PRODUCT USER MANUAL For Sea Level SLA products
PRODUCT USER MANUAL
For Sea Level SLA products
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
WP leader: CLS, Gilles Larnicol, France
Issue: 3.4
Contributors: Françoise Mertz, Rosmorduc Vinca, Anne Delamarche, Gilles Larnicol
MyOcean version scope : Version 2.2
Approval Date : 5 February 2013
Project N°: FP7-SPACE-2007-1
Work programme topic: SPA.2007.1.1.01 - development of upgraded capabilities for existing GMES fast-track
services and related (pre)operational services. Duration: 39 Months
PUM for Sea Level SLA Products
SEALEVEL_*_SLA_L3_OBSERVATIONS_008_00*
Ref
: MYO2-SL-PUM008-001-005
Date : 5 February 2013
Issue : 3.4
CHANGE RECORD
Issue
Date
§
Description of change
Author
Validated by
1.0
2011/01/01
all
First version of document
Françoise Mertz,
Vinca Rosmorduc,
Anne Delamarche
Gilles Larnicol
1.1
2011/02/23
all
Correction of anomalies in
the format of the file
Françoise Mertz,
Vinca Rosmorduc,
Anne Delamarche
Gilles Larnicol,
Gérald
Dibarboure
2.0
2011/09/01
all
Version V2 of MyOcean
products
Françoise Mertz,
Vinca Rosmorduc,
Anne Delamarche
Gilles Larnicol,
Gérald
Dibarboure
2.1
2011/10/31
all
New template
Françoise Mertz,
Vinca Rosmorduc,
Anne Delamarche
Gilles Larnicol,
Gérald
Dibarboure
2.2
2012/02/24
all
Version V2.1
Françoise Mertz,
Vinca Rosmorduc,
Anne Delamarche
Gilles Larnicol,
Gérald
Dibarboure
3.0
2012/05/25
all
End of Envisat mission and
addition of Jason-1 on its
geodetic orbit (j1g)
Françoise Mertz,
Vinca Rosmorduc,
Anne Delamarche
Gilles Larnicol,
Gérald
Dibarboure
3.1
2012/07/20
all
New version D of Jason-2
IGDR
Françoise Mertz,
Vinca Rosmorduc,
Anne Delamarche
Gilles Larnicol,
Gérald
Dibarboure
3.2
2012/10/20
all
Integration of Cryosat-2 in
Reprocessed products
Françoise Mertz,
Vinca Rosmorduc,
Anne Delamarche
Gilles Larnicol,
Gérald
Dibarboure
3.3
2012/12/04
all
NRT: Improvement in the
processing of Cryosat-2, Reprocessed: integration of
Jason-1 geodetic mission and
new version D of Jason-2
Françoise Mertz,
Vinca Rosmorduc,
Caroline Maheu
Gilles Larnicol,
Gérald
Dibarboure
3.4
2013/02/05
all
Global NRT: Integration of
"OGDR on the fly" data
Françoise Mertz,
Vinca Rosmorduc,
Caroline Maheu
Gilles Larnicol,
Gérald
Dibarboure
Page 1
PUM for Sea Level SLA Products
Ref
: MYO2-SL-PUM008-001-005
Date : 5 February 2013
Issue : 3.4
SEALEVEL_*_SLA_L3_OBSERVATIONS_008_00*
C ONTENTS
I. Introduction
11
II. Updates in 2012 and 2013
II.1. Integration of most recent data as soon as available: "OGDR on the fly" (February 2013) .
II.2. All the Sea Level SLA files are compressed (February 2013) . . . . . . . . . . . . . . . .
II.3. Version "D" of input IGDR/OGDR Jason-2 data (July 30, 2012 for NRT products , December 2012 for Reprocessed products) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
II.4. Integration of Jason-1 on its geodetic orbit (May 2012 for NRT products, December 2012
for Reprocessed products) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
II.5. Envisat has stopped sending data (April 2012) . . . . . . . . . . . . . . . . . . . . . . . .
II.6. Integration of the Cryosat2 Mission (February 2012 in NRT and in Reprocessed products)
II.6.1. Generalities about the mission . . . . . . . . . . . . . . . . . . . . . . . . . . . .
II.6.2. Integration in DUACS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
II.7. Addition of Europe and Arctic products (January 2012) in NRT processing . . . . . . . . .
III.SSALTO/DUACS system
III.1. Introduction . . . . . . . . . . . . . . . . . . . . .
III.2. Near Real Time processing steps . . . . . . . . . .
III.2.1. Input data, models and corrections applied .
III.2.2. Acquisition . . . . . . . . . . . . . . . . .
III.2.3. Homogenization . . . . . . . . . . . . . .
III.2.4. Input data quality control . . . . . . . . . .
III.2.5. Multi-mission cross-calibration . . . . . .
III.2.6. Product generation . . . . . . . . . . . . .
III.2.6.1. Computation of raw SLA . . . . . . .
III.2.6.2. Cross validation . . . . . . . . . . . .
III.2.6.3. Filtering and sub-sampling . . . . . .
III.2.7. Quality control . . . . . . . . . . . . . . .
III.2.7.1. Final quality Control . . . . . . . . .
III.2.7.2. Performance indicators . . . . . . . .
III.3. Delayed Time processing steps . . . . . . . . . . .
III.3.1. Input data, models and corrections applied .
III.3.2. Acquisition . . . . . . . . . . . . . . . . .
III.3.3. Homogenization . . . . . . . . . . . . . .
III.3.4. Input data quality control . . . . . . . . . .
III.3.5. Multi-mission cross-calibration . . . . . .
III.3.6. Product generation . . . . . . . . . . . . .
III.3.6.1. Computation of raw SLA . . . . . . .
III.3.6.2. Cross validation . . . . . . . . . . . .
III.3.6.3. Filtering and sub-sampling . . . . . .
III.3.7. Quality control . . . . . . . . . . . . . . .
III.3.7.1. Final quality Control . . . . . . . . .
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Page 2
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PUM for Sea Level SLA Products
Ref
: MYO2-SL-PUM008-001-005
Date : 5 February 2013
Issue : 3.4
SEALEVEL_*_SLA_L3_OBSERVATIONS_008_00*
IV. MyOcean Products
IV.1. Near Real Time Products . .
IV.1.1. Delay of the products
IV.1.2. Temporal availibility
IV.2. Delayed Time Products . . .
IV.2.1. Delay of the products
IV.2.2. Temporal availibility
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V. Description of the product specification
43
V.1. General information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
VI. Nomenclature of files
VI.1. Nomenclature of files downloaded through the MyOcean Web Portal DirectgetfileService
VI.1.1. Nomenclature of the product line . . . . . . . . . . . . . . . . . . . . . . . . .
VI.1.2. Nomenclature of the datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . .
VI.1.3. Nomenclature of the NetCdf files . . . . . . . . . . . . . . . . . . . . . . . . .
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VII.Data format
51
VII.1.NetCdf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
VII.2.Structure and semantic of NetCDF along-track files . . . . . . . . . . . . . . . . . . . . . . 52
VIII.
How to download a product
56
VIII.1.Download a product through the MyOcean Web Portal Directgetfile Service . . . . . . . . . 56
IX. News and Updates
57
IX.1. [Duacs] Operational news . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
IX.2. Updates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Page 3
PUM for Sea Level SLA Products
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Ref
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Date : 5 February 2013
Issue : 3.4
L IST OF TABLES
1
2
3
4
5
6
7
Characteristics of the geodetic orbit for Jason-1 since May 7th , 2012 . . . . . . . . . . . . .
SSALTO/DUACS Near-Real Time Input data overview . . . . . . . . . . . . . . . . . . . .
Corrections and models applied in SSALTO/DUACS NRT products produced from IGDRs. .
Corrections and models applied in SSALTO/DUACS NRT products produced from OGDRs.
SSALTO/DUACS Delayed Time Input data overview . . . . . . . . . . . . . . . . . . . . .
Corrections and models applied in SSALTO/DUACS DT products for TOPEX/Poseidon,
Jason-1, Jason-2 and GFO. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Corrections and models applied in SSALTO/DUACS DT products for ERS-1, ERS-2, Envisat and Cryosat-2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
14
21
22
23
32
33
34
L IST OF F IGURES
1
2
3
4
5
6
7
8
DUACS and AVISO, a user-driven altimetry service . . . . . . . . . . . . . . . . . . . . .
SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right) .
Coverage of the Europe product for Jason-1, Jason-2 and Envisat from August, 18th to
September, 9th 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012 . .
SSALTO/DUACS processing sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Overview of the near real time system data flow management . . . . . . . . . . . . . . . .
Merging pertinent information from IGDR and OGDR processing . . . . . . . . . . . . .
Example with the key performance indicator on 2009/06/27 . . . . . . . . . . . . . . . . .
