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The connection between the Atlantic meridional overturning circulation (AMOC) and the Atlantic multidecadal variability (AMV) is inspected in a suite of pre‐industrial integrations from the 6th phase of the Coupled Model Inter‐comparison Project (CMIP6), using a change‐point detection method to identify different AMOC‐AMV co‐variability regimes. A key finding of this study is that models robustly simulate multi‐decadal windows where the AMV and the AMOC are essentially uncorrelated. These regimes coexist with longer periods with relatively high correlation. Drops and recoveries of correlation are found to be often abrupt and confined in a temporal window of the order of 10 years. Phenomenological evidence suggests that the no‐correlation regimes may be explained by drops in the variance of the AMOC: a less variable meridional heat transport leads to a suppressed co‐variability of the AMV, leaving a larger role for non‐AMOC drivers, consistent with a non‐stationary AMOC‐stationary noise interpretative framework. The North Atlantic Ocean exhibits prominent multi‐decadal variability, modulating the climate and weather of the surrounding continental regions. A relevant fraction of this variability is explained by the interplay between ocean circulation and heat transport, leading to coordinated, basin‐wide fluctuations in surface temperatures. In this study we analyze the multi‐century stability of this interaction in a suite of climate model simulations, providing evidence for the occurrence of spontaneous breakings in the connection between ocean circulation and ocean surface temperatures. These events can be abrupt in time, last from decades to centuries, and are associated with synchronous changes in the characteristics of the oceanic variability. A conceptual model is provided to interpret these transitions. These findings raise concern about the potential occurrence of similar decoupling episodes in the future, and the need for adequately long observational records to fully represent the long‐term modulation of multi‐decadal variability in the Atlantic sector. Spontaneous breakings of the Atlantic meridional overturning circulation‐Atlantic multidecadal variability (AMOC‐AMV) connection are found in a suite of multi‐century control simulations from the 6th phase of the Coupled Model Inter‐comparison ProjectThe inception and demise of these AMOC‐AMV de‐coupling events can be abrupt in scale and last several decades or centuriesDecoupling between AMOC and AMV is more likely to occur when their respective variance is low Spontaneous breakings of the Atlantic meridional overturning circulation‐Atlantic multidecadal variability (AMOC‐AMV) connection are found in a suite of multi‐century control simulations from the 6th phase of the Coupled Model Inter‐comparison Project The inception and demise of these AMOC‐AMV de‐coupling events can be abrupt in scale and last several decades or centuries Decoupling between AMOC and AMV is more likely to occur when their respective variance is low

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. Tropical cyclones pose great risks to individuals and societies, particularly in terms of their local impacts, and how such risks may change in the future is a key question. In this work we use a common experimental framework with seven different state‐of‐the‐art global climate models, together with two different methods of identifying tropical cyclones. We find that the simulation of tropical cyclone frequency, spatial distribution, and intensity in some models approaches observed values with the model grid spacings of 20–50 km. Future projections to 2050 suggest that activity will generally decline in the South Indian Ocean while a more mixed picture is revealed in other regions. Biases in tropical cyclone distribution, frequency, and intensity are generally reduced in models at 25 km resolutionNorthern Hemisphere basins show mixed responses to future forcing, while Southern Indian Ocean activity projected to declineFuture changes in 10 m wind speed in coupled models are mixed, and models with lower bias suggest small increases

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. Models generally agree on an intensification of precipitation extremes at higher spatial atmospheric resolutionObservational uncertainties are substantial for precipitation extremes, which makes the evaluation of the models difficultIncreasing spatial resolution alone is not sufficient to obtain a systematic improvement in the simulation of precipitation extremes