Nils Brueggemann

and 10 more

Tido Semmler

and 6 more

The transient climate response (TCR) is 20% higher in the Alfred Wegener Institute Climate Model (AWI-CM) compared to the Max Planck Institute Earth System Model (MPI-ESM) whereas the equilibrium climate sensitivity (ECS) is only by less than 10% higher in AWI-CM. These results are largely independent of the two considered model resolutions for each model. The two coupled CMIP6 models share the same atmosphere-land component ECHAM6.3 developed at the Max Planck Institute for Meteorology (MPI-M). However, ECHAM6.3 is coupled to two different ocean models, namely the MPIOM sea ice-ocean model developed at MPI-M and the FESOM sea ice-ocean model developed at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI). A reason for the different TCR is related to ocean heat uptake in response to greenhouse gas forcing. Specifically, AWI-CM simulations show stronger surface heating than MPI-ESM simulations while the latter accumulate more heat in the deeper ocean. The vertically integrated ocean heat content is increasing slower in AWI-CM model configurations compared to MPI-ESM model configurations in the high latitudes. Weaker vertical mixing in AWI-CM model configurations compared to MPI-ESM model configurations seems to be key for these differences. The strongest difference in vertical ocean mixing occurs inside the Weddell Gyre and the northern North Atlantic. Over the North Atlantic, these differences materialize in a lack of a warming hole in AWI-CM model configurations and the presence of a warming hole in MPI-ESM model configurations. All these differences occur largely independent of the considered model resolutions.

Johann Jungclaus

and 40 more

• This work documents ICON-ESM 1.0, the first version of a coupled model based 19 on the ICON framework 20 • Performance of ICON-ESM is assessed by means of CMIP6 DECK experiments 21 at standard CMIP-type resolution 22 • ICON-ESM reproduces the observed temperature evolution. Biases in clouds, winds, 23 sea-ice, and ocean properties are larger than in MPI-ESM. Abstract 25 This work documents the ICON-Earth System Model (ICON-ESM V1.0), the first cou-26 pled model based on the ICON (ICOsahedral Non-hydrostatic) framework with its un-27 structured, icosahedral grid concept. The ICON-A atmosphere uses a nonhydrostatic dy-28 namical core and the ocean model ICON-O builds on the same ICON infrastructure, but 29 applies the Boussinesq and hydrostatic approximation and includes a sea-ice model. The 30 ICON-Land module provides a new framework for the modelling of land processes and 31 the terrestrial carbon cycle. The oceanic carbon cycle and biogeochemistry are repre-32 sented by the Hamburg Ocean Carbon Cycle module. We describe the tuning and spin-33 up of a base-line version at a resolution typical for models participating in the Coupled 34 Model Intercomparison Project (CMIP). The performance of ICON-ESM is assessed by 35 means of a set of standard CMIP6 simulations. Achievements are well-balanced top-of-36 atmosphere radiation, stable key climate quantities in the control simulation, and a good 37 representation of the historical surface temperature evolution. The model has overall bi-38 ases, which are comparable to those of other CMIP models, but ICON-ESM performs 39 less well than its predecessor, the Max Planck Institute Earth System Model. Problem-40 atic biases are diagnosed in ICON-ESM in the vertical cloud distribution and the mean 41 zonal wind field. In the ocean, sub-surface temperature and salinity biases are of con-42 cern as is a too strong seasonal cycle of the sea-ice cover in both hemispheres. ICON-43 ESM V1.0 serves as a basis for further developments that will take advantage of ICON-44 specific properties such as spatially varying resolution, and configurations at very high 45 resolution. 46 Plain Language Summary 47 ICON-ESM is a completely new coupled climate and earth system model that ap-48 plies novel design principles and numerical techniques. The atmosphere model applies 49 a non-hydrostatic dynamical core, both atmosphere and ocean models apply unstruc-50 tured meshes, and the model is adapted for high-performance computing systems. This 51 article describes how the component models for atmosphere, land, and ocean are cou-52 pled together and how we achieve a stable climate by setting certain tuning parameters 53 and performing sensitivity experiments. We evaluate the performance of our new model 54 by running a set of experiments under pre-industrial and historical climate conditions 55 as well as a set of idealized greenhouse-gas-increase experiments. These experiments were 56 designed by the Coupled Model Intercomparison Project (CMIP) and allow us to com-57 pare the results to those from other CMIP models and the predecessor of our model, the 58 Max Planck Institute for Meteorology Earth System Model. While we diagnose overall 59 satisfactory performance, we find that ICON-ESM features somewhat larger biases in 60 several quantities compared to its predecessor at comparable grid resolution. We empha-61 size that the present configuration serves as a basis from where future development steps 62 will open up new perspectives in earth system modelling. 63

Holger Pohlmann

and 5 more

We develop a data assimilation scheme with the Icosahedral Non-hydrostatic Earth System Model (ICON-ESM) for operational decadal and seasonal climate predictions at the German weather service. For this purpose, we implement an Ensemble Kalman Filter to the ocean component as a first step towards a weakly coupled data assimilation. We performed an assimilation experiment over the period 1960-2014. This ocean-only assimilation experiment serves to initialize 10-year long retrospective predictions (hindcasts) started each year on 1 November. On multi-annual time scales, we find predictability of sea surface temperature and salinity as well as oceanic heat and salt contents especially in the North Atlantic. The mean Atlantic Meridional Overturning Circulation is realistic and the variability is stable during the assimilation. On seasonal time scales, we find high predictive skill in the tropics with highest values in variables related to the El Niño/Southern Oscillation phenomenon. In the Arctic, the hindcasts correctly represent the decreasing sea ice trend in winter and, to a lesser degree, also in summer, although sea ice concentration is generally much too low in both hemispheres in summer. However, compared to other prediction systems, prediction skill is relatively low in regions apart from the tropical Pacific due to the missing atmospheric assimilation. In addition, we expect a better fine-tuning of the sea ice and the oceanic circulation in the Southern Ocean in ICON-ESM to improve the predictive skill. In general, we demonstrate that our data assimilation method is successfully initializing the oceanic component of the climate system.

Johann H Jungclaus

and 39 more

This work documents the ICON-Earth System Model (ICON-ESM V1.0), the first coupled model based on the ICON (ICOsahedral Non-hydrostatic) framework with its unstructured, isosahedral grid concept. The ICON-A atmosphere uses a nonhydrostatic dynamical core and the ocean model ICON-O builds on the same ICON infrastructure, but applies the Boussinesq and hydrostatic approximation. The oceanic carbon cycle and biogeochemistry is represented by the HAMOCC6 module and the terrestrial biogeophysical and biogeochemical process are integrated in the new JSBACH4 module. We describe the tuning and spin-up of a base-line version at a resolution typical for models participating in the Coupled Model Intercomparison Project (CMIP). The performance of ICON-ESM is assessed by means of a set of standard CMIP6 simulations. Achievements are well-balanced top-of-atmosphere radiation, stable key climate quantities in the control simulation, and a good representation of the historical surface temperature evolution. The model has overall biases, which are comparable to those of other CMIP models, but ICON-ESM performs less well than its predecessor, the MPI-ESM. Problematic biases are diagnosed in ICON-ESM in the vertical cloud distribution and the mean zonal wind field. In the ocean, sub-surface temperature and salinity biases are of concern as is a too strong seasonal cycle of the sea-ice cover in both hemispheres. ICON-ESM V1.0 serves as a basis for further developments that will take advantage of ICON-specific properties such as spatially varying resolution, and coupled configurations at very high resolution.