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PUM for Sea Level SLA Products
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Ref
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Date : 5 February 2013
Issue : 3.4
L IST OF ACRONYMS
ATP
ADT
AVISO
BGLO
Cal/Val
CERSAT
CMA
CORSSH
C2
DAC
DT
DTU
DUACS
E1
E2
EN
ENN
ECMWF
ENACT
G2
GIM
GDR
IERS
IGDR
J1
J1N
J1G
J2
JPL
LAS
LWE
MADT
MDT
MOE
MP
MSLA
MSS
NRT
OE
OER
Opendap
PF
PO.DAAC
POE
RD
SAD
Along-Track Product
Absolute Dynamic Topography
Archiving, Validation and Interpretation of Satellite Oceanographic data
Biais Grande Longueur d’Onde
Calibration - Validation
Centre ERS d’Archivage et de Traitement
Centre Multimission Altimetry center
CORrected Sea Surface Height
Cryosat-2
Dynamic Atmospheric Correction
Delayed Time
Mean Sea Surface computed by Technical University of Danemark
Data Unification and Altimeter Combination System
ERS-1
ERS-2
Envisat
Envisat on its non repetitive orbit (since cycle 94)
European Centre for Medium-range Weather Forecasting
ENhanced ocean data Assimilation and Climate prediction
Geosat Follow On
Global Ionospheric Maps
Geophysical Data Record(s)
International Earth Rotation Service
Interim Geophysical Data Record(s)
Jason-1
Jason-1 on its new orbit (since cycle 262)
Jason-1 on its geodetic orbit (since May 2012)
Jason-2
Jet Propulsion Laboratory
Live Access Server
Long Wavelength Errors
Map of Absolute Dynamic Topgraphy
Mean Dynamic Topography
Medium Orbit Ephemeris
Mean Profile
Map of Sea Level Anomaly
Mean Sea Surface
Near-Real Time
Orbit Error
Orbit Error Reduction
Open-source Project for a Network Data Access Protocol
Polynom Fit
Physical Oceanography Distributed Active Archive Centre
Precise Orbit Ephemeris
Reference Document
Static Auxiliary Data
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SI
SLA
SL TAC
SSALTO
SSH
TAC
T/P
TPN
Ref
: MYO2-SL-PUM008-001-005
Date : 5 February 2013
Issue : 3.4
Signed Integer
Sea Level Anomaly
Sea Level Thematic Assembly Centre
Ssalto multimission ground segment
Sea Surface Height
Thematic Assembly Centre
Topex/Poseidon
Topex/Poseidon on its new orbit (since cycle 369)
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Date : 5 February 2013
Issue : 3.4
R EFERENCES
[1] Andersen, O. B., The DTU10 Gravity filed and Mean sea surface (2010), Second international symposium of the gravity field of the Earth (IGFS2), Fairbanks, Alaska.
[2] Boy, F. et al (2011): "Cryosat LRM, TRK and SAR processing". Presented at the 2011 Ocean Surface Topography Science Team meeting. http://www.aviso.oceanobs.com/fileadmin/
documents/OSTST/2011/oral/01_Wednesday
[3] Carrere, L., F. Lyard, 2003, Modeling the barotropic response of the global ocean to atmospheric wind and pressure forcing- comparisons with observations. J. Geophys. Res., 30(6), 1275,
doi:10.1029/2002GL016473.
[4] Carrere L., 2003, Etude et modélisation de la réponse HF de l’océan global aux forçages
météorologiques. PhD thesis, Université Paul Sabatier (Toulouse III, France), 318 pp.
[5] Cartwright, D. E., R. J. Tayler, 1971, New computations of the tide-generating potential, Geophys. J.
R. Astr. Soc., 23, 45-74.
[6] Cartwright, D. E., A. C. Edden, 1973, Corrected tables of tidal harmonics, Geophys. J. R. Astr. Soc.,
33, 253-264.
[7] Following the scientific recommendations from the OSTST meeting (San Diego, October 2011), the
ESA Cryosat Project and the CNES SALP Project have been collaborating to generate these Cryosatderived L3 and L4 products. Level 1B and Level 2 products derived from CNES processors are not
distributed by AVISO as per the CNES / ESA agreement.
[8] Dibarboure G., C. Renaudie, M.-I. Pujol, S. Labroue, N. Picot, 2011, "A demonstration
of the potential of Cryosat-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
[9] 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.
[10] Dibarboure G., M-I.Pujol, F.Briol, PY.Le Traon, G.Larnicol, N.Picot, F.Mertz, M.Ablain, 2011: Jason2 in DUACS: first tandem results and impact on processing and products. Marine Geodesy, 34,(34),214-241.
[11] Dibarboure G., 2009: Using short scale content of OGDR data improve the Near Real Time products
of Ssalto/Duacs, oral presentation at Seattle OSTST meeting (pdf).
[12] Dorandeu, J., M. Ablain, Y. Faugère, F. Mertz, B. Soussi, and P. Vincent, 2004: Jason-1 global statistical evaluation and performance assessment. Calibration and cross-calibration results. Marine Geodesy,
27,(3-4), 345-372
[13] Dorandeu, J., M. Ablain, P.-Y. Le Traon, 2003: Reducing Cross-Track Geoid Gradient Errors around
TOPEX/Poseidon and Jason-1 Nominal Tracks: Application to Calculation of Sea Level Anomalies.
J. of Atmosph. and Ocean. Techn.,20, 1826-1838.
[14] Dorandeu, J. and P.-Y. Le Traon, 1999: Effects of global mean atmospheric pressure variations on
mean sea level changes from TOPEX/Poseidon. J. Atmos. Oceanic Technol., 16, 1279-1283.
[15] Ducet, N., P.-Y. Le Traon, and G. Reverdin, 2000: Global high resolution mapping of ocean circulation
from TOPEX/Poseidon and ERS-1 and -2. J. Geophys. Res., 105, 19477-19498.
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Date : 5 February 2013
Issue : 3.4
[16] Egbert, Gary D., Svetlana Y. Erofeeva, 2002: Efficient Inverse Modeling of Barotropic Ocean Tides. J.
Atmos. Oceanic Technol., 19, 183-204. doi: 10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2
[17] Gaspar, P., and F. Ogor, Estimation and analysis of the Sea State Bias of the ERS-1 altimeter. Report
of task B1-B2 of IFREMER Contract n˚ 94/2.426 016/C., 1994.
[18] Gaspar, P., F. Ogor and C. Escoubes, 1996, Nouvelles calibration et analyse du biais d’état de mer des
altimètres TOPEX et POSEIDON. Technical note 96/018 of CNES Contract 95/1523, 1996.
[19] Gaspar, P., and F. Ogor, Estimation and analysis of the Sea State Bias of the new ERS-1 and ERS-2
altimetric data (OPR version 6). Report of task 2 of IFREMER Contract n˚ 96/2.246 002/C, 1996.
[20] Gaspar, P., S. Labroue and F. Ogor. 2002, Improving nonparametric estimates of the sea state bias in
radar altimeter measurements of seal level, J. Atmos. Oceanic Technology, 19, 1690-1707.
[21] Hernandez, F., P.-Y. Le Traon, and R. Morrow, 1995: Mapping mesoscale variability of the Azores
Current using TOPEX/POSEIDON and ERS-1 altimetry, together with hydrographic and Lagrangian
measurements. Journal of Geophysical Research, 100, 24995-25006.
[22] Hernandez, F. and P. Schaeffer, 2000: Altimetric Mean Sea Surfaces and Gravity Anomaly maps intercomparisons AVI-NT-011-5242-CLS, 48 pp. CLS Ramonville St Agne.
[23] Hernandez, F., M.-H. Calvez, J. Dorandeu, Y. Faugère, F. Mertz, and P. Schaeffer, 2000: Surface Moyenne Océanique: Support scientifique à la mission altimétrique Jason-1, et à une mission micro-satellite altimétrique. Contrat SSALTO 2945 - Lot 2 - A.1. Rapport d’avancement.
CLS/DOS/NT/00.313, 40 pp. CLS Ramonville St Agne.
[24] Iijima, B.A., I.L. Harris, C.M. Ho, U.J. Lindqwiste, A.J. Mannucci, X. Pi, M.J. Reyes, L.C. Sparks,
B.D. Wilson, 1999: Automated daily process for global ionospheric total electron content maps and
satellite ocean altimeter ionospheric calibration based on Global Positioning System data, J. Atmos.
Solar-Terrestrial Physics, 61, 16, 1205-1218
[25] Labroue S., A. Ollivier, M. Guibbaud, F. Boy, N. Picot, P. Féménias, "Quality assessment of Cryosat-2 altimetric system over ocean", 2012, OSTST in Venice, available at http://www.aviso.oceanobs.com/fileadmin/documents/OSTST/2012/
posters/Labroue_Ollivier_Guibbaud_Final.pdf
[26] Labroue S., F. Boy, N. Picot, M. Urvoy, M. Ablain, "First quality assessment of the Cryosat-2 altimetric
system over ocean", J. Adv. Space Res., 2011, doi:10.1016/j.asr.2011.11.018. http://dx.doi.
org/10.1016/j.asr.2011.11.018
[27] Labroue, S., 2007: RA2 ocean and MWR measurement long term monitoring, 2007 report for WP3,
Task 2 - SSB estimation for RA2 altimeter. Contract 17293/03/I-OL. CLS-DOS-NT-07-198, 53pp.
