scholarly journals Downscaling CMIP6 Global Solutions to Regional Ocean Carbon Model: Connecting the Mississippi, Gulf of Mexico, and Global Ocean

2021 ◽  
Author(s):  
Le Zhang ◽  
Z. George Xue
Keyword(s):  
Gulf Of Mexico ◽  
Carbon Sink ◽  
Biological Activities ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Spatial And Temporal Patterns ◽  
Saturation State ◽  
Biogeochemical Models ◽  
Ocean Carbon ◽  
Carbon System

Abstract. Coupled physical-biogeochemical models can significantly reduce uncertainties in estimating the spatial and temporal patterns of the ocean carbon system. Challenges of applying a coupled physical-biogeochemical model in the regional ocean include the reasonable prescription of carbon model boundary conditions, lack of in situ observations, and the oversimplification of certain biogeochemical processes. In this study, we applied a coupled physical-biogeochemical model (Regional Ocean Modelling System, ROMS) to the Gulf of Mexico (GoM) and achieved an unprecedented 20-year high-resolution (5 km, 1/22°) hindcast covering the period of 2000–2019. The model’s biogeochemical cycle is driven by the Coupled Model Intercomparison Project 6-Community Earth System Model 2 products (CMIP6-CESM2) and incorporates the dynamics of dissolved organic carbon (DOC) pools as well as the formation and dissolution of carbonate minerals. Model outputs include generally interested carbon system variables, such as pCO2, pH, aragonite saturation state (ΩArag), calcite saturation state (ΩCalc), CO2 air-sea flux, carbon burial rate, etc. The model’s robustness is evaluated via extensive model-data comparison against buoy, remote sensing-based Machine Learning (ML) predictions, and ship-based measurements. Model results reveal that the GoM water has been experiencing an ~ 0.0016 yr−1 decrease in surface pH over the past two decades, accompanied by a ~ 1.66 µatm yr−1 increase in sea surface pCO2. The air-sea CO2 exchange estimation confirms that the river-dominated northern GoM is a substantial carbon sink. The open water of GoM, affected mainly by the thermal effect, is a carbon source during summer and a carbon sink for the rest of the year. Sensitivity experiments are conducted to evaluate the impacts from river inputs and the global ocean via model boundaries. Our results show that the coastal ocean carbon cycle is dominated by enormous carbon inputs from the Mississippi River and nutrient-stimulated biological activities, and the carbon system condition of the open ocean is primarily driven by inputs from the Caribbean Sea via Yucatan Channel.

The Southern Ocean carbon sink 1985-2018: first results of the RECCAP2 project

2021 ◽  
Author(s):  
Judith Hauck ◽  
Luke Gregor ◽  
Cara Nissen ◽  
Eric Mortenson ◽  
Seth Bushinsky ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Seasonal Cycle ◽  
Carbon Sink ◽  
Global Ocean ◽  
Biogeochemical Models ◽  
Wide Range ◽  
Data Products ◽  
First Results ◽  
Ocean Carbon ◽  
Indian Sector

<p>The Southern Ocean is the main gateway for anthropogenic CO<sub>2</sub> into the ocean owing to the upwelling of old water masses with low anthropogenic CO<sub>2</sub> concentration, and the transport of the newly equilibrated surface waters into the ocean interior through intermediate, deep and bottom water formation. Here we present first results of the Southern Ocean chapter of RECCAP2, which is the Global Carbon Project’s second systematic study on Regional Carbon Cycle Assessment and Processes. In the Southern Ocean chapter, we aim to assess the Southern Ocean carbon sink 1985-2018 from a wide range of available models and data sets, and to identify patterns of regional and temporal variability, model limitations and future challenges.</p><p>We gathered global and regional estimates of the air-sea CO<sub>2</sub> flux over the period 1985-2018 from global ocean biogeochemical models, surface pCO<sub>2</sub>-based data products, and data-assimilated models. The analysis on the Southern Ocean quantified geographical patterns in the annual mean and seasonal amplitude of air-sea CO<sub>2</sub> flux, with results presented here aggregated to the level of large-scale ocean biomes.</p><p>Considering the suite of observed and modelled estimates, we found that the subtropical seasonally stratified (STSS) biome stands out with the largest air-sea CO<sub>2</sub> flux per area and a seasonal cycle with largest ocean uptake of CO<sub>2</sub> in winter, whereas the ice (ICE) biome is characterized by a large ensemble spread and a pronounced seasonal cycle with the largest ocean uptake of CO<sub>2</sub> in summer. Connecting these two, the subpolar seasonally stratified (SPSS) biome has intermediate flux densities (flux per area), and most models have difficulties simulating the seasonal cycle with strongest uptake during the summer months.</p><p>Our analysis also reveals distinct differences between the Atlantic, Pacific and Indian sectors of the aforementioned biomes. In the STSS, the Indian sector contributes most to the ocean carbon sink, followed by the Atlantic and then Pacific sectors. This hierarchy is less pronounced in the models than in the data-products. In the SPSS, only the Atlantic sector exhibits net CO<sub>2</sub> uptake in all years, likely linked to strong biological production. In the ICE biome, the Atlantic and Pacific sectors take up more CO<sub>2</sub> than the Indian sector, suggesting a potential role of the Weddell and Ross Gyres.</p><p>These first results confirm the global relevance of the Southern Ocean carbon sink and highlight the strong regional and interannual variability of the Southern Ocean carbon uptake in connection to physical and biogeochemical processes.</p>

