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Nearly three years of Envisat altimetric observations over ocean are available in Geophysical Data Record (GDR) products. The quality assessment of these data is routinely performed at the CLS Space Oceanography Division in the frame of the CNES Segment Sol Altimétrie et Orbitographie (SSALTO) and ESA French Processing and Archiving Center (F-PAC) activities. This paper presents the main results in terms of Envisat data quality: verification of data availability and validity, monitoring of the most relevant altimeter (ocean1 retracking) and radiometer parameters, assessment of the Envisat altimeter system performances. This includes a cross-calibration analysis of Envisat data with Jason-1, ERS-2 and T/P. Envisat data show good general quality. A good orbit quality and a low level of noise allow Envisat to reach the high level of accuracy of other precise missions such as T/P and Jason-1. Some issues raised in this paper, as the gravity induced orbit errors, will be solved in the next version of GDR products. Some others, as the Envisat Mean Sea Level in the first year, still need further investigation.

Since its launch in March 2002, the European earth observation satellite Envisat has been providing measurements of the atmosphere, ocean, land, and ice. This advanced polar-orbiting satellite ensures the continuity of the altimetric observations started with the ERS-1 satellite in 1991, but with higher precision. Among many instruments, the satellite carries a new generation of dual frequency radar altimeter (RA-2) which allows correction of ionosphere effects, a microwave radiometer (MWR) and a laser reflector and a Doris receiver which highly improve the accuracy of the orbit determination.

Extensive work has been produced during the Envisat verification phase by the Cross-Calibration and Validation Team (CCVT) to check the quality of the Envisat altimetric measurements. Since September 2003, the GDR products have been routinely produced and disseminated. Envisat altimeter system quality is continuously checked by the Quality Working Group (QWG) members. First results from GDR data have been presented during the 2004 Symposium meeting in Salzburg (e.g. Dorandeu et al. 2004 [

This paper is basically concerned with long-term monitoring of the Envisat altimeter system over ocean. Indeed continuous quality control of the altimetric data is essential. These data are used by many applications, from scientific research to operational oceanography, that require a high level of accuracy. Improving altimetric data performances should also help developing new applications.

Data from GDR cycles 10 through 38 spanning nearly three years have been used for this analysis. All relevant altimeter parameters deduced from Ocean 1 retracking, radiometer parameters and geophysical corrections are evaluated and tested. This work is routinely performed at CLS, as part of the SSALTO and funded by ESA through F-PAC activities. In this frame, besides continuous analyses in terms of altimeter data quality, Envisat GDR Quality Assessment Reports (e.g. Faugere et al. 2003 [

The work performed in terms of data quality assessment also includes cross-calibration with Jason-1, ERS-2 and T/P. This kind of comparisons between coincident altimeter missions provides a large number of estimations and consequently efficient long-term monitoring of instrument measurements. This enables the detection of instrument drifts and inter-mission biases essential to obtain a consistent multi-satellite data set. Envisat Sea Level Anomalies (SLA) are also compared to an independent dataset, a tide gauge network.

After a preliminary section describing the data used, the paper is split into four main sections: first, data coverage and measurement validity issues are presented. Second, monitoring of the main altimeter and radiometer parameters is performed, describing the major impact in terms of data accuracy. Then, performances are assessed and discussed with respect to the major sources of errors. Finally, Envisat Sea Surface height (SSH) bias and MSL issues are analyzed.

Envisat Geophysical Data Records (GDRs) from cycle 10 to cycle 38 have been used to derive the results presented in this paper. This corresponds to a nearly three-year time period spanning from September 30^{th} 2002 to July 11^{th} 2005. The routine production started on September 2003 with cycle 15. In parallel, a backward reprocessing of cycle 14 to 9 has been implemented. With only 7 days of available data, cycle 9 has not been used in this work. Note that cycles 1 to 8, corresponding to the in-flight calibration period, have not been disseminated by ESA. All these data have been processed in the same ground processing version except cycles 15 to 18. On November 26^{th} 2003, the Instrument Processor Facility (IPF) version changed from 4.55 to 4.56. Consequently, from cycle 19 onwards and for the reprocessed cycles 10 to 14, the Automatic Gain Control (AGC) evaluation and the Intermediate Frequency (IF) mask correction (with slight impact on the data) have been modified.