CLS Ramonville St. Agne
[28] Labroue, S., P. Gaspar, J. Dorandeu, O.Z. Zanifé, F. Mertz, P. Vincent, and D. Choquet, 2004: Non
parametric estimates of the sea state bias for Jason-1 radar altimeter. Marine Geodesy, 27, 453-481.
[29] Lagerloef, G.S.E., G.Mitchum, R.Lukas and P.Niiler, 1999: Tropical Pacific near-surface currents
estimated from altimeter, wind and drifter data, J. Geophys. Res., 104, 23,313-23,326
[30] Le Traon, P.-Y. and F. Hernandez, 1992: Mapping the oceanic mesoscale circulation: validation of
satellite altimetry using surface drifters. J. Atmos. Oceanic Technol., 9, 687-698.
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[31] Le Traon, P.-Y., P. Gaspar, F. Bouyssel, and H. Makhmara, 1995: Using Topex/Poseidon data to enhance ERS-1 data. J. Atmos. Oceanic Technol., 12, 161-170.
[32] Le Traon, P.-Y., F. Nadal, and N. Ducet, 1998: An improved mapping method of multisatellite altimeter
data. J. Atmos. Oceanic Technol., 15, 522-534.
[33] Le Traon, P.-Y. and F. Ogor, 1998: ERS-1/2 orbit improvement using TOPEX/POSEIDON: the 2 cm
challenge. J. Geophys. Res., 103, 8045-8057.
[34] Le Traon, P.-Y. and G. Dibarboure, 1999: Mesoscale mapping capabilities of multi-satellite altimeter
missions. J. Atmos. Oceanic Technol., 16, 1208-1223.
[35] Le Traon, P.-Y., G. Dibarboure, and N. Ducet, 2001: Use of a High-Resolution Model to Analyze the
Mapping Capabilities of Multiple-Altimeter Missions. J. Atmos. Oceanic Technol., 18, 1277-1288.
[36] Le Traon, P.Y. and G. Dibarboure, 2002 Velocity mapping capabilities of present and future altimeter
missions: the role of high frequency signals. J. Atmos. Oceanic Technol., 19, 2077-2088.
[37] Le Traon, P.Y., Faugère Y., Hernandez F., Dorandeu J., Mertz F. and M. Ablain, 2002: Can we merge
GEOSAT Follow-On with TOPEX/POSEIDON and ERS-2 for an improved description of the ocean
circulation, J. Atmos. Oceanic Technol., 20, 889-895.
[38] Le Traon, P.Y. and G. Dibarboure, 2004: An Illustration of the Contribution of the TOPEX/PoseidonJason-1 Tandem Mission to Mesoscale Variability Studies. Marine Geodesy, 27 (1-2).
[39] Mertz F., F. Mercier, S. Labroue, N. Tran, J. Dorandeu, 2005: ERS-2 OPR data quality assessment ;
Long-term monitoring - particular investigation. CLS.DOS.NT-06.001 (pdf)
[40] MSS_CNES_CLS11 was produced by CLS Space Oceanography Division and distributed by Aviso,
with support from Cnes (
urlhttp://www.aviso.oceanobs.com/)".
[41] Pascual, A., Y. Faugère, G. Larnicol, P-Y Le Traon, 2006: Improved description of the ocean
mesoscale variability by combining four satellite altimeters. Geophys. Res. Lett., 33
[42] Pascual A., C. Boone, G. Larnicol and P-Y. Le Traon, 2009. On the quality of Real-Time altimeter
gridded fields: comparison with in-situ data. Journ. of Atm. and Ocean. Techn. Vol. 26(3) pp. 556-569,
DOI: 10.1175/2008JTECHO556.1
[43] Prandi P., M. Ablain, A. Cazenave, N. Picot, 2011, A new estimation of mean sea level in the Arctic
Ocean from satellite altimetry. Submitted to Marine Geodesy.
[44] Pujol M-I. et al., 2009. Three-satellite quality level restored in NRT, poster at OSTST meeting (pdf)
[45] Ray, R., 1999: A Global Ocean Tide model from TOPEX/Poseidon Altimetry, GOT99.2. NASA Tech.
Memo. NASA/TM-1999-209478, 58 pp. Goddard Space Flight Center, NASA Greenbelt, MD, USA.
[46] Rio, M.-H. and F. Hernandez, 2003: A Mean Dynamic Topography computed over the world
ocean from altimetry, in-situ measurements and a geoid model. J. Geophys. Res., 109, C12032,
doi:10.1029/2003JC002226.
[47] Rio, M.-H. and F. Hernandez, 2003: High frequency response of wind-driven currents measured by
drifting buoys and altimetry over the world ocean. J. Geophys. Res., 108, 39-1.
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[48] Rio, M.-H., 2003: Combinaison de données in situ, altimétriques et gravimétriques pour l’estimation
d’une topographie dynamique moyenne globale. Ed. CLS. PhD Thesis, University Paul Sabatier
(Toulouse III, France), 260pp.
[49] Scharroo, R. and P. Visser, 1998: Precise orbit determination and gravity field improvement for the
ERS satellites. J. Geophys. Res., 103, 8113-8127
[50] Scharroo, R., J. Lillibridge, and W.H.F. Smith, 2004: Cross-calibration and long-term monitoring of
the Microwave Radiometers of ERS, Topex, GFO, Jason-1 and Envisat. Marine Geodesy, 97.
[51] Tran N. and E. Obligis, December 2003, "Validation of the use of ENVISAT neural algorithms on
ERS-2", CLS.DOS/NT/03.901.
[52] Tran, N., S. Labroue, S. Philipps, E. Bronner, and N. Picot, 2010 : Overview and Update of the Sea
State Bias Corrections for the Jason-2, Jason-1 and TOPEX Missions. Marine Geodesy, accepted.
[53] Vincent, P., Desai S.D.,Dorandeu J., Ablain M., Soussi B., Callahan P.S. and B.J. Haines, 2003: Jason1 Geophysical Performance Evaluation. Marine Geodesy, 26, 167-186.
[54] Wahr, J. W., 1985, Deformation of the Earth induced by polar motion,J. of Geophys. Res. (Solid Earth),
90, 9363-9368.
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I. I NTRODUCTION
MyOcean is a European Network project aiming at monitoring, analyzing and forecasting the Ocean. It
uses satellite and in-situ data to describe the ocean in 3 dimensions and real time. More information can be
found on http://www.myocean.eu.org.
The aim of this document is to describe the products delivered by the Sea Level TAC (Thematic Assembly
Centre) which is one of the five TAC of the MyOcean project.
The data produced in the frame of this TAC are generated by the processing system named DUACS (Data
Unification and Altimeter Combination System).
DUACS is part of the CNES multi-mission ground segment (SSALTO). It processes data from all altimeter
missions: Cryosat-2, OSTM/Jason-2, Jason-1, Topex/Poseidon, Envisat, GFO, ERS-1&2 and even Geosat.
At this time (February 2013) DUACS is using three different altimeters in near real time .
Developed and operated by CLS, it started as an European Commission Project (Developing Use Of Altimetry 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
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The products lines described in this user manual are the following:
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)
and regional products are also computed over specific areas:
Mediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)
and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003).
Thanks to updates in 2012 (see section II.), new regional products are now available:
Europe (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)
and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005).
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II. U PDATES IN 2012 AND 2013
This section describes the updates of the SSALTO/DUACS system that occurred during 2012 and 2013,
allowing to add new products (Europe and Arctic), the integration of the Cryosat-2 data in the system, the
stopping delivery of Envisat data, the addition of Jason-1 data on geodetic orbit (j1g), the new version of
Jason-2 GDRs.
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.
II.1. Integration of most recent data as soon as available: "OGDR on the fly"
(February 2013)
Since February 5th , 2013, the most recent OGDR data are taken into account in the GLOBAL NRT product
as soon as available: indeed, the two latest files delivered each day can be updated during all the day in order
to take into account the latest available data. For example, if you download files at 15:00 for the day D:
• Before February 5, the last date of data that you could get in the last file delivered was 20:00 of the
day D-1.
• As from February 5, the same file is updated and you get data until 13:00 of the day D at the best (if
OGDR is valid).
This concerns all the datasets of the following product: SEALEVEL_GLO_SLA_L3_NRT_OBSERVATIONS_008_001_
II.2. All the Sea Level SLA files are compressed (February 2013)
All the Sea Level products are now compressed:
• Before February 5, you got a zip file containing *.nc files
• As from February 5, you get a zip file containing *.nc.gz files
This concerns all the datasets of the following products:
SEALEVEL_GLO_SLA_L3_NRT_OBSERVATIONS_008_001_a
SEALEVEL_BS_SLA_L3_NRT_OBSERVATIONS_008_001_a
SEALEVEL_MED_SLA_L3_NRT_OBSERVATIONS_008_001_a
SEALEVEL_EUR_SLA_L3_NRT_OBSERVATIONS_008_001_a
SEALEVEL_ARC_SLA_L3_NRT_OBSERVATIONS_008_001_a
SEALEVEL_GLO_SLA_L3_RAN_OBSERVATIONS_008_001_b
SEALEVEL_MED_SLA_L3_RAN_OBSERVATIONS_008_002_b
SEALEVEL_BS_SLA_L3_RAN_OBSERVATIONS_008_003_b
II.3. Version "D" of input IGDR/OGDR Jason-2 data (July 30, 2012 for NRT
products , December 2012 for Reprocessed products)
On July 30, 2012, the version of Jason-2 IGDR/OGDR has changed and is now the "D" version. Some
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corrections have thus been updated as detailed in tables 3 and 4 for Near Real Time processing and in tables
6 and 7 for Delayed Time processing.
