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Flooding events associated with extreme precipitation have had large impacts in Norway. It is well known that these Heavy precipitation events afecting Norway (and other parts of Europe) are strongly associated with atmospheric rivers (ARs). We assess trends in Norwegian AR characteristics, and the infuence of AR variability on extreme precipitation in Norway. We first evaluate the ability of a high-resolution global climate model (EC-Earth) to simulate ARs, compared to ERA-Interim. We evaluate the EC-Earth simulated relationship between ARs and extreme precipitation in western Norway, compared to the observed relationship. We find that EC-Earth is able to simulate well the statistics of AR events and the related precipitation. The intensity and frequency of ARs making landfall in Norway both increase by the end of the century and we find a shift in seasonality of AR events in the future period. In two regions on the west coast, the majority of winter precipitation maxima are associated with AR events (> 80% of cases). Next we assess the infuence of AR variability on Extreme precipitation. A non-stationary extreme value analysis indicates that the magnitude of extreme precipitation events in these regions is associated with AR intensity. Indeed, the 1-in-20 year extreme event is 17% larger when the AR-intensity is high, compared to when it is low. There is little infuence of specifc humidity on the variability of extreme precipitation after all variables are de-trended. Finally, we fnd that the region mean temperature during winter AR events increases in the future. In the future, when the climate is generally warmer, AR days will tend to make landfall when the temperature is above the freezing point. The partitioning of more precipitation as rain, rather than as snow, can have severe impacts on fooding and water resource management.

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.

We estimate the extent of spatial scales that atmospheric models in a new generation of global climate models, used in the Coupled Model Intercomparison Project 6, are able to resolve on the basis of kinetic energy spectra, commonly referred to as the effective resolution. We examine the spectra derived from the rotational and divergent parts of the wind for six state‐of‐the‐art global climate models that have been run with at least two horizontal resolutions. For each of the high resolution configurations, the effective resolution enhancement is less than proportional to the increase of the nominal resolution. The highest effective resolution obtained by the models in this study is roughly 200 km. This shows that the newest generation of high resolution climate models starts to resolve synoptic scales relevant for the dynamics of weather events. We estimate the extent of resolved spatial scales in atmospheric models from a new generation of global climate models on the basis of kinetic energy spectra. These models start to resolve synoptic scales (down to ~200 km) relevant for the dynamics of weather events

Tropical cyclones undergo extratropical transition (ET) in every ocean basin. Projected changes in ET frequency under climate change are uncertain and differ between basins, so multimodel studies are required to establish confidence. We used a feature-tracking algorithm to identify tropical cyclones and performed cyclone phase-space analysis to identify ET in an ensemble of atmosphere-only and fully coupled global model simulations, run at various resolutions under historical (1950–2014) and future (2015–50) forcing. Historical simulations were evaluated against five reanalyses for 1979–2018. Considering ET globally, ensemble-mean biases in track and genesis densities are reduced in the North Atlantic and western North Pacific when horizontal resolution is increased from ∼100 to ∼25 km. At high resolution, multi-reanalysismean climatological ET frequencies across most ocean basins as well as basins’ seasonal cycles are reproduced better than in low-resolution models. Skill in simulating historical ET interannual variability in the North Atlantic and western North Pacific is ∼0.3, which is lower than for all tropical cyclones. Models project an increase in ET frequency in the North Atlantic and a decrease in the western North Pacific. We explain these opposing responses by secular change in ET seasonality and an increase in lower-tropospheric, pre-ET warm-core strength, both of which are largely unique to the North Atlantic. Multimodel consensus about climate change responses is clearer for frequency metrics than for intensity metrics. These results help clarify the role of model resolution in simulating ET and help quantify uncertainty surrounding ET in a warming climate.

There is agreement on how the North Atlantic Oscillation forces the Atlantic Meridional Overturning Circulation, but the existence of a reversed interaction is widely disputed. Here, we investigate this type of ocean forcing the atmosphere by analysing several high- and low-resolution coupled climate models, ocean observations and reanalyses products of ocean and atmosphere. We find that in observations and about 50% of the coupled climate models, an ocean-forced negative North Atlantic Oscillation occurs at a lag of 5 years after the Atlantic Meridional Overturning Circulation peaks. Climate models with a strong cold temperature bias in the subpolar gyre and a positive sea-ice cover bias in the Atlantic and Arctic Ocean are unable to correctly simulate the heat flux pattern, resulting from the northward propagation of warm ocean temperatures, that forces the atmosphere. Efforts to remove this bias could therefore lead to substantial improvement in current decadal prediction systems. The negative North Atlantic Oscillation occurs around 5 years after the Atlantic Meridional Overturning Circulation peaks, coinciding with a positive North Atlantic Oscillation, according to a state-of-the-art multi-model ensemble as well as observational data.

