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

Seasonal wind and ocean thermal forcing influences on the generation of the Leeuwin Current and its eddies

A high-resolution, multi-level, primitive equation ocean model is used to examine the response of an idealized, flat-bottomed, eastern boundary oceanic regime on a beta-plane to constant ocean thermal and wind forcing by annual mean and seasonal mean climatologies. The focus of the study is the Leeuwin Current along the coastal region, from 20° S to 35° S, off Western Australia.http://archive.org/details/seasonalwindocea00baylThis project was funded by the National Science Foundation, 1800 G Street N. W. , Washington, DC 20550.Lieutenant Commander, United States NavyApproved for public release; distribution is unlimited

An Algorithm to Bias-Correct and Transform Arctic SMAP-Derived Skin Salinities into Bulk Surface Salinities

These are the data used to generate the figures for our Remote Sensing (2022) manuscrip

A Numerical Study of Wind- and Thermal-Forcing Effects on the Ocean Circulation off Western Australia

A high-resolution, multilevel, primitive equation model is initialized with climatological data to investigate the combined effects of wind and thermal forcing on the ocean circulation off Western Australia during the austral fall and winter, corresponding to the period of strongest flow for the anomalous Leeuwin Current. This process-oriented study builds on previous modeling studies, which have elucidated the role of thermal forcing in the generation of the Leeuwin Current and eddies, by including the additional effects of wind forcing for the eastern boundary current region off Western Australia. The ocean circulation is generated by the model using a combination of density forcing from the climatological Indian Ocean thermal structure, the influx of warm low-salinity waters from the North West (NW) Shelf, and the climatological wind stress. In the first experiment (case I), forcing by the Indian Ocean and wind stress are imposed, while in the second experiment (case 2), the additional effects of the North West (NW) Shelf waters are considered. In the absence of the NW Shelf waters (case I), geostrophic flow, driven by the Indian Ocean thermal gradient, dominates the wind forcing at the poleward end of the domain and establishes an equatorward undercurrent and a poleward surface current (the Leeuwin Current), which accelerates poleward into the prevailing wind. Wind-forcing effects are discernible only offshore at the equatorward end of the region. The inclusion of NW Shelf waters (case 2) completely dominates the wind forcing at the equatorward end of the model. The effects of the NW Shelf waters weaken away from the source region but they continue to augment the Indian Ocean forcing, resulting in a stronger flow along the entire coastal boundary. The ocean circulation also has significant mesoscale variability. In the first experiment, both the Indian Ocean thermal structure and wind forcing lead to the dominance of barotropic (horizontal shear) instability over baroclinic (vertical shear) instability. In the second ~xperiment, the NW Shelf waters add baroclinicity, which weakens poleward, to the Leeuwin Current and locally increase the barotropic instability near their source. Away from the source waters, where there is a mixed instability, the combined effect of the Indian Ocean thermal structure and wind forcing is stronger than the NW Shelf waters and leads to a dominance of barotropic over baroclinic instability. Several scales of eddies are found to be dominant. The forcing by the Indian Ocean and wind stress (case I ) leads to an eddy wavelength of -330 km. With the inclusion of the NW Shelf waters (case 2), the wavelengths associated with mesoscale variability are -150 and 330 km, consistent with observed. eddy length scales

Rossby wave–coastal Kelvin wave interaction. Part II: Formation of island circulation.

ABSTRACT The interaction of open and coastal oceans in a midlatitude ocean basin is investigated in light of Rossby and coastal Kelvin waves. The basinwide pressure adjustment to an initial Rossby wave packet is studied both analytically and numerically, with the focus on the low-frequency modulation of the resulting coastal Kelvin wave. It is shown that the incoming mass is redistributed by coastal Kelvin waves as well as eastern boundary planetary waves, while the incoming energy is lost mostly to short Rossby waves at the western boundary. The amplitude of the Kelvin wave is determined by two mass redistribution processes: a fast process due to the coastal Kelvin wave along the ocean boundary and a slow process due to the eastern boundary planetary wave in the interior ocean. The amplitude of the Kelvin wave is smaller than that of the incident planetary wave because the initial mass of the Rossby wave is spread to the entire basin. In a midlatitude ocean basin, the slow eastern boundary planetary wave is the dominant mass sink. The resulting coastal Kelvin wave peaks when the peak of the incident planetary wave arrives at the western boundary. The theory is also extended to an extratropical-tropical basin to shed light on the modulation effect of extratropical oceanic variability on the equatorial thermocline. In contrast to a midlatitude basin, the fast mass redistribution becomes the dominant process, which is now accomplished mainly by equatorial Rossby and Kelvin waves, rather than the coastal Kelvin wave. The coastal Kelvin wave and the modulation of the equatorial thermocline peak close to the time when the wave trail of the incident Rossby wave arrives at the western boundary. Finally, the theory is also applied to the wave interaction around an extratropical island

