scholarly journals The hidden influence of large particles on ocean colour

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emlyn J. Davies ◽  
Sünnje L. Basedow ◽  
David McKee
Keyword(s):  
Optical Properties ◽  
Significant Contribution ◽  
Ocean Color ◽  
Ocean Colour ◽  
Large Particles ◽  
Dissolved Matter ◽  
Bulk Absorption ◽  
New Applications ◽  
The Impact

AbstractOptical constituents in the ocean are often categorized as water, phytoplankton, sediments and dissolved matter. However, the optical properties of seawater are influenced, to some degree, by scattering and absorption by all particles in the water column. Here we assess the relevant size ranges for determining the optical properties of the ocean. We present a theoretical basis supporting the hypothesis that millimetre-size particles, including zooplankton and fish eggs, can provide a significant contribution to bulk absorption and scattering of seawater and therefore ocean color. Further, we demonstrate that existing in situ instruments are not capable of correctly resolving the impact of such large particles, possibly leading to their optical significance being overlooked. These findings refresh our perspective on the potential of ocean color and invite new applications of remote sensing for monitoring life close to the ocean surface.

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 Evaluating Model Parameterizations of Submicron Aerosol Scattering and Absorption with In Situ Data from ARCTAS 2008

2016 ◽  
Author(s):  
M. J. Alvarado ◽  
C. R. Lonsdale ◽  
H. L. Macintyre ◽  
H. Bian ◽  
M. 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 is 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 in situ size distribution information, 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 through out the aerosol size distribution. Using a core-shell mixing state in ASP overestimates aerosol absorption, especially for the fresh biomass burning aerosol measured in ARCTAS-B, suggesting the need for time-varying mixing states in future versions of ASP.

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.

scholarly journals Performance evaluation of ocean color satellite models for deriving accurate chlorophyll estimates in the Gulf of Saint Lawrence

2014 ◽  
Vol 11 (6) ◽  
pp. 9299-9340
Author(s):  
M. Montes-Hugo ◽  
H. Bouakba ◽  
R. Arnone
Keyword(s):  
Chlorophyll Concentration ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Relative Bias ◽  
Wide Field ◽  
Absolute Bias ◽  
Analysis System ◽  
Data Analysis System ◽  
The Impact

Abstract. The understanding of phytoplankton dynamics in the Gulf of the Saint Lawrence (GSL) is critical for managing major fisheries off the Canadian East coast. In this study, the accuracy of two atmospheric correction techniques (NASA standard algorithm, SA, and Kuchinke's spectral optimization, KU) and three ocean color inversion models (Carder's empirical for SeaWiFS (Sea-viewing Wide Field-of-View Sensor), EC, Lee's quasi-analytical, QAA, and Garver- Siegel-Maritorena semi-empirical, GSM) for estimating the phytoplankton absorption coefficient at 443 nm (aph(443)) and the chlorophyll concentration (chl) in the GSL is examined. Each model was validated based on SeaWiFS images and shipboard measurements obtained during May of 2000 and April 2001. In general, aph(443) estimates derived from coupling KU and QAA models presented the smallest differences with respect to in situ determinations as measured by High Pressure liquid Chromatography measurements (median absolute bias per cruise up to 0.005, RMSE up to 0.013). A change on the inversion approach used for estimating aph(443) values produced up to 43.4% increase on prediction error as inferred from the median relative bias per cruise. Likewise, the impact of applying different atmospheric correction schemes was secondary and represented an additive error of up to 24.3%. By using SeaDAS (SeaWiFS Data Analysis System) default values for the optical cross section of phytoplankton (i.e., aph(443) = aph(443)/chl = 0.056 m2mg−1), the median relative bias of our chl estimates as derived from the most accurate spaceborne aph(443) retrievals and with respect to in situ determinations increased up to 29%.

scholarly journals Neural Networks Technique for Filling Gaps in Satellite Measurements: Application to Ocean Color Observations

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Vladimir Krasnopolsky ◽  
Sudhir Nadiga ◽  
Avichal Mehra ◽  
Eric Bayler ◽  
David Behringer
Keyword(s):  
Ocean Color ◽  
Ocean Dynamics ◽  
Upper Ocean ◽  
Satellite Measurements ◽  
Cheap Method ◽  
Sensitivity Studies ◽  
The Impact ◽  
Ocean Observations ◽  
Satellite Ocean Color

