Application of Satellite Radar Altimeter Data to the Determination of Regional Tidal Constituents and the Mean Sea Surface

1981 ◽  
pp. 907-918 ◽  
Author(s):  
John M. Diamante ◽  
Tsun-Shi Nee
Keyword(s):  
Sea Surface ◽  
Altimeter Data ◽  
Radar Altimeter ◽  
Mean Sea Surface ◽  
The Mean ◽  
Satellite Radar ◽  
Tidal Constituents

scholarly journals MEAN SEA SURFACE (MSS) MODEL DETERMINATION FOR MALAYSIAN SEAS USING MULTI-MISSION SATELLITE ALTIMETER

2016 ◽  
Vol XLII-4/W1 ◽  
pp. 247-252
Author(s):  
N. A. Z. Yahaya ◽  
T. A. Musa ◽  
K. M. Omar ◽  
A. H. M. Din ◽  
A. H. Omar ◽  
...  
Keyword(s):  
Monsoon Season ◽  
Sea Surface ◽  
Dynamic Topography ◽  
Level Variation ◽  
Radar Altimeter ◽  
Satellite Altimeter ◽  
Sea Level Variation ◽  
Mission Satellite ◽  
Mean Sea Surface ◽  
Model Determination

The advancement of satellite altimeter technology has generated many evolutions to oceanographic and geophysical studies. A multi-mission satellite altimeter consists with TOPEX, Jason-1 and Jason-2, ERS-2, Envisat-1, CryoSat-2 and Saral are extracted in this study and has been processed using Radar Altimeter Database System (RADS) for the period of January 2005 to December 2015 to produce the sea surface height (hereinafter referred to SSH). The monthly climatology data from SSH is generated and averaged to understand the variation of SSH during monsoon season. Then, SSH data are required to determine the localised and new mean sea surface (MSS). The differences between Localised MSS and DTU13 MSS Global Model is plotted with root mean square error value is 2.217 metres. The localised MSS is important towards several applications for instance, as a reference for sea level variation, bathymetry prediction and derivation of mean dynamic topography.

scholarly journals Impact of Multiple Altimeter Data and Mean Dynamic Topography in a Global Analysis and Forecasting System

2019 ◽  
Vol 36 (7) ◽  
pp. 1255-1266 ◽  
Author(s):  
Mathieu Hamon ◽  
Eric Greiner ◽  
Pierre-Yves Le Traon ◽  
Elisabeth Remy
Keyword(s):  
Data Assimilation ◽  
Sea Surface ◽  
Global Ocean ◽  
Altimeter Data ◽  
Dynamic Topography ◽  
Mean Dynamic Topography ◽  
Ocean Data Assimilation ◽  
The Mean ◽  
Data Assimilation System ◽  
Assimilation System

AbstractSatellite altimetry is one of the main sources of information used to constrain global ocean analysis and forecasting systems. In addition to in situ vertical temperature and salinity profiles and sea surface temperature (SST) data, sea level anomalies (SLA) from multiple altimeters are assimilated through the knowledge of a surface reference, the mean dynamic topography (MDT). The quality of analyses and forecasts mainly depends on the availability of SLA observations and on the accuracy of the MDT. A series of observing system evaluations (OSEs) were conducted to assess the relative importance of the number of assimilated altimeters and the accuracy of the MDT in a Mercator Ocean global 1/4° ocean data assimilation system. Dedicated tools were used to quantify impacts on analyzed and forecast sea surface height and temperature/salinity in deeper layers. The study shows that a constellation of four altimeters associated with a precise MDT is required to adequately describe and predict upper-ocean circulation in a global 1/4° ocean data assimilation system. Compared to a one-altimeter configuration, a four-altimeter configuration reduces the mean forecast error by about 30%, but the reduction can reach more than 80% in western boundary current (WBC) regions. The use of the most recent MDT updates improves the accuracy of analyses and forecasts to the same extent as assimilating a fourth altimeter.

scholarly journals Geostatistical methods for mapping Antarctic ice surfaces at continental and regional scales

2000 ◽  
Vol 30 ◽  
pp. 76-82 ◽  
Author(s):  
Ute Christina Herzfeld ◽  
Ralf Stosius ◽  
Marcus Schneider
Keyword(s):  
Surface Elevation ◽  
Altimeter Data ◽  
Radar Altimeter ◽  
Sea Level Changes ◽  
Ice Streams ◽  
Geostatistical Methods ◽  
Ice Surface ◽  
Geophysical Study ◽  
Satellite Radar ◽  
The Antarctic

AbstractThe Antarctic ice sheet plays a major role in the global system and the large ice streams discharging into the circumpolar sea represent its gateways to the world’s oceans. Satellite radar-altimeter data provide an opportunity for mapping surface elevation at kilometer resolution with meter accuracy. Geostatistical methods have been developed to accomplish this. We distinguish two goals in mapping the Antarctic ice surface: (a) construction of a continent-wide atlas of maps and digital terrain models, and (b) calculation of maps and models suitable for the study of individual glaciers, ice streams and ice shelves. The atlases consist of accurate maps of ice-surface elevation compiled from Seasat, Geosat and ERS-1 altimeter data, covering all of Antarctica surveyed by Geosat (to 72.1° S) and by ERS-1 (to 81.5° S). With a 3 km grid they are the highest-resolution maps available today with continent-wide coverage. The resolution permits geophysical study and facilitates monitoring of changes in ice-surface elevation and changes in flux across the ice-ocean boundary, which is essential for monitoring sea-level changes.

scholarly journals Modeling the signature of a transponder in altimeter return data and determination of the reflection surface of the ice cap near the GRIP camp, Greenland

1998 ◽  
Vol 44 (148) ◽  
pp. 625-633
Author(s):  
G. Haardenog-Pedersen ◽  
K. Keller ◽  
C. C. Tscherning ◽  
N. Gundestrup
Keyword(s):  
Global Positioning System ◽  
Propagation Delay ◽  
Radar Altimeter ◽  
Reflection Point ◽  
Ice Cap ◽  
Global Positioning ◽  
Satellite Radar ◽  
The Difference ◽  
Satellite Radar Altimetry

AbstractUsing an active transponder with the ERS-I and ERS-2 radar altimeters, the distance to the satellite was measured at a location close to the GRIP site, Greenland, at an altitude of 3.2 km. The measurement was executed while the transponder was in the “ice-tracking mode”. It includes a bias due to the propagation delay. The location of the transponder was determined using the global positioning system.The transponder signal was modeled and the distance from the altimeter to the effective reflection point of the transponder was determined. Since the transponder was located within 1 km of the ground tracks, the measurement was corrected for this offset. A correction was also done for the surface slope, resulting in the distance (plus bias) to the closest sub-satellite point on the surface of the (compact) snow.The transponder signal was then removed from the radar altimeter waveform, enabling the determination of the distance (plus bias from the altimeter to the first reflective surface within the snow. The différence between this distance and that obtained using the transponder was < 2 m. This shows that the surface which gives rise to the first return of the reflection agrees with the surface of the (compact, dry) snow at this high-altitude location. This is an important result to be used when studying ice-cap topography using satellite radar altimetry.

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