scholarly journals Carbon-based phytoplankton size classes retrieved via ocean color estimates of the particle size distribution

Ocean Science ◽  
2016 ◽  
Vol 12 (2) ◽  
pp. 561-575 ◽  
Author(s):  
Tihomir S. Kostadinov ◽  
Svetlana Milutinović ◽  
Irina Marinov ◽  
Anna Cabré

Abstract. Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the “unit of accounting” in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size – picophytoplankton (0.5–2 µm in diameter), nanophytoplankton (2–20 µm) and microphytoplankton (20–50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield  ∼  0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.

2015 ◽  
Vol 12 (3) ◽  
pp. 573-644 ◽  
Author(s):  
T. S. Kostadinov ◽  
S. Milutinović ◽  
I. Marinov ◽  
A. Cabré

Abstract. Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the "unit of accounting" in Earth System models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing algorithms to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size – picophytoplankton (0.5–2 μm in diameter), nanophytoplankton (2–20 μm) and microphytoplankton (20–50 μm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e. oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have large biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield on average ~0.2–0.3 Gt of C, consistent with analogous estimates from two other ocean color algorithms, and several state-of-the-art Earth System models. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, because the PSD-based algorithm is not a priori empirically constrained and introduces improvement over the assumptions of the other approaches. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients.


2021 ◽  
Vol 21 (13) ◽  
pp. 10295-10335
Author(s):  
Ramiro Checa-Garcia ◽  
Yves Balkanski ◽  
Samuel Albani ◽  
Tommi Bergman ◽  
Ken Carslaw ◽  
...  

Abstract. This paper presents an analysis of the mineral dust aerosol modelled by five Earth system models (ESMs) within the project entitled Coordinated Research in Earth Systems and Climate: Experiments, kNowledge, Dissemination and Outreach (CRESCENDO). We quantify the global dust cycle described by each model in terms of global emissions, together with dry and wet deposition, reporting large differences in the ratio of dry over wet deposition across the models not directly correlated with the range of particle sizes emitted. The multi-model mean dust emissions with five ESMs is 2836 Tg yr−1 but with a large uncertainty due mainly to the difference in the maximum dust particle size emitted. The multi-model mean of the subset of four ESMs without particle diameters larger than 10 µ m is 1664 (σ=651) Tg yr−1. Total dust emissions in the simulations with identical nudged winds from reanalysis give us better consistency between models; i.e. the multi-model mean global emissions with three ESMs are 1613 (σ=278) Tg yr−1, but 1834 (σ=666) Tg yr−1 without nudged winds and the same models. Significant discrepancies in the globally averaged dust mass extinction efficiency explain why even models with relatively similar global dust load budgets can display strong differences in dust optical depth. The comparison against observations has been done in terms of dust optical depths based on MODIS (Moderate Resolution Imaging Spectroradiometer) satellite products, showing global consistency in terms of preferential dust sources and transport across the Atlantic. The global localisation of source regions is consistent with MODIS, but we found regional and seasonal differences between models and observations when we quantified the cross-correlation of time series over dust-emitting regions. To faithfully compare local emissions between models we introduce a re-gridded normalisation method that can also be compared with satellite products derived from dust event frequencies. Dust total deposition is compared with an instrumental network to assess global and regional differences. We find that models agree with observations within a factor of 10 for data stations distant from dust sources, but the approximations of dust particle size distribution at emission contributed to a misrepresentation of the actual range of deposition values when instruments are close to dust-emitting regions. The observed dust surface concentrations also are reproduced to within a factor of 10. The comparison of total aerosol optical depth with AERONET (AErosol RObotic NETwork) stations where dust is dominant shows large differences between models, although with an increase in the inter-model consistency when the simulations are conducted with nudged winds. The increase in the model ensemble consistency also means better agreement with observations, which we have ascertained for dust total deposition, surface concentrations and optical depths (against both AERONET and MODIS retrievals). We introduce a method to ascertain the contributions per mode consistent with the multi-modal direct radiative effects, which we apply to study the direct radiative effects of a multi-modal representation of the dust particle size distribution that includes the largest particles.


2021 ◽  
Author(s):  
Maria Ángeles Burgos Simón ◽  
Elisabeth Andrews ◽  
Gloria Titos ◽  
Angela Benedetti ◽  
Huisheng Bian ◽  
...  

