Representing Arctic coastal erosion in the Max Planck Institute Earth System Model (MPI-ESM)

2020 ◽  
Author(s):  
David Marcolino Nielsen ◽  
Johanna Baehr ◽  
Victor Brovkin ◽  
Mikhail Dobrynin
Keyword(s):  
Carbon Cycle ◽  
Sea Ice ◽  
Coastal Erosion ◽  
Global Carbon Cycle ◽  
System Model ◽  
The Arctic ◽  
Earth System ◽  
Max Planck ◽  
Erosion Rates ◽  
Global Carbon

<p>The Arctic has warmed twice as fast as the globe and sea-ice extent has decreased, causing permafrost to thaw and the duration of the open-water period to extend. This combined effect increases the vulnerability of the Arctic coast to erosion, which in turn releases substantial amounts of carbon to both the ocean and the atmosphere, potentially contributing to further warming due to a positive climate-carbon cycle feedback. Therefore, Arctic coastal erosion is an important process of the global carbon cycle.</p><p>Comprehensive modelling studies exploring Arctic coastal erosion within the Earth system are still in their infancy. Here, we describe the development of a semi-empirical Arctic coastal erosion model and its coupling with the Max Planck Institute Earth System Model (MPI-ESM). We also present preliminary results for historical and future climate projections of coastal erosion rates in the Arctic. The coupling consists on the exchange of a combination of driving forcings from the atmosphere and the ocean, such as surface air temperature, winds and sea-ice concentration, which result in annual coastal erosion rates. In a further setp, organic matter from the eroded permafrost is provided to the ocean biogeochemistry model and, consequently, to the global carbon cycle including atmospheric CO<sub>2</sub>.</p>

Sensitivity of organic carbon fluxes from Arctic coastal erosion to climate change

2021 ◽  
Author(s):  
David Marcolino Nielsen ◽  
Patrick Pieper ◽  
Victor Brovkin ◽  
Paul Overduin ◽  
Tatiana Ilyina ◽  
...  
Keyword(s):  
Climate Change ◽  
Organic Carbon ◽  
Sea Ice ◽  
Coastal Erosion ◽  
Earth System Model ◽  
System Model ◽  
The Arctic ◽  
Earth System ◽  
Carbon Release ◽  
Arctic Coast

<p>When unprotected by sea-ice and exposed to the warm air and ocean waves, the Arctic coast erodes and releases organic carbon from permafrost to the surrounding ocean and atmosphere. This release is estimated to deliver similar amounts of organic carbon to the Arctic Ocean as all Arctic rivers combined, at the present-day climate. Depending on the degradation pathway of the eroded material, the erosion of the Arctic coast could represent a positive feedback loop in the climate system, to an extent still unknown. In addition, the organic carbon flux from Arctic coastal erosion is expected to increase in the future, mainly due to surface warming and sea-ice loss. In this work, we aim at addressing the following questions: How is Arctic coastal erosion projected to change in the future? How sensitive is Arctic coastal erosion to climate change?</p><p>To address these questions, we use a 10-member ensemble of climate change simulations performed with the Max Planck Institute Earth System Model (MPI-ESM) for the Coupled Model Intercomparison Project phase 6 (CMIP6) to make projections of coastal erosion at a pan-Arctic scale. We use a semi-empirical approach to model Arctic coastal erosion, assuming a linear contribution of its thermal and mechanical drivers. The pan-Arctic carbon release due to coastal erosion is projected to increase from 6.9 ± 5.4 TgC/year (mean estimate ± two standard deviations from the distribution of uncertainties) during the historical period (mean over 1850 -1950) to between 13.1 ± 6.7 TgC/year and 17.2 ± 8.2 TgC/year in the period 2081-2100 following an intermediate (SSP2.4-5) and a high-end (SSP5.8-5) climate change scenario, respectively. The sensitivity of the organic carbon release from Arctic coastal erosion to climate warming is estimated to range from 1.52 TgC/year/K to 2.79 TgC/year/K depending on the scenario. Our results present the first projections of Arctic coastal erosion, combining observations and Earth system model (ESM) simulations. This allows us to make first-order estimates of sensitivity and feedback magnitudes between Arctic coastal erosion and climate change, which can lay out pathways for future coupled ESM simulations.</p><p> </p>

