Using HF radar coastal currents to correct satellite altimetry
Carolyn Roesler, William J. Emery and Waqas Qazi
CCAR
Aerospace Eng. Sci. Dept.
University of Colorado at Boulder
IGARSS 2011 , 24-29 July, Vancouver, Canada
Outline
• CODAR data set
• Coastal temporal and spatial scales
• Retrieval of synthetic CODAR heights
• Comparison with J-2 and PISTACH retrackers
• J-2 SSH errors: Waveform behavior and sea state
• Conclusions
Goal: to determine how the Jason waveforms might be retracked to better fit the CODAR synthetic heights
CALIFORNIAN CODAR DATA SET
At least 2 radar overlapping fields are needed to derive the currents
Using 2008 & 2009 hourly CODAR measured ocean surface currents on a resampled and post processed 6 km and 2 km grid. Courtesy of Sung Yon Kim, Scripps Institute of Oceanography.
Long range
Short range
Frequencies
4.66 MHz 13.54 MHz
Resolution
6 km 2 km
Up to 150 km 50 km offshore
Bathymetry and geography in the coastal transition zone
Data set geography Around Monterey Bay
Red Lines: bathymetry, 100 m and 250 m
Blue Lines: bathymetry, every 1000 m from 1000 to 4000 m every 1000 m from 500 to 3500 m
Green Line: boundary of 6 km CODAR set
~ 150 km from shore
In order to retrieve the geostrophic currents from the total velocity surface derived from HF radar, an analysis of the time and spatial scales of the coastal oceanic features is done. These features are expected to vary with the distance to the coastline and or bathymetry, and thus may vary regionally
CODAR TIME and SPATIAL SCALES
Time scale 10 days in the open ocean 3 days near the coast
From temporal covariance of velocities at zero spatial lag averaged over 2008
3 day averaging as a first approximation to the geostrophic flow
binned according to spatial lag X and Y normalized and averaged over 2008.
Looking at the shape of the velocity covariances we will
assume that locally, the homogeneous isotropic turbulent model is adequate.
Spatial Scale
Covariances of CODAR velocity Cuu and Cvv for 10 km width regions
Cuu
u cross shelf velocity
Cvvv along shelf velocity
Spatial scales
For homogeneous isotropic turbulence, velocity covariances are related to the stream-function covariance
We use the Waldstat (1991) streamfunction spatial covariance :
And find parameters :
For zone 50-60 km : a = 50 km, b = 70 km For zone 20-30 km: a = 35 km, b = 50 km
Cψψ= ( 1 - (r⁄b)2 ) exp( -(r⁄a)2 )
Fitted Observed
Optimal Interpolation (OI) [Bretherton et al. (1976)] to derive the estimated streamfunction
CODAR Geostrophic heights field
Region of P221 going through Monteray bay. The complex bathymetry generates the formation of Eddies. And this region is prone to have large SLA variations.3 day-averaged CODAR total currents minus a Mean current derived from the 0.02° gridded DNSC08 MSS
This mean was chosen due to the short span of the CODAR time series. A Mean dynamic topography should be removed, but would have more errors in the coastal region.
In the OI, the spatial scales L vary locally as a function of the grid point distance to coast, and only the surrounding observations at a distance less than L are considered.
The noise error for the CODAR was chosen to be constant = 15 cm/s although in reality it varies depending on the radar geometry, and weather conditions, and in our case to how close the geostrophic assumption is valid.CODAR ocean
currents u,v
3 day- averaged -Mean derived from DNSC08MSS
OI varying spatial scales
Synthetic height fields
CODAR 2 km Geostrophic field
Right: Effect of using a single spatial scale chosen at the 50 km zone (top), and the improved resolution using a varying spatial scale (bottom)
Left: A close up of the improved map underlying the input CODAR vectors cm
6 & 2 km CODAR SSH Along track P221
At the time of J1 passage
More variations in the 2 km set. But the 6 km set enables us to get information further offshore.
Later we combine both resolution products.
CODAR & weekly Merged MSLA
Aviso product: Weekly merged MSLA on a 1/3 °x1/3° grid, for 2008
CODAR SSH computed directly on the MSLA grid.
Interpolated at the J along track P221
JASONCorrected SSH Along track P221Distances more than 20 km off coast
Smoothed 25 km
Smoothed 50 km
Mean
of
ti
me
Series removed
CODAR ocean currents u,v
3 day- averaged -Mean current derived from DNSC08MSS
OI varying spatial scales
Synthetic height fields
Comparison
6-km-Codar and J2 SSH on P221 for 2009
J2 PISTACH coastal product resampled to 1 Hz using the MLE4 Ocean Brown model retracked range : Sea level relative to the DNSC08 MSS, all corrections applied.
We generate two smoothed SSH sets: cut-off frequency of 25 km cut-off frequency of 50 km
Codar 6 km Along track SSH amplified by 2
Mean of all time series removed
6-km-Codar and J2 SSH on P221 for 2009
OCE
6-km-Codar and J2 SSH on P221 for 2009 ( cont.)
