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SWOT Science Team meeting, March 2010
Towards an end‐to‐end of simula2on of SWOT performance for mesoscale and sub‐mesoscale
circula2on monitoring
P.Y. Le Traon, P. Klein, B. Chapron (Ifremer)
M.I. Pujol, G. Dibarboure (CLS)
SWOT Science Team meeting, March 2010
Ifremer/CLSstudyforSWOTprepara6on
Analysis of sampling capabili2es of SWOT using very high resolu2on basin scale model (1 ‐2 km) (SSH, velocity and ver2cal velocity).
Analysis of SWOT measurement errors (white/correlated noise, roll errors) and their impact on mission objec2ves.
Use tools developed and tested for conven2onal mul2ple al2meter and WSOA studies (Le Traon et al. 2001; Le Traon and Dibarboure, 2002).
A major issue is to have a precise error budget for SWOT and to analyze the impact of post‐processing of SWOT data on ocean signals (e.g. roll error reduc2on)
Study is on going (see hereaVer).
SWOT Science Team meeting, March 2010
Highresolu6onal6metry(SWOT)
mesoscale/submesoscaleinves6ga6ons
• Shouldallowacharacteriza6onofsubmesoscalesignals.Scales(wavelengths/2)between10and100km.
• Noiseisamajorissue(agoalof1cm/1kmforanuncorrelatednoiseisquitechallenging!).
• Timesamplingisanissue(exceptforthe3dayrepeatcycles)
Ducet et al., 2000
SWOT noise level ? (1 cm / 1 km)
10-20 km
Conventional altimeter noise level (2.5 cm – 7 km)
SWOT Science Team meeting, March 2010
SWOT OSSE
Reference data set: 50 days of SLA maps from two models : EarthSimulator (ES) and POP. ES has (much) more energy at short wavelengths (< 100 km) and high frequencies (< 10 days)
ES RMS(SLA)
0 20 cm
38
SLA
-40 40 cm
POP
38 SLA
-40 40
38 RMS(SLA)
0 40 cm
Model resolution: ES : 0.017°x0.032°; 12 h POP: 0.1°x0.1° and 3 days
SWOT Science Team meeting, March 2010
SWOT J2+EN+ GFO+J1N
J2+EN+GFO J2+EN
4 constellations studied :
SLA reconstruction with Objective Analysis method:
final grid resolution :1/8° - every 3 days
correlation scales: 100 km / 10 days
OSSE study
SWOT Science Team meeting, March 2010
Sampling effect on SLA
SWOT alone gives same results (ES), even better (POP), than for the 4-satellite constellation ES larger errors are due to small scales signals not present in POP simulation
50 % 2
J2+EN J2+EN+GFO J2+EN+GFO+J1N SWOT
Mapping error (in % of signal variance)
SLA error over high-variability areas (in % of signal variance)
-18% -32%
-28% -29%
-1% -22%
ES
POP
No noise considered in this part. “Perfect” measurements.
SWOT Science Team meeting, March 2010
With ES, the main part of the errors observed are induced by small scale structures ES : high-frequency↔ short and long wave signals POP : high-frequency↔ long wave signals (> 100 km)
From ES : entire signal
Frm ES : Long-wave (> 100 km) and low frequency (> 10 days)
From ES : Low-frequency part (> 10 days)
From ES : Long-wave signal (> 100 km)
From POP : entire signal
Sampling effect on SLA long/short‐wave and low/high‐frequency component
SLA error over high-variability areas, deduced from different reference signals (in % of signal variance)
Reference signals used
No noise considered in this part
SWOT Science Team meeting, March 2010
Sampling effect on SLA Sensibility to the la2tude with SWOT
In inter-track areas, SWOT SLA error budget is multiplied by 2. SWOT should be combined with others satellites
Formal mapping error (in % of signal variance)
50 % 2
SWOT 38°N
SWOT 45°N
-18% -28%
-28% -23%
-1% +153%
SLA error over high-variability areas (in % of signal variance)
ES (38°N)
ES (45°N)
No noise considered in this part
SWOT Science Team meeting, March 2010
The white noise: 3 cm rms for nadir measurement (corresponds to the real observation case) 0.45 cm rms for SWOT wide swath (corresponds to the optimistic case of white noise reduction)
Roll-error (SWOT): max 3.5 cm rms on swath extremity (pessimistic case [2 arcsec/120s] reduced to [0.1 arcsec/120s] after correction)
Residual orbit error: 1 cm rms / orbit and ½ orbit length
3 different noises are taken into account :
Impact of measurement noise (on going)
SWOT Science Team meeting, March 2010
Conclusions / Perspec2ves
SWOT alone gives equivalent results as with a conventional 4-altimeter constellation (mean mapping error) (even when taking into account noise)
These preliminary studies need to be completed:
Better parameterization of measurement noise and objective analysis
o higher white noise on SWOT wide swath and variable in space
o case of nadir absence on SWOT to be considered
o better parameterization of the noise for objective analysis
o adjustment of correlation scales and final grid resolution
Computational method is now extended to velocity (done) and 3D vertical velocity (using SQG approximation).
Analysis of SWOT results along the swaths only (snapshots)
Analysis of the 3-day repeat cycle
Analysis of the SWOT results combined with other satellites
SWOT Science Team meeting, March 2010
Recommenda6ons
Tools are in place to simulate the expected contribu2ons of SWOT. We plan to report on these studies at the next OST and Lisbon workshop.
Need a be\er/consolidated error budget for SWOT. Need also from the project to iden2fy the main scenarii that could be tested.
Need to simulate the effect of SWOT data (post) processing as part of this study. This post processing will likley remove ocean signals and this must be quan2fied (e.g. removing an along track slope over 1500 km on al2meter SLA does impact the mesoscale signals – see Le Traon, Boissier, Gaspar, JAOT, 1991).
We will also simulate the impact of the fast repeat cycle (3 days). Only this mode will allow (over limited areas) a space/2me monitoring of mesocale/submesoscale circula2on. The 10 day sampling will « only » provide a series of high resolu2on snapshots at 10 day interval.