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A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 25 km typically leads to more frequent and stronger tropical cyclones, together with improvements in spatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lower resolution. Using single ensemble members of each model, there is little evidence of systematic improvement in interannual variability in either storm frequency or accumulated cyclone energy as compared with observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic Ocean are also not robust to model resolution. However, using a larger ensemble of simulations (of up to 14 members) with one model at different resolutions does show evidence of increased skill at higher resolution. The ensemble mean correlation of Atlantic interannual tropical cyclone variability increases from ~0.5 to ~0.65 when resolution increases from 250 to 100 km. In the northwestern Pacific Ocean the skill keeps increasing with 50-km resolution to 0.7. These calculations also suggest that more than six members are required to adequately distinguish the impact of resolution within the forced signal from the weather noise.

Abstract. The Coupled Model Intercomparison Project phase 6 (CMIP6) HighResMIP is a new experimental design for global climate model simulations that aims to assess the impact of model horizontal resolution on climate simulation fidelity. We describe a hierarchy of global coupled model resolutions based on the Hadley Centre Global Environment Model 3 – Global Coupled vn 3.1 (HadGEM3-GC3.1) model that ranges from an atmosphere–ocean resolution of 130 km–1∘ to 25 km–1∕12∘, all using the same forcings and initial conditions. In order to make such high-resolution simulations possible, the experiments have a short 30-year spinup, followed by at least century-long simulations with constant forcing to assess drift. We assess the change in model biases as a function of both atmosphere and ocean resolution, together with the effectiveness and robustness of this new experimental design. We find reductions in the biases in top-of-atmosphere radiation components and cloud forcing. There are significant reductions in some common surface climate model biases as resolution is increased, particularly in the Atlantic for sea surface temperature and precipitation, primarily driven by increased ocean resolution. There is also a reduction in drift from the initial conditions both at the surface and in the deeper ocean at higher resolution. Using an eddy-present and eddy-rich ocean resolution enhances the strength of the North Atlantic ocean circulation (boundary currents, overturning circulation and heat transport), while an eddy-present ocean resolution has a considerably reduced Antarctic Circumpolar Current strength. All models have a reasonable representation of El Niño–Southern Oscillation. In general, the biases present after 30 years of simulations do not change character markedly over longer timescales, justifying the experimental design.

Future changes in tropical cyclone properties are an important component of climate change impacts and risk for many tropical and midlatitude countries. In this study we assess the performance of a multimodel ensemble of climate models, at resolutions ranging from 250 to 25 km. We use a common experimental design including both atmosphere‐only and coupled simulations run over the period 1950–2050, with two tracking algorithms applied uniformly across the models. There are overall improvements in tropical cyclone frequency, spatial distribution, and intensity in models at 25 km resolution, with several of them able to represent very intense storms. Projected tropical cyclone activity by 2050 generally declines in the South Indian Ocean, while changes in other ocean basins are more uncertain and sensitive to both tracking algorithm and imposed forcings. Coupled models with smaller biases suggest a slight increase in average TC 10 m wind speeds by 2050.

A multimodel, multiresolution ensemble using Coupled Model Intercomparison Project Phase 6 (CMIP6) High Resolution Model Intercomparison Project (HighResMIP) coupled experiments is used to assess the performance of key aspects of the North Atlantic circulation. The Atlantic Meridional Overturning Circulation (AMOC), and related heat transport, tends to become stronger as ocean model resolution is enhanced, better agreeing with observations at 26.5°N. However, for most models the circulation remains too shallow compared to observations and has a smaller temperature contrast between the northward and southward limbs of the AMOC. These biases cause the northward heat transport to be systematically too low for a given overturning strength. The higher‐resolution models also tend to have too much deep mixing in the subpolar gyre. In the period 2015–2050 the overturning circulation tends to decline more rapidly in the higher‐resolution models, which is related to both the mean state and to the subpolar gyre contribution to deep water formation. The main part of the decline comes from the Florida Current component of the circulation. Such large declines in AMOC are not seen in the models with resolutions more typically used for climate studies, suggesting an enhanced risk for Northern Hemisphere climate change. However, only a small number of different ocean models are included in the study.

