Satellite data reveal widespread changes in Earth’s vegetation cover. Regions intensively attended to by humans are mostly greening due to land management. Natural vegetation, on the other hand, is exhibiting patterns of both greening and browning in all continents. Factors linked to anthropogenic carbon emissions, such as CO2 fertilization, climate change, and consequent disturbances such as fires and droughts, are hypothesized to be key drivers of changes in natural vegetation. A rigorous regional attribution at the biome level that can be scaled to a global picture of what is behind the observed changes is currently lacking. Here we analyze different datasets of decades-long satellite observations of global leaf area index (LAI, 1981–2017) as well as other proxies for vegetation changes and identify several clusters of significant long-term changes. Using process-based model simulations (Earth system and land surface models), we disentangle the effects of anthropogenic carbon emissions on LAI in a probabilistic setting applying causal counterfactual theory. The analysis prominently indicates the effects of climate change on many biomes – warming in northern ecosystems (greening) and rainfall anomalies in tropical biomes (browning). The probabilistic attribution method clearly identifies the CO2 fertilization effect as the dominant driver in only two biomes, the temperate forests and cool grasslands, challenging the view of a dominant global-scale effect. Altogether, our analysis reveals a slowing down of greening and strengthening of browning trends, particularly in the last 2 decades. Most models substantially underestimate the emerging vegetation browning, especially in the tropical rainforests. Leaf area loss in these productive ecosystems could be an early indicator of a slowdown in the terrestrial carbon sink. Models need to account for this effect to realize plausible climate projections of the 21st century.

• 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

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.