II.4. Integration of Jason-1 on its geodetic orbit (May 2012 for NRT products,
December 2012 for Reprocessed products)
An anomaly occured on March 3rd , 2012 on the Jason-1 mission. On April 23rd , CNES began to command
the satellite into a nadir orientation and after some propulsion anomalies, CNES and NASA management,
through the Joint Steering Group, have directed the Jason-1 Project to then begin a series of maneuvers to
place Jason-1 into a new orbit as defined in table 1. After checking the current orbit carefully, the operational
team determined that a geodetic mission was still possible. It was also decided to preserve all remaining fuel
for future station keeping maneuvers which is mandatory in a geodetic orbit. Core payloads were switched
ON on May 4th and after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th
at 15:12:48 UTC.
Below are the characteristics of the new orbit which will be maintained, as before, within +/- 1km control
box at the Equator:
Semi major axis:
Eccentricity:
Altitude equator:
Orbital period:
Inclination:
Cycle:
Sub cycles:
7702.437 km
1.3 to 2.8 10-4
1324.0 km
6730s (1h52’10”)
66.042˚
406 days
3.9 - 10.9 - 47.5 - 179.5
days
Table 1: Characteristics of the geodetic orbit for Jason-1 since May 7th , 2012
For this new phase of the Jason-1 mission (called j1g), the cycle numbering will restart at 500. Off-line
products will be produced once a day for the IGDR, and every 11 days for the GDR’s. The integration of
Jason-1 data in the DUACS system is available since May 25th , 2012.
II.5. Envisat has stopped sending data (April 2012)
Since April 8th 2012, Envisat has stopped sending data to Earth. Esa’s mission control has worked to
re-establish contact with the satellite but there has been no reaction from the satellite. Thus Esa has declared officially the end of mission for Envisat (see http://www.esa.int/esaCP/SEM1SXSWT1H_
index_0.html). Therefore, no SL TAC NRT data from Envisat can be released since this date.
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II.6. Integration of the Cryosat2 Mission (February 2012 in NRT and in Reprocessed products)
Since February 6th , 2012, Cryosat-2 mission has been integrated in the sytem. This mission is dedicated to
the observation of the floating sea-ice as well as the continental ice sheets, but all data acquired over ocean
are valuable for the observation of oceanic circulation and mesoscale variations. This major change is the
result of the long-standing and fruitful partnership between ESA and CNES and a response to the request
from scientific and operational oceanography users [7]. The integration of Cryosat-2 impacts the delivering
of Near real time and Delayed time Sea Level Anomalies (SLA) .
II.6.1. Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al, 2011, [2]) has been developed on CNES
side to lay the ground for various SAR processing studies. The processing chains ingest Level-0 telemetry
files distributed by ESA, and perform the following steps to generate Sea Level Anomalies (SLA) values for
each altimeter measurements:
• Level-1: Decommutation, time-tagging and localization of measurements
• Level-1b: Calculation of instrumental corrections and geophysical/meteorological corrections
• Level-2: MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean, either in Low Resolution Mode (LRM) or in
the Doppler/SAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2).
Figure 2: SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWF
wet troposphere correction, validation activities showed (Labroue et al, 2011, [26]) that C2P outputs have an
accuracy roughly equivalent to Envisat’s Level 2 products if the latter are processed with the same standards.
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II.6.2. Integration in DUACS
The Cryosat-2 data are included in the Near Real time and Delayed time process. The chain delivers
now (for global coverage, Mediterranean, Black Seas, Europe and Arctic) along track data from Cryosat-2
(SLAs) . Note that the products distributed are of Level-3 and don’t replace Level-2 products distributed by
agencies.
The details of the processing are given in Dibarboure et al, 2011 [8].
Here, we just give an overview: the data are computed with the corrections given in section III.2.1.. The
filtering and sub-sampling of SLAs (section III.2.6.3.) are detailed in [8].
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II.7. Addition of Europe and Arctic products (January 2012) in NRT processing
Since the MyOcean V2, two new along-track products are computed in Near Real Time, intended for
addressing the needs of data assmilation and validation in regional models:
• Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched by
SL TAC with all the Modeling and Forecasting Centers (MFCs), the Europe regional products (PL
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3). They are
available in Near Real Time only.
They are studied to partly fulfil the needs of the Centers with adapted filtering and resolution. Those
parameters have been tuned in order to provide boundary conditions for the Atlantic assimilation
models. They are different from the ones used for Mediterranean and Black Seas products. If you need
to study the Mediterranean Sea or the Black Sea, you’d better use the dedicated products described
above since the processing parameters have been fitted to be adapted to the dynamics of the ocean in
those regions.
Figure 3: Coverage of the Europe product for Jason-1, Jason-2 and Envisat from August, 18th to September,
9th 2011
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• The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) cover
latitudes between 45 and 82 degrees (figure 4). They are available in Near Real Time only.
Figure 4: Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III. SSALTO/DUACS SYSTEM
III.1. Introduction
This chapter presents the input data used by SSALTO/DUACS system and an overview of the different processing steps necessary 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 quality 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 recommendations from the altimetry community.
Following figure gives an overview of DUACS system, where processing sequences can be divided into 7
main steps:
• acquisition
• homogenization
• input data quality control
• multi-mission cross-calibration
• product generation
• merging
• final quality control.
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Figure 5: SSALTO/DUACS processing sequences
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III.2. Near Real Time processing steps
III.2.1. Input data, models and corrections applied
To produce SLA in near-real time, the DUACS system uses two flows, based on the same instrumental measurements but with a different quality:
• The IGDR that are the latest high-quality altimeter data produced in near-real-time.
• The OGDR that includes real time data (OSTM/Jason-2 and Jason-1 OSDR) to complete IGDR. These
fast delivery products do not always benefit from precise orbit determination, nor from some external model-based corrections (Dynamic Atmospheric Correction (DAC), Global Ionospheric Maps
(GIM)).
Integration of OGDR data and the introduction of Jason-2/Jason-1 tandem increased the resilience and precision of the system. A better restitution of ocean variability is observed, especially in high energetic areas.
Altimetric product
Source
Availability
Type of orbit
Jason-2
CNES
~24h
CNES MOE GDR-C
until 2012/07/30
IGDR
CNES MOE GDR-D
since 2012/07/31
Jason-1
Cryosat-2
OGDR
NOAA/EUMETSAT
~3 to 5 h
IGDR
CNES/NASA
~48 h
OGDR
CNES/NASA
~3 to 12 h
IGDR-like
ESA/CNES
~48 h
CNES MOE GDR-D
since 2012/05/07
CNES MOE GDR-D
not delivered
Table 2: SSALTO/DUACS Near-Real Time Input data overview
See Figure 6: Overview of the near real time system data flow management.
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SEALEVEL_*_SLA_L3_OBSERVATIONS_008_00*
Product
standard ref
Orbit
Ionopheric
Dry tropo
Wet troposphere
DUACS NRT product from IGDR1
j2
j1n;j1g
version C until 2012/07/30
version C
c2
CPP [2]
and D after
CNES MOE GDR-C until
2012/07/30 GDR-D after
CNES MOE GDR-C for j1n
and CNES MOE GDR-D
for j1g
CNES MOE GDR-D
bi-frequency altimeter range measurements
GIM model for c>64
(Iijima et al,1998[24])
Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides
applied)
AMR radiometer
JMR radiometer
Model computed from
(enhancement in coastal
ECMWF Gaussian grids
regions since 2012/07/30)
DAC
Ocean tide
Pole tide
Solid earth
tide
Loading tide
Sea
state
bias
MOG2D High Resolution forced with ECMWF pressure and wind fields (S1
and S2 were excluded) (Carrere and Lyard, 2003[3])+ inverse barometer.
