Using new observations and Machine Learning to improve organic sinking processes in the PlankTOM global ocean biogeochemical model 

2021 ◽  
Author(s):  
Anna Denvil-Sommer ◽  
Corinne Le Quéré ◽  
Erik Buitenhuis ◽  
Lionel Guidi ◽  
Jean-Olivier Irisson
Keyword(s):  
Organic Carbon ◽  
Carbon Cycle ◽  
Deep Ocean ◽  
Ecosystem Dynamics ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Carbon Export ◽  
Mixing Depth ◽  
Chl A ◽  
Biogeochemical Models

<p>A lot of effort has been put in the representation of surface ecosystem processes in global carbon cycle models, in particular through the grouping of organisms into Plankton Functional Types (PFTs) which have specific influences on the carbon cycle. In contrast, the transfer of ecosystem dynamics into carbon export to the deep ocean has received much less attention, so that changes in the representation of the PFTs do not necessarily translate into changes in sinking of particulate matter. Models constrain the air-sea CO<sub>2</sub> flux by drawing down carbon into the ocean interior. This export flux is five times as large as the CO<sub>2</sub> emitted to the atmosphere by human activities. When carbon is transported from the surface to intermediate and deep ocean, more CO<sub>2 </sub>can be absorbed at the surface. Therefore, even small variability in sinking organic carbon fluxes can have a large impact on air-sea CO<sub>2</sub> fluxes, and on the amount of CO<sub>2</sub> emissions that remain in the atmosphere.</p><p>In this work we focus on the representation of organic matter sinking in global biogeochemical models, using the PlankTOM model in its latest version representing 12 PFTs. We develop and test a methodology that will enable the systematic use of new observations to constrain sinking processes in the model. The approach is based on a Neural Network (NN) and is applied to the PlankTOM model output to test its ability to reconstruction small and large particulate organic carbon with a limited number of observations. We test the information content of geographical variables (location, depth, time of year), physical conditions (temperature, mixing depth, nutrients), and ecosystem information (CHL a, PFTs). These predictors are used in the NN to test their influence on the model-generation of organic particles and the robustness of the results. We show preliminary results using the NN approach with real plankton and particle size distribution observations from the Underwater Vision Profiler (UVP) and plankton diversity data from Tara Oceans expeditions and discuss limitations.</p>

scholarly journals Global Ocean Particulate Organic Carbon Flux Merged with Satellite Parameters

2016 ◽  
Author(s):  
Colleen B. Mouw ◽  
Audrey Barnett ◽  
Galen A. McKinley ◽  
Lucas Gloege ◽  
Darren Pilcher
Keyword(s):  
Time Series ◽  
Organic Carbon ◽  
Particulate Organic Carbon ◽  
Net Primary Production ◽  
Mixed Layer Depth ◽  
Deep Ocean ◽  
Euphotic Zone ◽  
Sediment Traps ◽  
Global Ocean ◽  
Carbon Export

Abstract. Particulate organic carbon (POC) flux estimated from POC concentration observations from sediment traps and 234Th are compiled across the global ocean. The compilation includes six time series locations: CARIACO, K2, OSP, BATS, OFP and HOT. Efficiency of the biological pump of carbon to the deep ocean depends largely on biologically mediated export of carbon from the surface ocean and its remineralization with depth, thus biologically related parameters able to be estimated from satellite observations were merged at the POC observation sites. Satellite parameters include: net primary production, percent microplankton, sea surface temperature, photosynthetically active radiation, diffuse attenuation coefficient at 490 nm, euphotic zone depth, as well as, climatological mixed layer depth. 85 % of the observations across the globe are concentrated in the Northern Hemisphere with 44 % of the data record overlapping the satellite record. Time series sites accounted for 36 % of the data. 71 % of the data is measured at ≥ 500 m with the most common deployment depths between 1000 and 1500 m. This dataset is valuable for investigations of CO2 drawdown, carbon export, remineralization, and sequestration. The compiled data can be freely accessed at doi:10.1594/PANGAEA.855600.

scholarly journals Eukaryotic virus composition can predict the efficiency of carbon export in the global ocean

2019 ◽  
Author(s):  
Hiroto Kaneko ◽  
Romain Blanc-Mathieu ◽  
Hisashi Endo ◽  
Samuel Chaffron ◽  
Tom O. Delmont ◽  
...  
Keyword(s):  
Large Scale ◽  
Regional Scale ◽  
Deep Ocean ◽  
Global Scale ◽  
Ecosystem Dynamics ◽  
Global Ocean ◽  
Marker Genes ◽  
Carbon Export ◽  
Viral Marker ◽  
Carbon Pump