To perform this quality assessment work, conventional validation tools are used including editing procedures, crossover analysis, collinear differences, and a large number of statistical monitoring and visualization tools. All these tools are integrated and maintained as part of the CNES SSALTO (Segment Sol Altimétrie et Orbitographie) ground segment and F-PAC (French Processing and Archiving Centre) tools operated at CLS premises. Each cycle is carefully routinely analyzed before data release to end users. The main data quality features are reported in a cyclic quality assessment report (Faugere et al., 2003 [

As for all other existing altimeters, the Envisat GDR data are ingested in the Calval 1-Hz altimeter database maintained by the CLS Spatial Oceanography Division. This allows us to cross-calibrate and cross-compare Envisat data to other missions. In this study data from Jason-1 (from GDRs cycles 27 to 129), ERS-2 (from OPRs cycles 78 to 105), and TOPEX tandem data (from T/P MGDR_B cycles 370 to 472) are used. Jason-1 is the most suitable for Envisat cross calibration as it is available throughout the Envisat mission and has been extensively calibrated to T/P (Dorandeu et al., 2004b [

Most of this work has been carried out using parameters available in the GDR products. However, a few updates have been necessary to complete the analyses. First, as Jason-1 doesn't fly at the same altitude as Envisat, and ERS-2 has a mono-frequency altimeter on-board, it is not possible to use these satellites to assess the Envisat ionosphere path delay. Thus the JPL GPS-based global Ionospheric Maps (GIM) containing the vertical ionospheric total electron content are used here. Then, another set of orbits have been tested. They have been generated by the DEOS institute at Delft Institute of technology using the Grace Gravity Model EIGEN-GRACE01S instead of GRIM5 (Doornbos et al., 2005 [

This section mainly intends to analyze the ability of the Envisat altimeter system to correctly sample ocean surfaces. This obviously includes the tracking capabilities, but also the frequency of unavailable data and the ratio of valid measurements likely to be used by applications after the editing process.

From a theoretical ground track, a dedicated collocation tool allows determination of missing measurements relative to what is nominally expected. The cycle by cycle percentage of missing measurements over ocean has been plotted in

The Envisat MWR provides nearly 100% availability of data since the beginning of the mission (Dedieu et al., 2005 [

Data editing is necessary to remove altimeter measurements having lower accuracy. The first step of the editing procedure consists in removing data impacted by the S-Band anomaly or corrupted by sea ice. During the Commissioning Phase, it has been discovered that the RA-2 data are affected by the so-called S-Band anomaly. The anomaly results in the accumulation of the S-Band echo waveforms (Laxon and Roca, 2002 [

Since Envisat operates between ±82° of latitude, sea ice is an important issue for oceanic applications. No ice flag is currently available in the Envisat products, therefore alternate sea ice detection techniques are employed in order to retain only open ocean data. A study performed during the validation phase showed that the combination of altimetric and radiometric criteria was particularly efficient to flag most of the data over ice. The method is described in detail in (Faugere et al, 2003 [

The second step of the editing procedure consists in using thresholds on several parameters., The minimum and maximum thresholds used in the routine quality assessment are given in (Faugere et al., 2004 [

The percentage of edited measurements over ocean for the main altimeter and radiometer parameters has been plotted in

It has been necessary to apply additional editing criteria on SSH-MSS differences in order to remove remaining spurious data. The first criterion consists in removing measurements with SSH-MSS greater than 2m. The ratio is plotted in

The Envisat editing ratios are significantly lower than those observed on other altimeters like Jason or T/P. In

All GDR fields are systematically checked and carefully monitored as part of the Envisat routine calibration and validation tasks. However, only the main Ku-band parameters are presented here, as they are the most significant in terms of data quality and instrumental stability. Furthermore, all statistics are computed on valid ocean datasets after the editing procedure.

As part of the ground segment processing, a regression is performed to derive the 1 Hz range from 20 Hz data. Through an iterative regression process, elementary ranges too far from the regression line are discarded until convergence is reached. The mean number and RMS of Ku 20Hz elementary data used to compute the 1Hz average are plotted in

The off-nadir angle is estimated from the waveform shape during the altimeter processing. The square of the off-nadir angle is plotted in

^{2}. This mean value is not significant in terms of actual platform mispointing. This is due to the way the slope of the waveform trailing edge is computed and will be corrected in the next GDR version. The 0.005 deg^{2} jump between cycles 21 and 22 is due to the upgrade of the IF mask filter auxiliary data file. The slight rising trend observed on the curve might be due to the onboard filter which is not current (last update was November 2003).

