Ludivine Oruba

This study investigates the occurrence of surface elevation oscillations, known as seiches, at the atoll scale. We show that the innovative Ka‐band Radar Interferometer (KaRIn) onboard the Surface Water Ocean Topography (SWOT) satellite makes it possible to visualize seiche‐like structures within lagoons of French Polynesia. This ability to capture two‐dimensional sea surface undulations of low amplitude (on the order of a few centimeters) in relatively small water bodies (less than 80 km in length) is unprecedented in satellite altimetry, and opens new avenues of research into these events and their contribution to coastal erosion and flooding. Our study combines sea surface height observations from SWOT with in situ measurements conducted in the Raroia lagoon and theoretical calculations based on an eigenvalue model. These three complementary approaches—satellite remote sensing, in situ data, and theoretical modeling—allow us to investigate both the spatial and spectral properties of seiches in atoll islands.

The surface wave investigation and monitoring (SWIM) instrument, onboard China and France Oceanography Satellite (CFOSAT), is a Ku-band real-aperture radar, with six beams that illuminate the ocean surface at near-nadir incidences ranging from 0° to 10°. In this study, we investigate the effect of rain on the normalized radar cross section (NRCS) measured by SWIM under both tropical cyclone (TC) and non-TC conditions. Rain primarily attenuates the radar backscatter from the ocean surface. Under non-TC conditions, when wind speeds are below 21 m/s, the NRCS reduction is small (15 mm/h) conditions. The impact of rain generally decreases as wind speed increases, especially at the smallest incidence angle. At low wind speeds, the NRCS reduction is also sensitive to the incidence angle. Based on a simplified model and the differing sensitivities of NRCS to surface roughness at two near-nadir incidence angles, we find that rain also influences the surface signal at incidence angles below 10°, in addition to the dominant effect of atmospheric attenuation, which leads to a consistent NRCS reduction across all wind speeds and incidence angles. Specifically, it contributes positively to NRCS at wind speeds above 7 m/s and negatively at lower wind speeds. This behavior is attributed to increased surface roughness from splashes and ring waves at low wind speeds, and to decreased roughness due to wave damping at moderate and high wind speeds. In TC environments, the NRCS tends to saturate under light to moderate rain rates (15 mm/h) conditions, the NRCS continues to decrease as wind speed increases. In both TC and non-TC conditions, beyond atmospheric attenuation, the impact of rain on surface roughness must be considered to fully explain the observed NRCS variations with wind and rain rate.

We investigate the ocean wave field under Hurricane Sam (2021). Whilst measurements of waves under Tropical Cyclones are rare, an unusually large number of quality in situ and remote measurements are available in that case. First, we highlight the good consistency between the wave spectra provided by the Surface Waves Investigation and Monitoring (SWIM) instrument onboard the China‐France Oceanography SATellite, the in situ spectra measured by National Data Buoy Center buoys, and a saildrone. The impact of strong rains on SWIM spectra is then further investigated. We show that whereas the rain definitely affects the normalized radar cross section, both the innovative technology (beam rotating scanning geometry) and the post‐processing processes applied to retrieve the 2D wave spectra ensure a good quality of the resulting wave spectra, even in heavy rain conditions. On this basis, the satellite, airborne and in situ observations are confronted to the analytical model proposed by Kudryavtsev et al. (2015, https://doi.org/10.1002/2015JC011284). We show that an extended fetch mechanism may be invoked to explain the large significant wave height observed in the right front quadrant of Hurricane Sam.

This study examines 40 years of monthly precipitation data in Senegal (1979–2018) using Climatic Research Unit observations and ERA5 reanalyzes, aiming to understand the influence of oceanic and atmospheric factors on Senegal's precipitation in July, August and September (JAS). The variability of Senegal's precipitation is first compared with that of the broader Sahel region: although they share a significant portion of their variance, Senegal appears more closely related to the Northeastern Tropical Atlantic (NETA) Sea Surface Temperature (SST). A detailed examination of this region reveals that Senegal's increased precipitation is linked to the northward shift of the InterTropical Convergence Zone, consistent with numerous previous studies. Over the continent, this shift corresponds to a northward shift of the African Easterly Jet (AEJ) and, consequently, the mesoscale convective systems (MCSs) responsible for most precipitation. It seems primarily driven by the northward shift of the Heat Low. Over the ocean just west of Senegal, there is a comparable shift of the AEJ, accompanied by an increase in low‐level moisture transport convergence within the West African Westerly Jet (WAWJ) which explains the majority of the increase in JAS precipitation in Senegal. This phenomenon is triggered by a negative pressure anomaly in the NETA, located above a positive SST anomaly: we suggest that the latter is the origin of the former, forming a feedback mechanism that potentially significantly influences Senegal's precipitation. The mechanism involves a geostrophic adjustment of the WAWJ to the southern gradients of the SST anomaly.