SummaryThe biological carbon pump, in which carbon fixed by photosynthesis is exported to the deep ocean through sinking, is a major process in Earth’s carbon cycle. The proportion of primary production that is exported is termed the carbon export efficiency (CEE). Based on in-lab or regional scale observations, viruses were previously suggested to affect the CEE (i.e., viral “shunt” and “shuttle”). In this study, we tested associations between viral community composition and CEE measured at a global scale. A regression model based on relative abundance of viral marker genes explained 67% of the variation in CEE. Viruses with high importance in the model were predicted to infect ecologically important hosts. These results are consistent with the view that the viral shunt and shuttle functions at a large scale and further imply that viruses likely act in this process in a way dependent on their hosts and ecosystem dynamics.

scholarly journals Sinking rates and ballast composition of particles in the Atlantic Ocean: implications for the organic carbon fluxes to the deep ocean

2009 ◽  
Vol 6 (1) ◽  
pp. 85-102 ◽  
Author(s):  
G. Fischer ◽  
G. Karakaş
Keyword(s):  
Organic Carbon ◽  
Atlantic Ocean ◽  
Sediment Trap ◽  
Carbon Flux ◽  
Coastal Upwelling ◽  
Production Systems ◽  
Deep Ocean ◽  
Biogeochemical Model ◽  
Carbonate Content ◽  
Organic Carbon Flux

Abstract. The flux of materials to the deep sea is dominated by larger, organic-rich particles with sinking rates varying between a few meters and several hundred meters per day. Mineral ballast may regulate the transfer of organic matter and other components by determining the sinking rates, e.g. via particle density. We calculated particle sinking rates from mass flux patterns and alkenone measurements applying the results of sediment trap experiments from the Atlantic Ocean. We have indication for higher particle sinking rates in carbonate-dominated production systems when considering both regional and seasonal data. During a summer coccolithophorid bloom in the Cape Blanc coastal upwelling off Mauritania, particle sinking rates reached almost 570 m per day, most probably due the fast sedimentation of densely packed zooplankton fecal pellets, which transport high amounts of organic carbon associated with coccoliths to the deep ocean despite rather low production. During the recurring winter-spring blooms off NW Africa and in opal-rich production systems of the Southern Ocean, sinking rates of larger particles, most probably diatom aggregates, showed a tendency to lower values. However, there is no straightforward relationship between carbonate content and particle sinking rates. This could be due to the unknown composition of carbonate and/or the influence of particle size and shape on sinking rates. It also remains noticeable that the highest sinking rates occurred in dust-rich ocean regions off NW Africa, but this issue deserves further detailed field and laboratory investigations. We obtained increasing sinking rates with depth. By using a seven-compartment biogeochemical model, it was shown that the deep ocean organic carbon flux at a mesotrophic sediment trap site off Cape Blanc can be captured fairly well using seasonal variable particle sinking rates. Our model provides a total organic carbon flux of 0.29 Tg per year down to 3000 m off the NW African upwelling region between 5 and 35° N. Simple parameterisations of remineralisation and sinking rates in such models, however, limit their capability in reproducing the flux variation in the water column.

scholarly journals Large deep-sea zooplankton biomass mirrors primary production in the global ocean

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
S. Hernández-León ◽  
R. Koppelmann ◽  
E. Fraile-Nuez ◽  
A. Bode ◽  
C. Mompeán ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Primary Production ◽  
Deep Sea ◽  
Large Scale ◽  
Net Primary Production ◽  
Deep Ocean ◽  
Zooplankton Biomass ◽  
Global Ocean ◽  
Global Coupling ◽  
Do So

AbstractThe biological pump transports organic carbon produced by photosynthesis to the meso- and bathypelagic zones, the latter removing carbon from exchanging with the atmosphere over centennial time scales. Organisms living in both zones are supported by a passive flux of particles, and carbon transported to the deep-sea through vertical zooplankton migrations. Here we report globally-coherent positive relationships between zooplankton biomass in the epi-, meso-, and bathypelagic layers and average net primary production (NPP). We do so based on a global assessment of available deep-sea zooplankton biomass data and large-scale estimates of average NPP. The relationships obtained imply that increased NPP leads to enhanced transference of organic carbon to the deep ocean. Estimated remineralization from respiration rates by deep-sea zooplankton requires a minimum supply of 0.44 Pg C y−1 transported into the bathypelagic ocean, comparable to the passive carbon sequestration. We suggest that the global coupling between NPP and bathypelagic zooplankton biomass must be also supported by an active transport mechanism associated to vertical zooplankton migration.

