SSALTO/DUACS User Handbook - ICDC€¦ · SSALTO/DUACS User Handbook: (M)SLA and (M)ADT Near-Real...

SSALTO/DUACS User Handbook:

(M)SLA and (M)ADT Near-Real Time and Delayed Time Products

Reference : CLS-DOS-NT-06-034Nomenclature : SALP-MU-P-EA-21065-CLSIssue : 4rev 4Date : 2015/06/30

SSALTO/DUACS User Handbook:(M)SLA and (M)ADT Near-Real Time and Delayed Time Products

CLS-DOS-NT-06-034 - Issue 4.4 - Date : 2015/06/30 - Nomenclature : SALP-MU-P-EA-21065-CLS i.1

Chronology Issues :Issue : Date : Reason for change :

2.2 2010/11/18

2.3 2011/01/01 Modification of the commentary on the flags and of the part"Product generation"

2.4 2011/03/29 Addition of Mozambique products and temporal update ofDT products

2.5 2011/04/16 Addition of daily DT products

2.6 2011/09/01 New version of SLA NetCDF files

Addition of RT products

2.7 2012/01/10 NRT: Addition of Arctic and Europe products

2.8 2012/01/21 Cnes MOE GDR-D orbit on Envisat

2.9 2012/02/06 Addition of Cryosat-2 mission in NRT products

3.0 2012/05/25 End of Envisat mission and addition of Jason-1 on itsgeodetic orbit

3.1 2012/07/20 New version "D" of IGDR for Jason-2

3.2 2012/10/20 Addition of Cryosat-2 mission in DT products

3.3 2012/12/04 NRT: Improvement in the processing of Cryosat-2,

DT:integration of Jason-1 geodetic mission and new ver-sion D of Jason-2

3.4 2013/01/29 Global SLA NRT: Integration of "OGDR on the fly" data

3.5 2013/07/01 NRT: Integration of Saral/AltiKa and OGDR Cryosat-2data

3.6 2013/09/04 NRT: Improvement of DAC correction

4.0 2014/04/15 NRT and DT: DUACS 2014 version of products

4.1 2014/05/20 NRT: Addition of HY-2A mission

4.2 2014/11/15 DT: Addition of HY-2A mission

4.3 2015/05/18 NRT and DT: New orbit standards GDR-E (Jason-2,Cryosat-2, AltiKa)

4.4 2015/06/30 NRT and DT: Implementation of the Saral/AltiKa geode-tic orbit



List of Tables

1 SSALTO/DUACS Near-Real Time Input data overview . . . . . . . . . . . . . . . . . . . . 82 Corrections and models applied in SSALTO/DUACS NRT products produced from IGDRs. . 93 Corrections and models applied in SSALTO/DUACS NRT products produced from OGDRs. 104 SSALTO/DUACS Near-Real Time Filtering and sub-sampling values . . . . . . . . . . . . 175 Measurement noise error before/ after spatial filtering for Mediterranean and Black Sea

products (cms rms) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 Corrections and models applied to SSALTO/Duacs DT products for TOPEX/Poseidon, Jason-

1, Jason-2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Corrections and models applied in SSALTO/DUACS DT products for ERS-1, ERS-2, Envisat 258 Corrections and models applied in SSALTO/DUACS DT products for Cryosat-2, GFO, Al-

tiKa and HY-2A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 SSALTO/DUACS Delayed Time Filtering and sub-sampling values . . . . . . . . . . . . . 3210 Measurement noise error before/ after spatial filtering for Mediterranean and Black Sea

products (cms rms) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3311 List of the Along-track products in NRT . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3812 List of the Gridded products in NRT, 1/4˚ cartesian resolution for global and 1/8˚ cartesian

resolution for regional . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3813 List of the Along-track products in DT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4214 List of the Gridded products in DT, 1/4˚ cartesian resolution for global and 1/8˚ cartesian

resolution for regional . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

List of Figures

1 DUACS and AVISO, a user-driven altimetry service . . . . . . . . . . . . . . . . . . . . . . 12 Example of a map of Sea Level Anomalies (MSLA) where tracks of HY-2A are superimposed 53 SSALTO/DUACS processing sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 Overview of the near real time system data flow management . . . . . . . . . . . . . . . . . 115 Merging pertinent information from IGDR and OGDR processing . . . . . . . . . . . . . . 126 Impact in cm of the reference change from 7 years to 20 years ([1993-1999] to [1993-2012]) 147 Noise Level in 1hz Jason-2 SLA estimated from mean wavenumber spectra over 2011 in

10˚x10˚ boxes (cm rms) before 65km filtering (left) and after (right) . . . . . . . . . . . . . . 188 Example with the key performance indicator on 2009/06/27 . . . . . . . . . . . . . . . . . . 219 Impact in cm of the reference change from 7 years to 20 years ([1993-1999] to [1993-2012]) 2910 Noise Level in 1hz Jason-2 SLA estimated from mean wavenumber spectra over 2011 in

10˚x10˚ boxes (cm rms) before 65km filtering (left) and after (right) . . . . . . . . . . . . . . 3311 Three merged maps are produced daily: final map (d-6), intermediate map (d-3) and prlim-

inary map (d0) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3912 List of satellites in all-sat-merged products . . . . . . . . . . . . . . . . . . . . . . . . . . . 4413 List of satellites in two-sat-merged products . . . . . . . . . . . . . . . . . . . . . . . . . . 45



Applicable documents / reference documents

RD 1: AVISO User Handbook for Merged Topex/Poseidon products (M-GDR)Ref: AVI-NT-011-312-CN

RD 2: AVISO and PO.DAAC User Handbook - IGDR and GDR Jason-1 ProductsRef: SMM-MU-M5-OP-13184-CN

RD 3: CERSAT, 1996: Altimeter and Microwave Radiometer ERS Products User manualRef: C2-MUT-A-01-IF

RD 4: CLS, 1996: Validation of ERS-1/2 OPR cyclesRef: CLS.OC/NT/96.010 (ERS-1) and CLS.OC/NT/96.011 (ERS-2) (one reportper cycle)

RD 5: CLS, 2006: Envisat RA2/MWR ocean data validation and crosscalibration - Activi-ties Yearly report - Contract N˚ 03/CNES/1340/00/DSO310Ref: SALP-RP-MA-EA-21316-CLS

RD 6: CLS, 2006: Jason-1 validation and crosscalibration activities - Contract N˚03/CNES/1340/00/DSO310Ref: SALP-RP-MA-EA-21314-CLS

RD 7: OSTM /Jason-2 Products HandbookRef: SALP-MU-M-OP-15815-CN



List of acronyms

AL AltiKaATP Along-Track ProductADT Absolute Dynamic TopographyAVISO Archiving, Validation and Interpretation of Satellite Oceanographic dataBGLO Biais Grande Longueur d’OndeCal/Val Calibration - ValidationCERSAT Centre ERS d’Archivage et de TraitementCMA Centre Multimission Altimetry centerCORSSH CORrected Sea Surface HeightC2 Cryosat-2DAC Dynamic Atmospheric CorrectionDT Delayed TimeDTU Mean Sea Surface computed by Technical University of DanemarkDUACS Data Unification and Altimeter Combination SystemE1 ERS-1E2 ERS-2EN EnvisatENN Envisat on its non repetitive orbit (since cycle 94)ECMWF European Centre for Medium-range Weather ForecastingENACT ENhanced ocean data Assimilation and Climate predictionG2 Geosat Follow OnGIM Global Ionospheric MapsGDR Geophysical Data Record(s)HY-2A Haiyang-2AIERS International Earth Rotation ServiceIGDR Interim Geophysical Data Record(s)J1 Jason-1J1N Jason-1 on its new orbit (since cycle 262)J1G Jason-1 on its geodetic orbit (since May 2012)J2 Jason-2JPL Jet Propulsion LaboratoryLAS Live Access ServerLWE Long Wavelength ErrorsMADT Map of Absolute Dynamic TopgraphyMDT Mean Dynamic TopographyMOE Medium Orbit EphemerisMP Mean ProfileMSLA Map of Sea Level AnomalyMSS Mean Sea SurfaceNRT Near-Real TimeOE Orbit ErrorOER Orbit Error ReductionOpendap Open-source Project for a Network Data Access ProtocolPF Polynom FitPO.DAAC Physical Oceanography Distributed Active Archive Centre



POE Precise Orbit EphemerisRD Reference DocumentSAD Static Auxiliary DataSARAL Satellite with ARgos and ALtikaSI Signed IntegerSLA Sea Level AnomalySSALTO Ssalto multimission ground segmentSSH Sea Surface HeightT/P Topex/PoseidonTPN Topex/Poseidon on its new orbit (since cycle 369)



Contents

1. Introduction 11.1. Data policy and data access . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2. Geodetic orbit for AltiKa (June 2015 for NRT products) 4

3. Integration of the HaiYang-2A (HY-2A) Mission in NRT products (May 2014) and in DT prod-ucts (November 2014) 5

4. SSALTO/DUACS system 64.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64.2. Near Real Time processing steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

4.2.1. Input data, models and corrections applied . . . . . . . . . . . . . . . . . . . . . . . 84.2.2. Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114.2.3. Homogenization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124.2.4. Input data quality control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124.2.5. Multi-mission cross-calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134.2.6. Product generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

4.2.6.1. Change of Reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144.2.6.2. Computation of raw SLA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154.2.6.3. Cross validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164.2.6.4. Filtering and sub-sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174.2.6.5. Computation of ADT Products . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4.2.7. Generation of gridded Sea Level Anomalies (MSLA) products . . . . . . . . . . . . 194.2.7.1. Merging process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4.2.8. Quality control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214.2.8.1. Final quality Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214.2.8.2. Performance indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

4.3. Delayed Time processing steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234.3.1. Input data, models and corrections applied . . . . . . . . . . . . . . . . . . . . . . . 234.3.2. Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274.3.3. Homogenization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274.3.4. Input data quality control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274.3.5. Multi-mission cross-calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284.3.6. Product generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

4.3.6.1. Change of Reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294.3.6.2. Computation of raw SLA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304.3.6.3. Cross validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 314.3.6.4. Filtering and sub-sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324.3.6.5. Computation of ADT Products . . . . . . . . . . . . . . . . . . . . . . . . . . 34

4.3.7. Generation of gridded Sea Level Anomalies (MSLA) products . . . . . . . . . . . . 344.3.7.1. Merging process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

4.3.8. Quality control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364.3.8.1. Final quality Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36



5. SSALTO/DUACS Products 375.1. Near Real Time Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

5.1.1. Delay of the products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395.1.2. Temporal availibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

5.2. Delayed Time Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415.2.1. Delay of the products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 425.2.2. Temporal availibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

6. Data format 466.1. NetCdf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 466.2. Structure and semantic of NetCDF along-track (L3) files . . . . . . . . . . . . . . . . . . . 466.3. Structure and semantic of NetCDF maps (L4) files . . . . . . . . . . . . . . . . . . . . . . . 496.4. Structure and semantic of NetCDF Gridded Noise on Sea Level Anomaly files . . . . . . . . 526.5. Structure and semantic of NetCDF Gridded Change reference files . . . . . . . . . . . . . . 54

7. Accessibility of the products 567.1. Folders on the ftp server . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

7.1.1. Gridded Delayed-Time and Near-Real-Time products (SLA, ADT, Geostrophic cur-rents) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

7.1.2. Along-track Delayed Time and Near Real Time SLA and ADT files . . . . . . . . . 587.1.3. Gridded Change of Reference folders . . . . . . . . . . . . . . . . . . . . . . . . . 597.1.4. Gridded Noise estimations folders . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

8. News and Updates 608.1. [Duacs] Operational news . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 608.2. Updates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60


CLS-DOS-NT-06-034 - Issue 4.4 - Date : 2015/06/30 - Nomenclature : SALP-MU-P-EA-21065-CLS 1

1. Introduction

DUACS is part of the CNES multi-mission ground segment (SSALTO). It processes data from all altimetermissions: HY-2A, Saral/AltiKa, Cryosat-2, OSTM/Jason-2, Jason-1, Topex/Poseidon, Envisat, GFO, ERS-1&2.Developed and operated by CLS, it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies), funded under the European Commission and the Midi-Pyrénées regional council.It has been integrated to the CNES multi-mission ground segment SSALTO in 2001, and it is maintained,upgraded and operated with funding from CNES with shared costs from EU projects.At the beginning of 2004, DUACS was redefined as the Data Unification Altimeter Combination System.

Figure 1: DUACS and AVISO, a user-driven altimetry service

DUACS provides a consistent and homogeneous catalogue of products for varied applications, both for nearreal time applications and offline studies. Some DUACS gridded products are available free of charge. Com-mercial use of some gridded products is subject to separate agreement and licence (Contact [email protected]).



