scholarly journals Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery

2021 ◽  
Vol 13 (16) ◽  
pp. 3057
Author(s):  
Aline de M. Valerio ◽  
Milton Kampel ◽  
Vincent Vantrepotte ◽  
Nicholas D. Ward ◽  
Jeffrey E. Richey
Keyword(s):  
Particulate Matter ◽  
Optical Characterization ◽  
Amazon River ◽  
Optical Parameters ◽  
Index Method ◽  
Optical Index ◽  
In Situ Data ◽  
Relative Contribution ◽  
Spm Concentration

Optical water types (OWTs) were identified from an in situ dataset of concomitant biogeochemical and optical parameters acquired in the Amazon River and its tributaries, in the Lower Amazon region, at different hydrological conditions from 2014 to 2017. A seasonal bio-optical characterization was performed. The k-means classification was applied to the in situ normalized reflectance spectra (rn(λ)), allowing the identification of four OWTs. An optical index method was also applied to the rn(λ) defining the thresholds of the OWTs. Next, level-3 Sentinel-3 Ocean and Land Color Instrument images representative of the seasonal discharge conditions were classified using the identified in situ OWTs as reference. The differences between Amazon River and clearwater tributary OWTs were dependent on the hydrological dynamics of the Amazon River, also showing a strong seasonal variability. Each OWT was associated with a specific bio-optical and biogeochemical environment assessed from the corresponding absorption coefficient values of colored dissolved organic matter (aCDOM) and particulate matter (ap), chlorophyll-a and suspended particulate matter (SPM) concentrations, and aCDOM/ap ratio. The rising water season presented a unique OWT with high SPM concentration and high relative contribution of ap to total absorption compared to the other OWTs. This bio-optical characterization of Lower Amazon River waters represents a first step for developing remote sensing inversion models adjusted to the optical complexity of this region.

scholarly journals An Algorithm to Estimate Suspended Particulate Matter Concentrations and Associated Uncertainties from Remote Sensing Reflectance in Coastal Environments

2020 ◽  
Vol 12 (13) ◽  
pp. 2172 ◽  
Author(s):  
Juliana Tavora ◽  
Emmanuel Boss ◽  
David Doxaran ◽  
Paul Hill
Keyword(s):  
Remote Sensing ◽  
Optical Properties ◽  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Ocean Color ◽  
Major Constituent ◽  
Coastal Environments ◽  
Suspended Particulate ◽  
Spm Concentration

Suspended Particulate Matter (SPM) is a major constituent in coastal waters, involved in processes such as light attenuation, pollutant propagation, and waterways blockage. The spatial distribution of SPM is an indicator of deposition and erosion patterns in estuaries and coastal zones and a necessary input to estimate the material fluxes from the land through rivers to the sea. In-situ methods to estimate SPM provide limited spatial data in comparison to the coverage that can be obtained remotely. Ocean color remote sensing complements field measurements by providing estimates of the spatial distributions of surface SPM concentration in natural waters, with high spatial and temporal resolution. Existing methods to obtain SPM from remote sensing vary between purely empirical ones to those that are based on radiative transfer theory together with empirical inputs regarding the optical properties of SPM. Most algorithms use a single satellite band that is switched to other bands for different ranges of turbidity. The necessity to switch bands is due to the saturation of reflectance as SPM concentration increases. Here we propose a multi-band approach for SPM retrievals that also provides an estimate of uncertainty, where the latter is based on both uncertainties in reflectance and in the assumed optical properties of SPM. The approach proposed is general and can be applied to any ocean color sensor or in-situ radiometer system with red and near-infra-red bands. We apply it to six globally distributed in-situ datasets of spectral water reflectance and SPM measurements over a wide range of SPM concentrations collected in estuaries and coastal environments (the focus regions of our study). Results show good performance for SPM retrieval at all ranges of concentration. As with all algorithms, better performance may be achieved by constraining empirical assumptions to specific environments. To demonstrate the flexibility of the algorithm we apply it to a remote sensing scene from an environment with highly variable sediment concentrations.

