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Processing for Coastal CTOH X-TRACK products

Processing for Coastal CTOH X-TRACK products

The CTOH computes regional along-track sea level anomaly (SLA) products for the following altimeter missions: Topex/Poseidon, Jason-1, Jason-1 interleaved, Topex/Poseidon interleaved, Jason-2, Geosat Follow on (GFO) and Envisat.  Long time series of SLA combining altimeter data from T/P, Jason-1 and Jason-2 are also available.  See details on X-TRACK products (content, format, downloading, ...).

Using the GDR (Geophysical Data Record) data and additional altimetry corrections available in the CTOH database (see Processing method below for details), SLA projected onto reference tracks with a spatial interval of about 6-7 km between points (1 second) are computed using the X-TRACK software (Roblou et al., 2011), developed at Legos. The processing is done on a regional basis and for each region, both raw and along-track low-pass filtered (using a 40-km cutoff frequency) SLA are available.

Data use conditions

Publications should include the following statement in the Acknowledgments:

Altimetry data used in this study were developed, validated, and distributed by the CTOH/LEGOS, France”.

Processing method

Processing first includes parameters from the GDR products for each altimeter mission plus additional state-of-the-art corrections distributed by the CTOH. Details on selected corrections are given in the table below.

Details on the data processing can be found in Vignudelli et al. (2005), Roblou et al. (2011) and Durand et al. (2008, see appendix). See further References. It is summarized below.

Since altimetry observations degrade in accuracy near the coast, the processing starts by the selection of valid ocean data. Then, a precise land mask and a dedicated editing strategy are used. The latter includes two steps. The first step is to impose editing criteria, both on the altimeter measurements and on the corrective terms, that are designed to be more restrictive than the standard ones (AVISO, 1996, see References). These criteria are thresholds that have been chosen after several tests for each parameter, in order to ensure that all outliers are totally removed (indeed, one of the reasons found for the unrealistic large variability often observed in altimeter data near continental shelves is the presence of many outliers in the corrective terms). 

To solve this problem, the behaviour of all the corrective terms is analyzed along the track. Abrupt changes are assumed to be associated with erroneous data. Outliers are removed by means of a 3s (4s for specific areas and corrections) standard deviation filter (s is the standard deviation of the original along track record; one value per cycle and per parameter is specified). Not only are the outliers eliminated, but also their adjoining neighbors, that often contain erroneous values. 

Since the editing process lead to the rejection of all altimeter measurements for which at least one correction is selected as wrong, this strategy rejects much more data than the classical ones, even if the altimeter measurement is meaningful. However, in many circumstances, data analysis indicates that an accurate interpolated correction would allow us to recover valid altimeter observations. Thus, in a second step, all corrective terms are recomputed using Bezier interpolation curves, based on the valid data for each correction. This method therefore allows recovery of a lot more good measurements that are flagged in the standard product because of a deficient correction. 

Once the corrected sea surface heights (SSHs) are computed, they are then projected onto fixed points along the nominal ground track of the altimeter satellite and converted into SLAs (Sea Level Anomalies) by subtracting a precise mean sea surface height. The latter is computed at the fixed nominal points, by inversion of all the available SSH measurements along the repeated ground tracks of the altimeter mission considered. This procedure is important since it was found that, in coastal areas where the topographic gradients are large, using inaccurate mean sea surface led to significant errors in SLAs (Vignudelli et al., 2005, see References).

Potential remaining outliers in SLAs are finally removed by a 3s standard deviation filter. The background noise may be filtered using a Loess filter to remove wavelengths shorter than 40 km (filtered version of the SLA product).

CorrectionsT/PJason-1Jason-2EnvisatGFO
Ionosphere

From dual frequency altimeter range measurements + GCP (GDR Correction)

From dual frequency altimeter range measurementsFrom GIM model
Dry troposphereFrom ECMWF modelFrom NCEPFrom NCEP
Wet troposphereFrom radiometer + GCP correcion of radiometer drift affects+GCP correction of yaw effectsFrom enhanced radiometer correction (S. Brown)From modelFrom model
Sea State BiasFrom non parametric empirical modelCalculated as 4.5% of the Significant wave heightFrom non parametric empirical model
Solid tidesFrom tide potential model
Pole tidesFrom Wahr, 1985
Loading effectFrom FES1999
Atmospheric correction (DAC)From TUGOm 2D regional* or globak models for periods smaller than 20 days+Inverted barometer for periods greater than 20 days, derived from ECMWF pressure
Ocean tideFrom TUGOm 2D regional configuration if available*, from FES2012** or GOT4.8** models

(*) : T-UGOm 2D regional corrections are only distributed for the Mediterranean Sea for the moment.
(**) : in last product version, otherwise FES2004 or GOT4.7 models are used.

Corrections used 

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