The data provided to users have a global coverage and regional products are also computed over specificareas:Mediterranean Sea, Black Sea, Mozambique, Europe and Arctic .Since April 15th 2014, a new version of products are now distributed: in the former version, the productswere based on a 7-year reference period [1993, 1999]. As 20 years of altimeter measurements are nowavailable it is of high interest to change the reference period for a longer period: in the 2014 version wethus change to a 20-year reference period [1993, 2012], as presented by Pujol and Faugere, 2013 [54] at thelast Ocean Surface Topography Science Team meeting and in Aviso+ Newsletter9 by Maheu et al., 2013[46]. Depending on your application, you may wish to use this improved 20-year reference or you maywish to keep the original 7-year reference period. This is the reason why, new "ref20yto7y" products arealso distributed. They consist of corrective maps that allow the user to change the reference of the SLAand MDT products. Three corrective maps are available, for the Mediterranean Sea, Black Sea and GlobalOcean. See sections 4.2.6.1. and 4.3.6.1.Moreover noise estimations for Near-real-Time and Delayed-Time are also distributed. These are griddedproducts containing the noise of the filtering of SLA Global Ocean products and are described in section4.2.6.4. for NRT and 4.3.6.4. for DT. For Mediterranean and Black seas, only one value has been calculatedand is given in the same sections.

This document describes the along-track and gridded products generated by the SSALTO/DUACS near-realtime and delayed time altimeter data processing software. The updates and reprocessing are presented in firstpart. The SSALTO/DUACS system is then introduced: after a description of the input data, an overview ofthe processing steps is given. Then complete information about the SSALTO/DUACS output data (i.e userproducts, in Near-Real Time and in Delayed Time) is provided, giving nomenclature, format description,and software routines.

More information regarding the SSALTO/DUACS project and products may be found on the AVISO website at the respective addresses:http://www.aviso.altimetry.fr/duacs/http://www.aviso.altimetry.fr/en/data/products.html

http://www.aviso.altimetry.fr/duacs/

http://www.aviso.altimetry.fr/en/data/products.html



1.1. Data policy and data access

All SSALTO/DUACS product users need an account on FTP, whether for Near-Real-Time or for Delayed-Time data, for along-track and gridded products.The SSALTO/DUACS along-track data (level 3) are now shared with the MyOcean catalogue. MyOcean isan European project dedicated to operational oceanography. MyOcean Service provides the best set of infor-mation available on the Ocean for the large and regional scales (European seas), based on the combinationof space and in situ observations, and their use into models: temperature, salinity, currents, ice extent, sealevel, primary ecosystems... (see www.myocean.eu.org). When users choose these SSALTO/DUACSalong-track data, their personal information can be transmitted by Aviso/CNES to the MyOcean Europeanproject for their user databases, with the user’s agreement.Duacs gridded products (level 4) are available free of charge for scientific studies or non-profit projectsonly.Commercial use of gridded products or applications not in line with the standard license agreement is sub-ject to separate agreement and licence (Contact [email protected]).Please, subscribe to get access to SSALTO/DUACS products by filling the registration form on:http://www.aviso.altimetry.fr/en/data/data-access/registration-form.html.

www.myocean.eu.org

http://www.aviso.altimetry.fr/en/data/data-access/registration-form.html



2. Geodetic orbit for AltiKa (June 2015 for NRT products)

Due to reaction wheel issues, SARAL station keeping maneuvers have not been performed nominally sinceMarch 31st, 2015 . As a result, SARAL/AltiKa’s ground track has been drifting from the nominal track withdeviations overtaking 10km depending on the latitude, instead of +/-1km usually. This drift has an impacton the SSALTO/Duacs AL products since April 1st, 2015. Indeed, SARAL/AltiKa has been currently pro-cessed as a repetitive mission (like Jason-2). This processing includes the projection of the measurementinto a theoretical track position in order to benefit from the precise Mean Profile estimated from past mis-sions (ERS1/2, Envisat) (see 4.2.6.2. 4.3.6.2.). However, as the distance between the theoretical track andthe true track position is now large, this projection processing induces an additional error in the product.Since mid may 2015, we indeed observed an increase of the variability of the SARAL/AltiKa SLA at shortwavelengths (< about 200km).In order to limit the degradation of the quality of the product, the SARAL/AltiKa mission is processed sinceJune 30th, 2015 as a geodetic mission, i.e. avoiding projection on a theoretical track, as currently donefor Cryosat-2 or HY-2A processing. This implies that the measurement positions change from one cycleto another one. Moreover, a short wavelength error is induced on the raw SARAL/AltiKa measurement,due to the use of a gridded Mean Sea Surface solution rather than a more precise Mean Profile for SLAcomputation. However, SSALTO/Duacs processing includes an along-track filtering that strongly reducesthis error signature on filtered products (see 4.2.6.4. and 4.3.6.4.).



3. Integration of the HaiYang-2A (HY-2A) Mission in NRT products (May2014) and in DT products (November 2014)

HY-2A is the first altimetric and radiometric satellite launched by the China National Space Administration(CNSA) dedicated to oceanography. It has been developped with the support from the National SatelliteOcean Application Service (NSOAS). The mission HY-2A has been launched in August 2011. Thanksto CNES/NSOAS agreement on HY-2A, both agencies decided to collaborate and a processing prototype(HPP) with specific evolutions on the ground processing of the altimeter data (retracking of S-IGDRs) hasbeen developed. The Jason-1/Jason-2 retracking (MLE4, Amarouche et al., 2004 [1]) is used to recomputethe altimeter parameters. Complete information can be found in Picot et al., 2013 [51]. As the level ofHY-2A HPP is high, it has been decided to implement it in the SSALTO/Duacs multimission system. It willthus complement the sampling and will provide valuable information on the ocean mesoscale variability.

Figure 2: Example of a map of Sea Level Anomalies (MSLA) where tracks of HY-2A are superimposed



4. SSALTO/DUACS system

4.1. Introduction

This chapter presents the input data used by the system and an overview of the different processing stepsnecessary to produce the output data.SSALTO/DUACS system is made of two components: a Near Real Time one (NRT) and a Delayed Time(DT) one.In NRT, the system’s primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions available.In DT, it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry community.Following figure gives an overview of DUACS system, where processing sequences can be divided into 7main steps:

• acquisition

• homogenization

• input data quality control

• multi-mission cross-calibration

• product generation

• merging

• final quality control.



Figure 3: SSALTO/DUACS processing sequences




4.2. Near Real Time processing steps

4.2.1. Input data, models and corrections applied

To produce along-track (L3) and maps (L4) products in near-real time, the DUACS system uses two flows,based on the same instrumental measurements but with a different quality:

• The IGDRs that are the latest high-quality altimeter data produced in near-real-time.

• The OGDRs that include real time data (SARAL/AltiKa, OSTM/Jason-2 and Cryosat-2) to completeIGDRs. These fast delivery products do not always benefit from precise orbit determination, norfrom some external model-based corrections (Dynamic Atmospheric Correction (DAC), Global Iono-spheric Maps (GIM)).

Integration of OGDR data increased the resilience and precision of the system. A better restitution of oceanvariability is observed, especially in high energetic areas.

Altimetric product Source Availability Type of orbit

Jason-2 IGDR CNES ~24h CNES MOE GDR-Esince May 25, 2015

OGDR NOAA/EUMETSAT ~3 to 5 h

Cryosat-2 IGDR-like ESA/CNES ~48 h CNES MOE GDR-E

OGDR-like ESA/CNES best effort

Saral/AltiKa IGDR CNES ~48 h CNES MOE GDR-Duntil June 30, 2015CNES MOE GDR-Eafterwards

OGDR ISRO/EUMETSAT ~3 to 5 h

HY-2A IGDR CNES/NSOAS best effort (with amean delay of 72 h)

CNES MOE GDR-D

Table 1: SSALTO/DUACS Near-Real Time Input data overview

See Figure 4: Overview of the near real time system data flow management.



DUACS NRT product from IGDR1

j2 c2 al h2

Product version D CPP [4] version T patch 2 HPP [51]

Orbit CNES MOE GDR-E sinceMay 25, 2015

CNES MOE GDR-E CNES MOE GDR-Duntil June 30 2015,

CNES MOE GDR-Eafterwards

CNES MOE GDR-D

Ionopheric bi-frequency altimeterrange measurements

GIM model (Iijima et al,1998[31])

Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)

Wet tropo-sphere

AMR radiometer(enhancement in coastal

regions)

Model computed from ECMWF Gaussiangrids

Model computedfrom ECMWFGaussian grids

DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard, 2003[6])+ inverse barometer. Filtering temporal window is

recentered using forecasts

Ocean tide GOT4v8 (S1 and S2 are included) and TPX 07.2 [22] for Arctic products

Pole tide [Wahr, 1985 [69]]

Solid earthtide

Elastic response to tidal potential [Cartwright and Tayler, 1971[8]], [Cartwright and Edden,1973[9]]

Loading tide GOT4v8 (S1 and S2 are included)

Sea statebias

Non Parametric SSB [N.Tran et al., 2012[65]] (with

cycles J2 1-36 usingGDR-D

Non parametric SSBfrom J1 with

unbiased sigma0

Hybrid SSB (methodfrom Scharroo et al,

2004 [63] applied to al)

Calculated fromHPP [51]: -3.45%

of SWH

Orbit error Global multi-mission crossover minimization (Le Traon and Ogor,1998[40])

LW errors Optimal Interpolation [Le Traon et al., 1998[39]]

Intercalibration Reference from cycle 20

Mean profile(see 4.2.6.1.and 4.2.6.2.)

Computed with 20 years ofTP/J1/J2 data; referenced

[1993,2012]

MSS_CNES_CLS11[48] referenced

[1993,2012]

Until June 30th, 2015:Computed with 15 years

of E1/E2/EN data;referenced [1993,2012];

Since July 1st, 2015:MSS_CNES_CLS11

[48] referenced[1993,2012]

MSS_CNES_CLS11[48] referenced

[1993,2012]

(1) A flag included in the along-track files indicates the source of the production (OGDR/FDGDR or IGDR). If flag=0, the

processed data comes from OGDRs/FDGDRs; if flag=1, the processed data comes from IGDRs.

Table 2: Corrections and models applied in SSALTO/DUACS NRT products produced from IGDRs.

The period of reference has changed since April 2014: it is now 20 years instead of 7 years. Please refer tosection 4.2.6.1.



DUACS NRT product from OGDR 2

j2 c2 al

Productstandard ref

version D CPP [4] version T patch 2

Orbit Navigator

Ionopheric bi-frequency altimeter rangemeasurements

GIM model (Iijima et al,1998[31])

Dry tropo-sphere

Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)

Wet tropo-sphere

AMR radiometer(enhancement in coastal

regions)

Model computed from ECMWF Gaussian grids

DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2were excluded) (Carrere and Lyard, 2003[6])+ inverse barometer. Filtering temporal

window is decentered using forecasts

Ocean tide GOT4v8 (S1 and S2 are included) and TPX 07.2 [22] for Arctic products

Pole tide [Wahr, 1985 [69]]

Solid earthtide

Elastic response to tidal potential [Cartwright and Tayler, 1971[8]], [Cartwright and Edden,1973[9]]

Loading tide GOT4v8 (S1 and S2 are included)

Sea statebias

Non Parametric SSB [N. Tranet al., 2012[65]] (with cycles J2

1-36 using GDR-D

Non parametric SSB from J1with unbiased sigma0

Hybrid SSB (method fromScharroo et al, 2004 [63]

applied to al)

Orbit error Specific filtering of long-wavelength signal3

LW errors Optimal Interpolation [Le Traon et al., 1998[39]]

Intercalibration Reference from cycle 20

Mean profile(see 4.2.6.1.and 4.2.6.2.)


[1993,2012]

MSS_CNES_CLS11 [48]referenced [1993,2012]

Until June 30th, 2015:Computed with 15 years ofE1/E2/EN data; referenced

[1993,2012];Since July 1st, 2015:

MSS_CNES_CLS11 [48]referenced [1993,2012]

(2) A flag included in the along-track files indicates the source of the production (OGDR or IGDR). If flag=0, the processed data

comes from OGDRs; if flag=1, the processed data comes from IGDRs.

(3) Specific data processing was applied on long wave-length signal (§4.2.3. of the user manual)

Table 3: Corrections and models applied in SSALTO/DUACS NRT products produced from OGDRs.




4.2.2. Acquisition

The acquisition process is twofold:

• straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France, TEC grids from JPL,NRT MOG2D corrections,...) from external repositories.

• synchronisation process.

To be homogenized properly, altimeter data sets require various auxiliary data. The acquisition softwaredetects, downloads and processes incoming data as soon as they are available on remote sites (externaldatabase, FTP site). Data are split into passes if necessary. If data flows are missing or late, the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data. This processing step delivers "raw" data, that is to say data that have been dividedinto cycles and passes, and ordered chronologically.The acquisition step uses two different data flows in near-real time: the OGDR flow (within a few hours),and the IGDR flow (within a few days).For each OGDR input, the system checks that no equivalent IGDR entry is available in the data base beforeacquisition; for each IGDR input, the system checks and delete the equivalent OGDR entry in the data base.These operations aim to avoid duplicates in SSALTO/DUACS system.

