biogeochemical model
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2022 ◽  
Author(s):  
Yanda Ou ◽  
Z. George Xue

Abstract. A three-dimensional coupled hydrodynamic–biogeochemical model with N, P, Si cycles and multiple phytoplankton and zooplankton functional groups was developed and applied to the Gulf of Mexico to study bottom dissolved oxygen dynamics. A 15-year hindcast was achieved covering the period of 2006–2020. Extensive model validation against in situ data demonstrates that the model is capable of reproducing vertical distributions of dissolved oxygen (DO), frequency distributions of hypoxia thickness, spatial distributions of bottom DO concentration and interannual variations of hypoxic area. The impacts of river plume and along-shore currents on bottom DO dynamics were examined based on multiyear bottom DO climatology, the corresponding long-term trends, and interannual variability. Model results suggest that mechanisms of bottom hypoxia developments are different between the west and east Louisiana–Texas Shelf waters. The mid-Atchafalaya nearshore (10–20 m) region firstly suffers from hypoxia in May, followed by the west-Mississippi nearshore region in June. Hypoxic waters expand in the following months and eventually merge in August. Sediment oxygen consumption (SOC) and water stratification (measured by potential energy anomaly, PEA) are two main factors modulating the variability of bottom DO concentration. Generalized Boosted Regression Models provide analysis of the relative importance of PEA and SOC. The analysis indicates that SOC is the main regulator in nearshore regions, and water stratification outcompetes the sedimentary biochemical processes in the offshore (20–50 m) regions. A strong quadratic relationship was found between hypoxic volume and hypoxic area, which suggests that the volume mostly results from the low DO in bottom water and can be potentially estimated based on the hypoxic area.


2022 ◽  
Author(s):  
Chia-Te Chien ◽  
Jonathan V. Durgadoo ◽  
Dana Ehlert ◽  
Ivy Frenger ◽  
David P. Keller ◽  
...  

Abstract. The consideration of marine biogeochemistry is essential for simulating the carbon cycle in an Earth system model. Here we present the implementation and evaluation of a marine biogeochemical model, Model of Oceanic Pelagic Stoichiometry (MOPS) in the Flexible Ocean and Climate Infrastructure (FOCI) climate model. FOCI-MOPS enables the simulation of marine biological processes, the marine carbon, nitrogen and oxygen cycles, air-sea gas exchange of CO2 and O2, and simulations with prescribed atmospheric CO2 or CO2 emissions. A series of experiments covering the historical period (1850–2014) were performed following the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP6 (Coupled Model Intercomparison Project 6) protocols. Overall, modelled biogeochemical tracer distributions and fluxes, as well as transient evolution in surface air temperature, air-sea CO2 fluxes, and changes of ocean carbon and heat, are in good agreement with observations. Modelled inorganic and organic tracer distributions are quantitatively evaluated by statistically-derived metrics. Results of the FOCI-MOPS model, also including sea surface temperature, surface pH, oxygen (100–600 m), nitrate (0–100 m), and primary production, are within the range of other CMIP6 model results. Overall, the evaluation of FOCI-MOPS indicates its suitability for Earth climate system simulations.


2022 ◽  
Author(s):  
Laique Merlin Djeutchouang ◽  
Nicolette Chang ◽  
Luke Gregor ◽  
Marcello Vichi ◽  
Pedro Manuel Scheel Monteiro