Reconstructions and predictions of the global carbon cycle with an emission-driven Earth System Model

2021 ◽  
Author(s):  
Hongmei Li ◽  
Tatiana Ilyina ◽  
Tammas Loughran ◽  
Julia Pongratz
Keyword(s):  
Growth Rate ◽  
Carbon Cycle ◽  
Carbon Budget ◽  
Global Carbon Cycle ◽  
System Model ◽  
Earth System ◽  
Global Carbon Budget ◽  
Predictive Skill ◽  
Atmospheric Carbon ◽  
Global Carbon

<p>The global carbon budget including CO<sub>2</sub> fluxes among different reservoirs and atmospheric carbon growth rate vary substantially in interannual to decadal time-scales. Reconstructing and predicting the variable global carbon cycle is of essential value of tracing the fate of carbon and the corresponding climate and ecosystem changes. For the first time, we extend our prediction system based on the Max Planck Institute Earth system model (MPI-ESM) from concentration-driven to emission-driven taking into account the interactive carbon cycle and hence enabling prognostic atmospheric carbon increment. </p><p>By assimilating atmospheric and oceanic observational data products into MPI-ESM decadal prediction system, we can reproduce the observed variations of the historical global carbon cycle globally. The reconstruction from the fully coupled model enables quantification of global carbon budget within a close Earth system and therefore avoids the budget imbalance term of budgeting the carbon with standalone models. Our reconstructions of carbon budget provide a novel approach for supporting global carbon budget and understanding the dominating processes. Retrospective predictions based on the  emission-driven hindcasts, which are initiated from the reconstructions, show predictive skill in the atmospheric carbon growth rate, air-sea CO<sub>2</sub> fluxes, and air-land CO<sub>2</sub> fluxes. The air-sea CO<sub>2</sub> fluxes have higher predictive skill up to 5 years, and the air-land CO<sub>2</sub> fluxes and atmospheric carbon growth rate show predictive skill of 2 years. Our results also suggest predictions based on Earth system models enable reproducing and further predicting the evolution of atmospheric CO<sub>2</sub> concentration changes. The earth system predictions will provide valuable inputs for understanding the global carbon cycle and supporting climate relevant policy development. </p>

scholarly journals The global carbon cycle in the Canadian Earth system model (CanESM1): Preindustrial control simulation

2010 ◽  
Vol 115 (G3) ◽  
Author(s):  
J. R. Christian ◽  
V. K. Arora ◽  
G. J. Boer ◽  
C. L. Curry ◽  
K. Zahariev ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Control Simulation ◽  
Global Carbon

scholarly journals On constraining the strength of the terrestrial CO<sub>2</sub> fertilization effect in an Earth system model

2016 ◽  
Author(s):  
V. K. Arora ◽  
J. F. Scinocca
Keyword(s):  
Carbon Cycle ◽  
Carbon Budget ◽  
Co2 Flux ◽  
Global Carbon Cycle ◽  
System Model ◽  
Historical Period ◽  
Earth System ◽  
Co2 Fertilization ◽  
Fertilization Effect ◽  
Global Carbon