Figure 4: Overview of the near real time system data flow management



4.2.3. Homogenization

The homogenization process consists of applying the most recent corrections, models and references homo-geneously for all missions and recommended for altimeter products. Each mission is processed separatelyas its needs depend on the base input data. The list of corrections and models currently applied is providedin tables 2 and 3 for NRT data. The system includes SLA filtering to process OGDR data. DUACS extractfrom these data sets the short scales (space and time) which are useful to better describe the ocean variabil-ity in real time, and merge this information with a fair description of large scale signals provided by themulti-satellite observation in near real time (read: IGDR-based DUACS data). Finally an "hybrid" SLA iscomputed.

Figure 5: Merging pertinent information from IGDR and OGDR processing

4.2.4. Input data quality control

The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data. Thanks to the high quality of current missions, this process rejects a small percent-age of altimeter measurements, but these erroneous data could be the cause of a significant quality loss.The quality control relies on standard raw data editing with quality flags or parameter thresholds, but alsoon complex data editing algorithms based on the detection of erroneous artefacts, mono and multi-missioncrossover validation, and macroscopic statistics to edit out large data flows that do not meet the system’srequirements.



4.2.5. Multi-mission cross-calibration

The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information. It removes any residual orbit error (OE, Le Traon and Ogor, 1998[40]), or longwavelength error (LWE, Le Traon et al., 1998[39]), as well as large scale biases and discrepancies betweenvarious data flows.

This process is based on two very different algorithms: a global multi-mission crossover minimization fororbit error reduction (OER), and Optimal Interpolation (OI) for LWE.

Multi-satellite crossover determination is performed on a daily basis. All altimeter fields (measurement,corrections and other fields such as bathymetry, MSS,...) are interpolated at crossover locations and dates.Crossovers are then appended to the existing crossover database as more altimeter data become available.This crossover data set is the input of the Orbit Error Reduction (OER) method. Using the precision of thereference mission orbit (TP/J1/J2), a very accurate orbit error can be estimated. This processing step doesnot concern OGDR data.

LWE is mostly due to residual tidal, high frequency ocean signals remaining errors and residual orbit error.The OI used for LWE reduction uses precise parameters derived from:

• accurate statistical description of sea level variability

• regional correlation scales

• mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission).

4.2.6. Product generation

The product generation process is composed of four steps: computation of raw SLA, cross-validation,filtering&sub-sampling, and generation of by-products.



4.2.6.1. Change of Reference

As from April 2014, an important modification has been implemented in SSALTO/Duacs products. Indeed,the period of reference was 7 years in older version (from 1993 to 1999) and it is now 20 years (from1993 to 2012). This takes into account the variations of the oceans in the last years, as shown on Fig-ure 6. The detailed informations can be found in the document: http://www.aviso.altimetry.fr/fileadmin/documents/data/duacs/Duacs2014.pdf In order to give the users the time toadapt to this new reference period, three gridded products are delivered for global ocean, Mediterranean andBlack seas called "ref20yto7y" If you may wish to come back to the 7 year reference period (=SLA7years):for each measurement of SLA20years from the new products,

• since the REF20YTO7Y products are gridded, you need to interpolate at the location of the SLAmeasurement the variable ref20yto7y (see 6.5. for information about the format of the file)

• calculate SLA7years=SLA20years from the new products - ref20yto7y previously calculated

• The absolute Dynamic Topography field is unchanged (the ADT products have been calculated withconsistent SLA and MDT fields).

Figure 6: Impact in cm of the reference change from 7 years to 20 years ([1993-1999] to [1993-2012])

http://www.aviso.altimetry.fr/fileadmin/documents/data/duacs/Duacs2014.pdf




4.2.6.2. Computation of raw SLA

The SSH anomalies are used in oceanographic studies. They are computed from the difference of the in-stantaneous SSH minus a temporal reference. This temporal reference can be a Mean Profile (MP) in thecase of repeat track or a gridded MSS when the repeat track cannot be used. The errors affecting the SLAs,MPs and MSS have different magnitudes and wavelengths. The computation of the SLAs and their errorsassociated are detailed in Dibarboure et al, 2010 [14].

Use of a Mean ProfileIn the repeat track analysis at 1 Hz (when the satellites flies over a repetitive orbit), measurements are re-sampled along a theoretical ground track (or mean track) associated to each mission. Then a Mean Profile(MP) is subtracted from the re-sampled data to obtain SLA. The MP is a time average of similarly re-sampleddata over a long period.

• The Mean Profile used for Saral/Altika until June 30th, 2015 is computed with 15 years of ERS-1,ERS-2 and Envisat, referenced to the period [1993, 2012]. Since July 1st, 2015, no Mean Profile canbe used for AltiKa because the orbit is drifting. The MSS is used instead of the MP (see below).

• The Mean Profile used for Jason-2 is computed with 20 years of T/P, Jason-1 and Jason-2, referencedto years [1993, 2012].

• No Mean Profile can be used for Cryosat-2 mission (c2). The MSS must be used instead (see below).

• No Mean Profile can be used for HY-2A mission (h2) because there are not enough data to calculateit. The MSS must be used instead (see below).

Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible .

• Indeed, as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide, precise cross-track projection and/or interpolation schemes are required to avoid errors.

• The ocean variability is removed to minimize the seasonal/interannual aliasing effects. The mesoscalevariability error is eliminated with an iterative process using a priori knowledge from Sea Level mapsderived from previous iterations or from other missions.This process enables us to reference the meanprofiles for all missions to a common period (reference period) for the sake of consistency with othermissions. The reference period is [1993, 2012] and is thus independent from the number of years usedto compute mean profiles.

• Moreover, the inter-annual variabilty error is accounted for by using the MSS.

• Finally, for these Mean Profiles, the latest standards and a maximum of data were used in order toincrease as much as possible the quality of their estimation . Note that a particular care was broughtto the processing near coasts.

Use of a MSSThe repeat track analysis is impossible for Cryosat-2 mission (c2) and AltiKa mission after July 1st, 2015because the satellite is not in a repetitive orbit phase. Moreover, it is not possible for the moment to computea mean profile for HY-2A because there is not enough data to compute it.. The alternative is to use the MSSinstead. The gridded MSS is derived from along track MPs and data from geodetic phases. Thus any error



on the MP is also contained in the MSS. There are essentially 4 types of additional errors on gridded MSSwhich are hard to quantify separately:

• To ensure a global MSS coherency between all data sets, the gridding process averages all sensor-specific errors and especially geographically correlated ones.

• The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track, degrading along-track content.

• There are also errors related to the lack of spatial and temporal data (omission errors).

• The error stemming from the geodetic data: the variability not properly removed before the absorptionin the MSS.

The MSS used in the products is MSS_CNES_CLS11 [48], referenced [1993,2012]

4.2.6.3. Cross validation

After the repeat track analysis, the cross-validation technique is used as the ultimate screening process todetect isolated and slightly erroneous measurements. Small SLA flows are compared to previous and inde-pendent SLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal.



4.2.6.4. Filtering and sub-sampling

Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter. As dataare filtered from small scales, a sub-sampling is finally applied. Along-track SLA are then produced (thoseproducts are along-track *vfec* files). The filtering and sub-sampling is adapted to each region and prod-uct as a function of the characteristics of the area and of the assimilation needs. Details were presented inDufau et al., 2013 [21]. Please, refer to the technical note http://www.aviso.altimetry.fr/fileadmin/documents/data/duacs/Duacs2014.pdf for comparison between DUACS 2014and former version.

The values taken into account are the following:

Filtering Sub-sampling

Global 65 km 14km

Mediterranean Sea about 40km 14km

Black Sea about 40km 14km

Europe about 35km No (7km)

Arctic about 35km No (7km)

Table 4: SSALTO/DUACS Near-Real Time Filtering and sub-sampling values

Noise estimationSince April 2014, a new filtering level takes into account the mesoscale capability computed for the Jason-2 1hz SLA. Users recommendations from the TAPAS working group motivated the choice of a spatiallyuniform cut-off length to filter SLA in association with a more accurate measurement error description.Therefore, a cut-off length of 65km is applied everywhere to filter SLA. Compared to the previous SLAfiltering applied, it changes drastically the SLA resolution at low latitudes. In these areas, cut-off lengthsare reduced from more than 100km .In wavenumber spectra, the 1hz measurement error is the noise level estimated as the mean value of energyat high wavenumbers (below 20km in term of wave length). The 1hz noise level spatial distribution (Figure7) follows the instrumental white-noise linked to the Surface Wave Height but also connections with thebackscatter coefficient. The full understanding of this hump of spectral energy (Dibarboure et al., 2013[12]) still remain to be achieved and overcome with new retracking, new editing strategy or new technology.Users of non-filtered SLA will have to use the 1hz estimated white noise (Figure 7 left) whereas users offiltered SLA the remaining error level after filtering (Figure 7 right).





Figure 7: Noise Level in 1hz Jason-2 SLA estimated from mean wavenumber spectra over 2011 in 10˚x10˚boxes (cm rms) before 65km filtering (left) and after (right)

The regional products as Mediterranean Sea, Black Sea cover too small areas to be concerned by such a mapof 1hz measurement error. In this case, a mean wavenumber spectrum has been computed over each areaand the noise level estimated from it. A constant value is then prescribed for the 1hz noise level as well asthe remaining error after filtering:

Before Filtering After FilteringCryosat-2 2.08 0.84Jason-2 2.36 0.95Saral/AltiKa 1.75 0.71HY-2A 2.52 1.00

Table 5: Measurement noise error before/ after spatial filtering for Mediterranean and Black Sea products(cms rms)



4.2.6.5. Computation of ADT Products

Along-track ADT products are obtained as follows:ADT = SLA + MDT

where MDT is the Mean Dynamic Topography. The Mean Dynamic Topography is the part of Mean SeaSurface Height due to permanent currents, so MDT corresponds to the Mean Sea Surface Height minusGeoid. Since DUACS 2014 version, a new MDT has been used: it takes into account the recent geoid meanfield (GOCE DIR-R4) and in-situ dataset, as well as improved processing method. Details are presented inRio et al, 2013 [59].Note that the ADT products have been computed with consistent SLA and MDT fields:

ADT = SLA20years + MDT20years

The regional ADT product is computed using a specific regional MDT (Mediterranean Sea only) given inRio et al., 2014 [60]:

ADTMed = SLAMed + MDTMed

The product generation processing step is activated daily in near real time.

4.2.7. Generation of gridded Sea Level Anomalies (MSLA) products

4.2.7.1. Merging process

The Merging process is twofold: mapping and generation of by-products.

A mapping procedure using optimal interpolation with realistic correlation functions is applied to produceSLA and ADT maps (MSLA and MADT or L4 products) at a given date. The procedure generates acombined map merging measurements from all available altimeter missions (Ducet et al., 2000[20]). Themapping process takes into account an updated suboptimal Optimal Interpolation parameterization to min-imize transition artefacts. More accurate correlation scales are used compared to Ducet et al., taking intoaccount optimally the spatial variability of the signal.Combining data from different missions significantly improves the estimation of mesoscale signals (LeTraon and Dibarboure, 1999[41]), (Le Traon et al., 2001[42]), (Pascual et al., 2006[49]). Several improve-ments were made compared to the version used by (Le Traon et al., 1998[39]). An improved statisticaldescription of sea level variability, noise and long wavelength errors is used. Covariance functions includ-ing propagation velocities that depend on geographical position were thus used. For each grid point, thezonal and meridional spatial scales, the time scale and the zonal and meridional propagation velocities wereadjusted from five years of TP+ERS combined maps. In addition to instrumental noise, a noise of 10% ofthe signal variance was used to take into account the small scale variability which cannot be mapped andshould be filtered in the analysis.In the NRT DUACS processing, contrary to DT case, the products cannot be computed with a centred com-putation time window for OER, LWE and mapping processes: indeed, as the future data are not availableyet, the computation time window is not centered (For each day of production, 3 maps are computed: for



the maps of date D, D-3 and D-6 are using respectively the data in the time intervall of [D-42, D], [D-3-42,D+3] and [D-6-42, D+6]).

Change of resolutionIn DUACS 2014 version, after the feedback from users, the Mercator grid projection with 1/3˚ x1/3˚ spa-tial resolution (Global product) is abandoned. The DUACS 2014 Global products are directly computedon a Cartesian 1/4˚x1/4˚ spatial resolution. Please, refer to the technical note http://www.aviso.altimetry.fr/fileadmin/documents/data/duacs/Duacs2014.pdf for comparison betweenDUACS 2014 and former version.

