The groupy wave model for simulating dynamical sea surface

International audience— Simulated radar observations of the sea surface dynamics as used in the MODENA project, are based on an original methodology for sea states : the " groupy " wave model (GWM). Random wave fields can have very different modulations but nearly identical spectra. Nevertheless, the response of a floating object to waves depends strongly on the likelihood of large wave encounters. Sea surface fluxes also depend on wave breaking and air-flow separation, both being consequences of large-amplitude events. So wave group structure is one key description to simulate radar clutter under various environmental and instrumental configurations. The GWM builds on random distributions of wave groups and conditionally distributed breaking waves over these groups. Each wave group travels across the simulated area, and breaking waves appear dynamically on the wave crest at the rear of a group, propagating and disappearing at the front of this group. The generation of sea states follows a prescribed sea wave directional spectrum, and any breaking wave statistical distribution such as Λ(c)d c describing the total length of breaker per unit area and time with phase speed between c and c + d c. Accordingly, the group density per surface unit can lead to very different sea state structures, and the results will be discussed

On the use of rigorous microwave interaction models to support remote sensing of natural surfaces

A study has been undertaken which objective is to contribute to the investigation of the validity of microwave surface scattering models used in remote sensing applications, particularly when applied to realistic representations of natural surfaces. These investigations are based on recent implementations of rigorous methods (MoM and FDTD) and cover a wide range of configurations of observation (mono- and bi-static). Both land (bare soils) and sea surfaces are being investigated

Climate change initiative+ (CCI+) phase 1 sea surface salinity: Product validation and intercomparison report (PVIR)

The purpose of this document (D4.1 Product Validation and Intercomparison Report, PVIR, document version v3.0) is to describe the results of the validation of the Sea Surface Salinity (SSS) products obtained during the ESA CCI+ SSS project when compared with other data sources. The PVIR is a requirement of the Statement of Work (Task 3 SoW ref. ESA-CCI-PRGM-EOPS-SW-17- 0032). The PVIR contains a list of all reference datasets used for validation of each SSS product. This report contains an assessment of both the level 4 and level 3 (ascending, descending and combined ascending plus descending) products for weekly and monthly time periods. The products are based on a temporal optimal interpolation of SSS data measured by SMOS, Aquarius-SAC and SMAP satellite missions. All products are gridded on an equal area EASE-2 grid with a grid resolution of ~25 km

The Emissivity Of Foam-Covered Water Surface At L-Band: Theoretical Modeling And Experimental Results From The FROG 2003 Field Experiment

Sea surface salinity can be measured by microwave radiometry at L-band (1400-1427 MHz). This frequency is a compromise between sensitivity to the salinity, small atmospheric perturbation, and reasonable pixel resolution. The description of the ocean emission depends on two main factors: (1) the sea water permittivity, which is a function of salinity, temperature, and frequency, and (2) the sea surface state, which depends on the wind-induced wave spectrum, swell, and rain-induced roughness spectrum, and by the foam coverage and its emissivity. This study presents a simplified two-layer emission model for foam-covered water and the results of a controlled experiment to measure the foam emissivity as a function of salinity, foam thickness, incidence angle, and polarization. Experimental results are presented, and then compared to the two-layer foam emission model with the measured foam parameters used as input model parameters. At 37 psu salt water the foam-induced emissivity increase is /spl sim/0.007 per millimeter of foam thickness (extrapolated to nadir), increasing with increasing incidence angles at vertical polarization, and decreasing with increasing incidence angles at horizontal polarization.Peer Reviewe

Satellite and in situ sampling mismatches: Consequences for the estimation of satellite sea surface salinity uncertainties

Validation of satellite sea surface salinity (SSS) products is typically based on comparisons with in-situ measurements at a few meters’ depth, which are mostly done at a single location and time. The difference in term of spatio-temporal resolution between the in-situ near-surface salinity and the two-dimensional satellite SSS results in a sampling mismatch uncertainty. The Climate Change Initiative (CCI) project has merged SSS from three satellite missions. Using an optimal interpolation, weekly and monthly SSS and their uncertainties are estimated at a 50 km spatial resolution over the global ocean. Over the 2016–2018 period, the mean uncertainty on weekly CCI SSS is 0.13, whereas the standard deviation of weekly CCI minus in-situ Argo salinities is 0.24. Using SSS from a high-resolution model reanalysis, we estimate the expected uncertainty due to the CCI versus Argo sampling mismatch. Most of the largest spatial variability of the satellite minus Argo salinity is observed in regions with large estimated sampling mismatch. A quantitative validation is performed by considering the statistical distribution of the CCI minus Argo salinity normalized by the sampling and retrieval uncertainties. This quantity should follow a Gaussian distribution with a standard deviation of 1, if all uncertainty contributions are properly taken into account. We find that (1) the observed differences between Argo and CCI data in dynamical regions (river plumes, fronts) are mainly due to the sampling mismatch; (2) overall, the uncertainties are well estimated in CCI version 3, much improved compared to CCI version 2. There are a few dynamical regions where discrepancies remain and where the satellite SSS, their associated uncertainties and the sampling mismatch estimates should be further validated

