Sinking flux of particulate organic matter in the oceans: Sensitivity to particle characteristics

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Omand, M. M., Govindarajan, R., He, J., & Mahadevan, A. Sinking flux of particulate organic matter in the oceans: Sensitivity to particle characteristics. Scientific Reports, 10(1), (2020): 5582, doi:10.1038/s41598-020-60424-5.The sinking of organic particles produced in the upper sunlit layers of the ocean forms an important limb of the oceanic biological pump, which impacts the sequestration of carbon and resupply of nutrients in the mesopelagic ocean. Particles raining out from the upper ocean undergo remineralization by bacteria colonized on their surface and interior, leading to an attenuation in the sinking flux of organic matter with depth. Here, we formulate a mechanistic model for the depth-dependent, sinking, particulate mass flux constituted by a range of sinking, remineralizing particles. Like previous studies, we find that the model does not achieve the characteristic ‘Martin curve’ flux profile with a single type of particle, but instead requires a distribution of particle sizes and/or properties. We consider various functional forms of remineralization appropriate for solid/compact particles, and aggregates with an anoxic or oxic interior. We explore the sensitivity of the shape of the flux vs. depth profile to the choice of remineralization function, relative particle density, particle size distribution, and water column density stratification, and find that neither a power-law nor exponential function provides a definitively superior fit to the modeled profiles. The profiles are also sensitive to the time history of the particle source. Varying surface particle size distribution (via the slope of the particle number spectrum) over 3 days to represent a transient phytoplankton bloom results in transient subsurface maxima or pulses in the sinking mass flux. This work contributes to a growing body of mechanistic export flux models that offer scope to incorporate underlying dynamical and biological processes into global carbon cycle models.We thank NSF (OCE 1260080), NASA (NNX16AR48G), and the Ministry of Earth Sciences, Government of India (Monsoon Mission Project on the Bay of Bengal) for support. This work was largely done in 2012 while MMO was a postdoctoral associate at WHOI, during a visit by RG supported by The Mary Sears visiting scholar program to the Woods Hole Oceanographic Institution. Thanks also to Benjamin Hodges for many thoughtful contributions

Large-scale alignment of oceanic nitrate and density

Author Posting. © American Geophysical Union, 2013. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 118 (2013): 5322–5332, doi:10.1002/jgrc.20379.By analyzing global data, we find that over large scales, surfaces of constant nitrate are often better aligned with isopycnals than with isobars, particularly below the euphotic zone. This is unexplained by the movement of isopycnal surfaces in response to eddies and internal waves, and is perhaps surprising given that the biological processes that alter nitrate distributions are largely depth dependent. We provide a theoretical framework for understanding the orientation of isonitrate surfaces in relation to isopycnals. In our model, the nitrate distribution results from the balance between depth-dependent biological processes (nitrate uptake and remineralization), and the along-isopycnal homogenization of properties by eddy fluxes (parameterized by eddy diffusivity). Where the along-isopycnal eddy diffusivity is relatively large, nitrate surfaces are better aligned with isopycnals than isobars. We test our theory by estimating the strength of the eddy diffusivity and biological export production from global satellite data sets and comparing their contributions. Indeed, we find that below the euphotic zone, the mean isonitrate surfaces are oriented along isopycnals where the isopycnal eddy diffusivity is large, and deviate where the biological export of organic matter is relatively strong. Comparison of nitrate data from profiling floats in different regions corroborates the hypothesis by showing variations in the nitrate-density relationship from one part of the ocean to another.We acknowledge the support of the National Science Foundation (Grant OCE-0928617) and NASA (Grant NNX- 08AL80G).2014-04-1

The shape of the oceanic nitracline

In most regions of the ocean, nitrate is depleted near the surface by phytoplankton consumption and increases with depth, exhibiting a strong vertical gradient in the pycnocline (here referred to as the nitracline). The vertical supply of nutrients to the surface euphotic zone is influenced by the vertical gradient (slope) of the nitracline and by the vertical separation (depth) of the nitracline from the sunlit surface layer. Hence it is important to understand the shape (slope and curvature) and depth of the oceanic nitracline. By using density coordinates to analyze nitrate profiles from autonomous Autonomous Profiling EXplorer floats with In-Situ Ultraviolet Spectrophotometers (APEX-ISUS) and ship-based platforms (World Ocean Atlas – WOA09; Hawaii Ocean Time-series – HOT; Bermuda Atlantic Time-series Study – BATS; and California Cooperative Oceanic Fisheries Investigations – CalCOFI), we are able to eliminate much of the spatial and temporal variability in the profiles and derive robust relationships between nitrate and density. This allows us to characterize the depth, slope and curvature of the nitracline in different regions of the world\u27s oceans. The analysis reveals distinguishing patterns in the nitracline between subtropical gyres, upwelling regions and subpolar gyres. We propose a one-dimensional, mechanistic model that relates the shape of the nitracline to the relative depths of the surface mixed layer and euphotic layer. Though heuristic, the model accounts for some of the seasonal patterns and regional differences in the nitrate–density relationships seen in the data