Formal mapping errorThe formal mapping error represents a purely theoretical mapping error. It mainly represents errors inducedby the constellation sampling capability and consistency with the spatial/temporal scales considered, as de-scribed in Le Traon et al (1998) [39] or Ducet et al (2000) [20].In the former version, the formal mapping error was delivered as the "err" product, and expressed in version,it is expressed in meters and is delivered in the same NetCDF file as the SLA.SLA computation from OGDR is based on the same algorithms, only parameters are different to take intoaccount OGDR specificity. LWE and mapping process are based on IGDR and GDR available residuals,also with specific parameters.The combined map is used to generate by-products such as geostrophic currents or absolute dynamic topog-raphy.

Geostrophic currentsSince DUACS 2014 version, the geostrophic current computation is improved with:

• The use of the 9-point stencil width method (Arbic et al, 2012, [3]) at latitudes appart from ±5˚. Itcontributes to reduce the impact of the anisotropy introduced by the Cartesian 1/4˚ grid resolution.

• The SLA computation is Largerloef et al, 1999 [36] in the equatorial band is improved in order tosmooth the transition at ±5˚ and improve the consistency between altimeter products and drifter ob-servations.

More information can be found in http://www.aviso.altimetry.fr/fileadmin/documents/data/duacs/Duacs2014.pdf.







4.2.8. Quality control

The production of homogeneous products with a high quality data and within a short delay is the keyfeature of the DUACS processing system. But some events (failure on payload or on instruments, delay,maintenance on servers), can impact the quality of measurements or the data flows. A strict quality controlon each processing step is indispensable to appreciate the overall quality of the system and to provide thebest user services.

4.2.8.1. Final quality Control

The Quality Control is the final process used by DUACS before product delivery. In addition to daily au-tomated controls and warnings to the operators, each production delivers a large QC Report composed ofdetailed logs, figures and statistics of each processing step. Altimetry experts analyse these reports twicea week (only for internal validation, those reports are not disseminated). A shorter report is delivered toDUACS users upon each product delivery.This QC activity is used as a modest Cal/Val activity on NRT products. It provides level2 product centreswith a detailed feedback on potential anomalies for a fast reprocessing of erroneous IGDR flows.

The Quality Reports are now on the authenticated server. To access them via a browse, please type yourlogin and password in the following address:ftp://LOGIN:[email protected]/quality_report/

4.2.8.2. Performance indicators

To appreciate the quality situation of the DUACS system, performance indicators are computed daily. Theyaim at evaluate the status of the main processing steps of the system: the input data availability, the inputdata coverage, the input data quality and the output product quality. These indicators are computed for eachand every currently working satellite, and combined to obtain the overall status.

Figure 8: Example with the key performance indicator on 2009/06/27

ftp://LOGIN:[email protected]/quality_report/



See the description, the latest and previous indicators on Aviso website:http://www.aviso.altimetry.fr/en/data/product-information/information-about-mono-and-multi-mission-processing/ssaltoduacs-multimission-altimeter-products/key-performance-indicators.html

http://www.aviso.altimetry.fr/en/data/product-information/information-about-mono-and-multi-mission-processing/ssaltoduacs-multimission-altimeter-products/key-performance-indicators.html

http://www.aviso.altimetry.fr/en/data/product-information/information-about-mono-and-multi-mission-processing/ssaltoduacs-multimission-altimeter-products/key-performance-indicators.html



4.3. Delayed Time processing steps

4.3.1. Input data, models and corrections applied

Delayed Time products are generated:

• from Aviso GDR products for Saral/AltiKa, Jason-1 (historical , tandem track and geodetic track),Jason-2

• from ESA GDR products for Cryosat-2, Envisat (historical, new orbit and drifting track), ERS-1(historical and geodetic track) and ERS-2

• from NOAA GDR for GFO.

• from NSOAS GDR for HY-2A.

The GDR products are computed with updated orbit and corrections as described in the following table.



DUACS DT productj2 j1;j1n;j1g tp;tpn

Product GDR-D GDR-D GDR-COrbit Cnes POE (GDR-D standards

for cycles ≤253 and GDR-Eafterwards)

Cnes POE (GDR-D standards) GSFC (ITRF 2005,GRACE laststandards)

Ionopheric Dual frequency altimeter range measurements Dual frequency (Topex), DORIS(POSEIDON)

Dry tropo-sphere

Model computed fromECMWF Gaussian grids (newS1 and S2 atm. tides applied)

Model computed fromECMWF rectangular grids(new S1 and S2 atm. tides

included)

Model computed from ERAinterim Gaussian grids (new S1

and S2 atm. tides included)

Wet tropo-sphere

JMR/AMR radiometer TMR radiometer (Scharroo et al.2004 [62])

DAC MOG2D High Resolution forced with ECMWF pressure andwind fields (S1 and S2 excluded) + inverse barometer computed

from rectangular grids

MOG2D High Resolution forcedwith ERA-Interim pressure and

wind fields (S1 and S2 excluded) +inverse barometer computed from

rectangular gridsOcean tide GOT4v8 (S1 and S2 are included)Pole tide [Wahr, 1985[69]]Solid earthtide

Elastic response to tidal potential Cartwright and Tayler, 1971[8] ,Cartwright and Edden, 1973[9]

Loading tide GOT4v8 (S1 parameter is included)Sea statebias

Non Parametric SSB [N. Tranet al., 2012[65]] (with c J2 1-36

using GDR-D

Non Parametric SSB [N. Tranet al., 2012[65]](with c J1

1-111 using GDR-C standardsand GDR-D orbit

Non parametric SSB [N. Tran andal. 2010[67]] (using c 21-131 withGSFC orbit for TP-A; c 240-350

with GSFC orbit for TP-B)Orbit error Global multi-mission crossover minimization (Le Traon and Ogor, 1998 [40])LW errors Optimal Interpolation (Le Traon et al., 1998[39])Intercalibration Reference from cycle 11 Reference from cycle 1 to 354Global Bias Calibrated on J1+TP Mean Sea

Level (using c 1-11 J2); MSLzero reference in early 1993

Calibrated on TP Mean SeaLevel (using c 1-11 J1); MSLzero reference in early 1993

MSL zero reference in early 1993

Regional Bias Calibration on J2 Calibration on J1+J2Mean profile(see 4.3.6.1.and 4.3.6.2.)


[1993,2012]

TP/J1: Computed with 20 years of TP/J1/J2 data; referenced[1993,2012];

TPN/J1N: computed with 6 years of TPN/J1N; referenced[1993,2012]

Period of use from cycle 9 from cycle 9 cycles 1 to 481

Table 6: Corrections and models applied to SSALTO/Duacs DT products for TOPEX/Poseidon, Jason-1,Jason-2.




DUACS DT producte1 e2 en;enn

Product OPR GDR-V2.1+Orbit Reaper (Rudenko et al., 2012[61]) Cnes POE (GDR-D standards)Ionopheric Reaper (NIC09 model, Scharro

and Smith, 2010, [64])Bent model (c≤36), GIM

model (c≥37) ((Iijima et al,1998 [31])

Bi-frequency altimeter rangemeasurement (c≤64); GIM model

c≥65 (Iijima et al., 1999[31])corrected for 8 mm bias

Dry tropo-sphere

Model computed from ERA interim Gaussian grids (new S1and S2 atm. tides included)

Model computed from ECMWFGaussian grids (new S1 and S2

atm. tides applied)Wet tropo-sphere

MWR radiometer MWR corrected for 23.6GHzTB drift (Scharroo et al.,

2004[62])+ Neural Networkalgorithm (Tran and Obligis,

2003[66]

Cycles≤94: MWR (dist≥50kmfrom the coasts), ECMWF model

(50≥dist≥10km)Cycles≥95:MWR.

DAC MOG2D High Resolution forced with ERA-Interim pressureand wind fields (S1 and S2 excluded) + inverse barometer

computed from rectangular grids

MOG2D High Resolution forcedwith ECMWF pressure and wind

fields (S1 and S2 excluded) +inverse barometer computed from

rectangular gridsOcean tide GOT4v8 (S1 and S2 are included)Pole tide [Wahr, 1985[69]]]Solid earthtide

Elastic response to tidal potential Cartwright and Tayler, 1971[8] ,Cartwright and Edden, 1973[9]


BM3 [Gaspar and Ogor1994[24]]

Non parametric SSB [Mertz etal., 2005[47]]

Non Parametric SSB [N. Tran etal., 2012[65]] compatible with

enhanced MWROrbit error Global multi-mission crossover minimization (Le Traon and Ogor, 1998 [40])LW errors Optimal Interpolation (Le Traon et al., 1998[39])Global Bias Calibrated on TP/J1/J2 Mean Sea LevelMean profile(see 4.3.6.1.and 4.3.6.2.)

Computed with 15 years of E1/E2/EN data; referenced[1993,2012]

EN: Computed with 15 years ofE1/E2/EN data; referenced

[1993,2012]ENN: use of MSS_CNES_CLS11

[48], referenced [1993,2012]Period of use cycles 15 to 43 Including E-F

geodetic phasescycles 1 to 83 from cycle 9

Table 7: Corrections and models applied in SSALTO/DUACS DT products for ERS-1, ERS-2, Envisat

The period of reference has changed since April 2014: it is now 20 years instead of 7 years. Please referto section 4.3.6.1.



DUACS DT productc2 g2 al h2

Product CPP CNES [4] GDR (NOAA) GDR-T patch2 GDR (NSOAS)Orbit CNES POE (GDR-D

standards for cycles≤66 and GDR-E

afterwards)

GSFC (ITRF 2005,GRACE last standards

Cnes POE (GDR-Dstandards for cycles≤23 and GDR-E

afterwards)

Cnes POE (GDR-Dstandards)

Ionopheric From GIM model (Iijima et al, 1998 [31])Dry tropo-sphere

Model computed fromECMWF Gaussian

grids (new S1 and S2atm. tides applied)

Model computed fromECMWF rectangulargrids (new S1 and S2atm. tides included)

Model computed from ECMWF Gaussiangrids (new S1 and S2 atm. tides applied)

Wet tropo-sphere

ECMWF Model GFO radiometer radiometer ECMWF Model

DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2excluded) + inverse barometer computed from rectangular grids

Ocean tide GOT4v8 (S1 and S2 are included)Pole tide [Wahr, 1985[69]]]Solid earthtide

Elastic response to tidal potential Cartwright and Tayler, 1971[8] ,Cartwright and Edden,1973[9]


Non parametric SSBfrom J1 with unbiased

sigma0

Non parametric SSB[N. Tran et al.,

2010[67]] (using c130 to 172 with GSFC

orbit)

Hybrid SSB (methodfrom Scharroo et al,2004 [63] applied to

al)

Linear model

Orbit error Global multi-mission crossover minimization (Le Traon and Ogor, 1998 [40])LW errors Optimal Interpolation (Le Traon et al., 1998[39])Global Bias Calibrated on TP/J1/J2 Mean Sea LevelMean profile(see 4.3.6.1.and 4.3.6.2.)

Use ofMSS_CNES_CLS11

[48], referenced[1993,2012]

Computed with 8years of G2 ;referenced

[1993,2012]

Until March 31st,2015 (during c 22):Computed with 15years of E1/E2/EN

data; referenced[1993,2012];

Since April 1st, 2015(c 22): Use of

MSS_CNES_CLS11[48], referenced

[1993,2012]

Use ofMSS_CNES_CLS11

[48], referenced[1993,2012]

Period of use from cycle 14 cycles 37 to 222 from cycle 1 from cycle 67

Table 8: Corrections and models applied in SSALTO/DUACS DT products for Cryosat-2, GFO, AltiKa andHY-2A

The period of reference has changed since April 2014: it is now 20 years instead of 7 years. Please referto section 4.3.6.1.



4.3.2. Acquisition

The acquisition process in Delayed time consists in a synchronisation process of all the auxiliary data re-quired to homogenize propely the altimeter data sets. The acquisition step uses the GDRs provided by theagencies.

4.3.3. Homogenization

The homogenization process consists of applying the most recent corrections, models and references homo-geneously for all missions and recommended for altimeter products. Each mission is processed separatelyas its needs depend on the base input data. The list of corrections and models currently applied is providedin tables 6 for DT data.

4.3.4. Input data quality control

The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data. Thanks to the high quality of current missions, this process rejects a small percent-age of altimeter measurements, but these erroneous data could be the cause of a significant quality loss.The quality control relies on standard raw data editing with quality flags or parameter thresholds, but alsoon complex data editing algorithms based on the detection of erroneous artefacts, mono and multi-missioncrossover validation, and macroscopic statistics to edit out large data flows that do not meet the system’srequirements.



4.3.5. Multi-mission cross-calibration

The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information. It removes any residual orbit error (OE, Le Traon and Ogor, 1998[40]), or longwavelength error (LWE, Le Traon et al., 1998[39]), as well as large scale biases and discrepancies betweenvarious data flows.