<p>The particle hygroscopic growth impacts the optical properties of aerosols and, in turn, affects the aerosol-radiation interaction and calculation of the Earth’s radiative balance. The dependence of particle light scattering on relative humidity (RH) can be described by the scattering enhancement factor f(RH), defined as the ratio between the particle light scattering coefficient at a given RH divided by its dry value.</p><p>The first effort of the AeroCom Phase III – INSITU experiment was to develop an observational dataset of scattering enhancement values at 26 sites to study the uptake of water by atmospheric aerosols, and evaluate f(RH) globally (Burgos et al., 2019). Model outputs from 10 Earth System Models (CAM, CAM-ATRAS, CAM-Oslo, GEOS-Chem, GEOS-GOCART, MERRAero, TM5, OsloCTM3, IFS-AER, and ECMWF) were then evaluated against this in-situ dataset. Building on these results, we investigate f(RH) in the context of other aerosol optical and chemical properties, making use of the same 10 Earth System Models (ESMs) and in-situ measurements as in Burgos et al. (2020) and Titos et al. (2021).</p><p>Given the difficulties of deploying and maintaining instrumentation for long-term, accurate and comprehensive f(RH) observations, it is desirable to find an observational proxy for f(RH). This observation-based proxy would also need to be reproduced in modelling space. Our aim here is to evaluate how ESMs currently represent the relationship between f(RH), scattering Ångström exponent (SAE), and single scattering albedo (SSA). This work helps to identify current challenges in modelling water-uptake by aerosols and their impact on aerosol optical properties within Earth system models.</p><p>We start by analyzing the behavior of SSA with RH, finding the expected increase with RH for all site types and models. Then, we analyze the three variables together (f(RH)-SSA-SAE relationship). Results show that hygroscopic particles tend to be bigger and scatter more than non-hygroscopic small particles, though variability within models is noticeable. This relationship can be further studied by relating SAE to model chemistry, by selecting those grid points dominated by a single chemical component (mass mixing ratios > 90%). Finally, we analyze model performance at three specific sites representing different aerosol types: Arctic, marine and rural. At these sites, the model data can be exactly temporally and spatially collocated with the observations, which should help to identify the models which exhibit better agreement with measurements and for which aerosol type.</p><p> </p><p>Burgos, M.A. et al.: A global view on the effect of water uptake on aerosol particle light scattering. Sci Data 6, 157. https://doi.org/10.1038/s41597-019-0158-7, 2019.</p><p>Burgos, M.A. et al.: A global model–measurement evaluation of particle light scattering coefficients at elevated relative humidity, Atmos. Chem. Phys., 20, 10231–10258, https://doi.org/10.5194/acp-20-10231-2020, 2020.</p><p>Titos, G. et al.: A global study of hygroscopicity-driven light scattering enhancement in the context of other in-situ aerosol optical properties, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2020-1250, in review, 2020.</p>


2010 ◽  
Vol 7 (3) ◽  
pp. 4295-4340 ◽  
Author(s):  
T. S. Kostadinov ◽  
D. A. Siegel ◽  
S. Maritorena

Abstract. A new method of retrieving the parameters of a power-law particle size distribution (PSD) from ocean color remote sensing data was used to assess the global distribution and dynamics of phytoplankton functional types (PFT's). The method retrieves the power-law slope, ξ, and the abundance at a reference diameter, N0, based upon the shape and magnitude of the particulate backscattering coefficient spectrum. Relating the PSD to PFT's on global scales assumes that the open ocean particulate assemblage is biogenic. The retrieved PSD's can be integrated to define three size-based PFT's by the percent volume concentration contribution of three phytoplankton size classes – picoplankton (0.5–2 μm in equivalent spherical diameter), nanoplankton (2–20 μm) and microplankton (20–50 μm). Validation with in-situ HPLC diagnostic pigments results in satisfactory match-ups for the pico- and micro-phytoplankton size classes. Global climatologies derived from SeaWiFS monthly data reveal PFT and particle abundance spatial patterns that are consistent with current understanding. Oligotrophic gyres are characterized by lower particle abundance and higher contribution by picoplankton-sized particles than transitional or eutrophic regions. Seasonal succession patterns for size-based PFT's reveal good correspondence between increasing chl and percent contribution by microplankton, as well as increasing particle abundance. Long-term trends in particle abundances are generally inconclusive yet are well correlated with the MEI index indicating increased oligotrophy (i.e. lower particle abundance and increased contribution of picoplankton-sized particles) during the warm phase of an El Niño event. This work demonstrates the utility and future potential of assessing phytoplankton functional types using remote characterization of the particle size distribution.


2003 ◽  
Vol 42 (22) ◽  
pp. 5568-5575 ◽  
Author(s):  
Jun Yang ◽  
Ting-Jie Wang ◽  
Hong He ◽  
Fei Wei ◽  
Yong Jin

JOM ◽  
2019 ◽  
Vol 71 (11) ◽  
pp. 4050-4058 ◽  
Author(s):  
Swapnil Morankar ◽  
Monalisa Mandal ◽  
Nadia Kourra ◽  
Mark A. Williams ◽  
Rahul Mitra ◽  
...  

