Development of the UKESM-TOPAZ Earth System Model (Version 1.0) and Preliminary Evaluation of its Biogeochemical Simulations

AbstractEarth system models (ESMs) comprise various Earth system components and simulate the interactions between these components. ESMs can be used to understand climate feedbacks between physical, chemical, and biological processes and predict future climate. We developed a new ESM, UKESM-TOPAZ, by coupling the UK ESM (UKESM1) and the Tracers of Phytoplankton with Allometric Zooplankton (TOPAZ) biogeochemical module. We then compared the preliminary simulated biogeochemical variables, which were conducted over a period of 70 years, using observational and existing UKESM1 model data. Similar to UKESM1, the newly developed UKESM-TOPAZ closely simulated the relationship between the El Niño-Southern Oscillation and chlorophyll concentration anomalies during the boreal winter. However, there were differences in the chlorophyll distributions in the eastern equatorial Pacific between the two models, which were due to dissolved iron, as this value was higher in UKESM-TOPAZ than in UKESM1. In a mean field analysis, the distributions of the major marine biogeochemical variables in UKESM-TOPAZ (i.e., nitrate, silicate, dissolved oxygen, dissolved inorganic carbon, and alkalinity) were not significantly different from those of UKESM1, likely because the models share the same initial conditions. Our results indicate that TOPAZ has a simulation performance that does not lag behind UKESM1’s basic biogeochemical model (Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration, and Acidification; MEDUSA). The UKESM-TOPAZ model can simulate the variability of the observed Niño 3.4 and 4 indices more closely than UKESM1. Thus, the UKESM-TOPAZ model can be used to deepen our understanding of the Earth system and to estimate ESM uncertainty.

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MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies

Geoscientific Model Development Discussions ◽

10.5194/gmdd-6-1259-2013 ◽

2013 ◽

Vol 6 (1) ◽

pp. 1259-1365 ◽

Cited By ~ 7

Author(s):

A. Yool ◽

E. E. Popova ◽

T. R. Anderson

Keyword(s):

Carbon Cycle ◽

Ocean Acidification ◽

Inorganic Carbon ◽

Dissolved Inorganic Carbon ◽

World Ocean ◽

Ecosystem Dynamics ◽

Full Description ◽

Biogeochemical Model ◽

Intermediate Complexity ◽

Nutrient Utilisation

Abstract. MEDUSA-1.0 (Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification) was developed as an "intermediate complexity" plankton ecosystem model to study the biogeochemical response, and especially that of the so-called "biological pump", to anthropogenically-driven change in the World Ocean (Yool et al., 2011). The base currency in this model was nitrogen from which fluxes of organic carbon, including export to the deep ocean, were calculated by invoking fixed C:N ratios in phytoplankton, zooplankton and detritus. Since the beginning of the industrial era, the atmospheric concentration of carbon dioxide (CO2) has significantly increased above its natural, inter-glacial background concentration. Simulating and predicting the carbon cycle in the ocean in its entirety, including ventilation of CO2 with the atmosphere and the resulting impact of ocean acidification on marine ecosystems, therefore requires that both organic and inorganic carbon be afforded a full representation in the model specification. Here, we introduce MEDUSA-2.0, an expanded successor model which includes additional state variables for dissolved inorganic carbon, alkalinity, dissolved oxygen and detritus carbon (permitting variable C:N in exported organic matter), as well as a simple benthic formulation and extended parameterisations of phytoplankton growth, calcification and detritus remineralisation. A full description of MEDUSA-2.0, including its additional functionality, is provided and a multi-decadal hindcast simulation described (1860–2005), to evaluate the biogeochemical performance of the model.

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Inconsistent strategies to spin up models in CMIP5: implications for ocean biogeochemical model performance assessment

Geoscientific Model Development ◽

10.5194/gmd-9-1827-2016 ◽

2016 ◽

Vol 9 (5) ◽

pp. 1827-1851 ◽

Cited By ~ 41

Author(s):

Roland Séférian ◽

Marion Gehlen ◽

Laurent Bopp ◽

Laure Resplandy ◽

James C. Orr ◽

...