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 Wind-driven changes in the ocean carbon sink

2014 ◽  
Vol 11 (21) ◽  
pp. 6107-6117 ◽  
Author(s):  
N. C. Swart ◽  
J. C. Fyfe ◽  
O. A. Saenko ◽  
M. Eby
Keyword(s):  
Carbon Sink ◽  
Surface Wind ◽  
Extended Period ◽  
Meridional Overturning Circulation ◽  
Biogeochemical Model ◽  
Model Driven ◽  
Ocean Biogeochemical Model ◽  
Meridional Overturning ◽  
Ocean Carbon ◽  
Induced Changes

Abstract. We estimate changes in the historical ocean carbon sink and their uncertainty using an ocean biogeochemical model driven with wind forcing from six different reanalyses and using two different eddy parameterization schemes. First, we quantify wind-induced changes over the extended period from 1871 to 2010 using the 20th Century Reanalysis winds. Consistent with previous shorter-term studies, we find that the wind changes act to reduce the ocean carbon sink, but the wind-induced trends are subject to large uncertainties. One major source of uncertainty is the parameterization of mesoscale eddies in our coarse resolution simulations. Trends in the Southern Ocean residual meridional overturning circulation and the globally integrated surface carbon flux over 1950 to 2010 are about 2.5 times smaller when using a variable eddy transfer coefficient than when using a constant coefficient in this parameterization. A second major source of uncertainty arises from disagreement on historical wind trends. By comparing six reanalyses over 1980 to 2010, we show that there are statistically significant differences in estimated historical wind trends, which vary in both sign and magnitude amongst the products. Through simulations forced with these reanalysis winds, we show that the influence of historical wind changes on ocean carbon uptake is highly uncertain, and the resulting trends depend on the choice of surface wind product.

scholarly journals Seasonal patterns in phytoplankton biomass across the northern and deep Gulf of Mexico: a numerical model study

2018 ◽  
Vol 15 (11) ◽  
pp. 3561-3576 ◽  
Author(s):  
Fabian A. Gomez ◽  
Sang-Ki Lee ◽  
Yanyun Liu ◽  
Frank J. Hernandez Jr. ◽  
Frank E. Muller-Karger ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Primary Production ◽  
Phytoplankton Biomass ◽  
Mississippi Delta ◽  
Three Dimensional ◽  
Rate Of Change ◽  
Integrated Analysis ◽  
Biogeochemical Model ◽  
Seasonal Patterns ◽  
Biogeochemical Models

Abstract. Biogeochemical models that simulate realistic lower-trophic-level dynamics, including the representation of main phytoplankton and zooplankton functional groups, are valuable tools for improving our understanding of natural and anthropogenic disturbances in marine ecosystems. Previous three-dimensional biogeochemical modeling studies in the northern and deep Gulf of Mexico (GoM) have used only one phytoplankton and one zooplankton type. To advance our modeling capability of the GoM ecosystem and to investigate the dominant spatial and seasonal patterns of phytoplankton biomass, we configured a 13-component biogeochemical model that explicitly represents nanophytoplankton, diatoms, micro-, and mesozooplankton. Our model outputs compare reasonably well with observed patterns in chlorophyll, primary production, and nutrients over the Louisiana–Texas shelf and deep GoM region. Our model suggests silica limitation of diatom growth in the deep GoM during winter and near the Mississippi delta during spring. Model nanophytoplankton growth is weakly nutrient limited in the Mississippi delta year-round and strongly nutrient limited in the deep GoM during summer. Our examination of primary production and net phytoplankton growth from the model indicates that the biomass losses, mainly due to zooplankton grazing, play an important role in modulating the simulated seasonal biomass patterns of nanophytoplankton and diatoms. Our analysis further shows that the dominant physical process influencing the local rate of change of model phytoplankton is horizontal advection in the northern shelf and vertical mixing in the deep GoM. This study highlights the need for an integrated analysis of biologically and physically driven biomass fluxes to better understand phytoplankton biomass phenologies in the GoM.