This process is based on two very different algorithms: a global multi-mission crossover minimization fororbit error reduction (OER), and Optimal Interpolation (OI) for LWE.

Multi-satellite crossover determination is performed on a daily basis. All altimeter fields (measurement,corrections and other fields such as bathymetry, MSS,...) are interpolated at crossover locations and dates.Crossovers are then appended to the existing crossover database as more altimeter data become available.This crossover data set is the input of the Orbit Error Reduction (OER) method. Using the precision of thereference mission orbit (TP/J1/J2), a very accurate orbit error can be estimated.

LWE is mostly due to residual tidal, high frequency ocean signals remaining errors and residual orbit error.The OI used for LWE reduction uses precise parameters derived from:

• accurate statistical description of sea level variability

• regional correlation scales

• mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission).

4.3.6. Product generation

The product generation process is composed of four steps: computation of raw SLA, cross-validation,filtering&sub-sampling, and generation of by-products.



4.3.6.1. Change of Reference

As from April 2014, an important modification has been implemented in SSALTO/Duacs products. Indeed,the period of reference was 7 years in older version (from 1993 to 1999) and it is now 20 years (from1993 to 2012). This takes into account the variations of the oceans in the last years, as shown on Fig-ure 9. The detailed informations can be found in the document: http://www.aviso.altimetry.fr/fileadmin/documents/data/duacs/Duacs2014.pdf In order to give the users the time toadapt to this new reference period, three gridded products are delivered for global ocean, Mediterranean andBlack seas called "ref20yto7y" If you may wish to come back to the 7 year reference period (=SLA7years):for each measurement of SLA20years from the new products,

• since the REF20YTO7Y products are gridded, you need to interpolate at the location of the SLAmeasurement the variable ref20yto7y (see 6.5. for information about the format of the file)

• calculate SLA7years=SLA20years from the new products - ref20yto7y previously calculated

• The absolute Dynamic Topography field is unchanged (the ADT products have been calculated withconsistent SLA and MDT fields).

Figure 9: Impact in cm of the reference change from 7 years to 20 years ([1993-1999] to [1993-2012])





4.3.6.2. Computation of raw SLA

The SSH anomalies are used in oceanographic studies. They are computed from the difference of the in-stantaneous SSH minus a temporal reference. This temporal reference can be a Mean Profile (MP) in thecase of repeat track or a gridded MSS when the repeat track cannot be used. The errors affecting the SLAs,MPs and MSS have different magnitudes and wavelengths. The computation of the SLAs and their errorsassociated are detailed in Dibarboure et al, 2010 [14].

Use of a Mean ProfileIn the repeat track analysis at 1 Hz (when the satellites flies over a repetitive orbit), measurements are re-sampled along a theoretical ground track (or mean track) associated to each mission. Then a Mean Profile(MP) is subtracted from the re-sampled data to obtain SLA. The MP is a time average of similarly re-sampleddata over a long period.

• The Mean Profile used for Saral/Altika until March 31th, 2015 (during cycle 22) is computed with15 years of ERS-1, ERS-2 and Envisat, referenced to the period [1993, 2012]. Since April 1st, 2015(during cycle 22), no Mean Profile can be used for AltiKa because the orbit is drifting. The MSS isused instead of the MP (see below).

• The Mean Profile used for T/P (cycles 1 to 364), Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 20 years of T/P, Jason-1 and Jason-2, referenced to years [1993, 2012].

• The Mean Profile used for T/P (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 6 years of T/P and Jason-1, referenced to the period[1993, 2012].

• The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission, ERS-2, and Envisat (onlyfor the first orbit, before November 2010) is computed with 15 years of ERS-1, ERS-2 and Envisat,referenced to the period [1993, 2012].

• No Mean Profile can be used for Envisat on its new orbit (enn), Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2). The MSS must be used instead (see below).

• No Mean Profile can be used for HY-2A mission (h2) because there are not enough data to calculateit. The MSS must be used instead (see below).

• The Mean Profile used for GFO is computed with 8 years of G2, referenced to the period [1993,2012].

Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible .

• Indeed, as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide, precise cross-track projection and/or interpolation schemes are required to avoid errors.

• The ocean variability is removed to minimize the seasonal/interannual aliasing effects. The mesoscalevariability error is eliminated with an iterative process using a priori knowledge from Sea Level mapsderived from previous iterations or from other missions.This process enables us to reference the meanprofiles for all missions to a common period (reference period) for the sake of consistency with othermissions. The reference period is [1993, 2012] and is thus independent from the number of years usedto compute mean profiles.



• Moreover, the inter-annual variabilty error is accounted for by using the MSS.

• Finally, for these Mean Profiles, the latest standards and a maximum of data were used in order toincrease as much as possible the quality of their estimation (see tables 6 to 8: Corrections and modelsapplied in SSALTO/DUACS Delayed-Time products). Note that a particular care was brought to theprocessing near coasts.

Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since November 2010, for Jason-1 on its geodetic orbit (j1g), for Cryosat-2 mission (c2) and AltiKa mission after April 1st, 2015 because the satellite is not in a repetitive orbit phase.Moreover, it is not possible for the moment to compute a mean profile for HY-2A because there is notenough data to compute it.. The alternative is to use the MSS instead. The gridded MSS is derived fromalong track MPs and data from geodetic phases. Thus any error on the MP is also contained in the MSS.There are essentially 4 types of additional errors on gridded MSS which are hard to quantify separately:

• To ensure a global MSS coherency between all data sets, the gridding process averages all sensor-specific errors and especially geographically correlated ones.

• The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track, degrading along-track content.

• There are also errors related to the lack of spatial and temporal data (omission errors).

• The error stemming from the geodetic data: the variability not properly removed before the absorptionin the MSS.

The MSS used in the products is MSS_CNES_CLS11 [48], referenced [1993,2012]

4.3.6.3. Cross validation

After the repeat track analysis, the cross-validation technique is used as the ultimate screening process todetect isolated and slightly erroneous measurements. Small SLA flows are compared to previous and inde-pendent SLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal.



4.3.6.4. Filtering and sub-sampling

Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter. As dataare filtered from small scales, a sub-sampling is finally applied. Along-track SLA are then produced (thoseproducts are along-track *vfec* files). Note that in Delayed-time, files *vxxc* are also produced: they arenot filtered and not sub-sampled).The filtering and sub-sampling is adapted to each region and product as a function of the characteristicsof the area and of the assimilation needs. Details were presented in Dufau et al., 2013 [21]. Please, re-fer to the technical note http://www.aviso.altimetry.fr/fileadmin/documents/data/duacs/Duacs2014.pdf for comparison between DUACS 2014 and former version.

The values taken into account for the filtering are the following:

Filtering Sub-samplingGlobal 65 km 14km for filtered, 7km for unfilteredMediterranean Sea about 40km 14km for filtered, 7km for unfilteredBlack Sea about 40km 14km for filtered, 7km for unfiltered

Table 9: SSALTO/DUACS Delayed Time Filtering and sub-sampling values

Noise estimationSince April 2014, a new filtering level takes into account the mesoscale capability computed for the Jason-2 1hz SLA. Users recommendations from the TAPAS working group motivated the choice of a spatiallyuniform cut-off length to filter SLA in association with a more accurate measurement error description.Therefore, a cut-off length of 65km is applied everywhere to filter SLA. Compared to the previous SLAfiltering applied, it changes drastically the SLA resolution at low latitudes. In these areas, cut-off lengthsare reduced from more than 100km .In wavenumber spectra, the 1hz measurement error is the noise level estimated as the mean value of energyat high wavenumbers (below 20km in term of wave length). The 1hz noise level spatial distribution (Figure10) follows the instrumental white-noise linked to the Surface Wave Height but also connections with thebackscatter coefficient. The full understanding of this hump of spectral energy (Dibarboure et al., 2013 [12])still remain to be achieved and overcome with new retracking, new editing strategy or new technology.Users of non-filtered SLA will have to use the 1hz estimated white noise (Figure 10 left) whereas users offiltered SLA the remaining error level after filtering (Figure 10 right).





Figure 10: Noise Level in 1hz Jason-2 SLA estimated from mean wavenumber spectra over 2011 in 10˚x10˚boxes (cm rms) before 65km filtering (left) and after (right)

The regional products as Mediterranean Sea, Black Sea cover too small areas to be concerned by such a mapof 1hz measurement error. In this case, a mean wavenumber spectrum has been computed over each areaand the noise level estimated from it. A constant value is then prescribed for the 1hz noise level as well asthe remaining error after filtering:

Before Filtering After FilteringCryosat-2 2.08 0.84Jason-2 2.36 0.95Saral/AltiKa 1.75 0.71HY-2A 2.52 1.00ERS-1 2.89 1.15ERS-2 3.13 1.24Envisat 2.02 1.81Geosat Follow-on 2.66 1.06Jason-1 2.34 0.94Topex/Poseidon 1.92 0.78

Table 10: Measurement noise error before/ after spatial filtering for Mediterranean and Black Sea products(cms rms)



4.3.6.5. Computation of ADT Products

Along-track ADT products are obtained as follows:ADT = SLA + MDT

where MDT is the Mean Dynamic Topography. The Mean Dynamic Topography is the part of Mean SeaSurface Height due to permanent currents, so MDT corresponds to the Mean Sea Surface Height minusGeoid. Since DUACS 2014 version, a new MDT has been used: it takes into account the recent geoid meanfield (GOCE DIR-R4) and in-situ dataset, as well as improved processing method. Details are presented inRio et al, 2013 [59].Note that the ADT products have been computed with consistent SLA and MDT fields:

ADT = SLA20years + MDT20years

The regional ADT product is computed using a specific regional MDT (Mediterranean Sea only) given inRio et al., 2014 [60]:

ADTMed = SLAMed + MDTMed

4.3.7. Generation of gridded Sea Level Anomalies (MSLA) products

4.3.7.1. Merging process

The Merging process is twofold: mapping and generation of by-products.

A mapping procedure using optimal interpolation with realistic correlation functions is applied to produceSLA and ADT maps (MSLA and MADT or L4 products) at a given date. The procedure generates acombined map merging measurements from all available altimeter missions (Ducet et al., 2000[20]). Themapping process takes into account an updated suboptimal Optimal Interpolation parameterization to min-imize transition artefacts. More accurate correlation scales are used compared to Ducet et al., taking intoaccount optimally the spatial variability of the signal.Combining data from different missions significantly improves the estimation of mesoscale signals (LeTraon and Dibarboure, 1999[41]), (Le Traon et al., 2001[42]), (Pascual et al., 2006[49]). Several improve-ments were made compared to the version used by (Le Traon et al., 1998[39]). An improved statisticaldescription of sea level variability, noise and long wavelength errors is used. Covariance functions includ-ing propagation velocities that depend on geographical position were thus used. For each grid point, thezonal and meridional spatial scales, the time scale and the zonal and meridional propagation velocities wereadjusted from five years of TP+ERS combined maps. In addition to instrumental noise, a noise of 10% ofthe signal variance was used to take into account the small scale variability which cannot be mapped andshould be filtered in the analysis.In the DT DUACS processing, the products can be computed optimally with a centred computation timewindow for OER, LWE and mapping processes (if D is the date of the map, the time intervall of the datataken into account for the computation of the map is [D-6 weeks, D+6 weeks]).

Number of satellites to compute the mapsTwo series of maps are computed in Delayed-Time: two-sat-merged and all-sat-merged. You will find the



list of missions in figures 13 and 12 respectively. Note that when there are only one or two satellites flying,the two series have the same content. The list of satellites taken into account to compute the maps are alsoprovided in the gridded file in the global attribute "platform".

• two-sat-merged series takes into account 2 satellites maximum in the computation of the map. It ishomogeneous and stable in time dataset thanks to a stable sampling but it might not be the bestquality at a given time. The use of this series is mainly for applications in need of great stability.

• all-sat-merged takes into account the all the satellites available (up to 4 satellites). Thus it has the bestpossible sampling. This series is better in quality but not homogeneous over the time period,because it is based on the best sampling available in time.

Change of resolutionIn DUACS 2014 version, after the feedback from users, the Mercator grid projection with 1/3˚ x1/3˚ spa-tial resolution (Global product) is abandoned. The DUACS 2014 Global products are directly computedon a Cartesian 1/4˚x1/4˚ spatial resolution. Please, refer to the technical note http://www.aviso.altimetry.fr/fileadmin/documents/data/duacs/Duacs2014.pdf for comparison betweenDUACS 2014 and former version.

Formal mapping errorThe formal mapping error represents a purely theoretical mapping error. It mainly represents errors inducedby the constellation sampling capability and consistency with the spatial/temporal scales considered, as de-scribed in Le Traon et al (1998) [39] or Ducet et al (2000) [20].In the former version, the formal mapping error was delivered as the "err" product, and expressed in version,it is expressed in meters and is delivered in the same NetCDF file as the SLA.The combined map is used to generate by-products such as geostrophic currents or absolute dynamic topog-raphy.