Filtering temporal window is un-centered (no data in the future)
GOT4v8 (S1 and S2 are included) and TPX 07.2 [16] for Arctic products
[Wahr, 1985 [54]]
Elastic response to tidal potential [Cartwright and Tayler, 1971[5]],
[Cartwright and Edden, 1973[6]]
GOT4v8 (S1 and S2 are included)
Non parametric SSB
Non parametric SSB
Same as Jason-1 with
[Labroue, 2004[28]] (with
[Labroue, 2004[28]]
correction of a drift on
cycles J1 1 to 111 using
(with cycles 1 to 121
Sigma0 (Labroue et al.,
GDR-B standards until
using GDR-B standards)
2012[25]
2012/07/30 and derived
from Jason-2 after)
Orbit error
Global multi-mission crossover minimization (Le
Traon and Ogor, 1998[33])
Optimal Interpolation [Le Traon et al., 1998[32]]
Long wavelengh errors
Intercalibration Reference from cycle 20
Mean pro- Computed with cycles 11file
(see 353 TP data and with cyIII.2.6.1.)
cles 11-250 J1 data; referenced [1993,1999]
TPN/J1N:
computed
with cycles 369-479
TPN data; referenced
[1993,1999]. J1G: No
MP can be used, instead,
the MSS_CNES_CLS11
[40] is used
No Mean Profile can
be used for Cryosat2.
Instead,
the
MSS_CNES_CLS11
[40] is used
(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 3: Corrections and models applied in SSALTO/DUACS NRT products produced from IGDRs.
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Product standard ref
Orbit
Ionopheric
Dry troposphere
Wet
troposphere
DAC
Ocean tide
Pole tide
Solid earth tide
Loading tide
Sea state bias
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Date : 5 February 2013
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DUACS NRT product from OGDR 2
j2
j1n;j1g
version C until 2012/07/30 and D after
version C
Navigator
From-dual frequency altimeter range measurements
Model computed from ECMWF Gaussian grids (new S1 and S2 atmospheric
tides are applied)
AMR radiometer (enhancement in
JMR radiometer
coastal regions since 2012/07/30)
Inverse Barometer forecasted
GOT4v8 (S1 and S2 are included) and TPX 07.2 [16] for Arctic products
[Wahr, 1985 [54]]
Elastic response to tidal potential [Cartwright and Tayler, 1971[5]],
[Cartwright and Edden, 1973[6]]
GOT4v8 (S1 and S2 are included)
Non parametric SSB [Labroue, Non parametric SSB [Labroue,
2004[28]] (with cycles J1 1 to 11 using 2004[28]] (with cycles 1 to 21 using
GDR-B standards until 2012/07/30 and GDR-B standards)
derived from Jason-2 after)
Orbit error
Long
wavelengh errors
Intercalibration
Mean
profile
(see III.2.6.1.)
Specific filtering of long-wavelength
signal3
Optimal Interpolation [Le Traon et al., 1998[32]]
Reference from cycle 20
Computed with cycles 11-353 TP data
and with cycles 11-250 J1 data; referenced [1993,1999]
TPN/J1N: computed with cycles 369479 TPN data; referenced [1993,1999].
J1G: No MP can be used, instead, the
MSS_CNES_CLS11 [40] is used
(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 (§III.2.3. of the user manual)
Table 4: Corrections and models applied in SSALTO/DUACS NRT products produced from OGDRs.
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III.2.2. Acquisition
The acquisition process is twofold:
• straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure and
wet 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 software
detects, downloads and processes incoming data as soon as they are available on remote sites (external
database, FTP site). Data are split into passes if necessary. If data flows are missing or late, the synchronisation engine put unusable data in waiting queues and automatically unfreezes them upon reception of the
missing auxiliary data. This processing step delivers "raw" data, that is to say data that have been divided
into 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 before
acquisition; 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 6: Overview of the near real time system data flow management
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III.2.3. Homogenization
The Homogenization process consists in applying the most recent corrections, models and references recommended for altimeter products. Each mission is processed separately as its needs depend on the base
input data. The list of corrections and models currently applied is provided in tables 3 and 4 for NRT data.
The system includes SLA filtering to process OGDR data. DUACS extract from these data sets the short
scales (space and time) which are useful to better describe the ocean variability in real time, and merge this
information with a fair description of large scale signals provided by the multi-satellite observation in near
real time (read: IGDR-based DUACS data). Finally an "hybrid" SLA is computed.
Figure 7: Merging pertinent information from IGDR and OGDR processing
III.2.4. Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the most
accurate altimeter data. Thanks to the high quality of current missions, this process rejects a small percentage 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 also
on complex data editing algorithms based on the detection of erroneous artefacts, mono and multi-mission
crossover validation, and macroscopic statistics to edit out large data flows that do not meet the system’s
requirements.
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III.2.5. Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistent
and accurate information. It removes any residual orbit error (OE, Le Traon and Ogor, 1998[33]), or long
wavelength error (LWE, Le Traon et al., 1998[32]), as well as large scale biases and discrepancies between
various data flows.
This process is based on two very different algorithms: a global multi-mission crossover minimization for
orbit 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 the
reference mission orbit, a very accurate orbit error can be estimated. This processing step does not concern
OGDR data.
LWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals. The OI
used for LWE reduction uses precise parameters derived from:
• accurate statistical description of sea level variability
• localized correlation scales
• mission-specific noise and precise assumptions on the long wavelength errors to be removed (from a
recent analysis of one year of data from each mission).
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III.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.
III.2.6.1. Computation of raw SLA
Since the geoid is not well known yet, the SSH cannot be used directly, the SSH anomalies are used instead.
They are computed from the difference of the instantaneous SSH - a temporal reference. This temporal
reference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeat
track analysis cannot be used. The errors affecting the SLAs, MPs and MSS have different magnitudes and
wavelengths. The computation of the SLAs and their errors associated are detailed in Dibarboure et al, 2010
[9].
Use of a Mean Profile
In the repeat track analysis (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-sampled data
over a long period.
• The Mean Profile used for Jason-2 is computed with 10 years of T/P (cycles 11 to 353) and 6 years of
Jason-1 (cycles 11 to 250).
• The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved groundtracks) is computed with 3 years of T/P (cycles 369 to 479).
• No Mean Profile can be used for Envisat on its new orbit (enn), Jason-1 on its geodetic orbit (j1g) nor
for Cryosat-2 mission (c2) because there is no repetitive track. The MSS must be used instead (see
below).
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Computation of a Mean Profile
The computation of a Mean Profile is not a simple average of similarly co-located SSH data from the same
ground 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 about
1km wide, precise cross-track projection and/or interpolation schemes are required to avoid errors.
• The mesoscale variability error (which is <3.5 cm for MP between 3 to 5 years and <1cm for WL
of 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a priori
knowledge from Sea Level maps derived from previous iterations or from other missions.
• Moreover, the inter-annual variabilty error (<5cm for WL>5000km and <5-8cm for WL of 200500km) is accounted for by using the MSS computed over 1993-1999 (e.g. the GFO MP is computed
on 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions).
• Finally, for these Mean Profiles, the latest standards and a maximum of data were used in order to
increase as much as possible the quality of their estimation . Note that a particular care was brought
to the processing near coasts.
Use of a MSS
The repeat track analysis is impossible for Envisat since november 2010, for Jason-1 on its geodetic orbit
(j1g) and for Cryosat-2 mission (c2) because the satellite is not in a repetitive orbit phase. The alternative is
to use the MSS instead. 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 MSS which are hard to quantify separately:
• To ensure a global MSS coherency between all data sets, the gridding process averages all sensorspecific errors and especially geographically correlated ones.
• The gridding process has to perform some smoothing to make up for signals which cannot be resolved
away 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 absorption
in the MSS and the impossibility to compute mean sea surface height content.
Note that for the Arctic regional products, the DTU10 MSS [1] is taken into account instead of the CLS01
MSS. Indeed, the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sea
level anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al., [43]..
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III.2.6.2. Cross validation
After the repeat track analysis, the cross-validation technique is used as the ultimate screening process of
isolated and slightly erroneous measurements. Small SLA flows are compared to previous and independent
SLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal.
III.2.6.3. Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter. As data
are filtered from small scales, a sub-sampling is finally applied. Along-track SLA are then produced.
Note that the filtering and sub-sampling is adapted to each region and product as a function of the characteristics of the area and of the assimilation needs.
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III.2.7. Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature 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 control on each processing step is indispensable to appreciate the overall quality of the system and to provide the best user services.
III.2.7.1. Final quality Control
The Quality Control is the final process used by DUACS before product delivery. In addition to daily
automated controls and warnings to the operators, each production delivers a large QC Report composed of
detailed logs, figures and statistics of each processing step. Altimetry experts analyse these reports twice a
week.
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III.2.7.2. Performance indicators
To appreciate the quality situation of the DUACS system, new performance indicators are computed daily.
They aim at evaluate the status of the main processing steps of the system: the input data availability, the
input data coverage, the input data quality and the output product quality. These indicators are computed for
each and every currently working satellite, and combined to obtain the overall status.
Figure 8: Example with the key performance indicator on 2009/06/27
See the description, the latest and previous indicators on Aviso website:
http://www.aviso.oceanobs.com/index.php?id=1516
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III.3. Delayed Time processing steps
III.3.1. Input data, models and corrections applied
Delayed Time MyOcean products are generated:
• from Aviso GDR products for T/P, Jason-1, Jason-2 and Envisat (GDR-A: cycles 1 to 22 / GDR-B:
cycles 23 to 85 / GDR-C: from cycle 86),
• from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C
(1st 35-day repeat orbit period), phase E and F (geodetic phases), phase G for ERS-1 (last 35-day
repeat orbit period, tandem phase with ERS-2 ; phase A for ERS-2 (1st 35-day repeat orbit period,
tandem phase with ERS-1)).
