GLOBAL HIGH RESOLUTION MEAN SEA SURFACE BASED ON
ERS-l 35· AND 168- DAY CYCLES AND TOPEX DATA
Michael Anzenhofer, Thomas Gruber, Matthias Rentsch
GeoForschungsZentrum Potsdam, Div. 1
D.PAF, D-82230 OberpfatTenhofen, Germany
INTRODUCTION
At GFZJD-PAF ERS altimeter data is used to systematically generate geophysical
products. ERS fast delivery records are upgraded to QLOPR by means of a precise time
correlation, GFZJD-P AF preliminary orbit, new tidal model, actual meteorological data
and up to date ionospheric model. QLOPR can be accessed within 2 weeks from the time
of observation by FTP. As well as ERS processing, data from all other missions is
gathered and converted to a common data format.
The paper is focused on the generation of a combined global mean sea surface height
model (MSS95A) with a 3' grid resolution. Based on the experience of a 3' model with
ERS-l 's first 168 day cycle, a combination of ERS-l 35 day repeat data, TOPEX cycles
and both ERS-l 168 day cycles (the second was shifted 8 km) is performed resulting in
a data distribution pattern never before seen. A 3' spatial grid resolution indicates the
along-track quality as well as cross-track features. MSS95A is fixed to an ERS-l mean
sea surface, that is based on two years of ERS-l 35 day repeat data. Operational
GFZJD-PAF procedures are used to ensure a high level of quality.
MSS95A will help to improve the ocean geoid and to understand the dynamics of the
ocean.
The present paper begins with a description of the input data. The second part is
dedicated to the processing steps required in order to produce MSS95A focusing mainly
on the accumulation of data from different missions. The third part deals with product
quality and specifications.
DATA
MSS95A is generated from three different data sources. Firstly, one full year of the
precise ERS-l 35-day repeat cycle data (ERS-1.ALT.OPR2) is taken. Secondly, both 168day cycles of ERS-l QLOPR are merged. The shift of precise ERS-l data to the slightly
worse QLOPR was due to the time delay of precise data reception (6 months). TOPEX
GDR were taken as the third data source to maximize the spatial data distribution.
208
ERS-l 35· AND 168- DAY CYCLES AND TOPEX DATA
Michael Anzenhofer, Thomas Gruber, Matthias Rentsch
GeoForschungsZentrum Potsdam, Div. 1
D.PAF, D-82230 OberpfatTenhofen, Germany
INTRODUCTION
At GFZJD-PAF ERS altimeter data is used to systematically generate geophysical
products. ERS fast delivery records are upgraded to QLOPR by means of a precise time
correlation, GFZJD-P AF preliminary orbit, new tidal model, actual meteorological data
and up to date ionospheric model. QLOPR can be accessed within 2 weeks from the time
of observation by FTP. As well as ERS processing, data from all other missions is
gathered and converted to a common data format.
The paper is focused on the generation of a combined global mean sea surface height
model (MSS95A) with a 3' grid resolution. Based on the experience of a 3' model with
ERS-l 's first 168 day cycle, a combination of ERS-l 35 day repeat data, TOPEX cycles
and both ERS-l 168 day cycles (the second was shifted 8 km) is performed resulting in
a data distribution pattern never before seen. A 3' spatial grid resolution indicates the
along-track quality as well as cross-track features. MSS95A is fixed to an ERS-l mean
sea surface, that is based on two years of ERS-l 35 day repeat data. Operational
GFZJD-PAF procedures are used to ensure a high level of quality.
MSS95A will help to improve the ocean geoid and to understand the dynamics of the
ocean.
The present paper begins with a description of the input data. The second part is
dedicated to the processing steps required in order to produce MSS95A focusing mainly
on the accumulation of data from different missions. The third part deals with product
quality and specifications.
DATA
MSS95A is generated from three different data sources. Firstly, one full year of the
precise ERS-l 35-day repeat cycle data (ERS-1.ALT.OPR2) is taken. Secondly, both 168day cycles of ERS-l QLOPR are merged. The shift of precise ERS-l data to the slightly
worse QLOPR was due to the time delay of precise data reception (6 months). TOPEX
GDR were taken as the third data source to maximize the spatial data distribution.
208