Future altimetry design From impact studies to operational metrics or the reverse

1
Future altimetry designFrom impact studies to
operational metrics or the reverse ?
G.DibarboureJ.DorandeuP.Escudier
2
Introduction

• Should early impact studies define operational
  metrics or the reverse ?
• Framework support to future mission design
  (ESA, CNES, Eumetsat, Ifremer)
• Definition of Sentinel-3, Phasing options for the
  Jason tandem
• Figure of merits for future altimetry concepts
  wide-swath, large constellations
• Impact of payload changes noise level
  reduction, cost reduction
• Exploratory studies
• Iterative process (mission concept ? performance
  assessement)
• CLS Toolbox for Mission Analysis Testing and
  Optimisation (TOMATO)
• Two types of analysis mission analysis OI
  based OSSEs
• Need simple yet compelling results
• Subtle payload differences ? ? Metrics used must
  give a clear answer
• Conflicting mission objectives (e.g. OC vs
  Altimetry on S3) ?? Altimetry metrics must be
  convincing for decision-makers? E.g 15 of
  additional variability observed is not convincing
  for neophytes
• Illustration of the DUACS approach through two
  ongoing studies Post-EPS reference orbit
  High-resolution altimetry

3
Example 1 Post-EPS reference orbit

• Question asked by Eumetsat which orbit should
  be used for future reference missions ?
• Reference orbit (T/P, Jason) is exceedingly
  aggressive
• Onboard anomalies and failure (Jason-1 has burnt
  most redundant safeties)
• The motivations behind the TP orbit choice are no
  longer major constraints
• Many factors to take into account
• History and existing time series
• Sampling capability, Aliasing issues
• Error budget (e.g. POD performance vs orbit
  parameters)
• Many applications climate, mesoscale, ice
  monitoring, hydrology
• Mission cost (launch, operations, mission
  lifespan)
• And other altimetry missions !
• Unlikely to find a single perfect orbit, so the
  study rationale is to
• Sort out (many) bad options ? first filter no
  time wasted
• Analyze orbit candidates with more details ?
  second filter process when in doubt, trash it
• Keep only a handful of interesting orbits for the
  community to check out

4
Post-EPS Aliasing analyses

• First filter orbit geometry and base properties
• Acceptable altitude and inclination range
• Repetitive
• Acceptable repeat (sub)cycle duration
• Optimal to host a tandem of 2 altimeters
• Second filter tidal components
• Must allow tidal wave observation within 3 to 5
  years(aliasing under control)
• Tidal components must be separable within a
  reasonable time span
• Basic selection leads to 1400 options
• Drastic separability requirements 0 option
• Trade-offs ? many options with different
  pros/cons

5
Post EPS multi-satellite sampling analysis

• Geometrical sampling analysis (no model, no OI)
• Observation quality (correlation between
  structure and observation)
• Ability to detect mesoscale changes in NRT
• Observation isotropy (e.g. currents mapping,
  crossovers)
• Structure monitoring/tracking capability
• Protocol validation on historical missions
• After this screening process 12 candidates
  interesting

6
Post-EPS - Output of step 1 first orbit
selection
Initial selection (tidal filter nominal)
Additional selection (relaxed tidal aliasing
requirements, except on 4-9 cpy climate band)
7
Post-EPS Mesoscale sampling capability (1/2)

• Analysis performed from OI OSSE based on Mercator
  simulations
• Mercator  reality  ? Observation simulated ? OI
  used to reconstruct
• Reconstruction error gives access the sampling
  capability

8
Post-EPS Mesoscale sampling capability (2/2)

• Once suboptimal options are removed, the mapping
  processoffsets uneven sampling ?
  minordifferences
• Sampling error on U/V vary by 10 in non
  coordinated tandems
• Impact of orbit inclination on sampling isotropy
  still still visible after mapping (especially
  combined with high-inclination S3)
• Three good candidates (T/P-like with 10 more
  data thanks to lower altitude) results coherent
  with geometrical analysis
• SWOT orbit 22d is not the best option to host
  (only) a traditional altimeter
• Any contribution from GODAE would be useful to
  complete this study (model-based OSSE, metrics
  suggested)

