Hundreds of Volcanic Explosions Detected Underwater at Kīlauea

Hundreds of volcanic explosions detected underwater at KīlaueaThe explosions, identified during the 2018 eruption phase, offer a clear acoustic signal that researchers could use to measure ocean properties.

Simultaneous Aerosol and Ocean Properties From the PolCube CubeSat Polarimeter

We quantify the performance of aerosol and ocean remote sensing products from the PolCube instrument using a previously developed polarimeter retrieval algorithm based on optimal estimation. PolCube is a modified version of the PolCam lunar instrument on the Korea Pathfinder Lunar Orbiter that has been optimized for Earth-Science observations of aerosol, ocean, and thin cloud optical properties. The objective of the PolCube instrument is to retrieve detailed fine-mode (pollution and smoke) and coarse-mode (sea-salt and dust) aerosol properties over the ocean for a range of light to heavy aerosol loadings using its polarimetric-imaging capability at multiple angles and wavelengths from 410−865 nm. An additional objective is to discriminate aerosols from thin clouds. PolCube’s retrieval performance of aerosol optical and microphysical properties and ocean products is quantitatively assessed. We estimate that PolCube can retrieve total aerosol optical depth at 555 nm (AOD555) within ±0.068, fine-mode AOD555 within ±0.078, and fine-mode single-scattering albedo within ±0.036, where all uncertainties are expressed as one standard deviation (1σ). PolCube’s accurate and high-resolution aerosol-retrieval products will provide unique spatial and temporal coverage of the Earth that can be used synergistically with other instruments, such as the Geostationary Environmental Monitoring Spectrometer to improve air-quality forecasting.

Combining Argo and Satellite Data Using Model-Derived Covariances: Blue Maps

Blue Maps aims to exploit the versatility of an ensemble data assimilation system to deliver gridded estimates of ocean temperature, salinity, and sea-level with the accuracy of an observation-based product. Weekly maps of ocean properties are produced on a 1/10°, near-global grid by combining Argo profiles and satellite observations using ensemble optimal interpolation (EnOI). EnOI is traditionally applied to ocean models for ocean forecasting or reanalysis, and usually uses an ensemble comprised of anomalies for only one spatiotemporal scale (e.g., mesoscale). Here, we implement EnOI using an ensemble that includes anomalies for multiple space- and time-scales: mesoscale, intraseasonal, seasonal, and interannual. The system produces high-quality analyses that produce mis-fits to observations that compare well to other observation-based products and ocean reanalyses. The accuracy of Blue Maps analyses is assessed by comparing background fields and analyses to observations, before and after each analysis is calculated. Blue Maps produces analyses of sea-level with accuracy of about 4 cm; and analyses of upper-ocean (deep) temperature and salinity with accuracy of about 0.45 (0.15) degrees and 0.1 (0.015) practical salinity units, respectively. We show that the system benefits from a diversity of ensemble members with multiple scales, with different types of ensemble members weighted accordingly in different dynamical regions.

Similarities and Contrasts in Stationary Striations of Surface Tracers in Pacific Eastern Boundary Upwelling Systems

Eastern boundary upwelling systems feature strong zonal gradients of physical and biological ocean properties between cool, productive coastal oceans and warm, oligotrophic subtropical gyres. Zonal currents and jets (striations) are therefore likely to contribute to the transport of water properties between coastal and open oceanic regions. Multi-sensor satellite data are used to characterize the signatures of striations in sea surface temperature (SST), salinity (SSS), and chlorophyll-a (Chl-a) in subtropical eastern North/South Pacific (ENP/ESP) upwelling systems. In the ENP, tracers exhibit striated patterns extending up to ~2500 km offshore. Striations in SST and SSS are highly correlated with quasi-zonal jets, suggesting that these jets contribute to SST/SSS mesoscale patterns via zonal advection. Chl-a striations are collocated with sea surface height (SSH) bands, a possible result of mesoscale eddy trains trapping nutrients and forming striated signals. In the ESP, striations are only found in SST and coincide with SSH bands, consistently with quasi-zonal jets located outside major zonal tracer gradients. An interplay between large-scale SST/SSS advection by the quasi-zonal jets, mesoscale SST/SSS advection by the large-scale meridional flow and eddy advection may explain the persistent ENP hydrographic striations. These results underline the importance of quasi-zonal jets for surface tracer structuring at the mesoscale.