This study examines 40 years of monthly precipitation data in Senegal (1979-2018) using CRU observations and ERA5 reanalyses, aiming to understand the influence of oceanic and atmospheric factors on Senegal’s precipitation in July, August and September (JAS). Comparing Senegal’s precipitation variability with the broader Sahel region, it emerges that Senegal’s precipitation is more closely associated with the Northeastern Tropical Atlantic (NETA) Sea Surface Temperature (SST). The increased Senegal’s precipitation is linked to the northward shift of the InterTropical Convergence Zone (ITCZ), consistent with numerous previous studies. Over the continent, this shift corresponds to a northward shift of the African Easterly Jet (AEJ) and, consequently, the Mesoscale Convective Systems responsible for most precipitation. It seems primarily driven by the northward shift of the Heat Low.Over the ocean west of Senegal, there is a comparable shift of the AEJ, accompanied by increased low-level moisture transport convergence within the West African Westerly Jet (WAWJ). This phenomenon is triggered by a negative pressure anomaly in the NETA, located above a positive SST anomaly: we suggest that the latter is the origin of the former, forming a feedback mechanism that potentially significantly influences Senegal’s precipitation. The mechanism involves a geostrophic adjustment of the WAWJ to the southern gradients of the SST anomaly. To validate the NETA SST feedback’s role in Senegal’s precipitation, further investigations using daily data or regional atmospheric models are recommended. The findings hold potential for enhancing seasonal forecasting capabilities.

This study focuses on ocean waves impacting the Moorea Island in French Polynesia, where coral reefs play an essential role in the biodiversity and protection of habitations. We investigate how the innovative Surface Waves Investigation and Monitoring (SWIM) instrument of the Chinese‐French Oceanography SATellite satellite enables to document on a multi‐annual basis, the spectral properties of ocean waves reaching the coasts of the Moorea Island. Our analysis is based on comparisons with in situ measurements (wave gauges deployed on the outer slope of the coral reef), and with other satellite observations (altimeter, Synthetic Aperture Radar [SAR]). Accounting for local masking effects, we show that SWIM provides relevant information on short swell or wind waves, which is missed by the SAR observations, in particular in high sea‐state conditions, owing to the dominant propagation direction being close to the azimuth. We, nevertheless, also find that wave properties in low sea‐state conditions are better documented by SAR than by SWIM. Such results are important to accurately measure and predict the wave conditions which fragilize the coral reefs and to evaluate the impact of extreme events on tropical islands and coral reefs.

In an earlier paper, Oruba et al. (J. Fluid Mech., vol. 818, 2017, pp. 205–240) considered the primary quasi-steady geostrophic (QG) motion of a constant density fluid of viscosity ) that faithfully capture their true character.

This article describes the first results obtained from the Surface Waves Investigation and Monitoring (SWIM) instrument carried by the China France Oceanography Satellite (CFOSAT), which was launched on October 29, 2018. SWIM is a Ku-band radar with a near-nadir scanning beam geometry. It was designed to measure the spectral properties of surface ocean waves. First, the good behavior of the instrument is illustrated. It is then shown that the nadir products (significant wave height, normalized radar cross section, and wind speed) exhibit an accuracy similar to standard altimeter missions, thanks to a new retracking algorithm, which compensates a lower sampling rate compared to standard altimetry missions. The off-nadir beam observations are analyzed in detail. The normalized radar cross section varies with incidence and wind speed as expected from previous studies presented in the literature. We illustrate that, in order to retrieve the wave spectra from the radar backscattering fluctuations, it is crucial to apply a speckle correction derived from the observations. Directional spectra of ocean waves and their mean parameters are then compared to wave model data at the global scale and to in situ data from a selection of case studies. The good efficiency of SWIM to provide the spectral properties of ocean waves in the wavelength range [70-500 m] is illustrated. The main limitations are discussed, and the perspectives to improve the data quality are presented.