Keyword(s):

Performance Assessment ◽

Initial Conditions ◽

Model Performance ◽

Cmip5 Models ◽

Biogeochemical Model ◽

Earth System ◽

Model Intercomparison ◽

System Models ◽

Marine Biogeochemistry ◽

Earth System Models

Abstract. During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were made to systematically assess the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. In routine assessments model historical hindcasts were compared with available modern biogeochemical observations. However, these assessments considered neither how close modeled biogeochemical reservoirs were to equilibrium nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESMs) contributes to model-to-model differences in the simulated fields. We take advantage of a 500-year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O2, NO3, Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and holds when confronted with a larger ensemble of CMIP5 models. This shows that drift has implications for performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to-model uncertainty. This requires more attention in future model intercomparison exercises in order to provide quantitatively more correct ESM results on marine biogeochemistry and carbon cycle feedbacks.

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

Biogeosciences ◽

10.5194/bg-15-6685-2018 ◽

2018 ◽

Vol 15 (21) ◽

pp. 6685-6711 ◽

Cited By ~ 1

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.

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MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies

Geoscientific Model Development ◽

10.5194/gmd-6-1767-2013 ◽

2013 ◽

Vol 6 (5) ◽

pp. 1767-1811 ◽

Cited By ~ 92

Author(s):

A. Yool ◽

E. E. Popova ◽

T. R. Anderson

Keyword(s):

Carbon Cycle ◽

Ocean Acidification ◽

Inorganic Carbon ◽

Ecosystem Dynamics ◽

Anthropogenic Activity ◽

Full Description ◽

Biogeochemical Model ◽

Diverse Range ◽

Intermediate Complexity ◽

Nutrient Utilisation

Abstract. MEDUSA-1.0 (Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification) was developed as an "intermediate complexity" plankton ecosystem model to study the biogeochemical response, and especially that of the so-called "biological pump", to anthropogenically driven change in the World Ocean (Yool et al., 2011). The base currency in this model was nitrogen from which fluxes of organic carbon, including export to the deep ocean, were calculated by invoking fixed C:N ratios in phytoplankton, zooplankton and detritus. However, due to anthropogenic activity, the atmospheric concentration of carbon dioxide (CO2) has significantly increased above its natural, inter-glacial background. As such, simulating and predicting the carbon cycle in the ocean in its entirety, including ventilation of CO2 with the atmosphere and the resulting impact of ocean acidification on marine ecosystems, requires that both organic and inorganic carbon be afforded a more complete representation in the model specification. Here, we introduce MEDUSA-2.0, an expanded successor model which includes additional state variables for dissolved inorganic carbon, alkalinity, dissolved oxygen and detritus carbon (permitting variable C:N in exported organic matter), as well as a simple benthic formulation and extended parameterizations of phytoplankton growth, calcification and detritus remineralisation. A full description of MEDUSA-2.0, including its additional functionality, is provided and a multi-decadal spin-up simulation (1860–2005) is performed. The biogeochemical performance of the model is evaluated using a diverse range of observational data, and MEDUSA-2.0 is assessed relative to comparable models using output from the Coupled Model Intercomparison Project (CMIP5).

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Inconsistent strategies to spin up models in CMIP5: implications for ocean biogeochemical model performance assessment

Geoscientific Model Development Discussions ◽

10.5194/gmdd-8-8751-2015 ◽

2015 ◽

Vol 8 (10) ◽

pp. 8751-8808 ◽

Cited By ~ 2

Author(s):

R. Séférian ◽

M. Gehlen ◽

L. Bopp ◽

L. Resplandy ◽

J. C. Orr ◽

...

