Future altimeter systems : is mesoscale observability guaranteed for operational oceanography P.Escu

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Future altimeter systems is mesoscale
observability guaranteed for operational
oceanography?P.Escudier, G.Dibarboure,
J.Dorandeu, CLS, Space Oceanography Division
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Overview

• Until recently, the exceptional longevity of T/P
  and GFO added to the performance of Jason and
  ENVISAT were hiding the risk of future data gaps.
  
• The current missions are still performing well
  but exceeding designed lifetime
• With the current launch schedule (Jason2,
  CryoSat, AltiKa, Sentinel) can we guarantee a
  sufficient mesoscale observability for new and
  developing applications and for operational
  oceanography ?
• Use a probabilistic model to better assess the
  odds of having an observing system (multiple
  altimeters) accurate enough

• Minimum needed to monitor mesoscale structures
• 2 satellites in delayed time (offline),
• 3 satellites or more in near real time (Pascual
  et al)

Question asked in Venice meeting (2006)
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EKE in the Mediterranean sea depending on the
satellite configuration
50
350
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Approach and model used

• Lifespan probability model of a satellite driven
  by platform and payload design.
• Probability function approximated with a simple
  model fitted on lifespan computations from AAS

• Probability function for Each mission based
• launch date,
• expected lifespan as announced
• specific cases taken into account
• Cryosat considered as 50 operational on ocean
  payload limitation, non-repetitive ground track
• Lifetime limitation
• ie propellant limit for ENVISAT
• Missions grouped by ground track
• redundant measurements are not stacked, but
  likelihood to have the ground track covered
  increases
• Individual probability function combined to
  compute combinatorial probabilities

Probability function used for an altimeter with a
5 year lifespan
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Model validation

• The probability model is validated using
  historical datasets.
• actual coverage on ocean taken into account
  platform/payload events,
• Agreement between model prediction and observed
  reality fairly good
• Most significant differences
• GFO post-launch anomalies
• unexpected longevity of T/P
• In both cases, the event is against the base
  probability assumptions on the satellite 100
  success rate at launch, and 2.2 lifespan max

Number of Altimeters in operation
Data losses
T/P
ENVISAT
Jason1
GFO
ERS2
ERS1
Model
Reality
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Will altimetry provide the input needed by near
real time applications ?

• Probability to have the minimum observing system
  needed to monitor mesoscale
• 2 satellites for delayed time applications (red),
  
• 3 satellites for near real time applications
  (blue)
• Critical situations
• Probability less than 10 in 2008 for near real
  time applications,Probability less than 25
  until CryoSat.
• Odds fall down to 30 after the scheduled end of
  ENVISAT in 2010, and until both Sentinel-3 are
  operational
• Results are arguably optimistic
• altimeters assumed to be operational just after
  launch
• 100 launch success rate
• HY-2 to be added
• Jason-3 to be confirmed
• Launch dates to be tunedaccording to latest infos

Probability to get 2 satellites
available Probability to get 3 satellites
available
Jason -3
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Jason tandem phase

• The probabilistic model was used to explore
  alternate scenarios and to assess the impact of
  various decisions on the minimum observability
  needed for Near Real Time applications and
  operational oceanography
• As an illustration, shifting Jason-1 on a
  different orbit (tandem phase, similar to the
  Jason/TP phase in 2003/2005) would improve the
  NRT odds by 20
• The cross-calibration of both Jasons is
  mandatory, but if the tandem phase does not
  start six months after launch, the odds of
  getting the minimum NRT data reach 0

Probability to have the minimum NRT observability
without a Jason-1 tandem mission (green), or with
a Jason-1 tandem phase 6 months (red) or 1 year
(blue) after the launch of Jason-2
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Exploiting CryoSat data

• Similarly, an additional 20 chances can be
  gained if CryoSat data are fully exploited with a
  complete coverage on ocean (ice ocean as
  primary mission), and better geophysical
  corrections/references
• improved MSS to balance out the non-repetitive
  ground track,
• Improved model for ionosphere correction
• Improved model for wet troposphere correction

Probability to have the minimum NRT observability
with opportunistic ocean data from an
ice-oriented CryoSat (blue) and with perfect
ocean coverage and improved geophysical
corrections (green)
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Summary and Conclusions

• Minimum number of satellites in operations needed
  to monitor mesoscale structures
• 2 satellites in delayed time (offline studies)
• 3 satellites or more in near real time
• Simple probability model used to assess the odds
  of having an observing system (multiple
  altimeters) accurate enough to provide the input
  measurements needed for offline and Near Real
  Time applications
• Validation with historical data good
  consistency and global predictions but unexpected
  boolean events (T/P longevity, launch failure) ?
  Improvements possible on model
• Offline mesoscale observability is likely (Pgt60
  after Jason-2)
• Odds of meeting the NRT requirements are very
  poor until Jason-3 both Sentinel-3 (Plt25 until
  2010, and 40 until 2011). It is ironically when
  operational oceanography and NRT applications
  start to be fruitful that NRT altimeter data may
  be lacking.
• Odds can be improved with a Jason tandem phase or
  a better use of CryoSat on ocean
• One more reliable altimeter launched before 2013
  would almost double the NRT odds