This paper describes the development and evaluation of the UK's new high resolution global coupled model, HiGEM, which is based on the latest climate configuration of the Met Office Unified Model, HadGEM1. In HiGEM, the horizontal resolution has been increased to 1.25 • x 0.83 • in longitude and latitude for the atmosphere, and 1/3 • x 1/3 • globally for the ocean. Multi-decadal integrations of HiGEM, and the lower resolution HadGEM, are used to explore the impact of resolution on the fidelity of climate simulations.Generally SST errors are reduced in HiGEM. Cold SST errors associated with the path of the North Atlantic drift improve, and warm SST errors are reduced in upwelling stratocumulus regions where the simulation of low level cloud is better at higher resolution. The ocean model in HiGEM allows ocean eddies to be partially resolved, which dramatically improves the representation of sea surface height variability. In the Southern Ocean, most of the heat transports in HiGEM is achieved by resolved eddy motions which replaces the parametrised eddy heat transport in the lower resolution model. HiGEM is also able to more realistically simulate small-scale features in the windstress curl around islands and oceanic SST fronts, which may have implications for oceanic upwelling and ocean biology.Higher resolution in both the atmosphere and the ocean allows coupling to occur on small spatial scales. In particular the small scale interaction recently seen in satellite imagery between the atmosphere and Tropical instability waves in the Tropical Pacific ocean is realistically captured in HiGEM. Tropical instability waves play a role in improving the simulation of the mean state of the Tropical Pacific which has important implications for climate variability.In particular all aspects of the simulation of ENSO (spatial patterns, the timescales at which ENSO occurs, and global teleconnections) are much improved in HiGEM.2

The ability to run general circulation models (GCMs) at ever-higher horizontal resolutions has meant that tropical cyclone simulations are increasingly credible. A hierarchy of atmosphere-only GCMs, based on the Hadley Centre Global Environmental Model version 1 (HadGEM1) with horizontal resolution increasing from approximately 270 to 60 km at 50°N, is used to systematically investigate the impact of spatial resolution on the simulation of global tropical cyclone activity, independent of model formulation. Tropical cyclones are extracted from ensemble simulations and reanalyses of comparable resolutions using a feature-tracking algorithm. Resolution is critical for simulating storm intensity and convergence to observed storm intensities is not achieved with the model hierarchy. Resolution is less critical for simulating the annual number of tropical cyclones and their geographical distribution, which are well captured at resolutions of 135 km or higher, particularly for Northern Hemisphere basins. Simulating the interannual variability of storm occurrence requires resolutions of 100 km or higher; however, the level of skill is basin dependent. Higher resolution GCMs are increasingly able to capture the interannual variability of the large-scale environmental conditions that contribute to tropical cyclogenesis. Different environmental factors contribute to the interannual variability of tropical cyclones in the different basins: in the North Atlantic basin the vertical wind shear, potential intensity, and low-level absolute vorticity are dominant, whereas in the North Pacific basins midlevel relative humidity and low-level absolute vorticity are dominant. Model resolution is crucial for a realistic simulation of tropical cyclone behavior, and high-resolution GCMs are found to be valuable tools for investigating the global location and frequency of tropical cyclones.

Atmospheric rivers (ARs) are synoptic-scale features characterized by their striking geometry-extending thousands of kilometres in length and an order of magni tude less in width 1-and vertically coherent low-level moisture transport concentrated in the bottom 3 km of the atmosphere 2 (Fig. 1). In total, ARs are estimated to accomplish as much as 90% of poleward moisture transport 3,4 , which, in the North Pacific, averages 700 kg m −1 s −1 (Fig. 1b), more than twice the mean annual discharge found at the mouth of the Amazon River 5. ARs do not describe continuous moisture transport. Rather, they are continually evolving pathways that incorporate moisture from local convergence and evaporation along their track 6,7 or, in select cases, from distant source regions in the tropics or subtropics 8-12. Owing to the complexity of their evolution, our baseline knowledge of AR characteristics at the global scale is uncertain due to the dependency on identification algorithms (Box 1), with factors such as genesis, development and termination only recently being explored 13,14. However, ARs are known to operate as one part of a larger, synoptic-scale dynamical system driving the poleward transport of sensible and latent heat 4,15. They are generally found in the vicinity of extratropical cyclones. Over the North Pacific, for example, 85% of ARs are paired with extratropical cyclones 16 , consistent with their observed relationship with baroclinic instabilities and the mid-latitude storm track 3,6. However, this relationship is nuanced; only 45% of extratropical cyclones over the same region are associated with an AR 16. Similar non-linear relationships are observed in the North Atlantic, where the evolution and life cycle of a single AR can span that of several cyclones 9. While the phenomena are clearly related, their relationship is interactive, with potential implications on the inten sification of storms and the severity of precipitation impacts on land 17,18. Indeed, given their intense moisture transport and moist-neutrality, ARs exhibit conditions that are ideal for forced precipitation, either through interaction with topography or ascent along a warm conveyor belt or frontal boundary 19. Thus, when ARs make landfall, they can have a range of hydrological impacts, including precipitation extremes and related hazards,