9
Example 2 High resolution altimetry

• Explore the benefits of a 24 satellite
  constellation (Nadir only)
• Next generation of Iridium altimeter payload
  passengers ?
• Cost minimized (minimal payload, error budget
  tradeoffs)
• Comparison to a global wide-swath altimeter
  observation
• Impact of noise reduction (AltiKa, doppler
  altimetry, SWOT)
• First step geometrical analysis
• To provide a first quantification of the benefits
• To tune the altimeter payload distribution on the
  66 potential Iridium slots
• To explore multiple timespatial scales (e.g.
  meteo, mesoscale, submeso)
• Second step OI impact study on (sub)mesoscale
• Needed to quantify the impact on currents and
  vorticityand the HF or short scale specific
  error
• Work performed with support from CNES and Ifremer

Up Jason cycle / sub-cycle scanning
pattern Down Space/Time scale observation limit
10
High-resolution altimetry geometrical analysis
Constellation detection and monitoring skill
(left 150km, right 20km)
Instantaneous correlation between one snapshot
and past altimetry data (realistic correlation
model 150km/15d, arbitrary snapshot from day 12)
11
High-resolution altimetry OI impact study
Model EKE Los Alamos 1/10

• Reality used POP or Earth Simulator (ES)
  outputs
• Configurations analysed 1 to 4 sats, 24 Iridium,
  SWOT
• Realistic error levels on simulated observations
• Ongoing work
• Actual mapping reconstruction error (H,U/V,
  Vorticity)
• First step crude mapping parameters (100km, 5
  to 10d)
• Separation of error on HF/LF content (time
  space)
• Separation of error from mapping limitations
  sampling limitations
• For POP content SWOT sampling is good and Iridium
  excellent
• For ES, SWOT temporal sampling is more
  problematic, but correlation scales must be
  revisited

2000cm²/s²
Model EKE ES
12
High-resolution altimetry impact of noise level
SSH power spectrum (Jason-2 simulated data from
ES reality variable HF error level)

• Starting question how does the altimeter data
  high frequency error (instrument noise,
  processing error) affect the power spectrum ?
• Earth Simulator output ? Sampled along altimetry
  ground tracks (50 days of ideal obs)
• Variable white noise ? Realistic observations
• Consistent with spectrum slope of actual data in
  GulfStream (-3.4 for 90-200 km for 2.5 to 3cm
  HF content)
• Impact of SWOT rollbaseline error far range
  spectrum is K-3 and increasing to K-11/3 as the
  data get closer to the Nadir position in swath
• Reducing the high-frequency error is important
  Ka-Band, Doppler, SLOOP project processing

3 cm
K-5 or K-11/3 ?
1 cm
3 mm
13
Summary and Conclusion

• Overview of ongoing studies
• Long term questions new reference orbit, impact
  of HF error, high-resolution sampling
• Short answers 3 good orbits, reduce the noise,
  attractive 24 satellite concept (complement to
  SWOT )
• Two-types of studies carried out by CLS mission
  analysis OI impact studies
• Excellent way to explore unusual configurations
  or numerous variants (sort out poor options)
• Some metrics are more convincing for
  decision-makers than classical resultsE.g.
  mesocale can observed in real time with 12
  satellites is a stronger message than 4
  mesoscale observation error removed with 8 sats
• Full science content must be consolidated
  afterwards (finer quantification once the general
  concept is nailed down)
• Past impact studies helped define current
  operational metrics (DUACS K.P.I)
• Conversely any operational metric can be deployed
  for such a demonstration
• This logic is applicable to GODAE models
  design/impact studies ? operational metrics
• For future concepts, we need to be consistent
  with future operational metrics
• What routine-to-be metrics should be used to help
  design future observing systems ?
• So what will be requirements of GODAE models in
  2018 ?