A Higher‐resolution Version of the Max Planck Institute Earth System Model (MPI‐ESM1.2‐HR)

Müller, Wolfgang A.; Jungclaus, Johann; Mauritsen, Thorsten; Baehr, Johanna; Bittner, Matthias; Budich, Reinhard; Bunzel, Felix; Esch, Monika; Ghosh, Rohit; Haak, Helmuth; Ilyina, Tatiana; Kleine, Tobias; Kornblueh, Luis; Li, H.; Modali, Kameswarrao; Notz, Dirk; Pohlmann, Holger; Roeckner, Erich; Stemmler, Irene; Tian, F.; Marotzke, Jochem

doi:10.1029/2017ms001217

Cited by 366 publications

(243 citation statements)

References 121 publications

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“…MPI contributes to the High Resolution Intercomparison Project (HighResMIP; Haarsma et al, ) by providing global coupled climate simulations with varying horizontal resolutions that are higher than the standard resolution in Coupled Model Intercomparison Project‐Phase 6 (CMIP6; Eyring et al, ). Among the MPI‐ESM model (Mauritsen et al, ) configurations that are used in CMIP6, the highest standard resolution (Müller et al, ) uses a 0.4° ocean resolution with 40 vertical levels (TP04L40, tripolar grid) with a 1° atmosphere (T127 spectral model with 95 vertical hybrid levels). This setup corresponds to the low‐resolution setup for HighResMIP and is denoted as HR based on resolution naming convention within MPI‐ESM CMIP6 simulations.…”

Section: Model Configuration and Sensitivity Experimentsmentioning

confidence: 97%

Surface Flux Drivers for the Slowdown of the Atlantic Meridional Overturning Circulation in a High‐Resolution Global Coupled Climate Model

Putrasahan

Lohmann

Storch

et al. 2019

J Adv Model Earth Syst

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This paper investigates the causation for the decline of the Atlantic Meridional Overturning Circulation (AMOC) from approximately 17 Sv to about 9 Sv, when the atmospheric resolution of the Max Planck Institute‐Earth System Model is enhanced from ∼1° to ∼0.5°. The results show that the slowdown of the AMOC is caused by the cessation of deep convection. In most modeling studies, this is thought to be controlled by buoyancy fluxes in the convective regions, for example, by surface freshwater flux that is introduced locally or via enormous input from glacier or iceberg melts. While we find that freshwater is still the key to the reduction of AMOC seen in the higher‐resolution run, the freshening of the North Atlantic does not need to be directly caused by local freshwater fluxes. Instead, it can be caused indirectly through winds via a reduced wind‐driven gyre circulation and salinity transport associated to this circulation, as seen in the higher‐resolution run.

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Section: Model Configuration and Sensitivity Experimentsmentioning

confidence: 97%

Surface Flux Drivers for the Slowdown of the Atlantic Meridional Overturning Circulation in a High‐Resolution Global Coupled Climate Model

Putrasahan

Lohmann

Storch

et al. 2019

J Adv Model Earth Syst

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“…For the first simulation a low resolution (MPI-ESM1.2-LR) version of ECHAM6.3, T63L47, was run and in the second one a high-resolution (MPI-ESM1.2-HR) version, T127L95. A detailed evaluation and comparison of the coupled models MPI-ESM1.2-LR and MPI-ESM1.2-HR is conducted by Müller et al (2018) and so is omitted here.…”

Section: Appendix B: Evaluation Of Land-atmosphere Simulationsmentioning

confidence: 99%

Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1.2) and Its Response to Increasing CO₂

Mauritsen

Bader

Becker

et al. 2019

J Adv Model Earth Syst

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468

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A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI‐ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low‐level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO2 forcing, which nonetheless can be represented by a simple two‐layer model.