The cycle by cycle mean and standard deviation of Ku and S-band SWH are plotted in

The cycle by cycle mean and standard deviation Ku and S-band Sigma0 are plotted in

As performed on TOPEX (Le Traon et al. 1994 [

A neural network formulation has been used in the inversion algorithm retrieving the wet troposphere correction from the measured brightness temperatures (Obligis et al., 2005 [^{th} of January 2003. The impact of these changes has been found to be meteorologically positive, and it is confirmed by the improved consistency with the MWR. Note that this change did not impact the MWR-ECMWF mean differences. A complete monitoring of all the radiometer parameters is available in the cyclic Envisat Microwave Radiometer Assessment (Dedieu et al., 2005 [

One of the main objectives of the Calibration and Validation activities is to assess the performance of the whole altimeter system. This means that the quality of each parameter of the product is evaluated, in particular if it is likely to be used in the Sea Surface Height (SSH) computations. Conventional tools like crossover differences and repeat-track analyses are systematically used in order to monitor the quality of the system.

The standard SSH calculation for Envisat is defined as

The orbit and corrections used for Envisat, Jason-1 and T/P are detailed in

The Envisat SSB currently available in the GDR products has been designed during the validation phase from 3 cycles of data (10 to 12) (Labroue 2003 [^{2}.

A spectral analysis has been carried out during the validation phase (Faugere et al., 2003 [

^{-3}m^{2}s. This plateau is the signature of a 9.2 cm white noise. Assuming uncorrelated 20 Hz noise, it is equivalent to 2.1 cm for the 1 Hz averages. This value is fully consistent with the results obtained from the RMS of elementary measurements. The Jason-1 spectrum has a similar shape as Envisat with plateau at 6.10^{-4} m^{2}s, which corresponds to a white noise of 7.3 cm, that is 1.6 cm at 1 Hz. The Jason-1 noise level is thus lower at 20 Hz. However the swelling, visible on the two spectrums between 0.2 and 3 Hz, is much more pronounced on Jason-1 data. This feature would deserve further investigation because it should impact the performance of 1Hz data.

Using an along-track filtering method (Tran et al. 2002 [

SSH crossover differences are computed on a one-cycle basis, with a maximum time lag of 10 days, in order to reduce the impact of ocean variability which is a source of error in the performance estimation. The mean of crossover differences represents the average of SSH differences between ascending and descending passes. This difference can reflect orbit errors or errors in geophysical corrections. The fact that Envisat is Sun-synchronous can play a role since the ascending passes and descending passes respectively cross the equator at 10pm local time and 10am local time. Thus all the parameters with a daily cycle can induce errors resulting in ascending/descending differences. The error observed at crossovers can be split into two types: the time invariant errors and the time varying errors.

To analyze the time invariant errors, we have computed local averages of crossover differences over approximately one year (cycles 25 to 35). The map of the mean differences at crossovers is shown in

Besides the systematic ascending-descending errors, a time varying error can also be observed at crossovers. The cyclic mean ascending–descending SSH differences at crossovers shows this error in

In order to better analyze such annual signals, a sinusoidal function with a 365-day period has been fitted to mean crossover differences averaged into 10×10 degree bins:

Where t is the time in days, A the amplitude and φ the phase.

Only open ocean data are used in this analysis. Latitudes higher than 70 degree are also removed because the seasonal data unavailability at high latitudes corrupts the estimation of the annual signal. Regions of high mesoscale variability are also removed to reduce noise. After smoothing, the amplitude A of the estimated sinusoidal signal has been plotted in

The variance of crossover differences conventionally gives an estimate of the overall altimeter system performance. Indeed, it gathers error sources coming from orbit, geophysical corrections, instrumental noise, and part of the ocean variability. The standard deviation of the Envisat SSH crossover differences has been plotted in

In order to compare Envisat and Jason-1 performances at crossovers, Envisat and Jason-1 crossovers have been computed on the same area excluding latitude higher than 50 degree, shallow waters and using exactly the same interpolation scheme to compute SSH values at crossover locations. Performances at crossovers are compared, for the two satellites on

To estimate accurately the Envisat mean sea level bias and trend, two factors have to be taken into account. First, as previously mentioned, the range has to be corrected to compensate for the Ultra Stable Oscillator drift. The distributed correction is smoothed over a 1-month period to filter peaks and short period variations. The cyclic mean of the USO correction is plotted in

Envisat Mean Sea Level (MSL) estimations are plotted in

In order to compare Envisat and Jason-1 SSH estimations, 10-day dual crossovers have been computed for each Envisat cycle. The same ECMWF correction has been used for both Jason-1 and Envisat to avoid potential radiometer errors.

