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.
The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans, land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined.
We integrate the coupled climate model ECHAM5/MPIOM to equilibrium under atmospheric CO2 quadrupling. The equilibrium global-mean surface-temperature change is 10.8 K. The surface equilibrates within about 1,200 years, the deep ocean within 5,000 years. The impact of the deep ocean on the equilibrium surface-temperature response is illustrated by the difference between ECHAM5/MPIOM and ECHAM5 coupled with slab ocean model (ECHAM5/SOM). The equilibrium global-mean surface temperature response is 11.1 K in ECHAM5/SOM and is thus 0.3 K higher than in ECHAM5/MPIOM. ECHAM5/MPIOM shows less warming over the northern-hemisphere mid and high latitudes, but larger warming over the tropical ocean and especially over the southern-hemisphere high latitudes. ECHAM5/MPIOM shows similar polar amplification in both the Arctic and the Antarctic, in contrast to ECHAM5/SOM, which shows stronger polar amplification in the northern hemisphere. The southern polar warming in ECHAM5/MPIOM is greatly delayed by Antarctic deep-ocean warming due to convective and isopycnal mixing. The equilibrium ocean temperature warming under CO2 quadrupling is around 8.0 K and is near-uniform with depth. The global-mean steric sea-level rise is 5.8 m in equilibrium; of this, 2.3 m are due to the deep-ocean warming after the surface temperature has almost equilibrated. This result suggests that the surface temperature change is a poor predictor for steric sea-level change in the long term. The effective climate response method described in Gregory et al. (2004) is evaluated with our simulation, which shows that their method to estimate the equilibrium climate response is accurate to within 10 %
As a contribution towards improving the climate mean state of the atmosphere and the ocean in Earth system models (ESMs), we compare several coupled simulations conducted with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1.2) following the High-ResMIP protocol. Our simulations allow to analyse the separate effects of increasing the horizontal resolution of the ocean (0.4 to 0.1 • ) and atmosphere (T127 to T255) submodels, and the effects of substituting the Pacanowski and Philander (PP) vertical ocean mixing scheme with the K-profile parameterization (KPP).The results show clearly distinguishable effects from all three factors. The high resolution in the ocean removes biases in the ocean interior and in the atmosphere. This leads to the important conclusion that a high-resolution ocean has a major impact on the mean state of the ocean and the atmosphere. The T255 atmosphere reduces the surface wind stress and improves ocean mixed layer depths in both hemispheres. The reduced wind forcing, in turn, slows the Antarctic Circumpolar Current (ACC), reducing it to observed values. In the North Atlantic, however, the reduced surface wind causes a weakening of the subpolar gyre and thus a slowing down of the Atlantic meridional overturning circulation (AMOC), when the PP scheme is used. The KPP scheme, on the other hand, causes stronger open-ocean convection which spins up the subpolar gyres, ultimately leading to a stronger and stable AMOC, even when coupled to the T255 atmosphere, thus retaining all the positive effects of a higher-resolved atmosphere.
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