied

  • Long term mean and climactic mean removed
  • Iterative sinusoidal fit calculation
  • Return means
  • Apply correction based on fit
slide9
Orbit correction magnitude

Mean: 60.7 cm

RMS: 74.0 cm

slide11
apply: mean removed
  • Along track “box car” filter
  • Sanity checks
slide12
Sea ice issue?

High latitude makes

ice more important

Detection algorithm

or flag desireable

SSH anomaly plot suggests many

sea ice points remaining

slide14
Jason-1
  • Multiple causes for ice point drops
  • Lower latitude reduces importance
slide15
Percent data utilized

Jason (osdr) 84.73/85.20 %

Jason (igdr) 90.17/90.17 %

Ers-2 84.22/90.26 %

GFO (doppler) 87.49/87.49 %

GFO (laser) 90.30/90.30 %

slide17
Altimeter cross track intercomparisons
  • High latitude values sea ice influenced
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