Satellite-based observations of ground-level fine particulate matter and comparison to a regional air quality model

2020 ◽  
Author(s):  
Jana Handschuh ◽  
Frank Baier ◽  
Thilo Erbertseder ◽  
Martijn Schaap
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Air Pollutants ◽  
Fine Particulate Matter ◽  
Ground Level ◽  
In Situ Measurements ◽  
Satellite Observations ◽  
Optical Parameters ◽  
Fine Particulate

<p>Particulate matter and other air pollutants have become an increasing burden on the environment and human health. Especially in metropolitan and high-traffic areas, air quality is often remarkably reduced. For a better understanding of the air quality in specific areas, which is of great environment-political interest, data with high resolution in space and time is required. The combination of satellite observations and chemistry-transport-modelling has proven to give a good database for assessments and analyses of air pollution. In contrast to sample in-situ measurements, satellite observations provide area-wide coverage ​​of measurements and thus the possibility for an almost gapless mapping of actual air pollutants. For a high temporal resolution, chemistry-transport-models are needed, which calculate concentrations of specific pollutants in continuous time steps. Satellite observations can thus be used to improve model performances.</p><p>There are no direct satellite-measurements of fine particulate matter (PM2.5) but ground-level concentrations of PM2.5 can be derived from optical parameters such as aerosol optical depth (AOD). A wide range of methods for the determination of PM2.5 concentrations from AOD measurements has been developed so far, but it is still a big challenge. In this study a semi-empirical approach based on the physical relationships between meteorological and optical parameters was applied to determine a first-guess of ground-level PM2.5 concentrations for the year 2018 and the larger Germany region. Therefor AOD observations of MODIS (Moderate Resolution Imaging Spectroradiometer) aboard the NASA Aqua satellite were used in a spatial resolution of 3km. First results showed an overestimation of ground-level aerosols and quiet low correlations with in-situ station measurements from the European Environmental Agency (EEA). To improve the results, correction factors were calculated using the coefficients of linear regression between satellite-based and in-situ measured particulate matter concentrations. Spatial and seasonal dependencies were taken into account with it. Correlations between satellite and in-situ measurements could be improved applying this method.</p><p>The MODIS 3km AOD product was found to be a good base for area-wide calculations of ground-level PM2.5 concentrations. First comparisons to the calculated PM2.5 concentrations from chemistry-transport-model POLYPHEMUS/DLR showed significant differences though. Satellite observations will now be used to improve the general model performance, first by helping to find and understand regional and temporal dependencies in the differences. As part of the German project S-VELD funded by the Federal Ministry of Transport and Digital Infrastructure BMVI, it will help for example to adjust the derivation of particle emissions within the model.</p>

Hydrological variability and suspended particulate matter in the middle river Niger bassin

2021 ◽  
Author(s):  
Moussa Boubacar Moussa ◽  
Amadou Abdourhamane Touré ◽  
Bruno Lartiges ◽  
Emma Rochelle Newall ◽  
Laurent Kergoat ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Rainy Season ◽  
Radiometric Measurements ◽  
Suspended Particulate ◽  
Major Mode ◽  
Niger River ◽  
Spm Concentration ◽  
Very High

<p>In the Sahel, climate variability and high population growth have led to changes in surface conditions that resulted in increased runoff coefficients and discharge in the major Sahelian rivers. The mid reaches of the Niger river have experienced significant increases in the Red flood, or local flood, that occurs during the rainy season between June and September, relative to Black flood, or Guinean flood that arrives in Niamey from December onwards.<br>The objective of this work was to characterize suspended particulate matter (SPM) during the Red and Black floods in the Niamey area and analyse their spatio-temporal dynamics. Two approaches are used : the first one consists of regular in-situ measurements of SPM concentration and in their physical and mineral characterization by electron microscopy; the second is based on monitoring water color by both in-situ and satellite (Sentinel 2) radiometric measurements.<br>SPM are characterized by very fine particles (with a major mode around 0.1-0.2 micrometers) mainly composed by kaolinites (iron oxides are also observed during the Red flood). This, combined with the very high levels of SPM concentration reached during the rainy season, results in very high values of reflectance in the visible end infrared bands. Radiometric measurements in the nir band by both the in-situ SKYE sensor and the Sentinel2 sensor are found to be significantly correlated to in-situ SPM, allowing efficient monitoring of SPM concentration in time and space.<br>SPM-discharge curves, reveal a complex relationship : SPM increases very rapidly at the beginning of the rainy season when soils are washed out after the long dry period, reaching a peak before the first discharge peak (Red flood). SPM continues to decrease during the second discharge peak (Black flood) from December to February, providing a distinct and unique signature. Analysis of satellite data allowed identifying the main sources of SPM and to quantify the significant contribution of the right bank river tributaries to sediments in the middle Niger river bassin. This contribution may further increase in the context of global changes (climate and anthropogenic) with important consequences on sediment transport but also on water quality and bacterial concentration which are strongly influenced by high SPM.</p>