Towards Nebular Spectral Modeling of Magnetar-Powered Supernovae

Many energetic supernovae are thought to be powered by the rotational-energy of a highly-magnetized, rapidly-rotating neutron star. The emission from the associated luminous pulsar wind nebula (PWN) can photoionize the supernova ejecta, leading to a nebular spectrum of the ejecta with signatures possibly revealing the PWN. SN 2012au is hypothesized to be one such supernova. We investigate the impact of different ejecta and PWN parameters on the supernova nebular spectrum, and test if any photoionization models are consistent with SN 2012au. We study how constraints from the nebular phase can be linked into modelling of the diffusion phase and the radio emission of the magnetar. We present a suite of late-time (1-6y) spectral simulations of SN ejecta powered by an inner PWN. Over a large grid of 1-zone models, we study the behaviour of the SN physical state and line emission as PWN luminosity ($L_{\rm PWN}$), injection SED temperature ($T_{\rm PWN}$), ejecta mass ($M_{\rm ej}$), and composition (pure O or realistic) vary. We discuss the resulting emission in the context of the observed behaviour of SN 2012au, a strong candidate for a PWN-powered SN. The supernova nebular spectrum varies as $T_{\rm PWN}$ varies, as the ejecta become less ionized as $T_{\rm PWN}$ increases. Low ejecta mass models at high PWN power obtain runaway ionization for O I and, in extreme cases, also O II, causing a sharp decrease in their ion fraction over a small change in the parameter space. Certain models can reproduce the oxygen lines luminosities of SN 2012au reasonably well at individual epochs, but we find no model that fits over the whole time evolution; this is likely due to the simple model setup. Using our derived constraints from the nebular phase, we predict that the magnetar powering SN 2012au had an initial rotation period $\sim$ 15 ms, and should be a strong radio source (F > 100 mJy) for decades.Comment: 26 pages, 22 figures, submitted to A&A. Comments welcom

A Generalized Semi-Analytic Model for Magnetar-Driven Supernovae

Several types of energetic supernovae, such as superluminous supernovae (SLSNe) and broad-line Ic supernovae (Ic-BL SNe), could be powered by the spin-down of a rapidly rotating magnetar. Currently, most models used to infer the parameters for potential magnetar-driven supernovae make several unsuitable assumptions that likely bias the estimated parameters. In this work, we present a new model for magnetar-driven supernovae that relaxes several of these assumptions and an inference workflow that enables accurate estimation of parameters from lightcurves of magnetar-driven supernovae. In particular, in this model, we include the dynamical evolution of the ejecta, coupling it to the energy injected by the magnetar itself while also allowing for non-dipole spin down. We show that the model can reproduce SLSN and Ic-BL SN light curves consistent with the parameter space from computationally expensive numerical models. We also show the results of parameter inference on four well-known example supernovae, demonstrating the model's effectiveness at capturing the considerable diversity in magnetar-driven supernova lightcurves. The model fits each light curve well and recovers parameters broadly consistent with previous works. This model will allow us to explore the full diversity of magnetar-driven supernovae under one theoretical framework, more accurately characterize these supernovae from only photometric data, and make more accurate predictions of future multiwavelength emission to test the magnetar-driven scenario better.Comment: 16 pages, 12 pages including appendices. Submitted to MNRAS. Comments welcome. Model available in public code Redback: https://github.com/nikhil-sarin/redbac

ASIRI: An Ocean–Atmosphere Initiative for Bay of Bengal

Air–Sea Interactions in the Northern Indian Ocean (ASIRI) is an international research effort (2013–17) aimed at understanding and quantifying coupled atmosphere–ocean dynamics of the Bay of Bengal (BoB) with relevance to Indian Ocean monsoons. Working collaboratively, more than 20 research institutions are acquiring field observations coupled with operational and high-resolution models to address scientific issues that have stymied the monsoon predictability. ASIRI combines new and mature observational technologies to resolve submesoscale to regional-scale currents and hydrophysical fields. These data reveal BoB’s sharp frontal features, submesoscale variability, low-salinity lenses and filaments, and shallow mixed layers, with relatively weak turbulent mixing. Observed physical features include energetic high-frequency internal waves in the southern BoB, energetic mesoscale and submesoscale features including an intrathermocline eddy in the central BoB, and a high-resolution view of the exchange along the periphery of Sri Lanka, which includes the 100-km-wide East India Coastal Current (EICC) carrying low-salinity water out of the BoB and an adjacent, broad northward flow (∼300 km wide) that carries high-salinity water into BoB during the northeast monsoon. Atmospheric boundary layer (ABL) observations during the decaying phase of the Madden–Julian oscillation (MJO) permit the study of multiscale atmospheric processes associated with non-MJO phenomena and their impacts on the marine boundary layer. Underway analyses that integrate observations and numerical simulations shed light on how air–sea interactions control the ABL and upper-ocean processes

Environmental Scanning and Knowledge Representation for the Detection of Organised Crime Threats

ePOOLICE aims at developing an efficient and effective strategic early warning system that utilises environmental scanning for the early warning and detection of current, emergent and future organised crime threats. Central to this concept is the use of environmental scanning to detect ‘weak signals’ in the external environment to monitor and identify emergent and future threats prior to their materialization into tangible criminal activity. This paper gives a brief overview of the application of textual concept extraction and categorization, and the Semantic Web technologies Formal Concept Analysis and Conceptual Graphs as part of the systems technological architecture, describing their benefits in aiding effective early warning

Virtual Reality and Oceanography: Overview, Applications, and Perspective

With the ongoing, exponential increase in ocean data from autonomous platforms, satellites, models, and in particular, the growing field of quantitative imaging, there arises a need for scalable and cost-efficient visualization tools to interpret these large volumes of data. With the recent proliferation of consumer grade head-mounted displays, the emerging field of virtual reality (VR) has demonstrated its benefit in numerous disciplines, ranging from medicine to archeology. However, these benefits have not received as much attention in the ocean sciences. Here, we summarize some of the ways that virtual reality has been applied to this field. We highlight a few examples in which we (the authors) demonstrate the utility of VR as a tool for ocean scientists. For oceanic datasets that are well-suited for three-dimensional visualization, virtual reality has the potential to enhance the practice of ocean science