No Arabic abstract
During the Eddy Experiment, two synchronous GPS receivers were flown at 1 km altitude to collect L1 signals and their reflections from the sea surface for assessment of altimetric precision and accuracy. Wind speed (U10) was around 10 m/s, and SWH up to 2 m. A geophysical parametric waveform model was used for retracking and estimation of the lapse between the direct and reflected signals with a 1-second precision of 3 m. The lapse was used to estimate the SSH along the track using a differential model. The RMS error of the 20 km averaged GNSS-R absolute altimetric solution with respect to Jason-1 SSH and a GPS buoy measurement was of 10 cm, with a 2 cm mean difference. Multipath and retracking parameter sensitivity due to the low altitude are suspected to have degraded accuracy. This result provides an important milestone on the road to a GNSS-R mesoscale altimetry space mission.
We report on the retrieval of directional sea surface roughness, in terms of its full directional mean square slope (including direction and isotropy), from Global Navigation Satellite System Reflections (GNSS-R) Delay-Doppler-Map (DDM) data collected during an experimental flight at 1 km altitude. This study emphasizes the utilization of the entire DDM to more precisely infer ocean roughness directional parameters. In particular, we argue that the DDM exhibits the impact of both roughness and scatterer velocity. Obtained estimates are analyzed and compared to co-located Jason-1 measurements, ECMWF numerical weather model outputs and optical data.
In this paper we focus on the microwave bistatic scattering process, with the aim of deriving an expression for the interferometric complex field auto-correlation function from a static platform. We start from the Fresnel integral and derive the auto-correlation function in the Fraunhofer and Modified Fraunhofer regime. The autocorrelation function at short times can be expressed as a Gaussian with a direction dependent time scale. The directional modulation is a function of the angle between the scattering direction and the wave direction. The obtained relation can be used for directional sea state estimation using one or more GNSS-R coastal receivers.
The mesoscale eddy field plays a key role in the mixing and transport of physical and biological properties and redistribute energy budgets in the ocean. Eddy kinetic energy is commonly defined as the kinetic energy of the time-varying component of the velocity field. However, this definition contains all processes that vary in time, including coherent mesoscale eddies, jets, waves, and large-scale motions. The focus of this paper is on the eddy kinetic energy contained in coherent mesoscale eddies. We present a new method to decompose eddy kinetic energy into oceanic processes. The proposed method uses a new eddy-identification algorithm (TrackEddy). This algorithm is based on the premise that the sea level signature of a coherent eddy can be approximated as a Gaussian feature. The eddy Gaussian signature then allows for the calculation of kinetic energy of the eddy field through the geostrophic approximation. TrackEddy has been validated using synthetic sea surface height data, and then used to investigate trends of eddy kinetic energy in the Southern Ocean using Satellite Sea Surface Height anomaly (AVISO+). We detect an increasing trend of eddy kinetic energy associated with mesoscale eddies in the Southern Ocean. This trend is correlated with an increase of the coherent eddy amplitude and the strengthening of wind stress over the last two decades.
We address the feasibility of a GNSS-R code-altimetry space mission and more specifically a dominant term of its error budget: the reflected-signal range precision. This is the RMS error on the reflected-signal delay, as estimated by waveform retracking. So far, the approach proposed by [Lowe et al., 2002] has been the state of the art to theoretically evaluate this precision, although known to rely on strong assumptions (e.g., no speckle noise). In this paper, we perform a critical review of this model and propose an improvement based on the Cramer-Rao Bound (CRB) approach. We derive closed-form expressions for both the direct and reflected signals. The performance predicted by CRB analysis is about four times worse for typical space mission scenarios. The impact of this result is discussed in the context of two classes of GNSS-R applications: mesoscale oceanography and tsunami detection.
Eddy saturation is the regime in which the total time-mean volume transport of an oceanic current is relatively insensitive to the wind stress forcing and is often invoked as a dynamical description of Southern Ocean circulation. We revisit the problem of eddy saturation using a primitive-equations model in an idealized channel setup with bathymetry. We apply only mechanical wind stress forcing; there is no diapycnal mixing or surface buoyancy forcing. Our main aim is to assess the relative importance of two mechanisms for producing eddy saturated states: (i) the commonly invoked baroclinic mechanism that involves the competition of sloping isopycnals and restratification by production of baroclinic eddies, and (ii) the barotropic mechanism, that involves production of eddies through lateral shear instabilities or through the interaction of the barotropic current with bathymetric features. Our results suggest that the barotropic flow-component plays a crucial role in determining the total volume transport.