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3
months depending on the mission. For several missions, an updated orbit is used:
• For Jason-2, GDR-C orbit is used until 2012/06/18 and GDR-D after
• For Jason-1 geodetic orbit, GDR-D orbit is used (GDR-C before)
• For ERS-1&-2, the orbit used is DGME-04 provided by Delft Institute (http://www.deos.tudelft.nl/)
until June 2003,
• For Topex/Poseidon, the orbit used is GSFC (std0809) for the whole mission,
• For Envisat, CNES POE of GDR-C standard is used for the whole mission,
• For the whole GFO mission, the orbit used is GSFC (std0809) and when not available, NASA POE is
used.
Altimetric product
Source
Availability
Type of orbit
Topex/Poseidon GDR
NASA/CNES
-
GSFC POE
Jason-1 GDR (GDR-C)
CNES/NASA
~40 days
CNES POE
Jason-2 GDR (GDR-C)
CNES/NASA
~60 days
CNES POE
GFO GDR
NOAA
-
GSFC/NASA POE
ERS-1&2
IFREMER/ESA
-
DGME-04
Envisat (GDR-A, GDR-B and
GDR-C from cycle 86)
ESA
-
CNES POE
Cryosat-2
ESA/CNES
~40 days
CNES POE
Table 5: SSALTO/DUACS Delayed Time Input data overview
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Product
standard ref
Orbit
Ionopheric
Dry
troposphere
Wet troposphere
DAC
Ocean tide
Pole tide
Solid earth
tide
Loading tide
Sea
state
bias
Orbit error
Long wavelengh errors
Intercalibration
Mean profile
(see
III.3.6.1.)
Period of use
j2
GDR-C until 2012/06/18
and GDR-D after
Ref
: MYO2-SL-PUM008-001-005
Date : 5 February 2013
Issue : 3.4
DUACS DT product (>V3.0.0)
j1;j1n;j1g
tp;tpn
GDR-C
g2
GDR (NOAA)
Cnes POE GDR-C until
Cnes POE GDR-C for
2012/06/18 and GDR-D
j1,j1n and GDR-D for
after
j1g
Dual frequency altimeter range measurements
GSFC (ITRF
GSFC (ITRF 2005,
2005,GRACE last
GRACE last standards
standards)
Dual frequency
From GIM model
altimeter range
(Iijima et al, 1998 [24])
measurements (Topex),
DORIS (POSEIDON)
Model computed from ECMWF rectangular grids and gaussian grids from
November 20th , 2010 (new S1 and S2 atmospheric tides are included)
Model computed from
ECMWF Gaussian grids
(new S1 and S2
atmospheric tides are
applied)
JMR/AMR radiometer further than 50 km from
TMR radiometer
GFO radiometer
the coasts, From ECMWF model for distances
(Scharoo et al. 2004
between 10 and 50 km
[50])
MOG2D High Resolution forced with ECMWF pressure and wing fields (S1 and S2 were
excluded) + inverse barometer computed from rectangular grids
GOT4v7 (S1 and S2 are included)
[Wahr, 1985[54]]
Elastic response to tidal potential Cartwright and Tayler, 1971[5],Cartwright and Edden, 1973[6]
GOT4v7 (S1 parameter is included)
NP SSB [Labroue,
Non parametric SSB [N.
2004[28]] (with cycles 1
Tran and al. 2010[52]]
to 121 using GDR-B
standards)
NP SSB [Labroue,
Non parametric SSB [N.
2004[28]] (with cycles
Tran et al., 2010[52]]
J1 1 to 111 using
GDR-B standards until
2012/06/18 and derived
from Jason-2 after)
Global multi-mission crossover minimization (Le Traon and Ogor, 1998[33])
Optimal Interpolation (Le Traon et al., 1998[32])
Reference from cycle 11
Correction of regional
bias J2/J1 deduced from
intercalibration phase
( cycle 11 J2)
Computed with cycles
11-353 TP data and with
cycles 11-250 J1 data;
referenced [1993,1999]
from cycle 9
Reference from cycle 1
to 354
Correction of global
biais J1/TP déduced
from intercalibration
phase ( cycles 11 J1)
TP/J1: computed with cycles 11-353 TP data and
with cycles 11-250 J1 data; referenced
[1993,1999]
TPN/J1N: computed with cycles 369-479 TPN
data; referenced [1993,1999]
from cycle 9
cycles 1 to 481
Computed with cycles
37-187 G2 data ;
referenced [1993,1999]
cycles 37 to 222
Table 6: Corrections and models applied in SSALTO/DUACS DT products for TOPEX/Poseidon, Jason-1,
Jason-2 and GFO.
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e1
Product
standard ref
Orbit
Ionopheric
Dry troposphere
Wet troposphere
DAC
Ocean tide
Pole tide
Solid earth
tide
Loading tide
Sea
state
bias
Orbit error
Mean profile
(see
III.3.6.1.)
Period of use
OPR
Ref
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DUACS DT product (>V3.0.0)
e2
en;enn
GDR-A (c≤22)/GDR-B
(23≤c≤85)/GDR-C (c≥93)
c2
CPP [2]
DGME-04 (Scharroo and Visser, 1998[49]
CNES POE (GDR-B
CNES POE GDR-D
standards for c≤22; GDR-C
standards c≥23)
Bent model
Bent model (c≤36), GIM
Dual-frequency altimeter
From GIM model
modem c≥37 ((Iijima et al,
range measurement (c 9-64)
(Iijima et al, 1998
1998 [24])
and GIM model c≥65
[24])
(Iijima et al., 1999[24])
corrected from 8 mm bias
Model computed from ECMWF rectangular grids and gaussian grids from November 20th , 2010
(new S1 and S2 atmospheric tides are included)
MWR radiometer
MWR corrected of
MWR (dist≥50km from the
ECMWF Model
23.6GHz TB drift (Scharroo
coasts) and corrected from
et al., 2004[50])+Neural
side lobes (c≥41), from
Network algorithm (Tran
ECMWF model
and Obligis, 2003[51]
(50≥dist≥10km).
MOG2D High Resolution forced with ECMWF pressure and wing fields (S1 and S2 were
excluded) + inverse barometer computed from rectangular grids
GOT4v7 (S1 and S2 are included)
[Wahr, 1985[54]]
Elastic response to tidal potential [Cartwright and Tayler, 1971[5]], [Cartwright and Edden,
1973[6]]
GOT4v7 (S1 parameter is included)
Non parametric SSB [Mertz
Non parametric SSB
Same as Jason-1
et al., 2005[39]]
[Gaspar et al, 2002] with
with correction of a
GDR-B standards c≤85 and
drift on Sigma0
with GDR-C standards
(Labroue et al.,
c≥86
2012[25]
Global multi-mission crossover minimization (Le Traon and Ogor, 1998[33])
Computed with cycles 1-85 E2 data and with
EN: Computed with cycles
Use of
cycles 10-72 EN data; referenced [1993,1999]
1-85 E2 data and with
MSS_CNES_CLS11
cycles 10-72 EN data;
[40]
referenced [1993,1999]
ENN: use of
MSS_CNES_CLS11 [40]
cycles 15 to 43
cycles 1 to 83
from cycle 9
cycle 29
Including E-F
geodetic phases
BM3 [Gaspar and
Ogor 1994[17]]
Table 7: Corrections and models applied in SSALTO/DUACS DT products for ERS-1, ERS-2, Envisat and
Cryosat-2
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III.3.2. Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time: it consists in a synchronisation process of all the auxiliary data required to homogenize propely the altimeter data sets. The acquisition
step uses the GDRs or the OPRs provided by the agencies.
III.3.3. Homogenization
The Homogenization process consists in applying the most recent corrections, models and references recommended for altimeter products. Each mission is processed separately as its needs depend on the base
input data. The list of corrections and models currently applied is provided in tables 6 and 7 for DT data.
III.3.4. Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the most
accurate altimeter data. Thanks to the high quality of current missions, this process rejects a small percentage 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 also
on complex data editing algorithms based on the detection of erroneous artefacts, mono and multi-mission
crossover validation, and macroscopic statistics to edit out large data flows that do not meet the system’s
requirements.
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III.3.5. Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistent
and accurate information. It removes any residual orbit error (OE, Le Traon and Ogor, 1998[33]), or long
wavelength error (LWE, Le Traon et al., 1998[32]), as well as large scale biases and discrepancies between
various data flows.
This process is based on two very different algorithms: a global multi-mission crossover minimization for
orbit 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 the
reference mission orbit, a very accurate orbit error can be estimated. LWE is mostly due to residual tidal
or inverse barometer errors and high frequency ocean signals. The OI used for LWE reduction uses precise
parameters derived from:
• accurate statistical description of sea level variability
• localized correlation scales
• mission-specific noise and precise assumptions on the long wavelength errors to be removed (from a
recent analysis of one year of data from each mission).
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III.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.
III.3.6.1. Computation of raw SLA
Since the geoid is not well known yet, the SSH cannot be used directly, the SSH anomalies are used instead.
