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.

scholarly journals Swept under the carpet: the effect of organic matter burial in global biogeochemical ocean models

2013 ◽  
Vol 10 (7) ◽  
pp. 10859-10911 ◽  
Author(s):  
I. Kriest ◽  
A. Oschlies
Keyword(s):  
Organic Matter ◽  
Numerical Models ◽  
Global Scale ◽  
Benthic Fluxes ◽  
Biogeochemical Fluxes ◽  
Biogeochemical Models ◽  
Wide Range ◽  
Potential Impact ◽  
Bathypelagic Zone ◽  
Global Carbon

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 and may be influenced by the 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.

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 Defining BGC-Argo-based metrics of ocean health and biogeochemical functioning for the evaluation of global ocean models

2021 ◽  
Author(s):  
Alexandre Mignot ◽  
Hervé Claustre ◽  
Gianpiero Cossarini ◽  
Fabrizio D'Ortenzio ◽  
Elodie Gutknecht ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Dissolved Inorganic Carbon ◽  
Numerical Models ◽  
Co2 Flux ◽  
Global Scale ◽  
Global Ocean ◽  
Argo Floats ◽  
In Situ Data ◽  
Biogeochemical Models ◽  
The Impact

Abstract. Numerical models of ocean biogeochemistry are becoming a major tool to detect and predict the impact of climate change on marine resources and ocean health. Classically, validation of such models relies on comparison with surface quantities from satellite (such as chlorophyll-a concentrations), climatologies, or sparse in situ data (such as cruises observations, and permanent fixed oceanic stations). However, these datasets are not fully suitable to assess how models represent many climate-relevant biogeochemical processes.  These limitations now begin to be overcome with the availability of a large number of vertical profiles of light, pH, oxygen, nitrate, chlorophyll-a concentrations and particulate backscattering acquired by the Biogeochemical-Argo (BGC-Argo) floats network. Additionally, other key biogeochemical variables such as dissolved inorganic carbon and alkalinity, not measured by floats, can be predicted by machine learning-based methods applied to float oxygen concentrations. Here, we demonstrate the use of the global array of BGC-Argo floats for the validation of biogeochemical models at the global scale. We first present 18 key metrics of ocean health and biogeochemical functioning to quantify the success of BGC model simulations. These metrics are associated with the air-sea CO2 flux, the biological carbon pump, oceanic pH, oxygen levels and Oxygen Minimum Zones (OMZs). The metrics are either a depth-averaged quantity or correspond to the depth of a particular feature. We also suggest four diagnostic plots for displaying such metrics.

scholarly journals Evaluating CaCO<sub>3</sub>-cycle modules in coupled global biogeochemical ocean models

2013 ◽  
Vol 6 (4) ◽  
pp. 6117-6155 ◽  
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 remineralisation 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 remineralisation, 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. It 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 modeled true TA* and diagnosed TA* was below 10% (25%) in 73% (81%) of the ocean's volume. In the Pacific (and Indian) Oceans the RMS error of TA* 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.

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

&lt;p&gt;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&lt;sub&gt;2&lt;/sub&gt; flux by drawing down carbon into the ocean interior. This export flux is five times as large as the CO&lt;sub&gt;2&lt;/sub&gt; emitted to the atmosphere by human activities. When carbon is transported from the surface to intermediate and deep ocean, more CO&lt;sub&gt;2 &lt;/sub&gt;can be absorbed at the surface. Therefore, even small variability in sinking organic carbon fluxes can have a large impact on air-sea CO&lt;sub&gt;2&lt;/sub&gt; fluxes, and on the amount of CO&lt;sub&gt;2&lt;/sub&gt; emissions that remain in the atmosphere.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;

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

&lt;p&gt;The Southern Ocean is the main gateway for anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; into the ocean owing to the upwelling of old water masses with low anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; 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&amp;#8217;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.&lt;/p&gt;&lt;p&gt;We gathered global and regional estimates of the air-sea CO&lt;sub&gt;2&lt;/sub&gt; flux over the period 1985-2018 from global ocean biogeochemical models, surface pCO&lt;sub&gt;2&lt;/sub&gt;-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&lt;sub&gt;2&lt;/sub&gt; flux, with results presented here aggregated to the level of large-scale ocean biomes.&lt;/p&gt;&lt;p&gt;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&lt;sub&gt;2&lt;/sub&gt; flux per area and a seasonal cycle with largest ocean uptake of CO&lt;sub&gt;2&lt;/sub&gt; 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&lt;sub&gt;2&lt;/sub&gt; 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.&lt;/p&gt;&lt;p&gt;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&lt;sub&gt;2&lt;/sub&gt; uptake in all years, likely linked to strong biological production. In the ICE biome, the Atlantic and Pacific sectors take up more CO&lt;sub&gt;2&lt;/sub&gt; than the Indian sector, suggesting a potential role of the Weddell and Ross Gyres.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;