scholarly journals Decadal trends in the ocean carbon sink

2019 ◽  
pp. 201900371 ◽  
Author(s):  
Tim DeVries ◽  
Corinne Le Quéré ◽  
Oliver Andrews ◽  
Sarah Berthet ◽  
Judith Hauck ◽  
...  
Keyword(s):  
Climate Variability ◽  
Decadal Variability ◽  
Carbon Sink ◽  
Carbon Accumulation ◽  
Climate Projections ◽  
Biogeochemical Models ◽  
Ocean Carbon ◽  
Vegetation Models ◽  
Decadal Climate ◽  
Global Vegetation

Measurements show large decadal variability in the rate of CO2 accumulation in the atmosphere that is not driven by CO2 emissions. The decade of the 1990s experienced enhanced carbon accumulation in the atmosphere relative to emissions, while in the 2000s, the atmospheric growth rate slowed, even though emissions grew rapidly. These variations are driven by natural sources and sinks of CO2 due to the ocean and the terrestrial biosphere. In this study, we compare three independent methods for estimating oceanic CO2 uptake and find that the ocean carbon sink could be responsible for up to 40% of the observed decadal variability in atmospheric CO2 accumulation. Data-based estimates of the ocean carbon sink from pCO2 mapping methods and decadal ocean inverse models generally agree on the magnitude and sign of decadal variability in the ocean CO2 sink at both global and regional scales. Simulations with ocean biogeochemical models confirm that climate variability drove the observed decadal trends in ocean CO2 uptake, but also demonstrate that the sensitivity of ocean CO2 uptake to climate variability may be too weak in models. Furthermore, all estimates point toward coherent decadal variability in the oceanic and terrestrial CO2 sinks, and this variability is not well-matched by current global vegetation models. Reconciling these differences will help to constrain the sensitivity of oceanic and terrestrial CO2 uptake to climate variability and lead to improved climate projections and decadal climate predictions.

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 Using satellite-derived backscattering coefficients in addition to chlorophyll data to constrain a simple marine biogeochemical model

2009 ◽  
Vol 6 (2) ◽  
pp. 4201-4231
Author(s):  
H. Kettle
Keyword(s):  
Carbon Cycle ◽  
Biogeochemical Model ◽  
Model Parameters ◽  
Ocean Carbon Cycle ◽  
Empirical Relationships ◽  
Biogeochemical Models ◽  
Ocean Carbon ◽  
Model Tuning ◽  
Different Characteristics ◽  
Satellite Chlorophyll

Abstract. Biogeochemical models of the ocean carbon cycle are frequently validated by, or tuned to, satellite chlorophyll data. However, ocean carbon cycle models are required to accurately model the movement of carbon, not chlorophyll and due to the high variability of the carbon to chlorophyll ratio in phytoplankton, chlorophyll is not a robust proxy for carbon. Using inherent optical property (IOP) inversion algorithms it is now possible to also derive the amount of light backscattered by the upper ocean (bb) which is related to the amount of particulate organic carbon (POC) present. Using empirical relationships between POC and bb, a 1-d biogeochemical model is used to simulate bb at 490 nm thus allowing the model to be compared with either remotely-sensed chlorophyll or bb data. Here I test the hypothesis that using bb in conjunction with chlorophyll data can help to constrain more model parameters than using chlorophyll alone. This is done by tuning the parameters of the biogeochemical model with a genetic algorithm, so that the model is fitted to either chlorophyll or to both chlorophyll and bb data at three sites in the Atlantic with very different characteristics. There are several IOP algorithms available for estimating bb. Four of these are investigated and three of them used for model tuning. The effect of the different bb datasets on the behaviour of the tuned model is examined to ascertain whether the uncertainty in bb is significant. The results show that the addition of bb data can have a large effect on the modelled detritus and that differences in the IOP algorithms are not particularly significant.

Sailing meets Science

2021 ◽  
Author(s):  
Peter Landschützer ◽  
Toste Tanhua ◽  
Stefan Raimund ◽  
Keyword(s):  
High Performance ◽  
Carbon Sink ◽  
Vital Role ◽  
Global Ocean ◽  
Quality Data ◽  
Sensor Technology ◽  
Sink Strength ◽  
Low Weight ◽  
First Results ◽  
Ocean Carbon

