Variable phytoplankton size distributions reduce the sensitivity of global export flux to climate change

Abstract. Earth System Models predict a 10–20 % decrease in ocean carbon export production by the end of the 21st century due to global climate change. This decline is caused by increased stratification of the upper ocean, resulting in reduced shallow subsurface nutrient concentrations and a slower supply of nutrients to the surface euphotic zone. These predictions, however, do not account for associated changes in sinking particle size and remineralization depth. Here we combine satellite-derived export and particle size maps with a simple 3-D global biogeochemical model to investigate how shifts in sinking particle size may buffer predicted changes in surface nutrient supply and therefore export production. We show that higher export rates are correlated with larger phytoplankton and sinking particles, especially in tropical and subtropical regions. Incorporation of these empirical relationships into a global model shows that as circulation slows, a decrease in export and associated shift toward smaller phytoplankton yields particles that sink more slowly and are thus remineralized shallower; this in turn leads to greater recycling of nutrients in the upper water column and faster nutrient recirculation into the euphotic zone, boosting productivity and export to counteract the initial circulation-driven decreases. This negative feedback mechanism (termed the particle size-remineralization feedback) slows export decline over the next century by ~14 % globally and by ~20 % in the tropical and subtropical oceans, where export decreases are currently predicted to be greatest. Thus, incorporating dynamic particle size-dependent remineralization depths into Earth System Models will result in more robust predictions of changes in biological pump strength in a warming climate.

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Variable particle size distributions reduce the sensitivity of global export flux to climate change

Biogeosciences ◽

10.5194/bg-18-229-2021 ◽

2021 ◽

Vol 18 (1) ◽

pp. 229-250

Author(s):

Shirley W. Leung ◽

Thomas Weber ◽

Jacob A. Cram ◽

Curtis Deutsch

Keyword(s):

Climate Change ◽

Particle Size ◽

Euphotic Zone ◽

Nutrient Concentrations ◽

Biogeochemical Model ◽

Size Distributions ◽

Earth System ◽

Particle Size Distributions ◽

System Models ◽

Earth System Models

Abstract. Recent earth system models predict a 10 %–20 % decrease in particulate organic carbon export from the surface ocean by the end of the 21st century due to global climate change. This decline is mainly caused by increased stratification of the upper ocean, resulting in reduced shallow subsurface nutrient concentrations and a slower supply of nutrients to the surface euphotic zone in low latitudes. These predictions, however, do not typically account for associated changes in remineralization depths driven by sinking-particle size. Here we combine satellite-derived export and particle size maps with a simple 3-D global biogeochemical model that resolves dynamic particle size distributions to investigate how shifts in particle size may buffer or amplify predicted changes in surface nutrient supply and therefore export production. We show that higher export rates are empirically correlated with larger sinking particles and presumably larger phytoplankton, particularly in tropical and subtropical regions. Incorporating these empirical relationships into our global model shows that as circulation slows, a decrease in export is associated with a shift towards smaller particles, which sink more slowly and are thus remineralized shallower. This shift towards shallower remineralization in turn leads to greater recycling of nutrients in the upper water column and thus faster nutrient recirculation into the euphotic zone. The end result is a boost in productivity and export that counteracts the initial circulation-driven decreases. This negative feedback mechanism (termed the particle-size–remineralization feedback) slows export decline over the next century by ∼ 14 % globally (from −0.29 to −0.25 GtC yr−1) and by ∼ 20 % in the tropical and subtropical oceans, where export decreases are currently predicted to be greatest. Our findings suggest that to more accurately predict changes in biological pump strength under a warming climate, earth system models should include dynamic particle-size-dependent remineralization depths.

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An Overview of CMIP5 and the Experiment Design

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-11-00094.1 ◽

2012 ◽

Vol 93 (4) ◽

pp. 485-498 ◽

Cited By ~ 8089

Author(s):

Karl E. Taylor ◽

Ronald J. Stouffer ◽

Gerald A. Meehl

Keyword(s):

Climate Change ◽

Climate Models ◽

Global Climate ◽

Experiment Design ◽

Global Climate Models ◽

Model Output ◽

Earth System ◽

Intergovernmental Panel ◽

System Models ◽

Earth System Models

The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.

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Oceanic primary production decline halved in eddy-resolving simulations of global warming

Biogeosciences ◽

10.5194/bg-18-4321-2021 ◽

2021 ◽

Vol 18 (14) ◽

pp. 4321-4349

Author(s):

Damien Couespel ◽

Marina Lévy ◽

Laurent Bopp

Keyword(s):