Geostrophic currentsSince DUACS 2014 version, the geostrophic current computation is improved with:

• The use of the 9-point stencil width method (Arbic et al, 2012, [3]) at latitudes appart from ±5˚. Itcontributes to reduce the impact of the anisotropy introduced by the Cartesian 1/4˚ grid resolution.

• The SLA computation is Largerloef et al, 1999 [36] in the equatorial band is improved in order tosmooth the transition at ±5˚ and improve the consistency between altimeter products and drifter ob-servations.

More information can be found in http://www.aviso.altimetry.fr/fileadmin/documents/data/duacs/Duacs2014.pdf.







4.3.8. Quality control

The production of homogeneous products with a high quality data and within a short delay is the keyfeature of the DUACS processing system. But some events (failure on payload or on instruments, delay,maintenance on servers), can impact the quality of measurements or the data flows. A strict quality controlon each processing step is indispensable to appreciate the overall quality of the system and to provide thebest user services.

4.3.8.1. Final quality Control

The Quality Control is the final process used by DUACS before product delivery. In addition to daily au-tomated controls and warnings to the operators, each production delivers a large QC Report composed ofdetailed logs, figures and statistics of each processing step. Altimetry experts analyse these reports twicea week (only for internal validation, those reports are not disseminated). A shorter report is delivered toDUACS users upon each product delivery.

The Quality Reports are now on the authenticated server. To access them via a browse, please type yourlogin and password in the following address:ftp://LOGIN:[email protected]/quality_report/

ftp://LOGIN:[email protected]/quality_report/



5. SSALTO/DUACS Products

5.1. Near Real Time Products

The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimetermissions in near-real time (i.e. within a few days at most) and in real-time for global area on all satellites(i.e. within a few hours), the validation and correction of these altimeter data sets (i.e edition and selection,update of corrections and homogenization, orbit error reduction) in order to produce each day along-trackproducts and gridded products.Exploitation of real time OGDR/FDGDR data allows the DUACS system to produce multi-mission mapswith 0-day and 3-day delay whereas historical NRT (IGDR-based) production have a 6-day delay (inducedby historical trade-off in terms of timeliness vs quality).The quality measurements in the NRT processing is more sensitive to the number of altimeter missions in-volved in the system. This is mainly due to the orbit error and the non-centered processing time-window (inNRT case, "future" data are not available; the computation time window takes into account only the 6 weeksbefore the date).If two altimeters are acknowledged as the bare minimum needed to observe mesoscale signals in DT maps,three or even four missions are needed to obtain equivalent accuracy in NRT (Pascual et al., 2006[49]).

As described in 4.2.6.4. and 4.2.6.1. time invariant products are also disseminated:

• The noise level of along-track measurements is delivered. This is a gridded product. One file isprovided for the global Ocean and those values must be applied for Arctic and Europe products. ForMediterranean and Black seas, one value is given, as described in the following table.

• The "REF20YTO7Y" product is provided temporarily for the needs of users who wish to work withthe reference period of 7 years instead of 20 years (see 4.2.6.1.). This is a gridded product. There arethree zones provided: global Ocean, Mediterranean and Black seas. For Arctic and Europe areas, thefile to be taken into account is the global product.




Along-track products

NRT SLA NRT ADT Gridded Noise on SLANRT NOISE SLA

Gridded Change ofreference

CHANGE REF SLA

Filtered Filtered

Global X X X X

Mediterranean X X see table 5 X

Black Sea X - see table 5 X

Arctic X - Same as global Same as global

Europe X - Same as global Same as global

Mozambique X - Same as global Same as global

Table 11: List of the Along-track products in NRT

Gridded products

NRT MSLA NRT MADT Gridded Change ofreference

CHANGE REF SLA

h+err uv h uv

Global all sat all sat all sat all sat X

Mediterranean all sat all sat all sat all sat X

Black Sea all sat all sat - - X

Mozambique all sat all sat - - Same as global

Table 12: List of the Gridded products in NRT, 1/4˚ cartesian resolution for global and 1/8˚ cartesian reso-lution for regional




5.1.1. Delay of the products

The availability of the products in near real time is

• for along-track products: three to twelve hours after the measurement for regional products and 2hours for global Saral, and Jason-2 products and 3 hours for global Cryosat-2 products.

• for gridded products: day-0, day-3 and day-6 days.

Those products are delivered every day.

Three merged maps are produced daily, each with a different delay and quality:

• A 6-day delay, which represents a final NRT map production,

• A 3-day delay, which represents an intermediate map production,

• and a 0-day delay, which represents a preliminary map production, based on IGDR+OGDR produc-tion.

Then, these maps are replaced when a better quality data is available:

• At d0+3, the intermediate map replaces the preliminary map which was produced at d0.

• At d0+3, the final NRT map replaces the intermediate map which was produced at d0.

• At d0+6, the intermediate map replaces the preliminary map which was produced at d0+3.

• At d0+6, the final NRT map replaces the preliminary map which was produced at d0.

Figure 11: Three merged maps are produced daily: final map (d-6), intermediate map (d-3) and prliminarymap (d0)



5.1.2. Temporal availibility

The following table presents the available products by mission and by data period:Near real time products:

NRT Jason-2 Cryosat-2 Saral/AltiKa HY-2A Merged

Temporal Timeavailability

y/m∗

ongoing2012/01/01

ongoing2013/07/01

ongoing2014/04/29

ongoingy/m∗

ongoing

NRT-SLA X X X X

NRT-MSLA X

UV anomalies(∗∗) X

NRT-ADT X X X X

NRT-MADT X

Absolute UV(∗∗∗) X

∗y/m: the temporal coverage for NRT products is fluctuating and is updated regularly (3 to 4 times per year when DTproducts are updated). The users are advised thanks to the Aviso web at: http://www.aviso.oceanobs.com/en/data/product-information/duacs/presentation/updates/index.html∗∗ UV anomalies are Geostrophic velocities anomalies derived from NRT-MSLA∗∗∗ Absolute UV are absolute Geostrophic velocities derived from NRT-MADT

http://www.aviso.oceanobs.com/en/data/product-information/duacs/presentation/updates/index.html





5.2. Delayed Time Products

The Delayed Time component of SSALTO/DUACS system is responsible for the production of processed HY-2A,Saral/AltiKa, Cryosat-2, Jason-1, Jason-2, T/P, Envisat, GFO, ERS1/2 data in order to provide a homogeneous, inter-calibrated and highly accurate long time series of SLA and MSLA altimeter data .DT products are more precise than NRT products. Two reasons explain this quality difference. The first one is thebetter intrinsic quality of the POE orbit used in the GDR processing. The second reason is that in the DT DUACSprocessing, the products can be computed optimally with a centred computation time window for OER, LWE andmapping processes (6 weeks before and after the date) . On the contrary in NRT case, "future" data are not availableso the computation time window is not centred and therefore not optimal.As for NRT products, improved altimeter corrections and processing algorithms are used: ocean tide model to correctaltimeter data, improved methods for orbit error reduction and mapping.Two types of madt and msla gridded products are delivered:

• all-sat-merged (for "Combining all satellites available"):this is an up-to-date series using the whole missions available (up to 4 satellites at a given time). Thus it has thebest possible sampling. All-sat-merged series is better in quality but not homogeneous over the time period,because it is based on the best sampling available in time.

• two-sat-merged (for "Combining two satellites"):this set is based on only two missions at most: Jason-2/AltiKa or Jason-2/Cryosat-2 or Jason-2 / Envisat orJason-1 / Envisat or Topex/Poseidon / ERS, with the same groundtrack. Thus it is homogeneous all along theavailable time period. thanks to a stable sampling, but might not be the best in quality at a given time. Theuse of the two-sat-merged series is mainly for application in need of great stability (but it must be kept in mindthat the data might not be of the best possible quality).

The difference between these two processing series is thus the number of missions as key input of Optimal Interpola-tion (OI) Software for LWE (4.3.5.). Note that when there are only one or two satellites flying, the two series have thesame content. The list of satellites taken into account to compute the maps are also provided in the gridded file in theglobal attribute "platform".As described in 4.3.6.4. and 4.3.6.1. time invariant products are also disseminated:

• The noise level of along-track measurements is delivered. This is a gridded product. One file is provided forthe global Ocean. For Mediterranean and Black seas, values have been computed (see 4.3.6.4.).

• The "REF20YTO7Y" product is provided temporarily for the needs of users who wish to work with the ref-erence period of 7 years instead of 20 years (see 4.3.6.1.). This is a gridded product. There are three zonesprovided: global Ocean, Mediterranean and Black seas.

The final delivering of Delayed Time are:

All the gridded Delayed-Time products (merged global/regional - twosat/allsat) have been computed with a dailytemporal resolution. This means that the maps are reprocessed for every day.This ambitious reprocessing was motivated by the fact that the weekly resolution used so far for DT maps in formerversion was insufficient wherever the time decorrelation scale is close to 15 days, especially when end-users want toperform a simple linear time interpolation between consecutive maps.




Along-track products

DT SLA DT ADT Gridded Noise onSLA

DT NOISE SLA

Gridded Change ofreference

CHANGE REF SLA

Filtered Unfiltered Filtered Uniltered Filtered Unfiltered Filtered Unfiltered

VFEC VXXC VFEC VXXC

Global X X X X X X X X

Mediterranean X X X X see table 10 X Same asfiltered

Black Sea X X - - see table 10 X Same asfiltered

Table 13: List of the Along-track products in DT

Gridded products

DT MSLA DT MADT Gridded Change ofreference

CHANGE REF SLA

h+err uv h uv

Global all sat all sat all sat all sat X

two sat two sat two sat two sat

Mediterranean all sat all sat all sat all sat X

two sat two sat two sat two sat

Black Sea all sat all sat - - X

two sat two sat - -

Table 14: List of the Gridded products in DT, 1/4˚ cartesian resolution for global and 1/8˚ cartesian resolutionfor regional

5.2.1. Delay of the products

Daily products are delivered. The availability of the products in delayed time is at the best two months after the dateof the measurement. The product generation needs all the GDR data of all the missions to take into account the bestcorrections as possible. The time delay can be longer in the case of a missing mission.




5.2.2. Temporal availibility

The following table presents the available products by mission and by data period:Delayed time SSALTO/DUACS all-sat-merged products:

all sat Temporal availibility DT-SLA DT-MSLA

UVanomalies3

DT-ADT DT-MADT

AbsoluteUV4

begin date end date

HY-2A 2014/04 y/m1 X X

Saral/AltiKa 2013/03 y/m1 X X

Cryosat-2 2012/04 y/m1 X X

Jason-2 2008/10 y/m1 X X

Jason-1 geodetic2 2012/06 2013/04 X X

Jason-1 new2 2009/02 2012/03 X X

Jason-1 2002/04 2008/10 X X

GFO 2000/01 2008/09 X X

Envisat new2 2010/10 2012/04 X X

Envisat 2002/10 2010/10 X X

ERS-12/ERS-2 1992/10 2003/04 X X

Topex new2 2002/09 2005/10 X X

Topex 1993/01 2002/04 X X

Merged 1993/01 y/m1 X X X X

1y/m: the temporal coverage for DT products is fluctuating and is updated regularly (3 to 4 times per year). The usersare advised thanks to the Aviso web at: http://www.aviso.altimetry.fr/en/data/product-information/updates-and-reprocessing/ssaltoduacs-delayed-time-reprocessing.html

2 Jason-1 geodetic orbit: starting 2012/05, Jason-1 new orbit : starting 2009/02, Envisat new orbit : starting 2010/10,T/P new orbit : starting 2002/09, ERS-1 geodetic phases (E-F) are included. No ERS-1 data between December 23,1993 and April 10, 1994 (ERS-1 phase D - 2nd ice phase). Note that, during that time, merged products are based onlyon Topex/Poseidon data.

3, 4 UV are Geostrophic velocities derived from NRT-MSLA or NRT-MADT.

The merged products were obtained with the satellites given in figure 12. Note that when there are one or two satellitesto compute the map, the two series two-sat-merged and all-sat-merged are identical. Moreover, the global attribute inthe gridded file called "platform" gives the list of satellites used to compute the map.

http://www.aviso.altimetry.fr/en/data/product-information/updates-and-reprocessing/ssaltoduacs-delayed-time-reprocessing.html





Figure 12: List of satellites in all-sat-merged products




Delayed time SSALTO/DUACS two-sat-merged products:

two-sat Temporal availibility DT-MSLA

UVanomalies2

DT-MADT

AbsoluteUV3

begin date end date

Merged 1993/01 y/m1 X X X X

1y/m: the temporal coverage for DT products is fluctuating and is updated regularly (3 to 4 times per year). The usersare advised thanks to the Aviso web at: http://www.aviso.altimetry.fr/en/data/product-information/updates-and-reprocessing/ssaltoduacs-delayed-time-reprocessing.html

2, 3 UV are Geostrophic velocities derived from NRT-MSLA or NRT-MADT.