Keyword(s):

Performance Assessment ◽

Initial Conditions ◽

Model Performance ◽

Cmip5 Models ◽

Biogeochemical Model ◽

Earth System ◽

Model Intercomparison ◽

System Models ◽

Marine Biogeochemistry ◽

Earth System Models

Abstract. During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were carried out on the systematic assessment of the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. Mean-state assessments routinely compared model hindcasts to available modern biogeochemical observations. However, these assessments considered neither the extent of equilibrium in modeled biogeochemical reservoirs nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESM) contribute to model-to-model differences in the simulated fields. We take advantage of a 500 year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O2, NO3, Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and is consistent when confronted against a larger ensemble of CMIP5 models. This shows that drift has implications on their performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to-model uncertainty. This requires more attention in future model intercomparison exercices in order to provide realistic ESM results on marine biogeochemistry and carbon cycle feedbacks.

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Indian Ocean impact on ENSO evolution 2014–2016 in a set of seasonal forecasting experiments

Climate Dynamics ◽

10.1007/s00382-020-05607-6 ◽

2021 ◽

Author(s):

Michael Mayer ◽

Magdalena Alonso Balmaseda

Keyword(s):

Pacific Ocean ◽

Indian Ocean ◽

El Niño ◽

Initial Conditions ◽

El Nino ◽

Southern Oscillation ◽

Heat Content ◽

Tropical Pacific ◽

Decadal Variations ◽

The Indian Ocean

AbstractThis study investigates the influence of the anomalously warm Indian Ocean state on the unprecedentedly weak Indonesian Throughflow (ITF) and the unexpected evolution of El Niño-Southern Oscillation (ENSO) during 2014–2016. It uses 25-month-long coupled twin forecast experiments with modified Indian Ocean initial conditions sampling observed decadal variations. An unperturbed experiment initialized in Feb 2014 forecasts moderately warm ENSO conditions in year 1 and year 2 and an anomalously weak ITF throughout, which acts to keep tropical Pacific ocean heat content (OHC) anomalously high. Changing only the Indian Ocean to cooler 1997 conditions substantially alters the 2-year forecast of Tropical Pacific conditions. Differences include (i) increased probability of strong El Niño in 2014 and La Niña in 2015, (ii) significantly increased ITF transports and (iii), as a consequence, stronger Pacific ocean heat divergence and thus a reduction of Pacific OHC over the two years. The Indian Ocean’s impact in year 1 is via the atmospheric bridge arising from altered Indian Ocean Dipole conditions. Effects of altered ITF and associated ocean heat divergence (oceanic tunnel) become apparent by year 2, including modified ENSO probabilities and Tropical Pacific OHC. A mirrored twin experiment starting from unperturbed 1997 conditions and several sensitivity experiments corroborate these findings. This work demonstrates the importance of the Indian Ocean’s decadal variations on ENSO and highlights the previously underappreciated role of the oceanic tunnel. Results also indicate that, given the physical links between year-to-year ENSO variations, 2-year-long forecasts can provide additional guidance for interpretation of forecasted year-1 ENSO probabilities.

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GFDL’s ESM2 Global Coupled Climate–Carbon Earth System Models. Part I: Physical Formulation and Baseline Simulation Characteristics

Journal of Climate ◽

10.1175/jcli-d-11-00560.1 ◽

2012 ◽

Vol 25 (19) ◽

pp. 6646-6665 ◽

Cited By ~ 620

Author(s):

John P. Dunne ◽

Jasmin G. John ◽

Alistair J. Adcroft ◽

Stephen M. Griffies ◽

Robert W. Hallberg ◽

...

Keyword(s):

Climate Changes ◽

Southern Oscillation ◽

Heat Content ◽

Ocean Dynamics ◽

Thermocline Depth ◽

Earth System ◽

System Models ◽

Model Version ◽

Earth System Models

Abstract The physical climate formulation and simulation characteristics of two new global coupled carbon–climate Earth System Models, ESM2M and ESM2G, are described. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory’s previous Climate Model version 2.1 (CM2.1) while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4p1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in El Niño–Southern Oscillation being overly strong in ESM2M and overly weak in ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to total heat content variability given its lack of long-term drift, gyre circulation, and ventilation in the North Pacific, tropical Atlantic, and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to surface circulation given its superior surface temperature, salinity, and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. The overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon–climate models.

