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Stephanie Guinehut

Researcher at IFREMER

Publications -  47
Citations -  3199

Stephanie Guinehut is an academic researcher from IFREMER. The author has contributed to research in topics: Argo & Altimeter. The author has an hindex of 26, co-authored 47 publications receiving 2700 citations.

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New CNES‐CLS09 global mean dynamic topography computed from the combination of GRACE data, altimetry, and in situ measurements

TL;DR: In this article, a new global 1/4° resolution mean dynamic topography (MDT) was computed for the 1993-1999 time period with improved data and methodology compared to the previous RIO05 MDT field.
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Sea level budget over 2003-2008: A reevaluation from GRACE space gravimetry, satellite altimetry and Argo

TL;DR: In this paper, the authors used space gravimetry observations from GRACE to estimate the mass of the oceans and showed that recent years sea level rise can be mostly explained by an increase of the mass, which represents roughly 80% of the altimetry-based rate of sea level rises over that period.
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A new assessment of the error budget of global mean sea level rate estimated by satellite altimetry over 1993–2008

TL;DR: In this paper, a new error budget assessment of the global Mean Sea Level (MSL) determined by TOPEX/Poseidon and Jason-1 altimeter satellites between January 1993 and June 2008 is presented using last altimeter standards.
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High Resolution 3-D temperature and salinity fields derived from in situ and satellite observations

TL;DR: In this paper, an observation-based approach that efficiently combines the main components of the global ocean observing system using statistical methods is described, where accurate but sparse in situ temperature and salinity profiles (mainly from Argo for the last 10 yr) are merged with the lower accuracy but high-resolution synthetic data derived from satellite altimeter and sea surface temperature observations to provide global 3-D temperature and Salinity fields at high temporal and spatial resolution.
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The Ocean Reanalyses Intercomparison Project (ORA-IP)

TL;DR: In this article, a multi-reanalysis ensemble is used to estimate the signal-to-noise ratio (SNR) of the ocean state and to estimate uncertainty levels.