STORM ICE OIL WIND WAVE WATCH SYSTEM (SIOWS): WEB GIS APPLICATION FOR MONITORING THE ARCTIC

2017 ◽  
Author(s):  
Alexander Myasoedov ◽  
Alexander Myasoedov ◽  
Sergey Azarov ◽  
Sergey Azarov ◽  
Ekaterina Balashova ◽  
...  
Keyword(s):  
Satellite Data ◽  
Wind Wave ◽  
Arctic Region ◽  
Web Gis ◽  
The Arctic ◽  
Flexible Tool ◽  
In Situ Data ◽  
Current State ◽  
Watch System

Working with satellite data, has long been an issue for users which has often prevented from a wider use of these data because of Volume, Access, Format and Data Combination. The purpose of the Storm Ice Oil Wind Wave Watch System (SIOWS) developed at Satellite Oceanography Laboratory (SOLab) is to solve the main issues encountered with satellite data and to provide users with a fast and flexible tool to select and extract data within massive archives that match exactly its needs or interest improving the efficiency of the monitoring system of geophysical conditions in the Arctic. SIOWS - is a Web GIS, designed to display various satellite, model and in situ data, it uses developed at SOLab storing, processing and visualization technologies for operational and archived data. It allows synergistic analysis of both historical data and monitoring of the current state and dynamics of the "ocean-atmosphere-cryosphere" system in the Arctic region, as well as Arctic system forecasting based on thermodynamic models with satellite data assimilation.

scholarly journals Critical Dynamics of Defects and Mechanisms of Damage-Failure Transitions in Fatigue

Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2554
Author(s):  
Oleg Naimark ◽  
Vladimir Oborin ◽  
Mikhail Bannikov ◽  
Dmitry Ledon
Keyword(s):  
Fatigue Damage ◽  
Kinetic Equations ◽  
Experimental Methodology ◽  
Preliminary Deformation ◽  
Scaling Properties ◽  
In Situ Data ◽  
Number Of Cycles ◽  
Fish Eye ◽  
Very High

An experimental methodology was developed for estimating a very high cycle fatigue (VHCF) life of the aluminum alloy AMG-6 subjected to preliminary deformation. The analysis of fatigue damage staging is based on the measurement of elastic modulus decrement according to “in situ” data of nonlinear dynamics of free-end specimen vibrations at the VHCF test. The correlation of fatigue damage staging and fracture surface morphology was studied to establish the scaling properties and kinetic equations for damage localization, “fish-eye” nucleation, and transition to the Paris crack kinetics. These equations, based on empirical parameters related to the structure of the material, allows us to estimate the number of cycles for the nucleation and advance of fatigue crack.

scholarly journals Measuring and inferring the ice thickness distribution of four glaciers in the Tien Shan, Kyrgyzstan

2020 ◽  
pp. 1-18
Author(s):  
Lander Van Tricht ◽  
Philippe Huybrechts ◽  
Jonas Van Breedam ◽  
Johannes J. Fürst ◽  
Oleg Rybak ◽  
...  
Keyword(s):  
Cross Validation ◽  
Thickness Distribution ◽  
Tien Shan ◽  
Ice Thickness ◽  
Ice Volume ◽  
In Situ Data ◽  
Radio Echo Sounding ◽  
Thickness Measurements ◽  
Tien Shan Mountains

Abstract Glaciers in the Tien Shan mountains contribute considerably to the fresh water used for irrigation, households and energy supply in the dry lowland areas of Kyrgyzstan and its neighbouring countries. To date, reconstructions of the current ice volume and ice thickness distribution remain scarce, and accurate data are largely lacking at the local scale. Here, we present a detailed ice thickness distribution of Ashu-Tor, Bordu, Golubin and Kara-Batkak glaciers derived from radio-echo sounding measurements and modelling. All the ice thickness measurements are used to calibrate three individual models to estimate the ice thickness in inaccessible areas. A cross-validation between modelled and measured ice thickness for a subset of the data is performed to attribute a weight to every model and to assemble a final composite ice thickness distribution for every glacier. Results reveal the thickest ice on Ashu-Tor glacier with values up to 201 ± 12 m. The ice thickness measurements and distributions are also compared with estimates composed without the use of in situ data. These estimates approach the total ice volume well, but local ice thicknesses vary substantially.