Simulating detailed spatial patterns of ice shelf basal melt

<p>The contact between ice shelves and relatively warm ocean waters causes basal melt, ice shelf thinning, and ultimately ice sheet mass loss. This basal melt, and its dependence on ocean properties, is poorly understood due to an overall lack of direct observations and a difficulty in explicit simulation of the circulation in sub-shelf cavities. In this study, we compare a number of parameterisations and models of increasing complexity, up to a 2D ‘Layer’ model. Each model is aimed at quantifying basal melt rates as a function of offshore temperature and salinity. We test these models in an idealised setting (ISOMIP+) and in a realistic setting for the Amundsen Sea Embayment. All models show a comparable non-linear sensitivity of ice-shelf average basal melt to ocean warming, indicating a positive feedback between melt and circulation. However, the Layer model is the only one which explicitly resolves the flow direction of the buoyant melt plumes, which is primarily governed by rotation and by the basal topography of the ice shelves. At 500m resolution, this model simulates locally enhanced basal melt near the grounding line, in topographical channels, and near the western boundary. The simulated melt patterns for the Amundsen Sea ice shelves are compared to satellite observations of ice shelf thinning and to 3D numerical simulations of the sub-shelf cavity circulation. As detailed melt rates near the grounding line are essential for the stability of ice sheets, spatially realistic melt rates are crucial for future projections of ice sheet dynamics. We conclude that the Layer model can function as a relatively cheap yet realistic model to downscale 3D ocean simulations of ocean properties to sub-kilometer scale basal melt fields to provide detailed forcing fields to ice sheet models.</p>

Deep neural networks for active wave breaking classification

Wave breaking is an important process for energy dissipation in the open ocean and coastal seas. It drives beach morphodynamics, controls air-sea interactions, determines when ship and offshore structure operations can occur safely, and influences on the retrieval of ocean properties from satellites. Still, wave breaking lacks a proper physical understanding mainly due to scarce observational field data. Consequently, new methods and data are required to improve our current understanding of this process. In this paper we present a novel machine learning method to detect active wave breaking, that is, waves that are actively generating visible bubble entrainment in video imagery data. The present method is based on classical machine learning and deep learning techniques and is made freely available to the community alongside this publication. The results indicate that our best performing model had a balanced classification accuracy score of $$\approx$$ ≈ 90% when classifying active wave breaking in the test dataset. An example of a direct application of the method includes a statistical description of geometrical and kinematic properties of breaking waves. We expect that the present method and the associated dataset will be crucial for future research related to wave breaking in several areas of research, which include but are not limited to: improving operational forecast models, developing risk assessment and coastal management tools, and refining the retrieval of remotely sensed ocean properties.

Advances in the Monitoring of Algal Blooms by Remote Sensing: A Bibliometric Analysis

Since remote sensing of ocean colour began in 1978, several ocean-colour sensors have been launched to measure ocean properties. These measures have been applied to study water quality, and they specifically can be used to study algal blooms. Blooms are a natural phenomenon that, due to anthropogenic activities, appear to have increased in frequency, intensity, and geographic distribution. This paper aims to provide a systematic analysis of research on remote sensing of algal blooms during 1999–2019 via bibliometric technique. This study aims to reveal the limitations of current studies to analyse climatic variability effect. A total of 1292 peer-reviewed articles published between January 1999 and December 2019 were collected. We read all the literature individually to build a database. The number of publications increased since 2004 and reached the maximum value of 128 in 2014. The publications originated from 47 countries, but the number of papers published from the top 10 countries accounted for 77% of the total publications. To be able to distinguish between climate variability and changes of anthropogenic origin for a specific variable is necessary to define the baseline. However, long-term monitoring programs of phytoplankton are very scarce; only 1% of the articles included in this study analysed at least three decades and most of the existing algal blooms studies are based on sporadic sampling and short-term research programs.

Induced magnetic moments for near-spherical oceans: New methods for constraining ocean shape

<p>Magnetic induction has proven to be a powerful tool in the exploration and characterization of structure in planetary subsurfaces. This is especially true in the case of Europa, where perhaps the best evidence for an extant subsurface ocean comes from identification of magnetic moments that vary with time. Past investigations, however, have been limited by available techniques for calculating induced magnetic fields based on a supposed internal structure, an important prerequisite to the determination of ocean properties by way of magnetic exploration. Critically, existing techniques permit only a spherically symmetric interior structure. In this work, we expand the ice−ocean boundary in terms of spherical harmonics and derive changes to the induced magnetic moments for a given boundary shape. We also demonstrate the application of this technique to Europa for the purpose of constraining the shape of its conducting ocean.</p>