scholarly journals Skill assessment of the PELAGOS global ocean biogeochemistry model over the period 1980–2000

2009 ◽  
Vol 6 (11) ◽  
pp. 2333-2353 ◽  
Author(s):  
M. Vichi ◽  
S. Masina
Keyword(s):  
Organic Carbon ◽  
Mixed Layer ◽  
General Circulation ◽  
Net Primary Production ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Data Set ◽  
Surface Ocean ◽  
Ocean Biogeochemistry

Abstract. Global Ocean Biogeochemistry General Circulation Models are useful tools to study biogeochemical processes at global and large scales under current climate and future scenario conditions. The credibility of future estimates is however dependent on the model skill in capturing the observed multi-annual variability of firstly the mean bulk biogeochemical properties, and secondly the rates at which organic matter is processed within the food web. For this double purpose, the results of a multi-annual simulation of the global ocean biogeochemical model PELAGOS have been objectively compared with multi-variate observations from the last 20 years of the 20th century, both considering bulk variables and carbon production/consumption rates. Simulated net primary production (NPP) is comparable with satellite-derived estimates at the global scale and when compared with an independent data-set of in situ observations in the equatorial Pacific. The usage of objective skill indicators allowed us to demonstrate the importance of comparing like with like when considering carbon transformation processes. NPP scores improve substantially when in situ data are compared with modeled NPP which takes into account the excretion of freshly-produced dissolved organic carbon (DOC). It is thus recommended that DOC measurements be performed during in situ NPP measurements to quantify the actual production of organic carbon in the surface ocean. The chlorophyll bias in the Southern Ocean that affects this model as well as several others is linked to the inadequate representation of the mixed layer seasonal cycle in the region. A sensitivity experiment confirms that the artificial increase of mixed layer depths towards the observed values substantially reduces the bias. Our assessment results qualify the model for studies of carbon transformation in the surface ocean and metabolic balances. Within the limits of the model assumption and known biases, PELAGOS indicates a net heterotrophic balance especially in the more oligotrophic regions of the Atlantic during the boreal winter period. However, at the annual time scale and over the global ocean, the model suggests that the surface ocean is close to a weakly positive autotrophic balance in accordance with recent experimental findings and geochemical considerations.

scholarly journals A perturbed biogeochemistry model ensemble evaluated against in situ and satellite observations

2018 ◽  
Vol 15 (21) ◽  
pp. 6685-6711 ◽  
Author(s):  
Prima Anugerahanti ◽  
Shovonlal Roy ◽  
Keith Haines
Keyword(s):  
Peak Height ◽  
Ecosystem Dynamics ◽  
Abyssal Plain ◽  
Biogeochemical Model ◽  
Structural Sensitivity ◽  
Statistical Measures ◽  
Biogeochemical Models ◽  
Nutrient Utilisation ◽  
The Impact

Abstract. The dynamics of biogeochemical models are determined by the mathematical equations used to describe the main biological processes. Earlier studies have shown that small changes in the model formulation may lead to major changes in system dynamics, a property known as structural sensitivity. We assessed the impact of structural sensitivity in a biogeochemical model of intermediate complexity by modelling the chlorophyll and dissolved inorganic nitrogen (DIN) concentrations. The model is run at five different oceanographic stations spanning three different regimes: oligotrophic, coastal, and the abyssal plain, over a 10-year timescale to observe the effect in different regions. A 1-D Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration, and Acidification (MEDUSA) ensemble was used with each ensemble member having a combination of tuned function parameterizations that describe some of the key biogeochemical processes, namely nutrient uptake, zooplankton grazing, and plankton mortalities. The impact is quantified using phytoplankton phenology (initiation, bloom time, peak height, duration, and termination of phytoplankton blooms) and statistical measures such as RMSE (root-mean-squared error), mean, and range for chlorophyll and nutrients. The spread of the ensemble as a measure of uncertainty is assessed against observations using the normalized RMSE ratio (NRR). We found that even small perturbations in model structure can produce large ensemble spreads. The range of 10-year mean surface chlorophyll concentration in the ensemble is between 0.14 and 3.69 mg m−3 at coastal stations, 0.43 and 1.11 mg m−3 on the abyssal plain, and 0.004 and 0.16 mg m−3 at the oligotrophic stations. Changing both phytoplankton and zooplankton mortalities and the grazing functions has the largest impact on chlorophyll concentrations. The in situ measurements of bloom timings, duration, and terminations lie mostly within the ensemble range. The RMSEs between in situ observations and the ensemble mean and median are mostly reduced compared to the default model output. The NRRs for monthly variability suggest that the ensemble spread is generally narrow (NRR 1.21–1.39 for DIN and 1.19–1.39 for chlorophyll profiles, 1.07–1.40 for surface chlorophyll, and 1.01–1.40 for depth-integrated chlorophyll). Among the five stations, the most reliable ensembles are obtained for the oligotrophic station ALOHA (for the surface and integrated chlorophyll and bloom peak height), for coastal station L4 (for inter-annual mean), and for the abyssal plain station PAP (for bloom peak height). Overall our study provides a novel way to generate a realistic ensemble of a biogeochemical model by perturbing the model equations and parameterizations, which will be helpful for the probabilistic predictions.

