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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Andersen, Ole Baltazar
in Cooperation with on an Cooperation-Score of 37%
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Publications (5/5 displayed)
- 2018Mean Sea Level and Mean Dynamic Topography Determination From Cryosat-2 Data Around Australia
- 2018A New DTU18 MSS Mean Sea Surface – Improvement from SAR Altimetry
- 2016Improved oceanographic measurements fom SAR altimetry: Results and scientific roadmap from ESA cryosat plus for oceans project
- 2016Improved oceanographic measurements with cryosat sar altimetry: Application to the coastal zone and arctic
- 2016Deriving the DTU15 Global high resolution marine gravity field from satellite altimetry
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document
Mean Sea Level and Mean Dynamic Topography Determination From Cryosat-2 Data Around Australia
Abstract
Determination of Mean Sea Surface (MSS) is of a great importance in some geodesy and oceanographic applications and a couple of centimeters would change the calculated parameter significantly. The dense spatial coverage of Cryosat-2 data offers the opportunity of investigating the Sea Level Anomaly (SLA) over ocean in higher resolution from a single mission data. In other words, although multi mission data sets may have a considerable spatial density, the variation in data set qualities from different missions make the processing difficult, particularly in crossovers. Despite the fact that the main aim of Cryosat-2 mission is monitoring the thickness of ice sheets, it is also used over oceans for different purposes. To study the contribution of the Cryosat-2 data around Australia, 6 years data set of this mission are used. As the SSH values are too large in magnitude and any small variations would not be appeared clearly inthe analysis, to investigate the changes, SLA based on DTUMSS13 model is analysed as the main parameter. The strong striping effects, particularly in Gulf Carpentaria and South East, characterizes a substantial part of the map. This, in fact, implies presence of a strong periodic signal in the SLA data. The main reason behind the strong striping in the Gulf Carpentaria is related to presence of annual signal. To solve this issue, the annual signal should be extracted from the SLA data so that all of them refer to the same epoch of the year. The determined<br/>annual signal amplitude from Topex/Posseidon and follow-on missions are interpolated into the Cryosat-2 data points. The subtraction of constructed annual signal from the SLA of Cryosat-2 data reduce the striping effect substantially though a slight averaging is required to eliminate it completely. The final product represents a smooth mean SLA. The mean SLA is then added to DTUMSS13 to provide us with the MSS model of Cryosat- 2 data. This MSS model is used to calculate the mean dynamic topography around Australia.