They are computed from the difference of the instantaneous SSH - a temporal reference. This temporal
reference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeat
track analysis cannot be used. The errors affecting the SLAs, MPs and MSS have different magnitudes and
wavelengths. The computation of the SLAs and their errors associated are detailed in Dibarboure et al, 2010
[9].
Use of a Mean Profile
In the repeat track analysis (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-sampled data
over a long period.
• The Mean Profile used for T/P (cycles 1 to 364), Jason-1 (cycles 1 to 259) and Jason-2 is computed
with 10 years of T/P (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250).
• The Mean Profile used for T/P (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellites
are on interleaved ground-tracks) is computed with 3 years of T/P (cycles 369 to 479).
• The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission, ERS-2, and Envisat (only for
the first orbit, before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 years
of Envisat (cycles 10 to 72).
• No Mean Profile can be used for Envisat on its new orbit (enn), Jason-1 on its geodetic orbit (j1g) nor
for Cryosat-2 mission (c2) because there is no repetitive track. The MSS must be used instead (see
below).
• The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187.
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Computation of a Mean Profile
The computation of a Mean Profile is not a simple average of similarly co-located SSH data from the same
ground 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 about
1km wide, precise cross-track projection and/or interpolation schemes are required to avoid errors.
• The mesoscale variability error (which is <3.5 cm for MP between 3 to 5 years and <1cm for WL
of 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a priori
knowledge from Sea Level maps derived from previous iterations or from other missions.
• Moreover, the inter-annual variabilty error (<5cm for WL>5000km and <5-8cm for WL of 200500km) is accounted for by using the MSS computed over 1993-1999 (e.g. the GFO MP is computed
on 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions).
• Finally, for these Mean Profiles, the latest standards and a maximum of data were used in order to increase as much as possible the quality of their estimation (see tables 6 and 7: Corrections and models
applied in SSALTO/DUACS Delayed-Time products). Note that a particular care was brought to the
processing near coasts.
Use of a MSS
The repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April
1994 to March 1995) or for Envisat since november 2010, and for Cryosat-2 mission (c2) because the
satellite is not in a repetitive orbit phase. The alternative is to use the MSS instead. 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 MSS which are hard to quantify
separately:
• To ensure a global MSS coherency between all data sets, the gridding process averages all sensorspecific errors and especially geographically correlated ones.
• The gridding process has to perform some smoothing to make up for signals which cannot be resolved
away 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 absorption
in the MSS and the impossibility to compute mean sea surface height content.
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III.3.6.2. Cross validation
After the repeat track analysis, the cross-validation technique is used as the ultimate screening process of
isolated and slightly erroneous measurements. Small SLA flows are compared to previous and independent
SLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal.
III.3.6.3. Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter. As data
are filtered from small scales, a sub-sampling is finally applied. Along-track SLA are then produced.
Note that the filtering and sub-sampling is adapted to each region and product as a function of the characteristics of the area and of the assimilation needs.
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III.3.7. Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature 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 control on each processing step is indispensable to appreciate the overall quality of the system and to provide the best user services.
III.3.7.1. Final quality Control
The Quality Control is the final process used by DUACS before product delivery. In addition to daily
automated controls and warnings to the operators, each production delivers a large QC Report composed of
detailed logs, figures and statistics of each processing step. Altimetry experts analyse these reports twice a
week.
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SEALEVEL_*_SLA_L3_OBSERVATIONS_008_00*
IV. M YO CEAN P RODUCTS
IV.1. Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter missions in near-real time (i.e. within a few days at most), 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-track products
Products are as follows:
Along-track products, global and regional (Mediterranean and Black Seas , Arctic Ocean and Europe
areas):
• Sea Level Anomaly (NRT-SLA) for each mission, with NRT-SLA ephemeris
IV.1.1. Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for alongtrack products . Those products are delivered every day.
IV.1.2. Temporal availibility
The following table presents the available products by mission and by data period:
Near real time products:
NRT
Jason-2
Temporal Time availability
y/m∗
ongoing
NRT-SLA
X
Jason-1 and Jason-1
geodetic
y/m∗ -2012/03/03 for
repeat track and
2012/05/07-ongoing for
geodetic track
X
Envisat new
Cryosat-2
y/m∗
2012/04/08
2012/01/01
ongoing
X
X
∗ y/m:
the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time products. When DT products are updated (3 to 4 times per year), the oldest NRT products are replaced by the
better quality DT products so that the 2 series are overlapping on few weeks or few months.
IV.2. Delayed Time Products
The Delayed Time component of SSALTO/DUACS system is responsible for the production of processed
Cryosat-2, Jason-1, Jason-2, T/P, Envisat, GFO, ERS1/2 and even Geosat data in order to provide a homogeneous, inter-calibrated and highly accurate long time series of SLA .
DT products are more precise than NRT products. Two reasons explain this quality difference. The first
one is the better intrinsic quality of the POE orbit used in the GDR processing. The second reason is that
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in the DT DUACS processing, the products can be computed optimally with a centred computation time
window for OER, LWE . On the contrary in NRT case, "future" data are not available so 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 correct altimeter data, improved methods for orbit error reduction and mapping.
Along-Track products, global and regional (Mediterranean and Black Seas):
• Sea Level Anomaly (DT-SLA) for each mission,
IV.2.1. Delay of the products
Weekly products are delivered. The availability of the products in delayed time is at the best two months
after the date of the measurement. The product generation needs all the GDR data of all the missions to take
into account the best corrections as possible. The time delay can be longer in the case of a missing mission.
IV.2.2. Temporal availibility
The following table presents the available products by mission and by data period:
Delayed time SSALTO/DUACS products:
Temporal availibility
DT-SLA
begin date
end date
Cryosat-2
2012/04
y/m∗
X
Jason-2
2008/10
y/m∗
X
??
y/m∗
X
Jason-1 new∗∗
2009/02
2012/03
X
Jason-1
2002/04
2008/10
X
GFO
2000/01
2008/09
X
Envisat new∗∗
2010/10
2012/08
X
Envisat
2002/10
2010/10
X
ERS-1/ERS-2∗∗
1992/10
2003/04
X
Topex new∗∗
2002/09
2005/10
X
Topex
1992/09
2002/04
X
Jason-1 geodetic∗∗
∗
y/m: those dates are updated regularly (3 to 4 times per year) and are avalaible when you download the
data at http://www.myocean.eu/web/24-catalogue.php
∗∗
Jason-1 geodetic orbit: starting ???, 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).