Abstract. The Southern Ocean is a complex system yet is sparsely sampled in both space and time. These factors raise questions about the confidence in present sampling strategies and associated machine learning (ML) reconstructions. Previous studies have not yielded a clear understanding of the origin of uncertainties and biases for the reconstructions of the partial pressure of carbon dioxide (pCO2) at the surface ocean (pCO2ocean). Here, we examine these questions by investigating the sensitivity of pCO2ocean reconstruction uncertainties and biases to a series of semi-idealized observing system simulation experiments (OSSEs) that simulate spatio-temporal sampling scales of surface ocean pCO2 in ways that are comparable to ocean CO2 observing platforms (Ship, Waveglider, Carbon-float, Saildrone). These experiments sampled a high spatial resolution (±10 km) coupled physical and biogeochemical model (NEMO-PISCES) within a sub-domain representative of the Sub-Antarctic and Polar Frontal Zones in the Southern Ocean. The reconstructions were done using a two-member ensemble approach that consisted of two machine learning (ML) methods, (1) the feed-forward neural network and (2) the gradient boosting machines. With the baseline observations being from the simulated ships mimicking observations from the Surface Ocean CO2 Atlas (SOCAT), we applied to each of the scale-sampling simulation scenarios the two-member ensemble method ML2, to reconstruct the full sub-domain pCO2ocean and assess the reconstruction skill through a statistical comparison of reconstructed pCO2ocean and model domain mean. The analysis shows that uncertainties and biases for pCO2ocean reconstructions are very sensitive to both the spatial and temporal scales of pCO2 sampling in the model domain. The four key findings from our investigation are the following: (1) improving ML-based pCO2 reconstructions in the Southern Ocean requires simultaneous high resolution observations of the meridional and the seasonal cycle (< 3 days) of pCO2ocean; (2) Saildrones stand out as the optimal platforms to simultaneously address these requirements; (3) Wavegliders with hourly/daily resolution in pseudo-mooring mode improve on Carbon-floats (10-day period), which suggests that sampling aliases from the low temporal frequency have a greater negative impact on their uncertainties, biases and reconstruction means; and (4) the present summer seasonal sampling biases in SOCAT data in the Southern Ocean may be behind a significant winter bias in the reconstructed seasonal cycle of pCO2ocean.


2021 ◽  
Author(s):  
Le Zhang ◽  
Z. George Xue

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.


2021 ◽  
Author(s):  
Dóra Hidy ◽  
Zoltán Barcza ◽  
Roland Hollós ◽  
Laura Dobor ◽  
Tamás Ács ◽  
...  

Abstract. Terrestrial biogeochemical models are essential tools to quantify climate-carbon cycle feedback and plant-soil relations from local to global scale. In this study, theoretical basis is provided for the latest version of Biome-BGCMuSo biogeochemical model (version 6.2). Biome-BGCMuSo is a branch of the original Biome-BGC model with a large number of developments and structural changes. Earlier model versions performed poorly in terms of soil water content (SWC) dynamics in different environments. Moreover, lack of detailed nitrogen cycle representation was a major limitation of the model. Since problems associated with these internal drivers might influence the final results and parameter estimation, additional structural improvements were necessary. During the developments we took advantage of experiences from the crop modeller community where internal process representation has a long history. In this paper the improved soil hydrology and soil carbon/nitrogen cycle calculation methods are described in detail. Capabilities of the Biome-BGCMuSo v6.2 model are demonstrated via case studies focusing on soil hydrology and soil organic carbon content estimation. Soil hydrology related results are compared to observation data from an experimental lysimeter station. The results indicate improved performance for Biome-BGCMuSo v6.2 compared to v4.0 (explained variance increased from 0.121 to 0.8 for SWC, and from 0.084 to 0.46 for soil evaporation; bias changed from −0.047 to 0.007 m3 m−3 for SWC, and from −0.68 mm day−1 to −0.2 mm day−1 for soil evaporation). Sensitivity analysis and optimization of the decomposition scheme is presented to support practical application of the model. The improved version of Biome-BGCMuSo has the ability to provide more realistic soil hydrology representation and nitrification/denitrification process estimation which represents a major milestone.


2021 ◽  
Vol 8 ◽  
Author(s):  
Tarang Khangaonkar ◽  
Adi Nugraha ◽  
Su Kyong Yun ◽  
Lakshitha Premathilake ◽  
Julie E. Keister ◽  
...  