The formation, preservation and seismic signatures of chemical heterogeneities in the lower mantle

2020 ◽  
Author(s):  
Anna J. P. Gülcher ◽  
Maxim D. Ballmer ◽  
Paul J. Tackley ◽  
Paula Koelemeijer
Keyword(s):  
Physical Properties ◽  
Lower Mantle ◽  
Numerical Models ◽  
Bulk Composition ◽  
Oceanic Lithosphere ◽  
Global Scale ◽  
Seismic Velocities ◽  
Mantle Dynamics ◽  
Wide Range ◽  
Scientific Challenge

&lt;p&gt;Despite stirring by vigorous convection over billions of years, the Earth&amp;#8217;s lower mantle appears to be chemically heterogeneous on various length scales. Constraining this heterogeneity is key for assessing Earth&amp;#8217;s bulk composition and thermochemical evolution, but remains a scientific challenge that requires cross-disciplinary efforts. On scales below ~1 km, the concept of a &amp;#8220;marble cake&amp;#8221; mantle has gained wide acceptance, emphasising that recycled oceanic lithosphere, deformed into streaks of depleted and enriched compositions, makes up much of the mantle. On larger scales (10s-100s of km), compositional heterogeneity may be preserved by delayed mixing of this marble cake with either intrinsically-dense or intrinsically-strong materials. Intrinsically dense materials may accumulate as piles at the core-mantle boundary, while intrinsically viscous domains (e.g., enhanced in the strong mineral bridgmanite) may survive as &amp;#8220;blobs&amp;#8221; in the mid-mantle for large timescales, such as plums in the mantle &amp;#8220;plum pudding&amp;#8221;&lt;sup&gt;1,2&lt;/sup&gt;. While many studies have explored the formation and preservation of either intrinsically-dense (recycled) or intrinsically-strong (primordial) heterogeneity, only few if any have quantified mantle dynamics in the presence of different types of heterogeneity with distinct physical properties.&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;To address this objective, we use state-of-the-art 2D numerical models of global-scale mantle convection in a spherical-annulus geometry. We explore the effects of the &lt;em&gt;(i)&lt;/em&gt; physical properties of primordial material (density, viscosity), &lt;em&gt;(ii)&lt;/em&gt; temperature/pressure dependency of viscosity, &lt;em&gt;(iii)&lt;/em&gt; lithospheric yielding strength, and &lt;em&gt;(iv)&lt;/em&gt; Rayleigh number on mantle dynamics and mixing. Models predict that primordial heterogeneity is preserved in the lower mantle over &gt;4.5 Gyr as discrete blobs for high intrinsic viscosity contrast (&gt;30x) and otherwise for a wide range of parameters. In turn, recycled oceanic crust is preserved in the lower mantle as &amp;#8220;marble cake&amp;#8221; streaks or piles, particularly in models with a relatively cold and stiff mantle. Importantly, these recycled crustal heterogeneities can co-exist with primordial blobs, with piles often tending to accumulate beneath the primordial domains. This suggests that the modern mantle may be in a hybrid state between the &amp;#8220;marble cake&amp;#8221; and &amp;#8220;plum pudding&amp;#8221; styles.&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;Finally, we put our model predictions in context with recent discoveries from seismology. We calculate synthetic seismic velocities from predicted temperatures and compositions, and compare these synthetics to tomography models, taking into account the limited resolution of seismic tomography. Convection models including preserved bridgmanite-enriched domains along with recycled piles have the potential of reconciling recent seismic observations of lower-mantle heterogeneity&lt;sup&gt;3&lt;/sup&gt; with the geochemical record from ocean-island basalts&lt;sup&gt;4,5&lt;/sup&gt;, and are therefore relevant for assessing Earth&amp;#8217;s bulk composition and long-term evolution.&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; Ballmer et al. (2017), &lt;em&gt;Nat. Geosci&lt;/em&gt;., 10.1038/ngeo2898&lt;br&gt;&lt;sup&gt;2&lt;/sup&gt; G&amp;#252;lcher et al. (in review), &lt;em&gt;EPSL&lt;/em&gt;: Variable dynamic styles of primordial heterogeneity preservation in Earth&amp;#8217;s lower mantle &lt;br&gt;&lt;sup&gt;3&lt;/sup&gt; Waszek et al. (2018), &lt;em&gt;Nat. Comm., &lt;/em&gt;10.1038/s41467-017-02709-4 &lt;br&gt;&lt;sup&gt;4&lt;/sup&gt; Hofmann (1997), &lt;em&gt;Nature, &lt;/em&gt;10.1038/385219a0; &lt;br&gt;&lt;sup&gt;5&lt;/sup&gt; Mundl et al. (2017), &lt;em&gt;Science, &lt;/em&gt;10.1126/science.aal4179&lt;/p&gt;