Finer grids in global climate models could lead to an improvement in the simulation of precipitation extremes. We assess the influence on model performance of increasing spatial resolution by evaluating pairs of high‐ and low‐resolution forced atmospheric simulations from six global climate models (generally the latest CMIP6 version) on a common 1° × 1° grid. The differences in tuning between the lower and higher resolution versions are as limited as possible, which allows the influence of higher resolution to be assessed exclusively. We focus on the 1985–2014 climatology of annual extremes of daily precipitation over global land, and models are compared to observations from different sources (i.e., in situ‐based and satellite‐based) to enable consideration of observational uncertainty. Finally, we address regional features of model performance based on four indices characterizing different aspects of precipitation extremes. Our analysis highlights good agreement between models that precipitation extremes are more intense at higher resolution. We find that the spread among observations is substantial and can be as large as intermodel differences, which makes the quantitative evaluation of model performance difficult. However, consistently across the four precipitation extremes indices that we investigate, models often show lower skill at higher resolution compared to their corresponding lower resolution version. Our findings suggest that increasing spatial resolution alone is not sufficient to obtain a systematic improvement in the simulation of precipitation extremes, and other improvements (e.g., physics and tuning) may be required.

We describe the scientific and technical implementation of two models for a core set of experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The models used are the physical atmosphere-land-ocean-sea ice model HadGEM3-GC3.1 and the Earth system model UKESM1 which adds a carbon-nitrogen cycle and atmospheric chemistry to HadGEM3-GC3.1. The model results are constrained by the external boundary conditions (forcing data) and initial conditions. We outline the scientific rationale and assumptions made in specifying these. Notable details of the implementation include an ozone redistribution scheme for prescribed ozone simulations (HadGEM3-GC3.1) to avoid inconsistencies with the model's thermal tropopause, and land use change in dynamic vegetation simulations (UKESM1) whose influence will be subject to potential biases in the simulation of background natural vegetation. We discuss the implications of these decisions for interpretation of the simulation results. These simulations are expensive in terms of human and CPU resources and will underpin many further experiments; we describe some of the technical steps taken to ensure their scientific robustness and reproducibility. Plain Language SummaryComplex models of the Earth system are valuable tools for understanding the processes responsible for our changing climate. The Coupled Model Intercomparison Project (CMIP) is a well-established activity of the World Climate Research Programme that brings together results from these models to better understand their process representation and to pool their projections for robust understanding of future climate pathways. The latest phase of CMIP (CMIP6) is larger and more ambitious than previous phases. We detail the setup of two U.K. models (HadGEM3-GC3.1 and UKESM1) for a core set of experiments contributing to CMIP6, including simulations of historical and future periods covering 1850 to 2300. We highlight assumptions made in applying the prescribed CMIP6 input data to these models. We outline the technical steps to ensure the reproducibility of these simulations.

A dominant paradigm for mid-latitude air-sea interaction identifies the synoptic-scale atmospheric “noise” as the main driver for the observed ocean surface variability. While this conceptual model successfully holds over most of the mid-latitude ocean surface, its soundness over frontal zones (including western boundary currents; WBC) characterized by intense mesoscale activity, has been questioned in a number of studies suggesting a driving role for the small scale ocean dynamics (mesoscale oceanic eddies) in the modulation of air-sea interaction. In this context, climate models provide a powerful experimental device to inspect the emerging scale-dependent nature of mid-latitude air-sea interaction. This study assesses the impact of model resolution on the representation of air-sea interaction over the Gulf Stream region, in a multi-model ensemble of present-climate simulations performed using a common experimental design. Lead-lag correlation and covariance patterns between sea surface temperature (SST) and turbulent heat flux (THF) are diagnosed to identify the leading regimes of air-sea interaction in a region encompassing both the Gulf Stream system and the North Atlantic subtropical basin. Based on these statistical metrics it is found that coupled models based on “laminar” (eddy-parameterised) and eddy-permitting oceans are able to discriminate between an ocean-driven regime, dominating the region controlled by the Gulf Stream dynamics, and an atmosphere-driven regime, typical of the open ocean regions. However, the increase of model resolution leads to a better representation of SST and THF cross-covariance patterns and functional forms, and the major improvements can be largely ascribed to a refinement of the oceanic model component.