Particulate matter variability in Kathmandu based on in-situ measurements, remote sensing, and reanalysis data

2021 ◽  
pp. 105623
Author(s):  
Stefan Becker ◽  
Ramesh Prasad Sapkota ◽  
Binod Pokharel ◽  
Loknath Adhikari ◽  
Rudra Prasad Pokhrel ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Particulate Matter ◽  
Reanalysis Data ◽  
In Situ Measurements

scholarly journals Evaluating model parameterizations of submicron aerosol scattering and absorption with in situ data from ARCTAS 2008

2016 ◽  
Vol 16 (14) ◽  
pp. 9435-9455 ◽  
Author(s):  
Matthew J. Alvarado ◽  
Chantelle R. Lonsdale ◽  
Helen L. Macintyre ◽  
Huisheng Bian ◽  
Mian Chin ◽  
...  
Keyword(s):  
Optical Properties ◽  
Size Distribution ◽  
Aerosol Size Distribution ◽  
Visible Radiation ◽  
Submicron Aerosol ◽  
In Situ Data ◽  
Aerosol Absorption ◽  
Aerosol Scattering ◽  
The Impact

Abstract. Accurate modeling of the scattering and absorption of ultraviolet and visible radiation by aerosols is essential for accurate simulations of atmospheric chemistry and climate. Closure studies using in situ measurements of aerosol scattering and absorption can be used to evaluate and improve models of aerosol optical properties without interference from model errors in aerosol emissions, transport, chemistry, or deposition rates. Here we evaluate the ability of four externally mixed, fixed size distribution parameterizations used in global models to simulate submicron aerosol scattering and absorption at three wavelengths using in situ data gathered during the 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) campaign. The four models are the NASA Global Modeling Initiative (GMI) Combo model, GEOS-Chem v9-02, the baseline configuration of a version of GEOS-Chem with online radiative transfer calculations (called GC-RT), and the Optical Properties of Aerosol and Clouds (OPAC v3.1) package. We also use the ARCTAS data to perform the first evaluation of the ability of the Aerosol Simulation Program (ASP v2.1) to simulate submicron aerosol scattering and absorption when in situ data on the aerosol size distribution are used, and examine the impact of different mixing rules for black carbon (BC) on the results. We find that the GMI model tends to overestimate submicron scattering and absorption at shorter wavelengths by 10–23 %, and that GMI has smaller absolute mean biases for submicron absorption than OPAC v3.1, GEOS-Chem v9-02, or GC-RT. However, the changes to the density and refractive index of BC in GC-RT improve the simulation of submicron aerosol absorption at all wavelengths relative to GEOS-Chem v9-02. Adding a variable size distribution, as in ASP v2.1, improves model performance for scattering but not for absorption, likely due to the assumption in ASP v2.1 that BC is present at a constant mass fraction throughout the aerosol size distribution. Using a core-shell mixing rule in ASP overestimates aerosol absorption, especially for the fresh biomass burning aerosol measured in ARCTAS-B, suggesting the need for modeling the time-varying mixing states of aerosols in future versions of ASP.

scholarly journals Flux rope axis geometry of magnetic clouds deduced from in situ data

2013 ◽  
Vol 8 (S300) ◽  
pp. 265-268
Author(s):  
Miho Janvier ◽  
Pascal Démoulin ◽  
Sergio Dasso
Keyword(s):  
Interplanetary Medium ◽  
Magnetic Cloud ◽  
Flux Rope ◽  
Magnetic Clouds ◽  
Direct Integration ◽  
Axis Orientation ◽  
In Situ Data ◽  
Geometrical Features ◽  
Wide Range

AbstractMagnetic clouds (MCs) consist of flux ropes that are ejected from the low solar corona during eruptive flares. Following their ejection, they propagate in the interplanetary medium where they can be detected by in situ instruments and heliospheric imagers onboard spacecraft. Although in situ measurements give a wide range of data, these only depict the nature of the MC along the unidirectional trajectory crossing of a spacecraft. As such, direct 3D measurements of MC characteristics are impossible. From a statistical analysis of a wide range of MCs detected at 1 AU by the Wind spacecraft, we propose different methods to deduce the most probable magnetic cloud axis shape. These methods include the comparison of synthetic distributions with observed distributions of the axis orientation, as well as the direct integration of observed probability distribution to deduce the global MC axis shape. The overall shape given by those two methods is then compared with 2D heliospheric images of a propagating MC and we find similar geometrical features.

Sign in / Sign up

Export Citation Format

Share Document