Climate Change ◽

Global Warming ◽

Primary Production ◽

Nutrient Transport ◽

Biogeochemical Model ◽

Earth System ◽

System Models ◽

Marine Biomass ◽

Fish Catch ◽

Earth System Models

Abstract. The decline in ocean primary production is one of the most alarming consequences of anthropogenic climate change. This decline could indeed lead to a decrease in marine biomass and fish catch, as highlighted by recent policy-relevant reports. Because of computational constraints, current Earth system models used to project ocean primary production under global warming scenarios have to parameterize flows occurring below the resolution of their computational grid (typically 1∘). To overcome these computational constraints, we use an ocean biogeochemical model in an idealized configuration representing a mid-latitude double-gyre circulation and perform global warming simulations under an increasing horizontal resolution (from 1 to 1/27∘) and under a large range of parameter values for the eddy parameterization employed in the coarse-resolution configuration. In line with projections from Earth system models, all our simulations project a marked decline in net primary production in response to the global warming forcing. Whereas this decline is only weakly sensitive to the eddy parameters in the eddy-parameterized coarse 1∘ resolution simulations, the simulated decline in primary production in the subpolar gyre is halved at the finest eddy-resolving resolution (−12 % at 1/27∘ vs. −26 % at 1∘) at the end of the 70-year-long global warming simulations. This difference stems from the high sensitivity of the sub-surface nutrient transport to model resolution. Although being only one piece of a much broader and more complicated response of the ocean to climate change, our results call for improved representation of the role of eddies in nutrient transport below the seasonal mixed layer to better constrain the future evolution of marine biomass and fish catch potential.

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Assessing the capacity of Earth System Models to simulate spatiotemporal variability in fire weather indicators

10.5194/egusphere-egu21-12208 ◽

2021 ◽

Author(s):

Carolina Gallo Granizo ◽

Jonathan Eden ◽

Bastien Dieppois ◽

Matthew Blackett

Keyword(s):

Climate Change ◽

Spatial Scales ◽

Fire Danger ◽

Spatiotemporal Variability ◽

Global Evaluation ◽

Fire Weather ◽

Earth System ◽

Fire Weather Index ◽

System Models ◽

Earth System Models

Weather and climate play an important role in shaping global fire regimes and geographical distributions of burnable areas. At the global scale, fire danger is likely to increase in the near future due to warmer temperatures and changes in precipitation patterns, as projected by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). There is a need to develop the most reliable projections of future climate-driven fire danger to enable decision makers and forest managers to take both targeted proactive actions and to respond to future fire events.Climate change projections generated by Earth System Models (ESMs) provide the most important basis for understanding past, present and future changes in the climate system and its impacts. ESMs are, however, subject to systematic errors and biases, which are not fully taken into account when developing risk scenarios for wild fire activity. Projections of climate-driven fire danger have often been limited to the use of single models or the mean of multi-model ensembles, and compared to a single set of observational data (e.g. one index derived from one reanalysis).Here, a comprehensive global evaluation of the representation of a series of fire weather indicators in the latest generation of ESMs is presented. Seven fire weather indices from the Canadian Forest Fire Weather Index System were generated using daily fields realisations simulated by 25 ESMs from the 6th Coupled Model Intercomparison Project (CMIP6). With reference to observational and reanalysis datasets, we quantify the capacity of each model to realistically simulate the variability, magnitude and spatial extent of fire danger. The highest-performing models are identified and, subsequently, the limitations of combining models based on independency and equal performance when generating fire danger projections are discussed. To conclude, recommendations are given for the development of user- and policy-driven model evaluation at spatial scales relevant for decision-making and forest management.

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Analytically tractable climate–carbon cycle feedbacks under 21st century anthropogenic forcing

Earth System Dynamics ◽

10.5194/esd-9-507-2018 ◽

2018 ◽

Vol 9 (2) ◽

pp. 507-523 ◽

Cited By ~ 4

Author(s):

Steven J. Lade ◽

Jonathan F. Donges ◽

Ingo Fetzer ◽

John M. Anderies ◽

Christian Beer ◽

...

Keyword(s):

Carbon Cycle ◽

Global Climate ◽

Future Climate Change ◽

Earth System ◽

Co2 Solubility ◽

Carbon Cycle Model ◽

Ocean Climate ◽

System Models ◽

Analytical Expressions ◽

Earth System Models

Abstract. Changes to climate–carbon cycle feedbacks may significantly affect the Earth system's response to greenhouse gas emissions. These feedbacks are usually analysed from numerical output of complex and arguably opaque Earth system models. Here, we construct a stylised global climate–carbon cycle model, test its output against comprehensive Earth system models, and investigate the strengths of its climate–carbon cycle feedbacks analytically. The analytical expressions we obtain aid understanding of carbon cycle feedbacks and the operation of the carbon cycle. Specific results include that different feedback formalisms measure fundamentally the same climate–carbon cycle processes; temperature dependence of the solubility pump, biological pump, and CO2 solubility all contribute approximately equally to the ocean climate–carbon feedback; and concentration–carbon feedbacks may be more sensitive to future climate change than climate–carbon feedbacks. Simple models such as that developed here also provide workbenches for simple but mechanistically based explorations of Earth system processes, such as interactions and feedbacks between the planetary boundaries, that are currently too uncertain to be included in comprehensive Earth system models.

