Radar altimetry Frontiers 4:

1
Part 4

• Radar altimetry Frontiers (4)
• Altimetric gravity field in shallow water
• Altimetric gravity field in polar regions
• Gravity fields in lakes.
• Merging altimetry with other sources
• New Geopotential Models (GRACE, EGM05)
• Mean sea surface and ocean variability
• Time variations (5)
• El Nino
• Long Term Sea Level Change.
• Ocean Tides.
• Real Time altimetry
• Laser Altimetry. (6)

2
Gravity in shallow water

• Problem that sea state is high, and data are bad
  because of land-contamination.
• Altimetric data must look like normal ocean
  like waveform (Brown model) in order to determine
  the sea surface height.
• High percentages of sea ice-like and patch
  waveforms, and low percentages (10) of ocean
  waveforms are observed up to 5 km from the coast.
  
• After about 25 km ocean waveforms dominate
• The trick is to retrack data allowing for more
  waveform
• types (more by P Berry).
• This yields many more data close to the coast.

3
Retracking ERS-1 GM for geodetic purposes.

• ERS-GM have been retracked using the EAPRS
  rule-based Expert System (P. Berry - De Montford
  University).
• System contains 11 retrackers tuned for
  land,ocean, and ice retracking.
• The retrack-inversion uses logaritmic noise
  transformation.
• Retracking is more complicated but superior to
  retracking by Sandwell/Smith and GTech.
• Lakes, Ice evertying is retracked.

Much more by P. Berry
4
1 Hz NonRetracked
5
2 Hz.retracked
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Polar regions.

• Problem that only a few altimetric data look
  like normal ocean like waveform (Brown
  model).
• Only very few data from open water between or on
• Ice will create normal waveform.
• The trick is AGAIN to retrack
• data allowing for more
• Waveform types (more by P Berry).

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East Greenland importance of Retracking
1Hz Retracked Unretracked
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Comparisons.
LaxonMcAdoo 97
KMS04
Error - No data east of 15W
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Lakes
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Lake Victoria - Africa
Altimeter is in ice-model so only ice
retrackers can be use. Data is mainly retracked
using the EAPRS thresshold retracker. ocean-retrac
ker can be modified to retrack icedata (testing
ongoing)
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Lake Victoria
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Smaller lakes
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Merging Altimetry with other sources.

• Data in coastal regions (Disko Bay) on the West
  Greenland coast
• Airborne
• Marine
• Altimetry

14
Merging altimetry airborne gravity data.

• Using LSC to merge data
• Altimetric geoid height with airborne gravity
  observations
• Aposteriori gravity error.
• C Covariances,
• D Noise variance

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Interpolated onto high quality marine
observations.

• Notice Airborne constrain the mean value of
  altimetry.
• Airborne compared considerably better with marine
  data at x-over locations.

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New Satellites.

• CHAMP 2000, GRACE 2002, GOCE 2006
• Will improve global geopotential models at longer
  spatial
• wavelength
• With better geoid, we will also get better
  separation of
• mean dynamic topography using altimetry to
  constrain
• Mean Sea surface height

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EGM05.

• EGM96 Geoid Absolute Accuracy - worldwide 50 cm -
  1 meter (total omission commission global rms
  error to nm360)
• Next EGM Geoid Accuracy Goal - worldwide 15 cm
• (total omission commission global rms error to
  nm720)
• based on new satellite mission data from CHAMP,
  GRACE, GOCE
• new surface and airborne gravity data
• improved modeling of the data
• 4 cm commission error from GRACE and GOCE out to
  nm300
• 9 cm omission error beyond 720 following Kaula's
  Rule
• NMAs detailed gravity data are expected to meet
  a 11 cm commission error requirement for degrees
  301-720.
• KMS coorporates extensively with NMA on
  delivering airbornealtimetric gravity

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Mean Sea surfaces

• Reference surface
• Geo-centric
• Consistent with GPS / GNSS
• Example Mean sea surface from a merge of about
  10 years of altimetric sea surface heights.
• Study the MSS N MDT (GOCINA / OCTAS)
• Used to map mean currents MDT MSS-N

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KMS04 Global Mean sea surface.
In principle complete coverage in space and time
is needed. Get the best out of ERM (Variability
averaged out and GM (high spatial resolution)

• Completed March 2004.
• Derived from T/P, T/P TDM, ERS1 ERM, ERS2 ERM,
  GFO ERM data.
• Geosat GM, and ERS-1 GM data
• Based on 9 years of data using T/P as reference
  (all satellites referenced to T/P)
• Based on Pathfinder Data (ERM), RADS Data (GM)
• High resolution, 2 min grid. (82S to 82N)
• Editing relative to GGM01S
• EGM96 hybrid geoid model.

KMS04-N(EGM96)
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KMS04MSSError Field.
Accuracy 4 cm
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GOCINA is an EU FP5 project to improve Geoid M
ean Sea Surface Mean Dynamic Topography Investi
gating MSS N MDT Compare best MSS
(KMS04 MSS) N GRACE Airborne Tallin Geoid
MDT Ensemble of OCCAM, RIO Investigate
differences/errors to learn more. For joint
exploitation of ENVISAT and GOCE in ocean
circulation studies Climate modeling Operatio
nal assimilation
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EGM
EGM
GRACE
GRACE
OCCAM
WSOA
GOCINA
(Tapley et al. GRL, 2004)
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Arctic Ocean
KMS04 EGM96
KMS04 GGM01 / EGM96