Modification of phytoplankton group diversity over submesoscale fronts

2021 ◽  
Author(s):  
Clément Haëck ◽  
Marina Levy ◽  
Laurent Bopp ◽  
Roy El Hourany
Keyword(s):  
Total Biomass ◽  
Phytoplankton Diversity ◽  
Total Phytoplankton ◽  
Frontal Dynamics ◽  
In Situ Observations ◽  
Underlying Mechanisms ◽  
Group Diversity ◽  
Reflectance Data ◽  
Phytoplankton Group

<p>Over large parts of the ocean, submesoscale fronts are known to enhance total phytoplankton abundance because they are the location of intense vertical transport of nutrients. Disparate in situ observations suggest that such frontal dynamics not only affects the total biomass of phytoplankton, but also significantly modifies its composition. Here we make use of a newly developed algorithm able to distinguish a set of phytoplankton-specific pigments to statistically explore the change in phytoplankton community composition over basin-wide regions. We use 15 years of SST and reflectance data from the MODIS sensor on the Aqua satellite, at 1km and daily resolutions and focus on the oligotrophic North Atlantic subtropical gyre and on the more productive gulf stream region. We locate submesoscale fronts by computing an index quantifying SST patchiness. Our results confirm that submesoscale fronts are collocated with elevated Chlorophyll-a concentration and show significant changes in phytoplankton composition. These results underline the influence of submesocale dynamics on phytoplankton diversity, and stress the need to better understand the underlying mechanisms.</p>

scholarly journals A Photometric Study of Regolith Intimate Mixing with Ice-Like Impurity

2021 ◽  
Author(s):  
Dwaipayan Deb ◽  
Pavan Chakraborty
Keyword(s):  
Solar System ◽  
Linear Trend ◽  
Geological Processes ◽  
Solar System Objects ◽  
Shadowing Effect ◽  
Mixing Proportion ◽  
In Situ Observations ◽  
End Members ◽  
Reflectance Data

Abstract Surfaces of solid solar system objects are covered by layers of particulate materials called regolith originated from their surface bedrock. They preserve important information about surface geological processes. Often regolith is composed of more than one type of particle in terms of composition, maturity, size, etc. Experiments and theoretical works are being carried out to constrain the result of mixing and extract the abundance of compositional end-members from regolith spectra. In this work we have studied, photometric light scattering from simulated surfaces made of two different materials – one is highly bright quartz particles ≈ 80µm and the other moderately bright sandstone particles ≈ 250µm. The samples were mixed with varying proportions and investigated at normal illumination conditions to avoid the shadowing effect. Said combinations may resemble ice mixed regolith on various solar system objects and therefore important for in situ observations. We find that the combinations show a linear trend in the corresponding reflectance data in terms of their mixing proportion and some interesting facts come out when compared to previous studies.

scholarly journals An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI)

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4285 ◽  
Author(s):  
Shubha Sathyendranath ◽  
Robert Brewin ◽  
Carsten Brockmann ◽  
Vanda Brotas ◽  
Ben Calton ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Marine Ecosystem ◽  
Ocean Colour ◽  
Remote Sensing Reflectance ◽  
Resolution Imaging ◽  
In Situ Observations ◽  
Climate Studies ◽  
Reflectance Data

Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel.

scholarly journals Investigating tool engagement in groundwood pulping: finite element modelling and in-situ observations at the microscale

Holzforschung ◽  
2020 ◽  
Vol 74 (5) ◽  
pp. 477-487 ◽  
Author(s):  
Jenny Carlsson ◽  
Magnus Heldin ◽  
Per Isaksson ◽  
Urban Wiklund
Keyword(s):  
Finite Element ◽  
Numerical Models ◽  
X Ray ◽  
Tool Geometries ◽  
Commercial Use ◽  
X Ray Computed ◽  
In Situ Observations ◽  
Underlying Mechanisms

