1. Surface Water and Ocean Topography Mission (SWOT)
Lee-Lueng Fu (Jet Propulsion Laboratory)
The SWOT mission is being developed to meet the needs of two communities: oceanography and land hydrology. In this talk I will give a brief introduction to the mission and its ocean objectives. Doug Alsdorf will follow on the hydrology objectives.

2. A brief History
1998- Wide Swath Ocean Altimeter (WSOA) was selected for NASA’s Instrument Incubator Program (IIP).
2001 – Workshop on high-resolution ocean topography (chaired by Dudley Chelton).
2002 – Development of WSOA as a payload for OSTM/Jason-2 began.
2004 – WSOA was canceled due to budget problems (after spending $ 20 M on the program).
Joint US/European hydrology team formed and WatER proposal submitted to ESA (not selected due to programmatic issues)
2005 – Hydrosphere Mapper and WATER were submitted to the NRC Decadal Survey.
2007- Decadal Survey recommended SWOT as a combined mission for land hydrology and oceanography applications.
2007 – A joint informal NASA/CNES Science Working Group for SWOT was formed.
2008 – “Ka-band SAR Interferometry Studies for the SWOT Mission” was selected for NASA’s IIP.
2008 – NASA has authorized funding for risk-reduction studies of SWOT.
2008 – CNES plans to start a phase-A development of SWOT.

3. Space time sampling of radar altimetry missions
days
1000 km
100 km
This chart shows the fundamental trade-off between spatial and temporal sampling of conventional nadir-looking altimeters.
WSOA
10 km
SWOT

4. SWOT Measurement Concept
A SAR interferometry radar altimeter
h= H –r1 cos(Ө )
Conventional altimeters use pulse limited approach to get 1 km footprint for nadir returns. SWOT use a totally different approach. It will carry two radar antennas separated by a 10 m mast for interferometry measurement. Both antennas transmit and receive radar pulses. The return from a target on surface is received by both antennas. Although the range of the targets is precisely determined, we don’t know where the signal comes from, i.e., the incidence angle of the reception. Once the incidence angle is known, the height of the target is determined through triangulation.
Precision timing of the sampling system allows precise ranging of the returned signals.
Interferometry allows the determination of the direction of the signals from phase difference.
Use SAR technique to achieve resolution on the order of 50 m.
Spatial smoothing achieves measurement noise of 1 cm at 1 km resolution.

5. Radar Interferometry was successfully demonstrated by JPL’s Shuttle Radar Topography Mission (SRTM)

6. A Jason pass for the analysis of SSH signals and measurement errors
Now let’s take a look at the measurement of SSH made by existing altimeters at the meso- and submesoscales. I randomly selected a Jason pass crossing the eastern part of the Pacific Ocean.

7. SSH wavenumber spectrumkm
Jason pass 132 (147 cycle average)
k-3
Instrument noise
Power density (cm2/cycle/km)
k-2
SWOT noise at 1 km resolution
3 cm noise
30 km
1cm noise
10 km
Wavenumber (cycle/km)

8. Observations made by ADCP offshore from the US West Coast
Coastal currents have scales ~ 10 km. Velocity accuracy from SWOT is 3 cm/s at 10 km scale or 1 cm/s at 25 km scale.
42.5º N
 h ~ 5 cm
 v ~ 50 cm/sec
< 10 km
< 10 km
41.9º N
< 10 km
Observations made by ADCP offshore from the US West Coast
T. Strub

9. SWOT Temporal Sampling
Temporal sampling is irregular and location dependent.
1st nd rd th

10. Wavenumber spectra of SSH and measurement errorskm
SSH
iono
wet tropo
SSB
For SSH measurement at meso and submesoscales, most of the errors caused by the transmitting media and sea state effects become less important than measurement at large scales.
Media errors and sea-state errors have scales larger than 100 km and not affecting submesocale SSH measurement.

11. What is the state of the art in coastal tide modeling?
Errors in coastal tide models up to 20 cm are revealed from the Jason-T/P Tandem Mission.
What is the state of the art in coastal tide modeling?
But we are faced with new challenges at the smaller scales.
Andersen and Egbert (2005)

12. Besides the intrinsic science of internal tides, they introduce 2-5 cm/sec error in ocean current velocity. Is predicting internal tides from models feasible ?
R. Ray/GSFC

13. Systematic errors in the SWOT measurement
Look-angle errors due to uncertainly in the roll of the mast
Range errors due to media effects
Phase errors due to electronics
Correction through cross-over calibration using both the nadir altimeter and swath measurements
The spatial scales of the residual errors are in the range of mesoscale to basin scale, depending on the scales of the systematic errors.
We are sort of in an opposite situation than we were during the design of TOPEX/Poseidon. For T/P the design drivers were large-scale errors, such as orbit and media errors. For SWOT, the driver is the measurement random noise because the main objectives are the slope of SSH. So we are working from the high wavenumber end of the spectrum backward to low wavenumbers. There are several sources for systematic errors in the SWOT mesurement.
We need to quantify the scales of the residual systematic errors and evaluate the impact on mission science.

14. Conclusions
SWOT potentially can measure SSH at 1 km resolution with 1 cm precision, revealing ocean signals down to 10 km wavelengths.
Accuracy for surface geostrophic currents is about 3 cm/sec at 10 km wavelength and 1 cm/sec at 25 km wavelength.
Temporal sampling is a challenge: irregularly spaced varying from 2 samples/20 days to more than 5 at mid and high latitudes.
Coastal and internal tides have scales in the range of mesoscale and submesoscale, causing potential interference to ocean circulation studies.
Systematic errors in interferometry pose challenges at mesoscale to basin scale yet to be quantified.

15. k-11/3
SWOT noise level
20 km
Along-track altimeter wavenumber spectrum for the Kuroshio area for TOPEX/Poseidon, Jason-1, ENVISAT and GEOSAT Follow On. Spectral slopes were estimated in the 100 km to 300 km spectral band. A k-11/3 slope is also shown (dashed line). (Le Traon et al, 2008)

16. KE Spectrum from an OGCM simulation
Velocity error at 45º latitude with SSH noise of 1cm at 1 km resolution.
30 km wavelength

17. Finite-Time Lyapunov Exponent
(T=100 days)
AVISO data: 1 October 2007