A neural network (NN) technique to fill gaps in satellite data is introduced, linking satellite-derived fields of interest with other satellites andin situphysical observations. Satellite-derived “ocean color” (OC) data are used in this study because OC variability is primarily driven by biological processes related and correlated in complex, nonlinear relationships with the physical processes of the upper ocean. Specifically, ocean color chlorophyll-a fields from NOAA’s operational Visible Imaging Infrared Radiometer Suite (VIIRS) are used, as well as NOAA and NASA ocean surface and upper-ocean observations employed—signatures of upper-ocean dynamics. An NN transfer function is trained, using global data for two years (2012 and 2013), and tested on independent data for 2014. To reduce the impact of noise in the data and to calculate a stable NN Jacobian for sensitivity studies, an ensemble of NNs with different weights is constructed and compared with a single NN. The impact of the NN training period on the NN’s generalization ability is evaluated. The NN technique provides an accurate and computationally cheap method for filling in gaps in satellite ocean color observation fields and time series.

scholarly journals Assimilating GlobColour ocean colour data into a pre-operational physical-biogeochemical model

2012 ◽  
Vol 9 (2) ◽  
pp. 687-744 ◽  
Author(s):  
D. A. Ford ◽  
K. P. Edwards ◽  
D. Lea ◽  
R. M. Barciela ◽  
M. J. Martin ◽  
...  
Keyword(s):  
Real Time ◽  
Chlorophyll Concentration ◽  
Ocean Basin ◽  
Biogeochemical Model ◽  
State Variables ◽  
Ocean Colour ◽  
In Situ Observations ◽  
Time Basis ◽  
The Impact

Abstract. As part of the GlobColour project, daily chlorophyll-a observations, derived using remotely sensed ocean colour data from the MERIS, MODIS and SeaWiFS sensors, are produced. The ability of these products to be assimilated into a pre-operational global coupled physical-biogeochemical model has been tested, on both a hindcast and near-real-time basis, and the impact on the system assessed. The assimilation was found to immediately and significantly improve the bias, root mean square error and correlation of modelled surface chlorophyll concentration compared to the GlobColour observations, an improvement which was sustained throughout the year and in every ocean basin. Errors against independent in situ chlorophyll observations were also reduced, both at and beneath the ocean surface. However the model fit to in situ observations was not consistently better than that of climatology, due to errors in the underlying model. The assimilation scheme used is multivariate, updating all biogeochemical model state variables at all depths. Consistent changes were found in the other model variables, with reduced errors against in situ observations of nitrate and pCO2, and evidence of improved representation of zooplankton concentration. Annual mean surface fields of nutrients, alkalinity and carbon variables remained of similar quality compared to climatology. The near-real-time GlobColour products were found to be sufficiently reliable for operational purposes, and of benefit to both operational-style systems and reanalyses.

scholarly journals Impact of Temperature on Absorption Coefficient of Pure Seawater in the Blue Wavelengths Inferred from Satellite and In Situ Measurements

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Guomei Wei ◽  
Zhongping Lee ◽  
Xiuling Wu ◽  
Xiaolong Yu ◽  
Shaoling Shang ◽  
...  
Keyword(s):  
Absorption Coefficient ◽  
Chlorophyll Concentration ◽  
Ocean Color ◽  
Total Absorption ◽  
Laboratory Measurements ◽  
History Of ◽  
Phytoplankton Absorption ◽  
The Impact ◽  
The Relationship

There has been a long history of interest on how (if) the absorption coefficient of “pure” fresh water (afwλ) and “pure” seawater (aswλ) changes with temperature (T), yet the impact of T reported in the literature differs significantly in the blue domain. Unlike the previous studies based on laboratory measurements, we took an approach based on ~18 years (2002–2020) of MODIS ocean color and temperature measurements in the oligotrophic oceans, along with field measured chlorophyll concentration and phytoplankton absorption coefficient, to examine the relationship between T and the total absorption coefficient (aλ) at 412 and 443 nm. We found that the values of a412 and a443 in the summer are nearly flat (slightly decreasing) for the observed T range of ~19–27 °C. Since there are no detectable changes of chlorophyll during this period, the results suggest that T has a negligible impact on asw412 and asw443 in this T range. As a complement, the impact of salinity on afwλ was also evaluated using three independent determinations of aswλ and afwλ, where good agreements were found from these observations.

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