&lt;p&gt;The surface partial pressure of carbon dioxide (pCO2) is one of the main quantitates determining the ocean sink strength for CO2 and knowledge of surface ocean pCO2 plays a vital role in monitoring the global carbon budget. However, measuring pCO2 via infrared absorption requires repeated calibration and drift corrections, and therefore ships are still the major platform for these measurements. Given the limited number and availability of pCO2 observations, scientists have fostered collaborations with industrial partners, participating in the Ships of Opportunity (SOOP) program, to collect valuable pCO2 measurements. One fleet, however, has thus far been largely overlooked: sailing yachts. Modern sensor technology to-date allows for low weight and low energy consumption equilibrator systems that can be successfully mounted on recreational and high-performance sailing yachts with good quality data. Here we present the first results from 3 years of autonomous measurements aboard two IMOCA yachts, Seaexplorer -Yacht Club de Monaco (previously Malizia) and Newrest &amp;#8211;Art &amp; Fen&amp;#234;tres using a SubCtech flat membrane equilibrator system. First results indicate that sailing yachts provide crucial high frequency measurements to study open and coastal ocean systems, are well suited to study mesoscale variations in the ocean carbon sink and provide measurements beyond industrial shipping routes (e.g. the Southern Ocean). In summary, sail yachts are a promising way forward in order to complement the current observing system for the global ocean carbon cycle in a changing climate.&lt;/p&gt;

Global ocean biogeochemical modelling with FESOM2-REcoM

2021 ◽  
Author(s):  
Ozgur Gurses ◽  
Judith Hauck ◽  
Moritz Zeising ◽  
Laurent Oziel
Keyword(s):  
Sea Ice ◽  
Finite Volume ◽  
Computational Efficiency ◽  
Ocean Model ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Coupled Models ◽  
Data Set ◽  
Biogeochemical Models ◽  
Mesh Resolution

&lt;p&gt;Marine biogeochemistry models are generally coupled to a physical ocean model. The biases in these coupled models can be attributed to simplified and empirical representation of biogeochemical processes, insufficient spatial mesh resolution which has an impact on the transport and mixing of biogeochemical substances in the ocean, and a deficit of physical parameterizations that intent to mimic unresolved processes such as eddies. Ocean Biogeochemical models based on variable mesh resolution proved to be convenient tools due to their computational efficiency and flexibility. Unlike standard structured-mesh ocean models, the mesh flexibility allows for a realistic representation of eddy dynamics in certain regions. Here, we present preliminary results of the coupling between the Finite-volumE Sea ice-Ocean Model (FESOM2.0) and the biogeochemical model REcoM2 (Regulated Ecosystem Model 2) in a coarse spatial resolution global configuration.&lt;br&gt;Surface maps of the simulated nutrients, chlorophyll a and net primary production (NPP) are comparable to available observational data sets. The control simulation forced with the JRA55-do data set reveals a realistic spatial distribution of nutrients, nanophytoplankton and diatom NPP, carbon stocks and fluxes. &lt;br&gt;FESOM2 utilizes a new dynamical core based on a finite-volume approach. The computational efficiency is about 2-3 times higher than the previous version FESOM1.4, whereas the quality of the simulated ocean and sea ice conditions and representation of biogeochemical variables are comparable in the two models.&amp;#160;Thus, the new coupled model FESOM2- REcoM2 is very promising for ocean biogeochemical modelling applications.&lt;/p&gt;

scholarly journals Swept under the carpet: organic matter burial decreases global ocean biogeochemical model sensitivity to remineralization length scale

2013 ◽  
Vol 10 (12) ◽  
pp. 8401-8422 ◽  
Author(s):  
I. Kriest ◽  
A. Oschlies
Keyword(s):  
Organic Matter ◽  
Numerical Models ◽  
Global Scale ◽  
Heterogeneous Data ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Length Scale ◽  
Benthic Fluxes ◽  
Biogeochemical Models ◽  
Wide Range

Abstract. Although of substantial importance for marine tracer distributions and eventually global carbon, oxygen, and nitrogen fluxes, the interaction between sinking and remineralization of organic matter, benthic fluxes and burial is not always represented consistently in global biogeochemical models. We here aim to investigate the relationships between these processes with a suite of global biogeochemical models, each simulated over millennia, and compared against observed distributions of pelagic tracers and benthic and pelagic fluxes. We concentrate on the representation of sediment–water interactions in common numerical models, and investigate their potential impact on simulated global sediment–water fluxes and nutrient and oxygen distributions. We find that model configurations with benthic burial simulate global oxygen well over a wide range of possible sinking flux parameterizations, making the model more robust with regard to uncertainties about the remineralization length scale. On a global scale, burial mostly affects oxygen in the meso- to bathypelagic zone. While all model types show an almost identical fit to observed pelagic particle flux, and the same sensitivity to particle sinking speed, comparison to observational estimates of benthic fluxes reveals a more complex pattern, but definite interpretation is not straightforward because of heterogeneous data distribution and methodology. Still, evaluating model results against observed pelagic and benthic fluxes of organic matter can complement model assessments based on more traditional tracers such as nutrients or oxygen. Based on a combined metric of dissolved tracers and biogeochemical fluxes, we here identify two model descriptions of burial as suitable candidates for further experiments and eventual model refinements.

Sign in / Sign up

Export Citation Format

Share Document