Effects and impacts of the Northeast Pacific marine heatwave of 2014–2016 on the inner coastal estuarine waters of the Salish Sea were examined using a combination of monitoring data and an established three-dimensional hydrodynamic and biogeochemical model of the region. The anomalous high temperatures reached the U.S. Pacific Northwest continental shelf toward the end of 2014 and primarily entered the Salish Sea waters through an existing strong estuarine exchange. Elevated temperatures up to + 2.3°C were observed at the monitoring stations throughout 2015 and 2016 relative to 2013 before dissipating in 2017. The hydrodynamic and biogeochemical responses to this circulating high-temperature event were examined using the Salish Sea Model over a 5-year window from 2013 to 2017. Responses of conventional water-quality indicator variables, such as temperature and salinity, nutrients and phytoplankton, zooplankton, dissolved oxygen, and pH, were evaluated relative to a baseline without the marine heatwave forcing. The simulation results relative to 2014 show an increase in biological activity (+14%, and 6% Δ phytoplankton biomass, respectively) during the peak heatwave year 2015 and 2016 propagating toward higher zooplankton biomass (+14%, +18% Δ mesozooplankton biomass). However, sensitivity tests show that this increase was a direct result of higher freshwater and associated nutrient loads accompanied by stronger estuarine exchange with the Pacific Ocean rather than warming due to the heatwave. Strong vertical circulation and mixing provided mitigation with only ≈+0.6°C domain-wide annual average temperature increase within Salish Sea, and served as a physical buffer to keep waters cooler relative to the continental shelf during the marine heatwave.


2021 ◽  
Vol 8 ◽  
Author(s):  
Vivek Seelanki ◽  
Vimlesh Pant

The unprecedented nationwide lockdown due to the ‘coronavirus disease 2019’ (COVID-19) affected humans and the environment in different ways. It provided an opportunity to examine the effect of reduced transportation and other anthropogenic activities on the environment. In the current study, the impact of lockdown on chlorophyll-a (Chl-a) concentration, an index of primary productivity, over the northern Indian Ocean (IO), is investigated using the observations and a physical-biogeochemical model. The statistics of model validation against observations shows a correlation coefficient of 0.85 (0.89), index of agreement as 0.90 (0.91). Root mean square error of 0.45°C (0.50°C) for sea surface temperature over the Bay of Bengal (BoB) (Arabian Sea, AS) is observed. The model results are analyzed to understand the upper-oceanic physical and biological processes during the lockdown. A comparison of the observed and model-simulated data during the lockdown period (March–June, 2020) and pre-pandemic period (March–June, 2019) shows significant differences in the physical (temperature and salinity) and biogeochemical (Chl-a concentration, nutrient concentration, and dissolved oxygen) parameters over the western AS, western BoB, and regions of Sri Lanka. During the pandemic, the reduced anthropogenic activities lead to a decrease in Chl-a concentration in the coastal regions of western AS and BoB. The enhanced aerosol/dust transport due to stronger westerly winds enhanced phytoplankton biomass in the western Arabian Sea (WAS) in May–June of the pandemic period.


2021 ◽  
Vol 18 (23) ◽  
pp. 6213-6227
Author(s):  
Jenny Hieronymus ◽  
Kari Eilola ◽  
Malin Olofsson ◽  
Inga Hense ◽  
H. E. Markus Meier ◽  
...  

Abstract. Dense blooms of filamentous diazotrophic cyanobacteria are formed every summer in the Baltic Sea. These autotrophic organisms may bypass nitrogen limitation by performing nitrogen fixation, which also governs surrounding organisms by increasing bioavailable nitrogen. The magnitude of the nitrogen fixation is important to estimate from a management perspective since this might counteract eutrophication reduction measures. Here, a cyanobacteria life cycle model has been implemented for the first time in a high-resolution 3D coupled physical and biogeochemical model of the Baltic Sea, spanning the years 1850–2008. The explicit consideration of life cycle dynamics and transitions significantly improves the representation of the cyanobacterial phenological patterns compared to earlier 3D modeling efforts. Now, the rapid increase and decrease in cyanobacteria in the Baltic Sea are well captured, and the seasonal timing is in concert with observations. The current improvement also had a large effect on the nitrogen fixation load and is now in agreement with estimates based on in situ measurements. By performing four phosphorus sensitivity runs, we demonstrate the importance of both organic and inorganic phosphorus availability for historical cyanobacterial biomass estimates. The model combination can be used to continuously predict internal nitrogen loads via nitrogen fixation in Baltic Sea ecosystem management, which is of extra importance in a future ocean with changed conditions for the filamentous cyanobacteria.