Evaluating Simplified Numerical Models of Debris-Covered Glaciers

2021 ◽  
Author(s):  
James C. Ferguson ◽  
Tobias Bolch ◽  
Andreas Vieli
Keyword(s):  
Numerical Models ◽  
Spatial Scales ◽  
Global Scale ◽  
Glacier Surface ◽  
Ice Dynamics ◽  
Surface Mass ◽  
Wide Range ◽  
Debris Cover ◽  
Debris Transport ◽  
Modelling Studies

&lt;p&gt;The transient response of debris-covered glaciers to a changing climate is governed by nonlinear feedbacks between ice dynamics, debris transport, and glacier geometry and that act over a wide range of temporal and spatial scales. Current numerical models that are able to accurately represent the relevant physical processes are computationally expensive since they must track the debris transport not only at the glacier surface but also englacially. This makes such models difficult to use for simulations at the regional to global scale.&lt;/p&gt;&lt;p&gt;In order to address this challenge, we developed a fully coupled numerical model that solves both englacial debris transport and ice flow and includes the effect of debris cover on surface ablation. We use this model to evaluate different simplified approaches to modelling debris-covered glaciers. These simplifications include parametrized 1-D debris transport models, parametrized models of surface mass balance that include debris cover effects, and zero-dimensional models. We compare the model performances using a number of tests with an idealized synthetic glacier geometry and a range of forcings, thereby allowing for an evaluation of the relative merits of each approach. A key goal of this work is to provide guidance and tools for modelling studies involving debris cover at the regional to global scale.&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 A derivative-free optimisation method for global ocean biogeochemical models

2021 ◽  
Author(s):  
Sophy Elizabeth Oliver ◽  
Coralia Cartis ◽  
Iris Kriest ◽  
Simon F. B. Tett ◽  
Samar Khatiwala
Keyword(s):  
Global Ocean ◽  
Biogeochemical Model ◽  
Biogeochemical Models ◽  
Derivative Free ◽  
Observational Uncertainty ◽  
Parameter Configuration ◽  
Ocean Biogeochemical Model ◽  
Observational Noise ◽  
Parameter Values ◽  
Earth System Models

Abstract. The performance of global ocean biogeochemical models, and the Earth System Models in which they are embedded, can be improved by systematic calibration of the parameter values against observations. However, such tuning is seldom undertaken as these models are computationally very expensive. Here we investigate the performance of DFO-LS, a local, derivative-free optimisation algorithm which has been designed for computationally expensive models with irregular model-data misfit landscapes typical of biogeochemical models. We use DFO-LS to calibrate six parameters of a relatively complex global ocean biogeochemical model (MOPS) against synthetic dissolved oxygen, inorganic phosphate and inorganic nitrate observations from a reference run of the same model with a known parameter configuration. The performance of DFO-LS is compared with that of CMA-ES, another derivative-free algorithm that was applied in a previous study to the same model in one of the first successful attempts at calibrating a global model of this complexity. We find that DFO-LS successfully recovers 5 of the 6 parameters in approximately 40 evaluations of the misfit function (each one requiring a 3000 year run of MOPS to equilibrium), while CMA-ES needs over 1200 evaluations. Moreover, DFO-LS reached a baseline misfit, defined by observational noise, in just 11–14 evaluations, whereas CMA-ES required approximately 340 evaluations. We also find that the performance of DFO-LS is not significantly affected by observational sparsity, however fewer parameters were successfully optimised in the presence of observational uncertainty. The results presented here suggest that DFO-LS is sufficiently inexpensive and robust to apply to the calibration of complex, global ocean biogeochemical models.

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