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

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.

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

Ocean Science ◽

10.5194/os-12-561-2016 ◽

2016 ◽

Vol 12 (2) ◽

pp. 561-575 ◽

Cited By ~ 32

Author(s):

Tihomir S. Kostadinov ◽

Svetlana Milutinović ◽

Irina Marinov ◽

Anna Cabré

Keyword(s):

Particle Size ◽

Particle Size Distribution ◽

Size Distribution ◽

Ocean Color ◽

Earth System ◽

System Models ◽

Size Classes ◽

Carbon Biomass ◽

Earth System Models

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.

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Evaluation of natural aerosols in CRESCENDO Earth system models (ESMs): mineral dust

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-10295-2021 ◽

2021 ◽

Vol 21 (13) ◽

pp. 10295-10335

Author(s):

Ramiro Checa-Garcia ◽

Yves Balkanski ◽

Samuel Albani ◽

Tommi Bergman ◽

Ken Carslaw ◽

...

Keyword(s):

Particle Size ◽

Particle Size Distribution ◽

Size Distribution ◽

Dust Particle ◽

Wet Deposition ◽

Earth System ◽

Dust Emissions ◽

Dust Sources ◽

Global Emissions ◽

Earth System Models

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.

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Evaluating the ocean biogeochemical components of Earth system models using atmospheric potential oxygen and ocean color data

Biogeosciences ◽

10.5194/bg-12-193-2015 ◽

2015 ◽

Vol 12 (1) ◽

pp. 193-208 ◽

Cited By ~ 13

Author(s):

C. D. Nevison ◽

M. Manizza ◽

R. F. Keeling ◽

M. Kahru ◽

L. Bopp ◽

...

Keyword(s):

Net Primary Production ◽

Ocean Color ◽

Seasonal Cycles ◽

Geophysical Fluid Dynamics Laboratory ◽

Earth System ◽

System Models ◽

Color Data ◽

Ocean Biogeochemistry ◽

Earth System Models ◽

Potential Oxygen

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.

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Variable particle size distributions reduce the sensitivity of global export flux to climate change

Biogeosciences ◽

10.5194/bg-18-229-2021 ◽

2021 ◽

Vol 18 (1) ◽

pp. 229-250

Author(s):

Shirley W. Leung ◽

Thomas Weber ◽

Jacob A. Cram ◽

Curtis Deutsch

Keyword(s):

Climate Change ◽

Particle Size ◽

Euphotic Zone ◽

Nutrient Concentrations ◽

Biogeochemical Model ◽

Size Distributions ◽

Earth System ◽

Particle Size Distributions ◽

System Models ◽

Earth System Models

Abstract. Recent earth system models predict a 10 %–20 % decrease in particulate organic carbon export from the surface ocean by the end of the 21st century due to global climate change. This decline is mainly caused by increased stratification of the upper ocean, resulting in reduced shallow subsurface nutrient concentrations and a slower supply of nutrients to the surface euphotic zone in low latitudes. These predictions, however, do not typically account for associated changes in remineralization depths driven by sinking-particle size. Here we combine satellite-derived export and particle size maps with a simple 3-D global biogeochemical model that resolves dynamic particle size distributions to investigate how shifts in particle size may buffer or amplify predicted changes in surface nutrient supply and therefore export production. We show that higher export rates are empirically correlated with larger sinking particles and presumably larger phytoplankton, particularly in tropical and subtropical regions. Incorporating these empirical relationships into our global model shows that as circulation slows, a decrease in export is associated with a shift towards smaller particles, which sink more slowly and are thus remineralized shallower. This shift towards shallower remineralization in turn leads to greater recycling of nutrients in the upper water column and thus faster nutrient recirculation into the euphotic zone. The end result is a boost in productivity and export that counteracts the initial circulation-driven decreases. This negative feedback mechanism (termed the particle-size–remineralization feedback) slows export decline over the next century by ∼ 14 % globally (from −0.29 to −0.25 GtC yr−1) and by ∼ 20 % in the tropical and subtropical oceans, where export decreases are currently predicted to be greatest. Our findings suggest that to more accurately predict changes in biological pump strength under a warming climate, earth system models should include dynamic particle-size-dependent remineralization depths.