Processes ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 381 ◽  
Author(s):  
Johann Landauer ◽  
Petra Foerst

Triboelectric charging is a potentially suitable tool for separating fine dry powders, but the charging process is not yet completely understood. Although physical descriptions of triboelectric charging have been proposed, these proposals generally assume the standard conditions of particles and surfaces without considering dispersity. To better understand the influence of particle charge on particle size distribution, we determined the in situ particle size in a protein–starch mixture injected into a separation chamber. The particle size distribution of the mixture was determined near the electrodes at different distances from the separation chamber inlet. The particle size decreased along both electrodes, indicating a higher protein than starch content near the electrodes. Moreover, the height distribution of the powder deposition and protein content along the electrodes were determined in further experiments, and the minimum charge of a particle that ensures its separation in a given region of the separation chamber was determined in a computational fluid dynamics simulation. According to the results, the charge on the particles is distributed and apparently independent of particle size.


2015 ◽  
Vol 12 (1) ◽  
pp. 193-208 ◽  
Author(s):  
C. D. Nevison ◽  
M. Manizza ◽  
R. F. Keeling ◽  
M. Kahru ◽  
L. Bopp ◽  
...  

Abstract. The observed seasonal cycles in atmospheric potential oxygen (APO) at a range of mid- to high-latitude surface monitoring sites are compared to those inferred from the output of six Earth system models (ESMs) participating in the fifth phase of the Coupled Model Intercomparison Project phase 5 (CMIP5). The simulated air–sea O2 fluxes are translated into APO seasonal cycles using a matrix method that takes into account atmospheric transport model (ATM) uncertainty among 13 different ATMs. Three of the ocean biogeochemistry models tested are able to reproduce the observed APO cycles at most sites, to within the large TransCom3-era ATM uncertainty used here, while the other three generally are not. Net primary production (NPP) and net community production (NCP), as estimated from satellite ocean color data, provide additional constraints, albeit more with respect to the seasonal phasing of ocean model productivity than overall magnitude. The present analysis suggests that, of the tested ocean biogeochemistry models, the community ecosystem model (CESM) and the Geophysical Fluid Dynamics Laboratory (GFDL) ESM2M are best able to capture the observed APO seasonal cycle at both northern and southern hemispheric sites. In most models, discrepancies with observed APO can be attributed to the underestimation of NPP, deep ventilation or both in the northern oceans.


2002 ◽  
Vol 36 (1) ◽  
pp. 59-69 ◽  
Author(s):  
Teresa Serra ◽  
Xavier Casamitjana ◽  
Jordi Colomer ◽  
Timothy C. Granata

An in situ laser particle size analyzer (LISST-100, Sequoia Scientific, Inc.) has been used to study the particle size distribution and concentration of biological and non biological particles in the water column of a Mediterranean coastal system. Two field campaigns have been carried out during low and high energy conditions of the flow, caused by the passage of a storm front. For the low energy period, the water column remained stratified, whereas for the high energetic period the water column was warmer and well mixed. The first study dealt with the distribution of particles near the bottom of the coastal area. Here, two regions were taken into account. The first region was a sea-grass meadow of Posidonia oceanica and the second region was a barren sand area. The second study dealt with the determination of the vertical distribution of suspended particles in the whole water column of the system. The results showed a decrease in the vertical concentration of suspended particles in the water column with the passage of the storm front, which was associated with advection of warm water mass rather than by vertical mixing. In contrast, vertical resuspension determined the fate of suspended particles at the bottom of the water column and an increase of their concentration was found.


2018 ◽  
Author(s):  
Ufuk Utku Turuncoglu

Abstract. The data volume being produced by regional and global multi-component earth system models are rapidly increasing due to the improved spatial and temporal resolution of the model components, sophistication of the used numerical models in terms of represented physical processes and their non-linear complex interactions. In particular, very short time steps have to be defined in multi-component and multi-scale non-hydrostatic modelling systems to represent the evolution of the fast-moving processes such as turbulence, extra-tropical cyclones, convective lines, jet streams, internal waves, vertical turbulent mixing and surface gravity waves. Consequently, the used small time steps cause extra computation and disk I/O overhead in the used modelling system even if today's most powerful high-performance computing and data storage systems are being considered. Analysis of the high volume of data from multiple earth system model components at different temporal and spatial resolution also poses a challenging problem to efficiently perform integrated data analysis of the massive amounts of data by relying on the conventional post-processing methods available today. This study basically aims to explore the feasibility and added value of integrating existing in-situ visualization and data analysis methods with the model coupling framework (ESMF) to increase interoperability between multi-component simulation code and data processing pipelines by providing easy to use, efficient, generic and standardized modeling environment for earth system science applications. The new data analysis approach enables simultaneous analysis of the vast amount of data produced by multi-component regional earth system models (atmosphere, ocean etc.) during the run process. The methodology aims to create an integrated modeling environment for analyzing fast-moving processes and their evolution in both time and space to support better understanding of the underplaying physical mechanisms. The state-of-art approach can also be used to solve common problems in earth system model development workflow such as designing new sub-grid scale parametrizations (convection, air–sea interaction etc.) that requires inspecting the integrated model behavior in a higher temporal and spatial scale during the run or supporting visual debugging of the multi-component modeling systems, which usually are not facilitated by existing model coupling libraries and modeling systems.


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