scholarly journals Reduced carbon cycle resilience across the Palaeocene–Eocene Thermal Maximum

2018 ◽  
Vol 14 (10) ◽  
pp. 1515-1527 ◽  
Author(s):  
David I. Armstrong McKay ◽  
Timothy M. Lenton
Keyword(s):  
Organic Carbon ◽  
Carbon Cycle ◽  
Deep Ocean ◽  
Tipping Point ◽  
Tipping Points ◽  
Carbon Burial ◽  
Thermal Maximum ◽  
Organic Carbon Burial ◽  
Carbon Release ◽  
Hyperthermal Events

Abstract. Several past episodes of rapid carbon cycle and climate change are hypothesised to be the result of the Earth system reaching a tipping point beyond which an abrupt transition to a new state occurs. At the Palaeocene–Eocene Thermal Maximum (PETM) at ∼56 Ma and at subsequent hyperthermal events, hypothesised tipping points involve the abrupt transfer of carbon from surface reservoirs to the atmosphere. Theory suggests that tipping points in complex dynamical systems should be preceded by critical slowing down of their dynamics, including increasing temporal autocorrelation and variability. However, reliably detecting these indicators in palaeorecords is challenging, with issues of data quality, false positives, and parameter selection potentially affecting reliability. Here we show that in a sufficiently long, high-resolution palaeorecord there is consistent evidence of destabilisation of the carbon cycle in the ∼1.5 Myr prior to the PETM, elevated carbon cycle and climate instability following both the PETM and Eocene Thermal Maximum 2 (ETM2), and different drivers of carbon cycle dynamics preceding the PETM and ETM2 events. Our results indicate a loss of “resilience” (weakened stabilising negative feedbacks and greater sensitivity to small shocks) in the carbon cycle before the PETM and in the carbon–climate system following it. This pre-PETM carbon cycle destabilisation may reflect gradual forcing by the contemporaneous North Atlantic Volcanic Province eruptions, with volcanism-driven warming potentially weakening the organic carbon burial feedback. Our results are consistent with but cannot prove the existence of a tipping point for abrupt carbon release, e.g. from methane hydrate or terrestrial organic carbon reservoirs, whereas we find no support for a tipping point in deep ocean temperature.

scholarly journals Methods to evaluate CaCO<sub>3</sub> cycle modules in coupled global biogeochemical ocean models

2014 ◽  
Vol 7 (5) ◽  
pp. 2393-2408 ◽  
Author(s):  
W. Koeve ◽  
O. Duteil ◽  
A. Oschlies ◽  
P. Kähler ◽  
J. Segschneider
Keyword(s):  
Organic Matter ◽  
Carbon Cycle ◽  
Numerical Models ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Biogeochemical Processes ◽  
Data Set ◽  
Ocean Physics ◽  
The Difference ◽  
Ocean Carbon

Abstract. The marine CaCO3 cycle is an important component of the oceanic carbon system and directly affects the cycling of natural and the uptake of anthropogenic carbon. In numerical models of the marine carbon cycle, the CaCO3 cycle component is often evaluated against the observed distribution of alkalinity. Alkalinity varies in response to the formation and remineralization of CaCO3 and organic matter. However, it also has a large conservative component, which may strongly be affected by a deficient representation of ocean physics (circulation, evaporation, and precipitation) in models. Here we apply a global ocean biogeochemical model run into preindustrial steady state featuring a number of idealized tracers, explicitly capturing the model's CaCO3 dissolution, organic matter remineralization, and various preformed properties (alkalinity, oxygen, phosphate). We compare the suitability of a variety of measures related to the CaCO3 cycle, including alkalinity (TA), potential alkalinity and TA*, the latter being a measure of the time-integrated imprint of CaCO3 dissolution in the ocean. TA* can be diagnosed from any data set of TA, temperature, salinity, oxygen and phosphate. We demonstrate the sensitivity of total and potential alkalinity to the differences in model and ocean physics, which disqualifies them as accurate measures of biogeochemical processes. We show that an explicit treatment of preformed alkalinity (TA0) is necessary and possible. In our model simulations we implement explicit model tracers of TA0 and TA*. We find that the difference between modelled true TA* and diagnosed TA* was below 10% (25%) in 73% (81%) of the ocean's volume. In the Pacific (and Indian) Oceans the RMSE of A* is below 3 (4) mmol TA m−3, even when using a global rather than regional algorithms to estimate preformed alkalinity. Errors in the Atlantic Ocean are significantly larger and potential improvements of TA0 estimation are discussed. Applying the TA* approach to the output of three state-of-the-art ocean carbon cycle models, we demonstrate the advantage of explicitly taking preformed alkalinity into account for separating the effects of biogeochemical processes and circulation on the distribution of alkalinity. In particular, we suggest to use the TA* approach for CaCO3 cycle model evaluation.