2x{Codar}SSH filt 25 kmSSH filt 50 km
OCE
Correlation
Red points : statistically non significant
Mean( blue points) = 0.65
For the sets with a high correlation the
slope of the regression coefficient is around 2
Correlation Codar 6 km and 50-km-smoothed J2 between Along track distance 50 – 150 km
J2 PISTACH Retrackers
Data : Aviso 20 Hz-J2 PISTACH coastal product
Oce: ku Band range: Deep ocean Brown model: MLE4 (range, amplitude, significant wave height & mispointing angle)
Red3: MLE3
Ice3: 30 % threshold
Time period: 2009
Extracted range from 3 retrackers: ( from PISTACH handbook)
Principe of the Ice3 algorithm ( from PISTACH handbook)
Done on a smaller window selected
around the leading edge
J2 retrackers & 6-km-CODAR for P221
2x{Codar}SSH filt 25 kmSSH filt 50 km
If we assume Codar SSH to be the best estimate of the geostrophic field, then we can evaluate the retracking techniques. At this point, the shapes are more important than the exact values.
cm
C006 C007
Along track distance ( km)
For these first 4 cycles it seems that Ice3 fits better to the Codar SSH. Although they are quite similar except for the third case on C021, Feb -03
OCE
OCE OCE
OCE
OCE
J2 retrackers & 6-km-CODAR for P221
Here we only keep the best visually retracker fit either Ice3 or OCE, for the first 16 cycles of 2009
2x{Codar}SSH filt 25 kmSSH filt 50 km
The averaged correlation is now 0.82
Closer to shore use of 20 hz Pistach & Codar 2 km
To filter the noisy 20 hz data: iterative median and low Pass filter with a 3-sigma data selection [ Dufau Claire,2011] With wave length L = 21 points ( 7 km ) L = 61 points ( 21 km )
Sea level relative to a MSS, all corrections applied: use of decontaminated water vapor corr, GIMP ionospheric corr, SSB included ( may not be reliable over continental shelf)
3x{ Codar 2 km}
Mean of time series removed
Ice3 retracked range
Good fit Phase shift
wiggles
Jason-2 Ku 20 Hz Waveform time series for P221median tracker algorithm, Diode acquisition
mode
In some places the leading edge of the WF deviates from the predetermine tracker gate 31. They correspond with large offsets between Codar and altimetry SSH.
The median tracker algorithm uses the WF to update the tracker range. So large deviations could give us a clue to possible changes in WF shape and errors in retracking ranges.
Gate number
Alo
ng
tra
ck d
ista
nce
fro
m c
oast
sig0 and unretracked range relative to MSS
MLE4 Ku-band sig0 (dB)Unretracked range relative to MSSOce retracked – unretracked range
Strong correlation ( > 0.7) when sig0 > 15 dBIf not lower ( 0.6 ) due to signal to noise level
Sig0 = radar return backscattering cross section
C019, Jan 15 C031, May 14
C030, May 04
sig0 and unretracked range relative to MSS
J2, Jan 15
J1, Jan 15
Median tracker algorithm
Split gate tracker algorithm
J2 and J1 in flying phase formation, same orbit , 54 s delay
Both tracker algo behave similarly with a slight difference in the sensitivity of the echo shape
However the (sig0, unretracked range) relationship disappear when J2 is in the Diode/DEM coupling mode, because the tracking operations do not depend on echoes analysis anymore.
Diode/DEM mode
J2, Jun12
Sigma0 blooms
Altimetry data degraded by high sig0 [ Tournadre 2006, Thibaut 2007]
Occur in presence of weak winds ( cm scale waves absent) surface slick
WF may be corrupted due to the non uniform sig0 in the altimeter footprint with localized highly reflecting patches. various possible WF distortions
Consecutive 20 Hz WF, 30 km offshore in presence of a blooming event.
Trailing edge increasing
Peakiness increased
V shape orRound pattern similar to rain events
J2 C021 Feb03
Variations in sea states : Sig0 and SWH MLE4 retracked
Sig0 (dB)2x{SWH} (m)
Occurrence, size and strength of blooming events variable
Dots: regions where Ice3 and Red3 ranges diverge
1Blooms 30 km and 140 km
4Blooms before 40 km and after 60 kmSWH variable
5Sig0 > 15 dBSWH high and variable
2Bloom 30 km SWH high
3Sig0 < 14 dBNo blooms
6Sig0 ~ 15 dBA lit bloom at 140 km
C019, Jan 15 C021, Feb 03
C030, May 04
C034, Jun 12C031, May 14
C026, Mar 25
Ice 3 retracker Red 3 retracker
C019 Jan 15 C019 Jan 15
No blooming events Ice 3 performs well and better. Sig0 stays below 15 dBSWH < 2.5 m
Ice3 behaves well closer than 50 km , then Red3 until a little blooming event around 140 km Sig0 is about 15 dBSWH < 1.5 m
Ice3 fits well closer than 50 km when a strong blooming event starts, then Red3, until the next blooming event around 140 kmSWH < 2 m
Behavior of Ice3 and Red3 range related to the sea state
3
6
1
Along track distance from coast Along track distance from coast
Ice 3 retracker
Red 3 retracker
After the close to shore blooming event ( < 30 km), Red3 performs better, though it seems noisy.High SWH
Sig0 > 15 dB and high ; High variations of SWH
Ice3 and Red3 behave in a similar way and do not perform well.
A different retracking method should be adapted to this situation.
Behavior of Ice3 and Red3 range related to the sea state
2
5
Along track distance from coast
Conclusion and future work
• We have processed the CODAR current derived velocities into synthetic heights using a varying spatial scale OI technique, assuming a locally isotropic and homogeneous field.
• We have shown that there is a good relationship between JASON & CODAR SSH, further than 20 km off the coast.
• It seems promising as a tool to evaluate the several retracking techniques. They seem to perform differently depending on the sea state.
• In the presence of blooming events the altimetry data is corrupted. These could happen more frequently over the Californian coastal areas due to upwelling.
FUTURE WORK
• To correct for the blooming events using the Codar SSH as a reference.
• Redefine the retracking strategy: using the Codar SSH, find the corresponding retracking gate and deduce what type of retracking technique would fit.
• This should allow to make improvements on the coastal altimetry SSH accuracies.
Questions?
Thank you
Carolyn Roesler, William J. Emery and Waqas Qazi
CCARAerospace Eng. Sci. Dept.
University of Colorado at Boulder
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