AbstractWith industrial groundwood pulping processes relying on carefully designed grit surfaces being developed for commercial use, it is increasingly important to understand the mechanisms occurring in the contact between wood and tool. We present a methodology to experimentally and numerically analyse the effect of different tool geometries on the groundwood pulping defibration process. Using a combination of high-resolution experimental and numerical methods, including finite element (FE) models, digital volume correlation (DVC) of synchrotron radiation-based X-ray computed tomography (CT) of initial grinding and lab-scale grinding experiments, this paper aims to study such mechanisms. Three different asperity geometries were studied in FE simulations and in grinding of wood from Norway spruce. We found a good correlation between strains obtained from FE models and strains calculated using DVC from stacks of CT images of initial grinding. We also correlate the strains obtained from numerical models to the integrity of the separated fibres in lab-scale grinding experiments. In conclusion, we found that, by modifying the asperity geometries, it is, to some extent, possible to control the underlying mechanisms, enabling development of better tools in terms of efficiency, quality of the fibres and stability of the groundwood pulping process.

scholarly journals Altimetry-Based Diagnosis of Deep-Reaching Sub-Mesoscale Ocean Fronts

Fluids ◽  
2020 ◽  
Vol 5 (3) ◽  
pp. 145
Author(s):  
Lia Siegelman ◽  
Patrice Klein ◽  
Andrew F. Thompson ◽  
Hector S. Torres ◽  
Dimitris Menemenlis
Keyword(s):  
Finite Size ◽  
Elephant Seal ◽  
Ocean Fronts ◽  
Velocity Gradients ◽  
Lack Of Information ◽  
Frontal Dynamics ◽  
In Situ Observations ◽  
Circumpolar Current ◽  
The Antarctic

Recent studies demonstrate that energetic sub-mesoscale fronts (10–50 km width) extend in the ocean interior, driving large vertical velocities and associated fluxes. However, diagnosing the dynamics of these deep-reaching fronts from in situ observations remains challenging because of the lack of information on the 3-D structure of the horizontal velocity. Here, a realistic numerical simulation in the Antarctic Circumpolar Current (ACC) is used to study the dynamics of submesocale fronts in relation to velocity gradients, responsible for the formation of these fronts. Results highlight that the stirring properties of the flow at depth, which are related to the velocity gradients, can be inferred from finite-size Lyapunov exponent (FSLE) at the surface. Satellite altimetry observations of FSLE and velocity gradients are then used in combination with recent in situ observations collected by an elephant seal in the ACC to reconstruct frontal dynamics and their associated vertical velocities down to 500 m. The approach proposed here is well suited for the analysis of sub-mesoscale-resolving datasets and the design of future sub-mesoscale field campaigns.

In situ observations of electromigration induced void behavior

1995 ◽  
Vol 53 ◽  
pp. 244-245
Author(s):  
T. Marieb ◽  
J. C. Bravman ◽  
P. Flinn ◽  
D. Gardner ◽  
M. Madden
Keyword(s):  
Electron Microscopy ◽  
Void Nucleation ◽  
Plan View ◽  
Transmission Electron ◽  
Nucleation Sites ◽  
Microelectronics Industry ◽  
In Situ Observations ◽  
Backscatter Electron Detector ◽  
Voltage Scanning

Electromigration and stress voiding have been active areas of research in the microelectronics industry for many years. While accelerated testing of these phenomena has been performed for the last 25 years[1-2], only recently has the introduction of high voltage scanning electron microscopy (HVSEM) made possible in situ testing of realistic, passivated, full thickness samples at high resolution.With a combination of in situ HVSEM and post-testing transmission electron microscopy (TEM) , electromigration void nucleation sites in both normal polycrystalline and near-bamboo pure Al were investigated. The effect of the microstructure of the lines on the void motion was also studied.The HVSEM used was a slightly modified JEOL 1200 EX II scanning TEM with a backscatter electron detector placed above the sample[3]. To observe electromigration in situ the sample was heated and the line had current supplied to it to accelerate the voiding process. After testing lines were prepared for TEM by employing the plan-view wedge technique [6].

scholarly journals In situ observations of coral spawning and spawn slick at Lankayan Island, Sabah, Malaysia

2021 ◽  
Vol 51 (1) ◽  
Author(s):  
Sze Hoon Gan ◽  
Zarinah Waheed ◽  
Fung Chen Chung ◽  
Davies Austin Spiji ◽  
Leony Sikim ◽  
...  
Keyword(s):  
Coral Spawning ◽  
In Situ Observations

scholarly journals Snow Depth Fusion Based on Machine Learning Methods for the Northern Hemisphere