Abstract. Earth system models (ESMs) explicitly simulate the interactions between the physical climate system components and biogeochemical cycles. Physical and biogeochemical aspects of ESMs are routinely compared against their observation-based counterparts to assess model performance and to evaluate how this performance is affected by ongoing model development. Here, we assess the performance of version 4.2 of the Canadian Earth system model against four, land carbon cycle focused, observation-based determinants of the global carbon cycle and the historical global carbon budget over the 1850–2005 period. Our objective is to constrain the strength of the terrestrial CO2 fertilization effect which is known to be the most uncertain of all carbon cycle feedbacks. The observation-based determinants include (1) globally-averaged atmospheric CO2 concentration, (2) cumulative atmosphere–land CO2 flux, (3) atmosphere–land CO2 flux for the decades of 1960s, 1970s, 1980s, 1990s and 2000s and (4) the amplitude of the globally-averaged annual CO2 cycle and its increase over the 1980 to 2005 period. The optimal simulation that satisfies constraints imposed by the first three determinants yields a net primary productivity (NPP) increase from ~ 58 Pg C yr−1 in 1850 to about ~ 74 Pg C yr−1 in 2005; an increase of ~ 27 % over the 1850–2005 period. The simulated loss in the global soil carbon amount due to anthropogenic land use change over the historical period is also broadly consistent with empirical estimates. Yet, it remains possible that these determinants of the global carbon cycle are insufficient to adequately constrain the historical carbon budget, and consequently the strength of terrestrial CO2 fertilization effect as it is represented in the model, given the large uncertainty associated with LUC emissions over the historical period.

scholarly journals Constraining the strength of the terrestrial CO<sub>2</sub> fertilization effect in the Canadian Earth system model version 4.2 (CanESM4.2)

2016 ◽  
Vol 9 (7) ◽  
pp. 2357-2376 ◽  
Author(s):  
Vivek K. Arora ◽  
John F. Scinocca
Keyword(s):  
Carbon Cycle ◽  
Carbon Budget ◽  
Co2 Flux ◽  
Global Carbon Cycle ◽  
System Model ◽  
Historical Period ◽  
Earth System ◽  
Co2 Fertilization ◽  
Fertilization Effect ◽  
Global Carbon

Abstract. Earth system models (ESMs) explicitly simulate the interactions between the physical climate system components and biogeochemical cycles. Physical and biogeochemical aspects of ESMs are routinely compared against their observation-based counterparts to assess model performance and to evaluate how this performance is affected by ongoing model development. Here, we assess the performance of version 4.2 of the Canadian Earth system model against four land carbon-cycle-focused, observation-based determinants of the global carbon cycle and the historical global carbon budget over the 1850–2005 period. Our objective is to constrain the strength of the terrestrial CO2 fertilization effect, which is known to be the most uncertain of all carbon-cycle feedbacks. The observation-based determinants include (1) globally averaged atmospheric CO2 concentration, (2) cumulative atmosphere–land CO2 flux, (3) atmosphere–land CO2 flux for the decades of 1960s, 1970s, 1980s, 1990s, and 2000s, and (4) the amplitude of the globally averaged annual CO2 cycle and its increase over the 1980 to 2005 period. The optimal simulation that satisfies constraints imposed by the first three determinants yields a net primary productivity (NPP) increase from  ∼  58 Pg C year−1 in 1850 to about  ∼  74 Pg C year−1 in 2005; an increase of  ∼  27 % over the 1850–2005 period. The simulated loss in the global soil carbon amount due to anthropogenic land use change (LUC) over the historical period is also broadly consistent with empirical estimates. Yet, it remains possible that these determinants of the global carbon cycle are insufficient to adequately constrain the historical carbon budget, and consequently the strength of terrestrial CO2 fertilization effect as it is represented in the model, given the large uncertainty associated with LUC emissions over the historical period.

scholarly journals Comparison of ocean vertical mixing schemes in the Max Plank Institute Earth System Model (MPI-ESM1.2)

2020 ◽  
Author(s):  
Oliver Gutjahr ◽  
Nils Brüggemann ◽  
Helmuth Haak ◽  
Johann H. Jungclaus ◽  
Dian A. Putrasahan ◽  
...  
Keyword(s):  
Vertical Mixing ◽  
Global Scale ◽  
Earth System Model ◽  
System Model ◽  
The Arctic ◽  
Earth System ◽  
Max Planck ◽  
Vertical Diffusion ◽  
Mixing Schemes ◽  
Mean State