The merged products were obtained with the satellites given in figure 13. Moreover, the global attribute in the griddedfile called "platform" gives the list of satellites used to compute the map.

Figure 13: List of satellites in two-sat-merged products






6. Data format

This chapter presents the data storage format used for SSALTO/DUACS products.

6.1. NetCdf

The products are stored using the NetCDF format. NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface. The netCDF library also definesa machine-independent format for representing scientific data. Together, the interface, library, and format support thecreation, access, and sharing of scientific data. The netCDF software was developed at the Unidata Program Center inBoulder, Colorado. The netCDF libraries define a machine-independent format for representing scientific data. Pleasesee Unidata NetCDF pages for more information, and to retreive NetCDF software package on:http://www.unidata.ucar.edu/packages/netcdf/index.html.

NetCDF data is:

• Self-Describing. A netCDF file includes information about the data it contains.

• Architecture-independent. A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers, characters, and floating-point numbers.

• Direct-access. A small subset of a large dataset may be accessed efficiently, without first reading through allthe preceding data.

• Appendable. Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure. The structure of a netCDF dataset can be changed, though this sometimes causes thedataset to be copied.

• Sharable. One writer and multiple readers may simultaneously access the same netCDF file.

6.2. Structure and semantic of NetCDF along-track (L3) files

The NetCDF SSALTO/DUACS files are based on the attribute data tags defined by the Cooperative Ocean/AtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions. The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasets.A wide range of software is available to write or read NetCDF/CF files. API are made available by UNIDATA(http://www.unidata.ucar.edu/software/netcdf):

• C/C++/Fortran

• Java

• MATLAB, Objective-C, Perl, Python, R, Ruby, Tcl/Tk

In addition to these conventions, the files are using a common structure and semantic:

• 1 dimension is defined:

– time: it is used to check NetCDF variables depending on time.

• 6 variables are defined:

http://www.unidata.ucar.edu/packages/netcdf/index.html

http://www.unidata.ucar.edu/software/netcdf




– short SLA or ADT: contains the Sea Level Anomaly or Absolute Dynamic Topography values for eachtime given,

– int longitude : contains the longitude for each measurement,

– int latitude : contains the latitude for each measurement,

– short track : contains the track number for each measurement,

– double time : contains the time in days since 1950-01-01 00:00:00 UTC for each measurement,

– short flag : only for NRT products. flag=0, the processed data comes from OGDR; if flag=1, the processeddata comes from the IGDR

– short cycle : contains the cycle number for each measurement.

• global attributes:

– the global attributes gives information about the creation of the file.

Example of a NetCDF sla file:

netcdf nrt_global_c2_sla_vfec_20131128_20131219 {dimensions:

time = 22699 ;variables:

short SLA(time) ;SLA:coordinates = "longitude latitude" ;SLA:long_name = "Sea Level Anomaly" ;SLA:_FillValue = 32767s ;SLA:add_offset = 0. ;SLA:scale_factor = 0.001 ;SLA:units = "m" ;SLA:standard_name = "sea_surface_height_above_sea_level" ;

int longitude(time) ;longitude:long_name = "Longitude of measurement" ;longitude:add_offset = 0. ;longitude:standard_name = "longitude" ;longitude:scale_factor = 1.e-06 ;longitude:units = "degrees_east" ;

short track(time) ;track:long_name = "Track in cycle the measurement belongs to" ;track:units = "1" ;track:coordinates = "longitude latitude" ;

double time(time) ;time:long_name = "Time of measurement" ;time:axis = "T" ;time:standard_name = "time" ;time:units = "days since 1950-01-01 00:00:00 UTC" ;

int latitude(time) ;latitude:long_name = "Latitude of measurement" ;latitude:add_offset = 0. ;latitude:standard_name = "latitude" ;latitude:scale_factor = 1.e-06 ;latitude:units = "degrees_north" ;

short flag(time) ;flag:coordinates = "longitude latitude" ;flag:_FillValue = 3267s ;flag:long_name = "data origin" ;flag:long_name = "The origin of the data is determined by the types of geophysical data




records (GDR) used in computation of the SLA: 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)." ;

short cycle(time) ;cycle:long_name = "Cycle the measurement belongs to" ;cycle:units = "1" ;cycle:coordinates = "longitude latitude" ;

// global attributes::history = "19-Dec-2013 13:58:37 UTC : File created by the SSLATO/DUACS system version 14.0.1" ;:comment = "Produce from Cryosat-2 satellite altimetry data" ;:institution = "CLS/CNES";:references = "http://www.aviso.altimetry.fr" ;:contact = "[email protected]" ;:license = "http://www.aviso.altimetry.fr/fileadmin/documents/data/License_Aviso.pdf" ;:source = "satellite altimetry" ;:title = "along track Sea Level Anomaly" ;:Conventions = "CF-1.6" ;

}




6.3. Structure and semantic of NetCDF maps (L4) files

The NetCDF SSALTO/DUACS files are based on the attribute data tags defined by the Cooperative Ocean/AtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions. The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasets.A wide range of software is available to write or read NetCDF/CF files. API are made available by UNIDATA(http://www.unidata.ucar.edu/software/netcdf):

• C/C++/Fortran

• Java

• MATLAB, Objective-C, Perl, Python, R, Ruby, Tcl/Tk

In addition to these conventions, the files are using a common structure and semantic:

• 4 Dimensions are defined:

– time: date of the map,

– lat: contains the latitude of grid points ,

– lon: contains the longitude of grid points,

– nv: used for mapping conventions

• 8 or 9 Variables are used for all grids defined below:

– float time : contains the time in days since 1950-01-01 00:00:00 UTC,

– float lat : contains the latitude for each measurement,

– float lon : contains the longitude for each measurement,

– float lat_bnds : contains the min and max in latitude of each box,

– float lon_bnds : contains the min and max in longitude of each box,

– int crs: used for mapping conventions

– the fields used are: for msla_h files

∗ int sla: contains the eea level anomalies of the measurements and∗ int err: contains the formal mapping error in meters

or for msla_uv and madt_uv files

∗ int u: contains the zonal component of the geostrophic velocity of the measurements and∗ int v: contains the meridian component of the geostrophic velocity of the measurements

or for madt_h files

∗ int adt: contains the absolute dynamic topography of the measurements


– the global attributes gives information about the creation of the file. Not that there is a new global attributecalled "platform" indicating the list of satellites taken into account to compute the maps.

Example of NetCDF msla_h file:

netcdf dt_global_allsat_msla_h_20121205_20140106 {dimensions:

time = 1 ;lat = 720 ;lon = 1440 ;

http://www.unidata.ucar.edu/software/netcdf




nv = 2 ;variables:

float time(time) ;time:long_name = "Time" ;time:standard_name = "time" ;time:units = "days since 1950-01-01 00:00:00 UTC" ;time:calendar = "julian" ;time:axis = "T" ;

float lat(lat) ;lat:long_name = "Latitude" ;lat:standard_name = "latitude" ;lat:units = "degrees_north" ;lat:bounds = "lat_bnds" ;lat:axis = "Y" ;lat:valid_min = -90. ;lat:valid_max = 90. ;

float lat_bnds(lat, nv) ;float lon(lon) ;

lon:long_name = "Longitude" ;lon:standard_name = "longitude" ;lon:units = "degrees_east" ;lon:bounds = "lon_bnds" ;lon:axis = "X" ;lon:valid_min = 0. ;lon:valid_max = 360. ;

float lon_bnds(lon, nv) ;int crs ;

crs:grid_mapping_name = "latitude_longitude" ;crs:semi_major_axis = 6371000. ;crs:inverse_flattening = 0 ;

int nv(nv) ;int sla(time, lat, lon) ;

sla:_FillValue = -2147483647 ;sla:long_name = "Sea Level Anomalies" ;sla:standard_name = "sea_surface_height_above_sea_level" ;sla:units = "m" ;sla:scale_factor = 0.0001 ;

int err(time, lat, lon) ;err:_FillValue = -2147483647 ;err:long_name = "Formal mapping error" ;err:comment = "The formal mapping error represents a purely theoretical mapping error.It mainly traduces errors induced by the constellation sampling capability and consistencywith the spatial/temporal scales considered, as described inLe Traon et al (1998) or Ducet et al (2000)" ;err:units = "m" ;err:scale_factor = 0.0001 ;

// global attributes::cdm_data_type = "Grid" ;:title = "DT merged Global Ocean Gridded Sea Level Anomalies SSALTO/Duacs L4 product" ;:summary = "This dataset contains Delayed Time Level-4 sea surface height aboveMean Sea Surface productsfrom multi-satellite observations over Global Ocean." ;:comment = "Surface product; Sea Level Anomalies referenced to the [1993, 2012] period" ;:time_coverage_resolution = "P1D" ;:product_version = "5.0" ;




:institution = "CNES, CLS" ;:project = "SSALTO/DUACS" ;:references = "www.aviso.altimetry.fr" ;:contact = "[email protected]" ;:license = "http://www.aviso.altimetry.fr/fileadmin/documents/data/License_Aviso.pdf" ;:platform = "Jason-1 Geodetic Phase, Jason-2, Cryosat-2" ;:date_created = "2014-02-21 09:52:28" ;:history = "2014-02-21 09:52:28:creation" ;:Conventions = "CF-1.6" ;:standard_name_vocabulary = "http://cf-pcmdi.llnl.gov/documents/cf-standard-names/standard-name-table/12/cf-standard-name-table.html" ;:geospatial_lat_min = -90. ;:geospatial_lat_max = 90. ;:geospatial_lon_min = 0. ;:geospatial_lon_max = 360. ;:geospatial_vertical_min = "0.0" ;:geospatial_vertical_max = "0.0" ;:geospatial_lat_units = "degrees_north" ;:geospatial_lon_units = "degrees_east" ;:geospatial_lat_resolution = 0.25 ;:geospatial_lon_resolution = 0.25 ;

}




6.4. Structure and semantic of NetCDF Gridded Noise on Sea Level Anomaly files

The files are using the following structure and semantic:• 3 dimensions are defined:

– lat: Latitude of measurements.

– lon: Longitude of measurements.

– nv: definition of bounds.


– int noise : contains the noise at the grid point,



– float lon_bnds : contains the bounds in longitude ,

– float lat_bnds : contains the bounds in latitude ,

– int crs : useful for mapping,



Example of a NetCDF noise sla file:

netcdf dt_global_al_sla_noise_vfec {dimensions:

lat = 89 ;lon = 180 ;nv = 2 ;

variables:float lat(lat) ;

lat:long_name = "Latitude" ;lat:standard_name = "latitude" ;lat:units = "degrees_north" ;lat:bounds = "lat_bnds" ;lat:axis = "Y" ;lat:valid_min = -90. ;lat:valid_max = 90. ;





int noise(lat, lon) ;noise:_FillValue = -2147483647 ;noise:long_name = "Sea Level Anomalies measurement noise" ;




noise:standard_name = "sea_surface_height_above_sea_level" ;noise:units = "m" ;noise:scale_factor = 0.0001 ;

// global attributes::history = "2013-12-17 16:15:38:creation" ;:comment = "Surface product;" ;:institution = "CLS/CNES";:Conventions = "CF-1.6" ;:cdm_data_type = "Grid" ;:geospatial_lat_min = -90. ;:geospatial_lat_max = 88. ;:geospatial_lon_min = -1. ;:geospatial_lon_max = 359. ;:geospatial_vertical_min = "0.0" ;:geospatial_vertical_max = "0.0" ;:geospatial_lat_units = "degrees_north" ;:geospatial_lon_units = "degrees_east" ;:geospatial_lat_resolution = 2. ;:geospatial_lon_resolution = 2. ;:title = "SSALTO/Duacs Altimetric Level4 product: SARAL/AltiKa sea level anomaliesmeasurement noise on global area" ;:summary = "This dataset contains the measurement noise for filtered SARAL/AltiKa1-Hz measurements." ;:product_version = "5.0" ;:project = "CNES SSALTO/DUACS" ;:references = "http://www.aviso.altimetry.fr" ;:contact = "[email protected]" ;:license = "http://www.aviso.altimetry.fr/fileadmin/documents/data/License_Aviso.pdf" ;:date_created = "2013-12-17 16:15:38" ;:standard_name_vocabulary ="http://cf-pcmdi.llnl.gov/documents/cf-standard-names/standard-name-table/12/cf-standard-name-table.html" ;

}




6.5. Structure and semantic of NetCDF Gridded Change reference files

The files are using the following structure and semantic:• 3 dimensions are defined:

– lat: Latitude of measurements.

– lon: Longitude of measurements.

– nv: definition of bounds.