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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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Resolving ecological feedbacks on the ocean carbon sink in Earth system models

10.5194/esd-2020-41 ◽

2020 ◽

Author(s):

David I. Armstrong McKay ◽

Sarah E. Cornell ◽

Katherine Richardson ◽

Johan Rockström

Keyword(s):

Climate Change ◽

Carbon Sink ◽

Biological Pump ◽

Earth System ◽

Temperature Dependent ◽

System Models ◽

Plankton Ecology ◽

Ocean Carbon ◽

The Impact ◽

Earth System Models

Abstract. The Earth’s oceans are one of the largest sinks in the Earth system for anthropogenic CO2 emissions, acting as a negative feedback on climate change. Earth system models predict, though, that climate change will lead to a weakening ocean carbon uptake rate as warm water holds less dissolved CO2 and biological productivity declines. However, most Earth system models do not incorporate the impact of warming on bacterial remineralisation and rely on simplified representations of plankton ecology that do not resolve the potential impact of climate change on ecosystem structure or elemental stoichiometry. Here we use a recently-developed extension of the cGEnIE Earth system model (ecoGEnIE) featuring a trait-based scheme for plankton ecology (ECOGEM), and also incorporate cGEnIE's temperature-dependent remineralisation (TDR) scheme. This enables evaluation of the impact of both ecological dynamics and temperature-dependent remineralisation on the soft-tissue biological pump in response to climate change. We find that including TDR strengthens the biological pump relative to default runs due to increased nutrient recycling, while ECOGEM weakens the biological pump by enabling a shift to smaller plankton classes. However, interactions with concurrent ocean acidification cause opposite sign responses for the carbon sink in both cases: TDR leads to a smaller sink relative to default runs whereas ECOGEM leads to a larger sink. Combining TDR and ECOGEM results in a net strengthening of the biological pump and a small net reduction in carbon sink relative to default. These results clearly illustrate the substantial degree to which ecological dynamics and biodiversity modulate the strength of climate-biosphere feedbacks, and demonstrate that Earth system models need to incorporate more ecological complexity in order to resolve carbon sink weakening.

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Anticipating the computational performance of Earth System Models for pre-exascale systems

10.5194/egusphere-egu21-7888 ◽

2021 ◽

Author(s):

Xavier Yepes-Arbós ◽

Miguel Castrillo ◽

Mario C. Acosta ◽

Kim Serradell

Keyword(s):

Computational Efficiency ◽

Climate Model ◽

Global Climate ◽

Horizontal Resolution ◽

Limiting Factor ◽

Earth System ◽

Computational Point ◽

System Models ◽

Computational Performance ◽

Earth System Models

The increase in the capability of Earth System Models (ESMs) is strongly linked to the amount of computing power, given that the spatial resolution used for global climate experimentation is a limiting factor to correctly reproduce climate mean state and variability. However, higher spatial resolutions require new High Performance Computing (HPC) platforms, where the improvement of the computational efficiency of ESMs will be mandatory. In this context, porting a new ultra-high resolution configuration into a new and more powerful HPC cluster is a challenging task, involving technical expertise to deploy and improve the computational performance of such a novel configuration.To take advantage of this foreseeable landscape, the new EC-Earth 4 climate model is being developed by coupling OpenIFS 43R3 and NEMO 4 as atmosphere and ocean components respectively. An important effort has been made to improve the computational efficiency of this new EC-Earth version, such as extending the asynchronous I/O capabilities of the XIOS server to OpenIFS.&#160;In order to anticipate the computational behaviour of EC-Earth 4 for new pre-exascale machines such as the upcoming MareNostrum 5 of the Barcelona Supercomputing Center (BSC), OpenIFS and NEMO models are therefore benchmarked on a petascale machine (MareNostrum 4) to find potential computational bottlenecks introduced by new developments or to investigate if previous known performance limitations are solved. The outcome of this work can also be used to efficiently set up new ultra-high resolutions from a computational point of view, not only for EC-Earth, but also for other ESMs.Our benchmarking consists of large strong scaling tests (tens of thousands of cores) by running different output configurations, such as changing multiple XIOS parameters and number of 2D and 3D fields. These very large tests need a huge amount of computational resources (up to 2,595 nodes, 75 % of the supercomputer), so they require a special allocation that can be applied once a year.OpenIFS is evaluated with a 9 km global horizontal resolution (Tco1279) and using three different output data sets: no output, CMIP6-based fields and huge output volume (8.8 TB) to stress the I/O part. In addition, different XIOS parameters, XIOS resources, affinity, MPI-OpenMP hybridisation and MPI library are tested. Results suggest new features introduced in 43R3 do not represent a bottleneck in terms of performance as the model scales. The I/O scheme is also improved when outputting data through XIOS according to the scalability curve.NEMO is scaled using a 3 km global horizontal resolution (ORCA36) with and without the sea-ice module. As in OpenIFS, different I/O configurations are benchmarked, such as disabling model output, only enabling 2D fields, or either producing 3D variables on an hourly basis. XIOS is also scaled and tested with different parameters. While NEMO has good scalability during the most part of the exercise, a severe degradation is observed before the model uses 70% of the machine resources (2,546 nodes). The I/O overhead is moderate for the best XIOS configuration, but it demands many resources.

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