Abstract. We compare the effects of four different ocean vertical mixing schemes on the ocean mean state simulated by the Max Planck Institute Earth System Model (MPI-ESM1.2) in the framework of the Community Vertical Mixing (CVMix) library. Besides the PP and KPP scheme, we implemented the TKE scheme and a recently developed prognostic scheme for internal wave energy and its dissipation (IDEMIX) to replace the often assumed constant background diffusivity in the ocean interior. We analyse in particular the effects of IDEMIX on the ocean mean state, when combined with TKE (TKE+IDEMIX). In general, we find little sensitivity of the ocean surface, but considerable effects for the interior ocean. Overall, we cannot classify any scheme as superior, because they modify biases that vary by region or variable, but produce a similar pattern on the global scale. However, using a more realistic and energetically consistent scheme (TKE+IDEMIX) produces a more heterogeneous pattern of vertical diffusion, with lower diffusivity in deep and flat-bottom basins and elevated turbulence over rough topography. In addition, TKE+IDEMIX improves the circulation in the Nordic Seas and Fram Strait, thus reducing the warm bias of the Atlantic water (AW) layer in the Arctic Ocean to a similar extent as has been demonstrated with eddy-resolving ocean models. We conclude that although shortcomings due to model resolution determine the global-scale bias pattern, the choice of the vertical mixing scheme may play an important role for regional biases.

scholarly journals Description and evaluation of NorESM1-F: A fast version of the Norwegian Earth System Model (NorESM)

2018 ◽  
Author(s):  
Chuncheng Guo ◽  
Mats Bentsen ◽  
Ingo Bethke ◽  
Mehmet Ilicak ◽  
Jerry Tjiputra ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Sea Ice ◽  
Large Scale ◽  
Coupled Model ◽  
Coupled System ◽  
Internal Variability ◽  
Earth System Model ◽  
Meridional Overturning Circulation ◽  
System Model ◽  
Earth System

Abstract. A new computationally efficient version of the Norwegian Earth System Model (NorESM) is presented. This new version (here termed NorESM1-F) runs about 2.5 times faster (e.g. 90 model years per day on current hardware) than the version that contributed to the fifth phase of the Coupled Model Intercomparison project (CMIP5), i.e., NorESM1-M, and is therefore particularly suitable for multi-millennial paleoclimate and carbon cycle simulations or large ensemble simulations. The speedup is primarily a result of using a prescribed atmosphere aerosol chemistry and a tripolar ocean-sea ice horizontal grid configuration that allows an increase of the ocean-sea ice component time steps. Ocean biogeochemistry can be activated for fully coupled and semi-coupled carbon cycle applications. This paper describes the model and evaluates its performance using observations and NorESM1-M as benchmarks. The evaluation emphasises model stability, important large-scale features in the ocean and sea ice components, internal variability in the coupled system, and climate sensitivity. Simulation results from NorESM1-F in general agree well with observational estimates, and show evident improvements over NorESM1-M, for example, in the strength of the meridional overturning circulation and sea ice simulation, both important metrics in simulating past and future climates. Whereas NorESM1-M showed a slight global cool bias in the upper oceans, NorESM1-F exhibits a global warm bias. In general, however, NorESM1-F has more similarities than dissimilarities compared to NorESM1-M, and some biases and deficiencies known in NorESM1-M remain.

Aerosols and their impacts on future Arctic climate change under different emission projections in the GISS-E2.1 Earth system model

2021 ◽  
Author(s):  
Ulas Im ◽  
Kostas Tsigaridis ◽  
Gregory S. Faluvegi ◽  
Peter L. Langen ◽  
Joshua P. French ◽  
...  
Keyword(s):  
Sea Ice ◽  
Earth System Model ◽  
System Model ◽  
The Arctic ◽  
Earth System ◽  
Anthropogenic Aerosols ◽  
Emission Reductions ◽  
Air Temperatures ◽  
The Future ◽  
Emission Projections