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V. D ESCRIPTION OF THE PRODUCT SPECIFICATION
V.1. General information
Product Specification
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage
global
Variables
latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time
Yes
Reanalysis
Yes
Available time series
see sections IV.2.2. for RAN and IV.1.2. for NRT
Temporal resolution
Daily for NRT and weekly for RAN
Target delivery time
3-4 months for RAN and up to 10 times a day for NRT
Delivery mechanism
MyOcean Information System
Horizontal resolution
20-50km for filtered, 7km for unfiltered
Number of vertical levels
1
Format
Netcdf CF1.0
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage
5.5˚W-35˚E ; 30˚N-46˚N
Variables
latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time
Yes
Reanalysis
Yes
Available time series
see sections IV.2.2. for RAN and IV.1.2. for NRT
Temporal resolution
Daily for NRT and weekly for RAN
Target delivery time
3-4 months for RAN and daily for NRT
Delivery mechanism
MyOcean Information System
Horizontal resolution
14km for filtered, 7km for unfiltered
Number of vertical levels
1
Format
Netcdf CF1.0
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage
27˚E-42˚E ; 40˚N-47˚N
Variables
latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time
Yes
Reanalysis
Yes
Available time series
see sections IV.2.2. for RAN and IV.1.2. for NRT
Temporal resolution
Daily for NRT and weekly for RAN
Target delivery time
3-4 months for RAN and daily for NRT
Delivery mechanism
MyOcean Information System
Horizontal resolution
7km
Number of vertical levels
1
Format
Netcdf CF1.0
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage
25˚W-42˚E ; 21˚N-66˚N
Variables
latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time
Yes
Reanalysis
Yes
Available time series
see sections IV.2.2. for RAN and IV.1.2. for NRT
Temporal resolution
Daily for NRT
Target delivery time
daily for NRT
Delivery mechanism
MyOcean Information System
Horizontal resolution
7km
Number of vertical levels
1
Format
Netcdf CF1.0
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage
0˚W-360˚E ; 50˚N-82˚N
Variables
latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time
Yes
Reanalysis
Yes
Available time series
see sections IV.2.2. for RAN and IV.1.2. for NRT
Temporal resolution
Daily for NRT
Target delivery time
daily for NRT
Delivery mechanism
MyOcean Information System
Horizontal resolution
14km
Number of vertical levels
1
Format
Netcdf CF1.0
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI. N OMENCLATURE OF FILES
VI.1. Nomenclature of files downloaded through the MyOcean Web Portal
Directgetfile Service
VI.1.1. Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by:
SEALEVEL_<REGION>_SLA_L3_<DELAY>_OBSERVATIONS_008_<ZONE>_<LETTER>
where:
REGION
DELAY
ZONE
GLO
global geographic coverage product
BS
Black Sea products
MED
Mediterranean products
ARC
Arctic products (for NRT products)
EUROPE
Europe products (for NRT products)
NRT
near real time products
RAN
delayed time or reanalysis products
001
number on 3 digits
002
003
004
LETTER
a
letter on 1 digit
b
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VI.1.2. Nomenclature of the datasets
The nomenclature used is:
dataset-duacs-<delay>-<zone>-<mission>-<type of sla>-l3
where the fileds in "<>" are described below:
delay
zone
mission
type of sla
nrt
ran
global
medsea
blacksea
arctic
europe
e1
e2
tp
tpn
g2
j1
j1n
j1g
j2
en
enn
c2
sla
sla_unfiltered
near-real time products
delayed time products
global geographic coverage product
Mediterranean products
Black Sea products
Arctic products (only for nrt)
Europe products (only for nrt)
ERS-1 (only for ran)
ERS-2 (only for ran)
TOPEX/Poseidon (only for ran)
TOPEX/Poseidon on its new orbit (only for
ran)
GFO (only for ran)
Jason-1 (only for ran)
Jason-1 on its new orbit
Jason-1 on its geodetic orbit
Jason-2
Envisat (only for ran)
Envisat on its new orbit
Cryosat-2
filtered sla
non filtered sla (only for ran products)
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VI.1.3. Nomenclature of the NetCdf files
The nomenclature used is:
<delay>_<zone>_<mission>_sla_<variable>_<datebegin>_<dateend>_<dateprod>.<format> where the fileds in "<>"
are described below:
delay
nrt
dt
global
med
mfstep
blacksea
arctic
europe
e1
e2
tp
tpn
g2
j1
j1n
j1g
j2
en
enn
c2
vfec
vxxc
near-real time products
delayed time products
zone
global geographic coverage product
Mediterranean products (for dt)
Mediterranean products (for nrt)
Black Sea products
Arctic products (only for nrt)
Europe products (only for nrt)
mission
ERS-1
ERS-2
TOPEX/Poseidon
TOPEX/Poseidon on its new orbit
GFO
Jason-1
Jason-1 on its new orbit
Jason-1 on its geodetic orbit
Jason-2
Envisat
Envisat on its new orbit
Cryosat-2
variable
filtered and sub-sampled sla
non filtered and non sub-sampled sla (only
for dt)
datebegin
YYYYMMDD(*)
beginning date of the dataset
dateend
YYYYMMDD(*)
end date of the dataset
dateprod
YYYYMMDD
production date of the dataset
format
.nc.gz
compressed NetCdf CF1.0
(*) For dt data: as the dates in the file names are rounded, the user wanting data for date T has to read the files
containing dates T+1 and T-1 in their name and check inside the files if there are some data for date T.
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VII. DATA FORMAT
This chapter presents the data storage format used for MyOcean products.
VII.1. NetCdf
The products are stored using the NetCDF format. NetCDF (network Common Data Form) is an interface for arrayoriented data access and a library that provides an implementation of the interface. The netCDF library also defines
a machine-independent format for representing scientific data. Together, the interface, library, and format support the
creation, access, and sharing of scientific data. The netCDF software was developed at the Unidata Program Center in
Boulder, Colorado. The netCDF libraries define a machine-independent format for representing scientific data. Please
see 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 different 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 all
the preceding data.
• Appendable. Data can be appended to a netCDF dataset along one dimension without copying the dataset or
redefining its structure. The structure of a netCDF dataset can be changed, though this sometimes causes the
dataset to be copied.
• Sharable. One writer and multiple readers may simultaneously access the same netCDF file.
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VII.2. Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative Ocean/Atmosphere
Research Data Service (COARDS) and Climate and Forecast (CF) metadata conventions. The CF convention generalises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifies
methods for reducing the size of datasets.
A wide range of software are 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.
• 8 variables are defined:
– short SLA : contains the Sea Level Anomaly values for each time given,
– int longitude : contains the longitude 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 mean_profile_point_index: index of the corrsponding point in the track of the mean profile
– byte flag : flag=0, the processed data comes from OGDR; if flag=1, the processed data comes from the
IGDR
– int latitude : contains the latitude for each measurement,
– 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:
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 {
dimensions:
time = 10385 ;
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:_FillValue = 2147483647 ;
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:_FillValue = 32767s ;
track:units = "1" ;
track:coordinates = "longitude latitude" ;
double time(time) ;
time:long_name = "Time of measurement" ;
time:_FillValue = 1.84467440737096e+19 ;
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:_FillValue = 2147483647 ;
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:flag_values = 1s, 0s ;
flag:flag_meanings = "igdr_like non_igdr_like" ;
flag:comment = "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) and
0 for Operational GDR (OGDR)." ;
short cycle(time) ;
cycle:long_name = "Cycle the measurement belongs to" ;
cycle:_FillValue = 32767s ;
cycle:units = "1" ;
cycle:coordinates = "longitude latitude" ;
// global attributes:
:history = "22-Feb-2011 15:52:43 CET : File created by the SSLATO/DUACS system version 10.0.1"
:comment = "Produce from ENVISAT Extension Phase satellite altimetry data" ;
:institution = "CLS/CNES" ;
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:references = "http://www.aviso.oceanobs.com/fileadmin/documents/data/tools/hdbk_duacs.pdf" ;
:source = "satellite altimetry" ;
:title = "along track Sea Level Anomaly" ;
:Conventions = "CF-1.4" ;
}
data:
SLA =
7, 7, 11, 10, -2, -22, -39, -41, -30, -13, -3, -5, -16, -26, -32, -35,
-35, -35, -37, -35, -31, -29, -31, -35, -32, -21, -10, -10, -19, -20, -1,
...
-69, -57, -49, -45, -39, -30, -28, -31, -27, -13, -2, -5, -15, -3, 11,
12, 3, -7, -10, -14, -15, -22, -31, -37, -32, -17, -10 ;
longitude =
74743328, 74868400, 74993968, 75120040, 75246616, 75373728,
75501368, 75629568, 75758320, 75887656, 76017568, 76148080, 76279208,
76388952, 76477056, 76565456, 76654144, 76743128, 76832400, 76921984,
...
329429568, 329535424, 329641792, 329748672, 329856096, 329964032,
330072512, 330181536, 330291072, 330401184 ;
track =
92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92,
92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92, 92,
...
113, 113, 113, 113, 113, 113, 113, 113, 113, 113, 113, 113, 113, 113,
113, 113, 113, 113, 113, 113, 113, 113, 113 ;
time =
22278.0000565705, 22278.0001314719, 22278.0002063733,
22278.0002812747, 22278.0003561761, 22278.0004310775, 22278.0005059788,
22278.0005808802, 22278.0006557816, 22278.000730683, 22278.0008055844,
22278.0008804858, 22278.0009553872, 22278.001017805, 22278.0010677393,
...
22278.8257112198, 22278.8257486705, 22278.8257861212, 22278.8258235719,
22278.8258610226, 22278.8258984733, 22278.8259359239, 22278.8259733746,
22278.8260108253, 22278.826048276 ;
mean_profile_point_index =
1872, 1878, 1884, 1890, 1896, 1902, 1908, 1914,
1920, 1926, 1932, 1938, 1944, 1949, 1953, 1957, 1961, 1965, 1969, 1973,
...
2306, 2309, 2312, 2315, 2318, 2321, 2327, 2330, 2333, 2336, 2339, 2342,
2345, 2348, 2351, 2354, 2357, 2360, 2363, 2366 ;
flag =
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
...
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ;
latitude =
-16225506, -16539731, -16853833, -17167810, -17481660, -17795380,
-18108966, -18422418, -18735729, -19048899, -19361924, -19674801,
-19987527, -20248015, -20456329, -20664569, -20872739, -21080837,
...
39481297, 39628277, 39775133, 39921866, 40068472, 40214953, 40361308,
40507533, 40653629, 40799592, 40945423, 41091120, 41236684, 41382111 ;
cycle =
331, 331, 331, 331, 331, 331, 331, 331, 331, 331, 331, 331, 331,
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...
331, 331, 331, 331, 331, 331, 331, 331, 331, 331, 331, 331, 331, 331,
331, 331, 331, 331, 331, 331, 331, 331, 331, 331, 331, 331 ;
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VIII. H OW TO DOWNLOAD A PRODUCT
VIII.1. Download a product through the MyOcean Web Portal Directgetfile
Service
You first need to register. Please find below the registration steps:
http://www.myocean.eu/web/34-products-and-services-faq.php#1
Once registered, the MyOcean FAQ http://www.myocean.eu/web/34-products-and-services-faq
will guide you on How to download a product through the MyOcean Web Portal Directgetfile Service.
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IX. N EWS AND U PDATES
IX.1. [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACS
processing system, see the [Duacs] operational news on the Aviso website:
http://www.aviso.oceanobs.com/en/data/operational-news/index.html.
IX.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. The
main 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
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