Satellite Salinity Observing System: Recent Discoveries and the Way Forward

Advances in L-band microwave satellite radiometry in the past decade, pioneered by ESA’s SMOS and NASA’s Aquarius and SMAP missions, have demonstrated an unprecedented capability to observe global sea surface salinity (SSS) from space. Measurements from these missions are the only means to probe the very-near surface salinity (top cm), providing a unique monitoring capability for the interfacial exchanges of water between the atmosphere and the upper-ocean, and delivering a wealth of information on various salinity processes in the ocean, linkages with the climate and water cycle, including land-sea connections, and providing constraints for ocean prediction models. The satellite SSS data are complimentary to the existing in situ systems such as Argo that provide accurate depiction of large-scale salinity variability in the open ocean but under-sample mesoscale variability, coastal oceans and marginal seas, and energetic regions such as boundary currents and fronts. In particular, salinity remote sensing has proven valuable to systematically monitor the open oceans as well as coastal regions up to approximately 40 km from the coasts. This is critical to addressing societally relevant topics, such as land-sea linkages, coastal-open ocean exchanges, research in the carbon cycle, near-surface mixing, and air-sea exchange of gas and mass. In this paper, we provide a community perspective on the major achievements of satellite SSS for the aforementioned topics, the unique capability of satellite salinity observing system and its complementarity with other platforms, uncertainty characteristics of satellite SSS, and measurement versus sampling errors in relation to in situ salinity measurements. We also discuss the need for technological innovations to improve the accuracy, resolution, and coverage of satellite SSS, and the way forward to both continue and enhance salinity remote sensing as part of the integrated Earth Observing System in order to address societal needs

Satellite remote sensing of surface winds, waves, and currents: Where are we now?

This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind- and wave- induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields

STAT-1 decoy oligodeoxynucleotide inhibition of acute rejection in mouse heart transplants

During acute rejection of cardiac transplants endothelial cell–leukocyte interaction fuelled by co-stimulatory molecules like CD40/CD154 may ultimately lead to graft loss. One key player in up-regulating the expression of such pro-inflammatory gene products is the interferon-γ-dependent transcription factor STAT-1. Hence down-regulating interferon-γ-stimulated pro-inflammatory gene expression in the graft endothelial cells by employing a decoy oligodeoxynucleotide (dODN) neutralising STAT-1 may protect the graft. To verify this hypothesis, heterotopic mouse heart transplantation was performed in the allogeneic B10.A(2R) to C57BL/6 and syngeneic C57BL/6 to C57BL/6 strain combination without immunosuppression. Graft vessels were pre-treated with STAT-1 dODN, mutant control ODN (10 μM each) or vehicle (Ringer solution). Cellular rejection (vascular and interstitial component) was graded histologically and CD40, ICAM-1, VCAM-1, MCP-1, E-selectin and RANTES expression in the graft monitored by real time PCR 24 h and 9 days post-transplantation. Nine days after transplantation both rejection scores were significantly diminished by 85 and 70%, respectively, in STAT-1 dODN-treated allografts as compared to mutant control ODN-treated allografts. According to immunohistochemistry analysis, this was accompanied by a reduced infiltration of monocyte/macrophages and T cells into the graft myocardium. In addition, pro-inflammatory gene expression was strongly impaired by more than 80% in STAT-1 dODN-treated allografts 24 h post-transplantation but not in mutant control ODN or vehicle-treated allografts. This inhibitory effect on pro-inflammatory gene expression was no longer detectable 9 days post-transplantation. Single periprocedural treatment with a STAT-1 dODN thus effectively reduces cellular rejection in mouse heart allografts. This effect is associated both with an early decline in pro-inflammatory gene expression and a later drop in mononuclear cell infiltration

Interprétation et modélisation de mesures à distance de la surface marine dans le domaine micro onde

Cette thèse présente une étude générale sur l'utilisation et l'interprétation de mesures à distance de la surface océaniques dans le domaine micro-onde dans le but de caractériser les effets de la rugosité de surface sur l émissivité. Une revue synthétique des théories électromagnétiques de diffusion/émission par/de la surface marine est proposée. Les liens théoriques entre les mesures à distance actives et passives sont rappelés et discutés. Basé sur l'analyse des modèles électromagnétiques et de différents jeux de données actives et passives, un modèle semi-empirique de la variation d'émissivité en fonction de la rugosité de la surface a été développé. Celui-ci caractérise de manière empirique les changements d émissivité en fonction du coefficient de réflexion de Fresnel et de deux paramètres statistiques de la surface. Sur la base de cette paramétrisation, une méthodologie est proposée pour quantifier les impacts de la rugosité de la surface océanique sur la température de brillance observée dans les nouvelles données du satellite SMOS.This dissertation presents a general investigation on the use and interpretation of remote sensing measurements of the sea surface at microwave frequencies and specifically aims at better characterizing sea surface roughness effects on emissivity. A review of the state of the art of the scattering and emission theories of the sea surface at microwave frequencies is first proposed. Theorical links between active and passive remote sensing measurements are recalled and discused. Based on electromagnetic models and several active/passive data set analysis, a consistent semi-empirical model of the mutl-incidence angle emissivity change associated with the surface roughness variation is developed. The latter characterizes emissivity changes in terms of Fresnel Reflection coefficient and two rough sea surface statistical parameters. Based on this parameterization, a methodology is proposed to quantify the impacts of ocean surface roughness on the brightness temperature observed in the new mutli-angular data from SMOS.VERSAILLES-BU Sciences et IUT (786462101) / SudocSudocFranceF