2021 ◽  
Vol 13 (7) ◽  
pp. 1250
Author(s):  
Yanxing Hu ◽  
Tao Che ◽  
Liyun Dai ◽  
Lin Xiao
Keyword(s):  
Machine Learning ◽  
Northern Hemisphere ◽  
Snow Depth ◽  
Learning Algorithm ◽  
Random Forest Regression ◽  
Machine Learning Methods ◽  
Long Time ◽  
In Situ Observations ◽  
Input Variables

In this study, a machine learning algorithm was introduced to fuse gridded snow depth datasets. The input variables of the machine learning method included geolocation (latitude and longitude), topographic data (elevation), gridded snow depth datasets and in situ observations. A total of 29,565 in situ observations were used to train and optimize the machine learning algorithm. A total of five gridded snow depth datasets—Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) snow depth, Global Snow Monitoring for Climate Research (GlobSnow) snow depth, Long time series of daily snow depth over the Northern Hemisphere (NHSD) snow depth, ERA-Interim snow depth and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) snow depth—were used as input variables. The first three snow depth datasets are retrieved from passive microwave brightness temperature or assimilation with in situ observations, while the last two are snow depth datasets obtained from meteorological reanalysis data with a land surface model and data assimilation system. Then, three machine learning methods, i.e., Artificial Neural Networks (ANN), Support Vector Regression (SVR), and Random Forest Regression (RFR), were used to produce a fused snow depth dataset from 2002 to 2004. The RFR model performed best and was thus used to produce a new snow depth product from the fusion of the five snow depth datasets and auxiliary data over the Northern Hemisphere from 2002 to 2011. The fused snow-depth product was verified at five well-known snow observation sites. The R2 of Sodankylä, Old Aspen, and Reynolds Mountains East were 0.88, 0.69, and 0.63, respectively. At the Swamp Angel Study Plot and Weissfluhjoch observation sites, which have an average snow depth exceeding 200 cm, the fused snow depth did not perform well. The spatial patterns of the average snow depth were analyzed seasonally, and the average snow depths of autumn, winter, and spring were 5.7, 25.8, and 21.5 cm, respectively. In the future, random forest regression will be used to produce a long time series of a fused snow depth dataset over the Northern Hemisphere or other specific regions.

scholarly journals Pelagic deep-sea fauna observed on video transects in the southern Norwegian Sea

Polar Biology ◽  
2021 ◽  
Author(s):  
Philipp Neitzel ◽  
Aino Hosia ◽  
Uwe Piatkowski ◽  
Henk-Jan Hoving
Keyword(s):  
First Record ◽  
Observation System ◽  
In Situ Observation ◽  
Norwegian Sea ◽  
Video Recordings ◽  
In Situ Observations ◽  
Abundance And Distribution ◽  
Oceanic Food Webs ◽  
Deep Sea Fauna

AbstractObservations of the diversity, distribution and abundance of pelagic fauna are absent for many ocean regions in the Atlantic, but baseline data are required to detect changes in communities as a result of climate change. Gelatinous fauna are increasingly recognized as vital players in oceanic food webs, but sampling these delicate organisms in nets is challenging. Underwater (in situ) observations have provided unprecedented insights into mesopelagic communities in particular for abundance and distribution of gelatinous fauna. In September 2018, we performed horizontal video transects (50–1200 m) using the pelagic in situ observation system during a research cruise in the southern Norwegian Sea. Annotation of the video recordings resulted in 12 abundant and 7 rare taxa. Chaetognaths, the trachymedusaAglantha digitaleand appendicularians were the three most abundant taxa. The high numbers of fishes and crustaceans in the upper 100 m was likely the result of vertical migration. Gelatinous zooplankton included ctenophores (lobate ctenophores,Beroespp.,Euplokamissp., and an undescribed cydippid) as well as calycophoran and physonect siphonophores. We discuss the distributions of these fauna, some of which represent the first record for the Norwegian Sea.

In situ observations of isothermal cuspidine crystallization in molten mould fluxes with varying basicity

2020 ◽  
pp. 1-6
Author(s):  
Jiangling Li ◽  
Feifei Lai ◽  
Mei Leng ◽  
Qingcai Liu ◽  
Jian Yang ◽  
...  
Keyword(s):  
In Situ Observations
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