– int ref20yto7y : contains the value at the grid point,



– float lon_bounds : contains the bounds in longitude ,

– float lat_bounds : contains the bounds in latitude ,

– int crs : useful for mapping,



Example of a NetCDF ref20yto7y file:

netcdf med_ref20yto7y {dimensions:

lat = 129 ;lon = 345 ;nv = 2 ;

variables:float lat(lat) ;

lat:long_name = "Latitude" ;lat:standard_name = "latitude" ;lat:units = "degrees_north" ;lat:bounds = "lat_bnds" ;lat:axis = "Y" ;lat:valid_min = -90. ;lat:valid_max = 90. ;








int ref20yto7y(lat, lon) ;ref20yto7y:_FillValue = -2147483647 ;ref20yto7y:long_name = "Averaged Sea Level Anomaly 1993 to 1999" ;ref20yto7y:standard_name = "sea_surface_height_above_sea_level" ;ref20yto7y:units = "m" ;ref20yto7y:scale_factor = 0.0001 ;

// global attributes::cdm_data_type = "Grid" ;:geospatial_lat_min = 29.9375 ;:geospatial_lat_max = 46.0625 ;:geospatial_lon_min = 353.9375 ;:geospatial_lon_max = 397.0625 ;:geospatial_vertical_min = "0.0" ;:geospatial_vertical_max = "0.0" ;:geospatial_lat_units = "degrees_north" ;:geospatial_lon_units = "degrees_east" ;:geospatial_lat_resolution = 0.125 ;:geospatial_lon_resolution = 0.125 ;:title = "SSALTO/Duacs Altimetric Level4 product: sea level anomalies 20-year/7-yearreference change correction for Mediterranean Sea" ;:summary = "This dataset contains Delayed Time Level-4 monthly mean of sea surfaceheight above ellipsoid products from multi-satellite observations over Mediterranean Sea.It represents the correction for changing from the 20-year reference [1993,2012] to the7-year reference [1993,1999]. It must be substracted to the 20-year referenced SLA in orderto obtain a 7-y referenced SLA." ;:comment = "Test file; Surface product; Sea Level Anomalies referenced to the [1993, 2012] period" ;:product_version = "5.0" ;:institution = "CNES, CLS" ;:project = "SSALTO/DUACS" ;:references = "http://www.aviso.altimetry.fr" ;:contact = "[email protected]" ;:license = "http://www.aviso.altimetry.fr/fileadmin/documents/data/License_Aviso.pdf" ;:date_created = "2013-12-17 11:26:12" ;:history = "2013-12-17 11:26:12:creation" ;:Conventions = "CF-1.6" ;:standard_name_vocabulary ="http://cf-pcmdi.llnl.gov/documents/cf-standard-names/standard-name-table/12/cf-standard-name-table.html" ;

}




7. Accessibility of the products

Aviso proposes several ways of accessing data. Some of them need an authentication. If you are not registered andwant to access to an authenticated service, we request you to fill in the online form.According to the type of SSALTO/DUACS data, products are available:

• Via authenticated FTP onftp://ftp.aviso.altimetry.fr/Note that once your request is processed (after filling the online form), Aviso will send you your own access(login/password) by e-mail as soon as possible. If you don’t enter your login/password, you will only access tothe anonymous FTP, where you won’t find the data you’re interested in.

• Via the Live Access Server (LAS) on the AVISO web site(http://www.aviso.altimetry.fr/en/data/data-access/las-live-access-server.html). The LAS is a tool to draw your own map.Only gridded products are accessible via the LAS.

• Via authenticated OpenDap, a framework that simplifies all aspects of scientific data networking (http://www.aviso.altimetry.fr/en/data/data-access/aviso-opendap.html). Only gridded products are accessible via OpenDap.

• Via the authenticated Aviso data extraction (http://www.aviso.altimetry.fr/en/data/data-access/gridded-data-extraction-tool.html) tool enables you to extract a data sub-set from the Avisogridded datasets. You can choose either an area (by its geographical coordinates or among pre-defined re-gions), or a period for variable(s) within a given dataset

FTP Opendap1 Aviso extractionService1

LAS1

Near Real-Time x

« Historical » NRT(for data >1 month)

x x x x

Delayed time x x x x

(1) Only gridded products 7.1. Folders on the ftp server

We keep your attention to well enter your login/password to get access to FTP server, if not, you will access onlythe anonymous FTP(/donnees/ftpsedr/ftpanonymous/pub/oceano/AVISO/SSH/duacs), where you only find sample data sets.

Access restrictions are applied on folders. Your account gives you an access to a given list of altimetry data. Thus, thefolders you’re not subscribed to are empty.

7.1.1. Gridded Delayed-Time and Near-Real-Time products (SLA, ADT, Geostrophic currents)

The nomenclature used for the folders is:

<ZONE>_<DELAY>_gids_<NBSAT>_<PRODUCT>_<VARIABLE>_<YEAR>

ftp://ftp.aviso.altimetry.fr/

http://www.aviso.altimetry.fr/en/data/data-access/las-live-access-server.html

http://www.aviso.altimetry.fr/en/data/data-access/las-live-access-server.html

http://www.aviso.altimetry.fr/en/data/data-access/aviso-opendap.html

http://www.aviso.altimetry.fr/en/data/data-access/aviso-opendap.html

http://www.aviso.altimetry.fr/en/data/data-access/gridded-data-extraction-tool.html

http://www.aviso.altimetry.fr/en/data/data-access/gridded-data-extraction-tool.html




ZONE global global geographic coverage product

regional-mediterranean Mediterranean products

regional-blacksea Black Sea products

regional-mozambique Mozambique area products (only for nrt)

DELAY delayed-time delayed time products

near-real-time near-real time products

NBSAT all-sat-merged maximum 4 satellites to compute the map

two-sat-merged maximum 2 satellites to compute the map

PRODUCT msla maps of sea level anomaly

madt(1) maps of absolute dynamic topography

VARIABLE h sea surface heights and error

uv sea surface geostrophic currents

YEAR YYYY year of the maps (only in DT)(1) No MADT files for Black Sea regional products.




7.1.2. Along-track Delayed Time and Near Real Time SLA and ADT files

The nomenclature used for the along-track SLA and ADT folders is:

<ZONE>_<DELAY>_along-track_<FILTERING>_<PRODUCT>_<MISSION>_<YEAR>




regional-arctic Arctic products

regional-europe Europe products

regional-mozambique Mozambique area products (only for nrt)



FILTERING filtered filtered and sub-sampled products (*vfec*)

unfiltered not filtered and not sub-sampled products(*vxxc*)

PRODUCT sla sea level anomaly

adt(1) absolute dynamic topography

MISSION e1 ERS-1

e2 ERS-2

tp Topex/Poseidon

tpn Topex/Poseidon on its new orbit

g2 GFO

j1 Jason-1

j1n Jason-1 on its new orbit

j2 Jason-2

en Envisat

enn Envisat on its new orbit

c2 Cryosat-2

al Saral/AltiKa

h2 HY-2A

YEAR YYYY year of the maps (only in DT)(1) No ADT files for Black Sea , Arctic Ocean and Europe areas regional products .




7.1.3. Gridded Change of Reference folders

Those products are available in the following folders:

<ZONE>_ref20yto7y




7.1.4. Gridded Noise estimations folders

Those products are available in the following folders:

global_<DELAY>_along-track_<FILTERING>_noise-sla_<MISSION>



FILTERING filtered filtered and sub-sampled products (*vfec*)

unfiltered not filtered and not sub-sampled products(*vxxc*)

MISSION e1 ERS-1

e2 ERS-2

tp Topex/Poseidon

tpn Topex/Poseidon on its new orbit

g2 GFO

j1 Jason-1

j1n Jason-1 on its new orbit

j2 Jason-2

en Envisat

enn Envisat on its new orbit

c2 Cryosat-2

al Saral/AltiKa

h2 HY-2A




8. News and Updates

8.1. [Duacs] Operational news

To be kept informed on events occurring on the satellites and on the eventual interruption of the services of theDUACS processing system, see the [Duacs] operational news on the Aviso website:http://www.aviso.oceanobs.com/en/data/operational-news/index.html.

8.2. Updates

To have the information of the DUACS changes, improvements and updates of the system, please refer to:http://www.aviso.oceanobs.com/en/data/product-information/duacs/presentation/updates/index.html.Since 2010, a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available. Themain changes introduced in the Duacs DT v3.0.0 reprocessed data set in "SSALTO/DUACS reprocessed DT data set"are listed here:http://www.aviso.oceanobs.com/fileadmin/documents/data/duacs/duacs_DT_2010_reprocessing_impact.pdf

http://www.aviso.oceanobs.com/en/data/operational-news/index.html



http://www.aviso.oceanobs.com/fileadmin/documents/data/duacs/duacs_DT_2010_reprocessing_impact.pdf

http://www.aviso.oceanobs.com/fileadmin/documents/data/duacs/duacs_DT_2010_reprocessing_impact.pdf




References

[1] Amarouche L., P. Thibaut, O. Zanife, J.-P. Dumont, P. Vincent, and N. Steunou, "Improving the Jason-1 groundretracking to better account for attitude effects", Marine Geodesy, vol. 27, pp. 171-197, 2004.

[2] Andersen, O. B., The DTU10 Gravity filed and Mean sea surface (2010), Second international symposium of thegravity field of the Earth (IGFS2), Fairbanks, Alaska.

[3] Arbic B. K, R. B. Scott, D. B. Chelton, J. G. Richman and J. F. Shriver, 2012, Effects on stencil width onsurface ocean geostrophic velocity and vorticity estimation from gridded satellite altimeter data, J. Geophys.Res., vol117, C03029, doi:10.1029/2011JC007367.

[4] Boy, F. et al (2011): "Cryosat LRM, TRK and SAR processing". Presented at the 2011 Ocean Surface Topogra-phy Science Team meeting. http://www.aviso.altimetry.fr/fileadmin/documents/OSTST/2011/oral/01_Wednesday/Splinter%201%20IP/06%20%20Boy%20CPP%20Presentation.pdf

[5] Carrère, L, F. Lyard, M. Cancet, A. Guillot, L. Roblou, FES2012: A new global tidal model taking advantage ofnearly 20 years of altimetry, Proceedings of meeting "20 Years of Altimetry, Venice 2012.

[6] Carrere, L., F. Lyard, 2003, Modeling the barotropic response of the global ocean to atmospheric wind andpressure forcing- comparisons with observations. J. Geophys. Res., 30(6), 1275, doi:10.1029/2002GL016473.

[7] Carrere L., 2003, Etude et modélisation de la réponse HF de l’océan global aux forçages météorologiques. PhDthesis, Université Paul Sabatier (Toulouse III, France), 318 pp.

[8] Cartwright, D. E., R. J. Tayler, 1971, New computations of the tide-generating potential, Geophys. J. R. Astr.Soc., 23, 45-74.

[9] Cartwright, D. E., A. C. Edden, 1973, Corrected tables of tidal harmonics, Geophys. J. R. Astr. Soc., 33, 253-264.

[10] Following the scientific recommendations from the OSTST meeting (San Diego, October 2011), the ESA CryosatProject and the CNES SALP Project have been collaborating to generate these Cryosat-derived L3 and L4 prod-ucts. Level 1B and Level 2 products derived from CNES processors are not distributed by AVISO as per theCNES / ESA agreement.

[11] Davis, R.E. 1998, Preliminary results from directly measuring middepth circulation in the tropical and SouthPacific. Journal of Geophysical Research 103 (C11): PP. 24,619 24,639. doi:199810.1029/98JC01913.

[12] Dibarboure G., F. Boy, J.D.Desjonqueres, S.Labroue, Y.Lasne, N.Picot, J.C.Poisson, P.Thibaut, In-vestigating short wavelength correlated errors on low-resolution mode altimetry, OSTST 2013,http://www.aviso.altimetry.fr/fileadmin/documents/OSTST/2013/oral/THIBAUT_SmallScales_OSTST_Boulder.pdf

[13] Dibarboure G., C. Renaudie, M.-I. Pujol, S. Labroue, N. Picot, 2011, "A demonstration of the potential ofCryosat-2 to contribute to mesoscale observation", J. Adv. Space Res., doi:10.1016/j.asr.2011.07.002. http://dx.doi.org/10.1016/j.asr.2011.07.002

[14] Dibarboure G., P. Schaeffer, P. Escudier, M-I.Pujol, J.F. Legeais, Y. Faugère, R. Morrow, J.K. Willis, J. Lambin,J.P. Berthias, N. Picot, 2010: Finding desirable orbit options for the "Extension of Life" phase of Jason-1.Submitted to Marine Geodesy.

[15] Dibarboure G., M-I.Pujol, F.Briol, PY.Le Traon, G.Larnicol, N.Picot, F.Mertz, M.Ablain, 2011: Jason-2 inDUACS: first tandem results and impact on processing and products. Marine Geodesy, 34,(3-4),214-241.

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