scholarly journals Presence of <i>Prochlorococcus</i> in the aphotic waters of the western Pacific Ocean

2013 ◽  
Vol 10 (6) ◽  
pp. 9345-9371 ◽  
Author(s):  
N. Jiao ◽  
T. Luo ◽  
R. Zhang ◽  
W. Yan ◽  
Y. Lin ◽  
...  
Keyword(s):  
Pacific Ocean ◽  
Organic Carbon ◽  
Euphotic Zone ◽  
Western Pacific ◽  
Global Ocean ◽  
Western Pacific Ocean ◽  
Carbon Export ◽  
Carbon Pump ◽  
Primary Producer ◽  
The Western Pacific

Abstract. Prochlorococcus, the smallest but most abundant marine primary producer, plays an important role in carbon cycling of the global ocean. As a phototroph, Prochlorococcus is thought to be confined to the euphotic zone, with commonly observed maximum depths of ∼150–200 m. But here we show, using flow cytometry and cellular ribosomal content, for the first time the presence of abundant and active Prochlorococcus in the dark ocean ("deep Prochlorococcus" hereafter). Intensive studies at the Luzon strait in the western Pacific Ocean show that the deep Prochlorococcus populations are exported from the euphotic zone. Multiple physical processes including internal solitary waves could be responsible for the transportation. The unexpected abundance of the tiny phototrophs in the dark ocean reveals a novel mechanism for picoplankton carbon export other than the known mechanisms such as sinking of phytodetritus and aggregates or grazing-mediated transportation. Such direct transportation of picoplanktonic phototrophs from surface to deep waters is poorly understood, but could significantly contribute to both the biological pump (through particulate organic carbon) and the microbial carbon pump (through release of dissolved organic carbon from microbial processes) for carbon sequestration in the ocean.

scholarly journals Simulating the growth and distribution of planktic foraminifer using an ecophysiological multi-species model

2011 ◽  
Vol 8 (1) ◽  
pp. 1-49
Author(s):  
F. Lombard ◽  
L. Labeyrie ◽  
E. Michel ◽  
L. Bopp ◽  
E. Cortijo ◽  
...  
Keyword(s):  
Growth Rates ◽  
Food Concentration ◽  
Growth Potential ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Model Parameters ◽  
Field Observations ◽  
Lower Efficiency ◽  
Data Set ◽  
Chl A

Abstract. We present an eco-physiological model reproducing the growth of eight foraminifer species (Neogloboquadrina pachyderma, Neogloboquadrina incompta, Neogloboquadrina dutertrei, Globigerina bulloides, Globigerinoides ruber, Globigerinoides sacculifer, Globigerinella siphonifera and Orbulina universa). By using the main physiological rates of foraminifers (nutrition, respiration, symbiotic photosynthesis), this model estimates their growth as a function of temperature, light availability, and food concentration. Model parameters are directly derived or calibrated from experimental observations and only the influence of food concentration (estimated via chl-a concentration) was calibrated against field observations. Growth rates estimated from the model show positive correlation with observed abundance from plankton net data suggesting close coupling between individual and assemblage growth rates. This observation was used to directly estimate potential abundance from the model-derived growth. Using satellite data, the model simulate the dominant foraminifer with a 70.5% efficiency when compared to a data set of 576 field observations worldwide. Using outputs of a biogeochemical model of the global ocean (PISCES) instead of satellite images as forcing variables gives also good results, but with lower efficiency (58.9%). The model also correctly reproduces the relative worldwide abundance and the diversity of the eight species when compared to core tops observations both using satellite and PISCES data. This model allows prediction of the season and water depth at which each species has its highest growth potential. This offers promising perspectives for both an improved quantification of paleoceanographic reconstructions and for a better understanding of the foraminiferal role in the marine carbon cycle.

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