Adjusting Neural Network to a Particular Problem: Neural Network-Based Empirical Biological Model for Chlorophyll Concentration in the Upper Ocean

The versatility of the neural network (NN) technique allows it to be successfully applied in many fields of science and to a great variety of problems. For each problem or class of problems, a generic NN technique (e.g., multilayer perceptron (MLP)) usually requires some adjustments, which often are crucial for the development of a successful application. In this paper, we introduce a NN application that demonstrates the importance of such adjustments; moreover, in this case, the adjustments applied to a generic NN technique may be successfully used in many other NN applications. We introduce a NN technique, linking chlorophyll “a” (chl-a) variability—primarily driven by biological processes—with the physical processes of the upper ocean using a NN-based empirical biological model for chl-a. In this study, satellite-derived surface parameter fields, sea-surface temperature (SST) and sea-surface height (SSH), as well as gridded salinity and temperature profiles from 0 to 75m depth are employed as signatures of upper-ocean dynamics. Chlorophyll-a fields from NOAA’s operational Visible Imaging Infrared Radiometer Suite (VIIRS) are used, as well as Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a concentrations. Different methods of optimizing the NN technique are investigated. Results are assessed using the root-mean-square error (RMSE) metric and cross-correlations between observed ocean color (OC) fields and NN output. To reduce the impact of noise in the data and to obtain a stable computation of the NN Jacobian, an ensemble of NN with different weights is constructed. This study demonstrates that the NN technique provides an accurate, computationally cheap method to generate long (up to 10 years) time series of consistent chl-a concentration that are in good agreement with chl-a data observed by different satellite sensors during the relevant period. The presented NN demonstrates a very good ability to generalize in terms of both space and time. Consequently, the NN-based empirical biological model for chl-a can be used in oceanic models, coupled climate prediction systems, and data assimilation systems to dynamically consider biological processes in the upper ocean

16.6 ABSTRACT NOAA’s NESDIS SATELLITE OCEANOGRAPHY

Satellite oceanography within the National Oceanic and Atmospheric Administration (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS) focuses on observation retrieval and applications to address the NOAA missions of environmental assessment, prediction, and stewardship. The Satellite Oceanography Division encompasses three functional areas: satellite ocean sensors, ocean dynamics / data assimilation, and marine ecosystems / climate. The breadth of scientific investigation includes sea-surface temperature, sea-surface height, sea-surface roughness, ocean color, surface vector winds, sea ice, data assimilation, and operational oceanography

Implications of ocean color in the upper water thermal structure at NINO3.4 region: a sensitivity study for optical algorithms and ocean color variabilities

Chlorophyll a (Chl-a) has been the most commonly used biomass metric in biological oceanographic processes. Although limited to two-dimensional surfaces, remote-sensing tools have been successfully providing the most recent state of marine phytoplankton biomass to better understand bottom-up processes initiating daily marine material cycles. In this exercise, ocean color products with various time-scales, derived from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), were used to investigate how their bio-optical properties affect the upper-ocean thermal structure in a global ocean modeling framework. This study used a ¼-degree Hybrid Coordinate Ocean Model forced by hourly atmospheric fluxes from the Climate Forecast System Reanalysis at National Oceanic Atmospheric Administration. Three numerical experiments were prepared by combining two ocean color products – downwelling diffuse attenuation coefficients (KdPAR) and chlorophyll a (Chl-a) – and two shortwave radiant flux algorithms. These three runs are: (1) KparCLM, based on a 13-year long-term climatological KdPAR derived from SeaWiFS; (2) ChlaCLM, based on a 13-year long-term Chl-a derived from SeaWiFS; and (3) ChlaID, which uses the inter-annual time-series of monthly-mean SeaWiFS Chl-a product. The KparCLM experiment uses a Jerlov-like two-band scheme; whereas, both ChlaCLM and ChlaID use a two-band scheme that considers inherent (absorption (a) and backscattering (bb) coefficients) and apparent optical properties (downwelling attenuation coefficient (Kd) and solar zenith angle (θ, varying 0–60°)). It is found that algorithmic differences in optical parameterizations have a bigger impact on the simulated temperatures in the upper-100 m of the eastern equatorial Pacific, NINO3.4 region, than other parts of the ocean. Overall, the KdPAR-based approach estimated relatively low surface temperatures compared to those estimated from the chlorophyll-based method. In specific, this cold bias, pronounced in the upper 20–30 m, is speculated to be due to optical characteristics of the algorithm and KdPAR products, or due to nonlinear hydrodynamical processes involving displacement of mixed-layer depth. Comparisons between each experiment against Global Ocean Data Assimilation System (GODAS; Behringer and Xue 2004) analyses find that KparCLM-based simulations have lower mean differences and variabilities with higher cross-correlation coefficients compared to ChlaCLM- and ChlaID-based experiments