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Evaluating the ocean biogeochemical components of earth system models using atmospheric potential oxygen (APO) and ocean color data

Biogeosciences Discussions ◽

10.5194/bgd-11-8485-2014 ◽

2014 ◽

Vol 11 (6) ◽

pp. 8485-8529

Author(s):

C. D. Nevison ◽

M. Manizza ◽

R. F. Keeling ◽

M. Kahru ◽

L. Bopp ◽

...

Keyword(s):

Transport Model ◽

Net Primary Production ◽

Ocean Color ◽

Seasonal Cycles ◽

Earth System ◽

System Models ◽

Color Data ◽

Ocean Biogeochemistry ◽

Earth System Models ◽

Potential Oxygen

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 6 Earth System Models participating in the fifth phase of the Coupled Model Intercomparison Project (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. Half of the ocean biogeochemistry models tested are able to reproduce the observed APO cycles at most sites, to within the current large ATM uncertainty, while the other half 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 the overall magnitude. The present analysis suggests that, of the tested ocean biogeochemistry models, CESM and GFDL ESM2M are best able to capture the observed APO seasonal cycle at both Northern and Southern Hemisphere sites. In the northern oceans, the comparison to observed APO suggests that most models tend to underestimate NPP or deep ventilation or both.

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Corrigendum to "Evaluating the ocean biogeochemical components of Earth system models using atmospheric potential oxygen and ocean color data" published in Biogeosciences, 12, 193–208, 2015

Biogeosciences ◽

10.5194/bg-12-2891-2015 ◽

2015 ◽

Vol 12 (10) ◽

pp. 2891-2891

Author(s):

C. D. Nevison ◽

M. Manizza ◽

R. F. Keeling ◽

M. Kahru ◽

L. Bopp ◽

...

Keyword(s):

Ocean Color ◽

Earth System ◽

System Models ◽

Color Data ◽

Earth System Models ◽

Potential Oxygen

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Variable phytoplankton size distributions reduce the sensitivity of global export flux to climate change

10.5194/bg-2020-156 ◽

2020 ◽

Author(s):

Shirley W. Leung ◽

Thomas Weber ◽

Jacob A. Cram ◽

Curtis Deutsch

Keyword(s):

Climate Change ◽

Particle Size ◽

Global Climate ◽

Euphotic Zone ◽

Nutrient Concentrations ◽

Biogeochemical Model ◽

Earth System ◽

Export Production ◽

System Models ◽

Earth System Models

Abstract. Earth System Models predict a 10–20 % decrease in ocean carbon export production by the end of the 21st century due to global climate change. This decline is caused by increased stratification of the upper ocean, resulting in reduced shallow subsurface nutrient concentrations and a slower supply of nutrients to the surface euphotic zone. These predictions, however, do not account for associated changes in sinking particle size and remineralization depth. Here we combine satellite-derived export and particle size maps with a simple 3-D global biogeochemical model to investigate how shifts in sinking particle size may buffer predicted changes in surface nutrient supply and therefore export production. We show that higher export rates are correlated with larger phytoplankton and sinking particles, especially in tropical and subtropical regions. Incorporation of these empirical relationships into a global model shows that as circulation slows, a decrease in export and associated shift toward smaller phytoplankton yields particles that sink more slowly and are thus remineralized shallower; this in turn leads to greater recycling of nutrients in the upper water column and faster nutrient recirculation into the euphotic zone, boosting productivity and export to counteract the initial circulation-driven decreases. This negative feedback mechanism (termed the particle size-remineralization feedback) slows export decline over the next century by ~14 % globally and by ~20 % in the tropical and subtropical oceans, where export decreases are currently predicted to be greatest. Thus, incorporating dynamic particle size-dependent remineralization depths into Earth System Models will result in more robust predictions of changes in biological pump strength in a warming climate.

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