Finally MSL estimations from Envisat, Jason-1 and T/P have been compared. The results are obtained after area weighting (Dorandeu and Le Traon 1999 [

Tide gauges provide independent measurements of sea surface height variations. Long term altimeter monitoring using a global tide gauge network was successfully performed by Mitchum [

The same SSH calculation technique as previously is used but without applying the USO correction. The cyclic mean of the difference is plotted in

To avoid this, a long wave length error correction has been performed by global minimization of crossover differences using a 1 and 2 cycles/revolution sinusoidal model. Using this correction, less time series have been edited during the tide gauge selection, meaning that the consistency between the 2 datasets has been improved. The new estimated trend, plotted in

A statistical evaluation of Envisat altimetric measurements over ocean has been presented in this paper. With nearly three years of data now available in a homogeneous time series, Envisat altimetric measurements show good general results. A very good availability on every surface and very low editing ratios over ocean are observed. One of the major improvements of the RA-2 with respect to ERS RA is the S-band allowing range corrections due to ionospheric effects. However the so-called S-Band anomaly impacts more than 4 % of the available data on average. This ratio has been improved since cycle 31 and a method is currently under development to reconstruct the impacted S-band waveforms. The ocean-1 altimeter parameters are stable, compared to Jason-1 and ERS-2. The MWR wet troposphere correction has a small trend relative to the ECMWF model. Both high frequency and crossover analysis show that Envisat has performances similar to Jason-1. The time invariant errors, observed on the crossover mean, are mainly due to gravity induced orbit errors and are well corrected by the use of a Grace Gravity model. The time varying errors have to be analysed further to confirm the possible aliasing effect of oceanic tide components. Envisat MSL global trend is consistent to Jason-1 and T/P on the two last years of the period. However, the issue of the unexplained behavior of the first year still remains.

A new configuration will be operational in September 2005 and a reprocessing of the whole Envisat altimetric mission is expected to start early 2006. Several improvements in terms of data quality will be included in this new version of GDR products, for instance a new orbit configuration, an improved Sea State bias modeling and new geophysical corrections such as the correction of High Frequency Ocean signals. These new products will further improve the high quality level of the Envisat altimetric mission and will make easier the data fusion for multi-mission altimetry, as is essential for oceanography applications such as mesoscale current mapping and forecasting, and for climate studies.

This work has been funded by ESA through ENVISAT F-PAC activities. The quality assessment activities described in this paper are embedded in the CNES SSALTO. The authors would like to thank M. Ablain, G. Dibarboure, S. Labroue, E. Obligis and F. Mertz who contributed to this work through numerous discussions and technical help.

a) Monitoring of the percentage of missing measurements relative to what is theoretically expected over ocean. b) Envisat missing measurements for cycle 25.

Cycle by cycle percentages of missing MWR measurements.

Cycle by cycle percentages of data impacted by the S-Band anomaly.

Cycle per cycle percentages of edited measurements by the main Envisat altimeter and radiometer parameters: a) Standard deviation of 20 Hz range measurements > 25 cm, Number of 20-Hz range measurements < 10. b) Square of off-nadir angle (from waveforms) out of the [-0.2 deg^{2}, 0.16 deg^{2}] range. Dual frequency ionosphere correction out of [-40, 4 cm]. c) Ku-band significant wave height > 11 m, Ku band backscatter coefficient out of the [7 dB, 30 dB] range. d) MWR wet troposphere correction out of the [-50 cm, -0.1 cm] range. e) SSH-MSS out of the [-2, 2m] and edited using thresholds on the mean and standard deviation of SSH-MSS on each pass.

Comparison of Envisat edited measurement to Jason-1. Maps of rejected measurements, with the same editing procedure for: a) 10 days of Envisat cycle 38 b) the corresponding Jason-1 cycle 128. c) Percentage of edited measurements, over ocean, for the two satellites, from the beginning of the Envisat mission.

a) Cycle mean of the number of 20 Hz elementary range measurements used to compute 1 Hz range. b) Cycle mean of the standard deviation of 20 Hz measurements.

Cycle mean of the square of the off-nadir angle deduced from waveforms (deg^{2}).

