Details

Autor(en) / Beteiligte

• Gravalon, Théo
• Seoane, Lucía
• Ramillien, Guillaume
• Darrozes, José
• Roblou, Laurent

Titel

Determination of weather-induced short-term sea level variations by GNSS reflectometry

Ist Teil von

• Remote sensing of environment, 2022-09, Vol.279, p.113090, Article 113090

Ort / Verlag

Elsevier Inc

Erscheinungsjahr

2022

Quelle

ScienceDirect

Beschreibungen/Notizen

• •Coastal sea level variations are extracted from GNSS reflectometry (GNSS-R).•Differences between GNSS-R and tide gauges observations are of the centimeter order.•GNSS-R tide-free sea level is compared to weather sea surface response models.•Observation of the weather impact on sea level with GNSS-R is site dependant. We propose to derive local sea level variations by using the Signal-to-Noise Ratio (SNR) of the GNSS reflected signals at four GNSS single antenna sites (ILDG, TAR0, FFT2, LYTT) located at different latitudes. For these sites representing various ocean conditions (waves, tides, storm surges, etc…), tides estimates by SNR are highly consistent to tide gauges records as highlighted by tidal harmonic analysis, with a Root-Sum-Square (RSS) ranging from few centimeter in micro-tidal environment to near a decimeter in macro-tidal environment. SNR non-tidal residuals (NTR) are compared to two modelled sea level responses to meteorological forcing, namely the analytical Local Inverse Barometer (LIB) model and the numerical Dynamic Atmospheric Correction (DAC). Both DAC and LIB models are coherent with this non-tidal SNR residual in a 2-days to 2-months time window with correlations reaching 0.7 and high coherences. Several noteworthy atmospheric events are observed in the time series of about one year. During intense events, SNR and models are highly correlated. According to the results obtained in this study, we conclude that the GNSS reflectometry technique is relevant to derive sea level variations at tidal periods but also for studying the behaviour of the sea surface in response to atmospheric forcing at short-term scales.