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“…The analysis of the time horizon for skillful QBO predictions has shown predictability of more than 3 years in decadal climate prediction systems (Pohlmann et al, 2013;Scaife et al, 2014). In this study, we show that the update in higher resolved version of the Max Planck Institute Earth System Model (MPI-ESM-HR) historical simulations (Mauritsen et al, 2019;Müller et al, 2018) and decadal hindcast simulations with the MiKlip decadal climate prediction system (Marotzke et al, 2016) from Coupled Model Intercomparison Project Phase 5 (CMIP5; Taylor et al, 2012) to CMIP6 (Eyring et al, 2016) external forcing data leads to a realistic QBO variability.…”

Section: Introductionmentioning

confidence: 64%

“…We use the MPI-ESM-HR (Mauritsen et al, 2019;Müller et al, 2018) together with the historical simulations using CMIP5 (Taylor et al, 2012) and CMIP6 (Eyring et al, 2016) forcing. MPI-ESM-HR uses the European Centre Hamburg version 6.3 (ECHAM6.3) as the atmospheric component with a resolution of T127L95 (~100 km in the horizontal with 95 vertical levels) and the Max Planck Institute ocean model as the oceanic component of TP0.4 (0.4°nominal) resolution.…”

Section: The Miklip Decadal Prediction Systemmentioning

confidence: 99%

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Realistic Quasi‐Biennial Oscillation Variability in Historical and Decadal Hindcast Simulations Using CMIP6 Forcing

Pohlmann

Müller

Bittner

et al. 2019

Geophysical Research Letters

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We analyze the quasi-biennial oscillation (QBO) variability of historical and decadal hindcast simulations of the MiKlip (Mittelfristige Klimavorhersagen) decadal prediction system using the higher resolved version of the Max Planck Institute Earth System Model. We find a realistic variability of the QBO in historical simulations when changing from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to the Coupled Model Intercomparison Project Phase 6 (CMIP6) external forcing. This agreement between the simulated and the observed QBO is improved by the initialization of decadal hindcast simulations with CMIP6 forcing in the first three lead years. In the decadal hindcast simulations, the agreement is similar to a persistence forecast in the first five lead years and higher than the persistence forecast in the later lead years. We find a strong relation between the QBO and the ozone variability in the stratosphere and conclude that the change of the ozone data from CMIP5 to CMIP6 leads to the improved QBO variability and prediction skill in our simulations.Plain Language Summary The quasi-biennial oscillation (QBO) is a climate mode in the stratosphere with the feature of reversing wind directions above the equator roughly every second year (period of 28 months). The QBO variability has worldwide implications for other climate modes like the strength of the polar vortex that influences Europe via the North Atlantic Oscillation. Previous historical simulations with our climate model show that with a high vertical resolution, the model is able to produce a QBO variability, however, with an unrealistic phase. These historical simulations need external forcing like greenhouse gases and ozone concentrations. We show that in our simulations, the QBO variability becomes realistic when we use the updated external forcing data from Coupled Model Intercomparison Project Phase 6 (CMIP6) instead of those from CMIP5. Moreover, we find evidence that the variability of the stratospheric ozone data leads to the realistic QBO variability in our climate simulations. This has implications for decadal climate predictions since-for a good climate prediction-the stratospheric ozone variability must be projected into the future.

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A Higher‐resolution Version of the Max Planck Institute Earth System Model (MPI‐ESM1.2‐HR)

Cited by 366 publications

References 121 publications

Surface Flux Drivers for the Slowdown of the Atlantic Meridional Overturning Circulation in a High‐Resolution Global Coupled Climate Model

Surface Flux Drivers for the Slowdown of the Atlantic Meridional Overturning Circulation in a High‐Resolution Global Coupled Climate Model

Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1.2) and Its Response to Increasing CO₂

Realistic Quasi‐Biennial Oscillation Variability in Historical and Decadal Hindcast Simulations Using CMIP6 Forcing

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A Higher‐resolution Version of the Max Planck Institute Earth System Model (MPI‐ESM1.2‐HR)

Cited by 366 publications

References 121 publications

Surface Flux Drivers for the Slowdown of the Atlantic Meridional Overturning Circulation in a High‐Resolution Global Coupled Climate Model

Surface Flux Drivers for the Slowdown of the Atlantic Meridional Overturning Circulation in a High‐Resolution Global Coupled Climate Model

Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1.2) and Its Response to Increasing CO2

Realistic Quasi‐Biennial Oscillation Variability in Historical and Decadal Hindcast Simulations Using CMIP6 Forcing

Contact Info

Product

Resources

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Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1.2) and Its Response to Increasing CO₂