Global statistics (m) of Envisat Ku and S SWH a) Mean and b) Standard deviation. c) Mean Envisat-Jason-1 Ku SWH differences at 3h EN/J1 crossovers computed with 120 days running means. d) Mean. ERS-2-Envisat Ku SWH collinear differences over the Atlantic Ocean.

Global statistics (dB) of Envisat Ku and S Sigma0 a) Mean and b) Standard deviation. c) Mean Envisat-Jason-1 Ku Sigma0 differences at 3h EN/J1 crossovers computed with 120 days running means. d) Mean ERS-2-Envisat Ku Sigma0 collinear differences over the Atlantic Ocean.

Comparison of global statistics of Envisat dual-frequency and JPL-GIM ionosphere corrections (cm). a) Cycle mean of dual-frequency and GIM correction. b) Mean of the differences c) Standard deviation of the differences.

Comparison of global statistics of Envisat MWR and ECMWF wet troposphere corrections (cm). a) Cycle mean of MWR and ECMWF corrections. b) Mean of the differences. c) Standard deviation of the differences.

Power spectrum of (a) 20 Hz Envisat SSH, (b) 20 Hz Jason-1 SSH, (c) 1 Hz Envisat SSH, (d) 1 Hz Jason-1 SSH.

Maps of the σ[HF(SSH_{Jason-1}-MSS]]- σ[HF(SSH_{Envisat}-MSS]] (cm) in (4deg × 4 deg) geographical bins through a 35-day period (cycle Envisat 23) where σ[HF(SSH-MSS;] is the standard deviation of the high frequency part of the SSH–MSS signal.

Maps of the time invariant 35-day crossover mean differences (cm) for Envisat averaged in (4deg × 4 deg) geographical bins through a one year period (cycle 25-35) a) using GDRs POE orbit (GRIM5 gravity model) and b) using Delft POE orbit (EIGEN-GRACE01S gravity model;.

Time varying 35-day crossover mean differences (cm). a) Cycle per cycle Envisat crossover mean differences. An annual cycle is clearly visible. Diamonds: shallow waters (1000 m) are excluded. Triangles: shallow waters excluded, latitude within [−50S, +50N], high ocean variability areas excluded b) Map of the geographic distribution of the amplitude of the annual cycle of the crossover means shown in a) averaged in 10deg × 10deg geographical bins (after smoothing).

a) Standard deviation (cm) of Envisat 35-day SSH crossover differences depending on data selection. Dots: without any selection. Diamonds: shallow waters (1000 m) are excluded. Triangles: shallow waters excluded, latitude within [−50S, +50N], high ocean variability areas excluded. b) Comparison of the Standard deviation (cm) of Envisat (dot) and Jason-1 (diamond) 10-day SSH crossover differences.

USO correction computed from auxiliary files. The raw correction is averaged over 1 month.

Mean of Envisat sea level depending on data selection. Dots: without any selection. Diamonds: shallow waters (1000 m) are excluded. Triangles: shallow waters excluded, latitude within [−50S, +50N], high ocean variability areas excluded.

Mean of Envisat –Jason-1 differences at 10-day dual crossovers. Dots: Global. Diamonds: Northern Hemisphere. Triangle: Southern Hemisphere.

Envisat, Jason-1 and T/P global MSL trends a) over the whole Envisat mission, b) over the two first years of Envisat mission (cycle 10 to 29), c) over the two last years of Envisat mission (cycle 19 to 38).

Comparison of Envisat MSL to tide gauges. a) No USO correction applied and no long wave length error applied (dots), No USO correction applied and but a long wave length applied (diamonds); b) USO correction applied and a long wave length applied.

Description of the SSH corrections.

Envisat | Jason-1 | T/P | |
---|---|---|---|

Orbit | CNES POE (grim5) | CNES POE (JGM3) | NASA POE (JGM3) |

Additional Range correction | USO correction | none | none |

SSB | Non parametric SSB (GDR) | Non parametric SSB (Labroue and Gaspar, 2002 [ | |

Wet troposphere | For performance assessment: MWR | ||

Dry troposphere | Based on ECMWF sea level pressure, rectangular grids | ||

Ionosphere | Dual-frequency altimeter (filter 300km) | ||

Inverse barometer | Based on ECMWF sea level pressure relative to global mean, rectangular grids | ||

Tides | Pole tide, solid earth tide, GOT00.2 ocean and load tides | ||

Mean sea surface | CLS01V1 |