&lt;p&gt;In order to study the future aerosol burdens and their radiative and climate impacts over the Arctic (&gt;60 &amp;#176;N), future (2015-2050) simulations have been carried out using the GISS-E2.1 Earth system model. Different future anthrpogenic emission projections have been used from the Eclipse V6b and the Coupled Model Intercomparison Project Phase 6 (CMIP6) databases. Results showed that&amp;#160;Arctic BC, OC and SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt; burdens decrease significantly in all simulations following the emission projections, with the CMIP6 ensemble showing larger reductions in Arctic aerosol burdens compared to the Eclipse ensemble. For the 2030-2050 period, both the Eclipse Current Legislation (CLE) and the Maximum Feasible Reduction (MFR) ensembles simulated an aerosol top of the atmosphere (TOA) forcing of -0.39&amp;#177;0.01 W m&lt;sup&gt;-2&lt;/sup&gt;, of which -0.24&amp;#177;0.01 W m&lt;sup&gt;-2&lt;/sup&gt; were attributed to the anthropogenic aerosols. The CMIP6 SSP3-7.0 scenario simulated a TOA aerosol forcing of -0.35 W m&lt;sup&gt;-2&lt;/sup&gt; for the same period, while SSP1-2.6 and SSP2-4.5 scenarios simulated a slightly more negative TOA forcing (-0.40 W m&lt;sup&gt;-2&lt;/sup&gt;), of which the anthropogenic aerosols accounted for -0.26 W m&lt;sup&gt;-2&lt;/sup&gt;. The 2030-2050 mean surface air temperatures are projected to increase by 2.1 &amp;#176;C and 2.4 &amp;#176;C compared to the 1990-2010 mean temperature according to the Eclipse CLE and MFR ensembles, respectively, while the CMIP6 simulation calculated an increase of 1.9 &amp;#176;C (SSP1-2.6) to 2.2 &amp;#176;C (SSP3-7.0). Overall, results show that even the scenarios with largest emission reductions lead to similar impact on the future Arctic surface air temperatures compared to scenarios with smaller emission reductions, while scenarios with no or little mitigation leads to much larger sea-ice loss, implying that even though the magnitude of aerosol reductions lead to similar responses in surface air temperatures, high mitigation of aerosols are still necessary to limit sea-ice loss.&amp;#160;&lt;/p&gt;

scholarly journals Description and evaluation of NorESM1-F: a fast version of the Norwegian Earth System Model (NorESM)

2019 ◽  
Vol 12 (1) ◽  
pp. 343-362 ◽  
Author(s):  
Chuncheng Guo ◽  
Mats Bentsen ◽  
Ingo Bethke ◽  
Mehmet Ilicak ◽  
Jerry Tjiputra ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Sea Ice ◽  
Large Scale ◽  
Coupled Model ◽  
Coupled System ◽  
Internal Variability ◽  
Earth System Model ◽  
Meridional Overturning Circulation ◽  
System Model ◽  
Earth System

Abstract. A new computationally efficient version of the Norwegian Earth System Model (NorESM) is presented. This new version (here termed NorESM1-F) runs about 2.5 times faster (e.g., 90 model years per day on current hardware) than the version that contributed to the fifth phase of the Coupled Model Intercomparison project (CMIP5), i.e., NorESM1-M, and is therefore particularly suitable for multimillennial paleoclimate and carbon cycle simulations or large ensemble simulations. The speed-up is primarily a result of using a prescribed atmosphere aerosol chemistry and a tripolar ocean–sea ice horizontal grid configuration that allows an increase of the ocean–sea ice component time steps. Ocean biogeochemistry can be activated for fully coupled and semi-coupled carbon cycle applications. This paper describes the model and evaluates its performance using observations and NorESM1-M as benchmarks. The evaluation emphasizes model stability, important large-scale features in the ocean and sea ice components, internal variability in the coupled system, and climate sensitivity. Simulation results from NorESM1-F in general agree well with observational estimates and show evident improvements over NorESM1-M, for example, in the strength of the meridional overturning circulation and sea ice simulation, both important metrics in simulating past and future climates. Whereas NorESM1-M showed a slight global cool bias in the upper oceans, NorESM1-F exhibits a global warm bias. In general, however, NorESM1-F has more similarities than dissimilarities compared to NorESM1-M, and some biases and deficiencies known in NorESM1-M remain.

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