2021 ◽  
Vol 14 (12) ◽  
pp. 7255-7285
Author(s):  
Karin Kvale ◽  
David P. Keller ◽  
Wolfgang Koeve ◽  
Katrin J. Meissner ◽  
Christopher J. Somes ◽  
...  

Abstract. We describe and test a new model of biological marine silicate cycling, implemented in the Kiel Marine Biogeochemical Model version 3 (KMBM3), embedded in the University of Victoria Earth System Climate Model (UVic ESCM) version 2.9. This new model adds diatoms, which are a key component of the biological carbon pump, to an existing ecosystem model. This new model combines previously published parameterizations of a diatom functional type, opal production and export with a novel, temperature-dependent dissolution scheme. Modelled steady-state biogeochemical rates, carbon and nutrient distributions are similar to those found in previous model versions. The new model performs well against independent ocean biogeochemical indicators and captures the large-scale features of the marine silica cycle to a degree comparable to similar Earth system models. Furthermore, it is computationally efficient, allowing both fully coupled, long-timescale transient simulations and “offline” transport matrix spinups. We assess the fully coupled model against modern ocean observations, the historical record starting from 1960 and a business-as-usual atmospheric CO2 forcing to the year 2300. The model simulates a global decline in net primary production (NPP) of 1.4 % having occurred since the 1960s, with the strongest declines in the tropics, northern midlatitudes and Southern Ocean. The simulated global decline in NPP reverses after the year 2100 (forced by the extended RCP8.5 CO2 concentration scenario), and NPP returns to 98 % of the pre-industrial rate by 2300. This recovery is dominated by increasing primary production in the Southern Ocean, mostly by calcifying phytoplankton. Large increases in calcifying phytoplankton in the Southern Ocean offset a decline in the low latitudes, producing a global net calcite export in 2300 that varies only slightly from pre-industrial rates. Diatom distribution moves southward in our simulations, following the receding Antarctic ice front, but diatoms are outcompeted by calcifiers across most of their pre-industrial Southern Ocean habitat. Global opal export production thus drops to 75 % of its pre-industrial value by 2300. Model nutrients such as phosphate, silicate and nitrate build up along the Southern Ocean particle export pathway, but dissolved iron (for which ocean sources are held constant) increases in the upper ocean. This different behaviour of iron is attributed to a reduction of low-latitude NPP (and consequently, a reduction in both uptake and export and particle, including calcite scavenging), an increase in seawater temperatures (raising the solubility of particulate iron) and stratification that “traps” the iron near the surface. These results are meant to serve as a baseline for sensitivity assessments to be undertaken with this model in the future.


2021 ◽  
Vol 18 (23) ◽  
pp. 6147-6166
Author(s):  
Anna Teruzzi ◽  
Giorgio Bolzon ◽  
Laura Feudale ◽  
Gianpiero Cossarini

Abstract. Data assimilation has led to advancements in biogeochemical modelling and scientific understanding of the ocean. The recent operational availability of data from BGC-Argo (biogeochemical Argo) floats, which provide valuable insights into key vertical biogeochemical processes, stands to further improve biogeochemical modelling through assimilation schemes that include float observations in addition to traditionally assimilated satellite data. In the present work, we demonstrate the feasibility of joint multi-platform assimilation in realistic biogeochemical applications by presenting the results of 1-year simulations of Mediterranean Sea biogeochemistry. Different combinations of satellite chlorophyll data and BGC-Argo nitrate and chlorophyll data have been tested, and validation with respect to available independent non-assimilated and assimilated (before the assimilation) observations showed that assimilation of both satellite and float observations outperformed the assimilation of platforms considered individually. Moreover, the assimilation of BGC-Argo data impacted the vertical structure of nutrients and phytoplankton in terms of deep chlorophyll maximum depth, intensity, and nutricline depth. The outcomes of the model simulation assimilating both satellite data and BGC-Argo data provide a consistent picture of the basin-wide differences in vertical features associated with summer stratified conditions, describing a relatively high variability between the western and eastern Mediterranean, with thinner and shallower but intense deep chlorophyll maxima associated with steeper and narrower nutriclines in the western Mediterranean.


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