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Ubiquity of human-induced changes in climate variability

Earth System Dynamics ◽

10.5194/esd-12-1393-2021 ◽

2021 ◽

Vol 12 (4) ◽

pp. 1393-1411

Author(s):

Keith B. Rodgers ◽

Sun-Seon Lee ◽

Nan Rosenbloom ◽

Axel Timmermann ◽

Gokhan Danabasoglu ◽

...

Keyword(s):

Climate Change ◽

Climate Variability ◽

Climate Adaptation ◽

Southern Oscillation ◽

System Modeling ◽

Greenhouse Warming ◽

Earth System ◽

Wide Range ◽

State Changes ◽

Mean State

Abstract. While climate change mitigation targets necessarily concern maximum mean state changes, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Thus far Earth system modeling efforts have primarily focused on projected mean state changes and the sensitivity of specific modes of climate variability, such as the El Niño–Southern Oscillation. However, our knowledge of forced changes in the overall spectrum of climate variability and higher-order statistics is relatively limited. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 over 1850–2100 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming in the model alters variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production, or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, seasonal predictions, and assessing potential stressors for terrestrial and marine ecosystems.

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

10.5194/egusphere-egu21-11356 ◽

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

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 CO2 flux by drawing down carbon into the ocean interior. This export flux is five times as large as the CO2 emitted to the atmosphere by human activities. When carbon is transported from the surface to intermediate and deep ocean, more CO2 can be absorbed at the surface. Therefore, even small variability in sinking organic carbon fluxes can have a large impact on air-sea CO2 fluxes, and on the amount of CO2 emissions that remain in the atmosphere.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.

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Dependence of global monsoon response to volcanic eruptions on the background oceanic states

10.5194/egusphere-egu21-1003 ◽

2021 ◽

Author(s):

Meng Zuo ◽

Tianjun Zhou ◽

Wenmin Man

Keyword(s):

Radiative Forcing ◽

Initial Conditions ◽

Southern Oscillation ◽

Volcanic Eruptions ◽

Initial Condition ◽

Monsoon Precipitation ◽

Surface Cooling ◽

Global Monsoon ◽

Precipitation Changes ◽

Sst Anomalies

Both proxy data and climate modeling show divergent responses of global monsoon precipitation to volcanic eruptions. The reason is however unknown. Here, based on analysis of the CESM Last Millennium Ensemble simulation, we show evidences that the divergent responses are dominated by the pre-eruption background oceanic states. We found that under El Ni&#241;o-Southern Oscillation (ENSO) neutral and warm phases initial conditions, the Pacific favors an El Ni&#241;o-like anomaly after volcanic eruptions, while La Ni&#241;a-like SST anomalies tend to occur following eruptions under ENSO cold phase initial condition, especially after southern eruptions. The cold initial condition is associated with stronger upper ocean temperature stratification and shallower thermocline over the eastern Pacific than normal. The easterly anomalies triggered by surface cooling over the tropical South America continent can generate changes in SST through anomalous advection and the ocean subsurface upwelling more efficiently, causing La Ni&#241;a-like SST anomalies. Whereas under warm initial condition, the easterly anomalies fail to develop and the westerly anomalies still play a dominant role, thus forms an El Ni&#241;o-like SST anomaly. Such SST response further regulates the monsoon precipitation changes through atmospheric teleconnection. The contribution of direct radiative forcing and indirect SST response to precipitation changes show regional differences, which will further affect the intensity and sign of precipitation response in submonsoon regions. Our results imply that attention should be paid to the background oceanic state when predicting the global monsoon precipitation responses to volcanic eruptions.

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