A new global high-resolution coupled climate model, EC-Earth3P-HR has been developed by the EC-Earth consortium, with a resolution of approximately 40 km for the atmosphere and 0.25∘ for the ocean, alongside with a standard-resolution version of the model, EC-Earth3P (80 km atmosphere, 1.0∘ ocean). The model forcing and simulations follow the High Resolution Model Intercomparison Project (HighResMIP) protocol. According to this protocol, all simulations are made with both high and standard resolutions. The model has been optimized with respect to scalability, performance, data storage and post-processing. In accordance with the HighResMIP protocol, no specific tuning for the high-resolution version has been applied.Increasing horizontal resolution does not result in a general reduction of biases and overall improvement of the variability, and deteriorating impacts can be detected for specific regions and phenomena such as some Euro-Atlantic weather regimes, whereas others such as the El Niño–Southern Oscillation show a clear improvement in their spatial structure. The omission of specific tuning might be responsible for this.The shortness of the spin-up, as prescribed by the HighResMIP protocol, prevented the model from reaching equilibrium. The trend in the control and historical simulations, however, appeared to be similar, resulting in a warming trend, obtained by subtracting the control from the historical simulation, close to the observational one.

Warm sea surface temperature (SST) biases in the tropical Atlantic Ocean form a longstanding problem in coupled general circulation models (CGCMs). Considerable efforts to understand the origins of these biases and alleviate them have been undertaken, but state-of-the-art CGCMs still suffer from biases that are very similar to those of the generation of models before. In this study, we use a powerful combination of in situ moored buoy observations and a new coupled ocean–atmosphere single-column model (SCM) with parameterization that is identical to that of a three-dimensional CGCM to investigate the SST bias. We place the SCM at the location of a Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) mooring in the southeastern tropical Atlantic, where large SST biases occur in CGCMs. The SCM version of the EC-Earth state-of-the-art coupled GCM performs well for the first five days of the simulation. Then, it develops an SST bias that is very similar to that of its three-dimensional counterpart. Through a series of sensitivity experiments we demonstrate that the SST bias can be reduced by 70%. We achieve this result by enhancing the turbulent vertical ocean mixing efficiency in the ocean parameterization scheme. The under-representation of vertical mixing in three-dimensional CGCMs is a candidate for causing the warm SST bias. We further show that surface shortwave radiation does not cause the SST bias at the location of the PIRATA mooring. Rather, a warm atmospheric near-surface temperature bias and a wet moisture bias contribute to it. Strongly nudging the atmosphere to profiles from reanalysis data reduces the SST bias by 40%.

Sea surface temperature (SST) biases in the tropical Atlantic are a long-standing problem among coupled global climate models (CGCMs). They occur in equilibrated state, as well as in initialised seasonal to decadal simulations. The bias is typically characterised by too high SST in upwelling regions and associated errors of wind and precipitation. We examine the SST bias in the state-of-the-art CGCM EC-Earth by means of an upper ocean heat budget analysis. Horizontal advection processes affect the SST bias development only to a small extent, and surface heat fluxes mostly dampen the warm bias. Subgrid-scale upper ocean vertical mixing is too low in EC-Earth when compared to estimates from reanalysis data, potentially giving rise to the warm bias. We perform sensitivity experiments to examine the effect of enhanced vertical mixing on the SST bias in quasi equilibrium present day climate and its impact on projected climate change. Enhanced mixing in historical simulation mode ( MixUp pr ) reduces the SST bias in the tropical Atlantic compared to the control experiment ( Control pr ). Associated atmospheric biases of precipitation and surface winds are also reduced in MixUp pr . We further perform climate projections under the RCP8.5 emission scenario ( Control fu and MixUp fu ). Under increasing greenhouse gas forcing, the tropical Atlantic warms by up to 4.5 ∘ C locally, and maritime precipitation increases in boreal winter and spring. We show that the vertical mixing parameterisation influences future climate. In MixUp fu , SSTs remain 0.5 ∘ C colder in boreal winter and spring, but increase with the same amplitude in summer and fall. The strength and location of the projected intertropical convergence zone also depends on the ocean vertical mixing efficiency. The rain band moves southward in summer, and its strength increases in winter in MixUp fu as compared to Control fu .

In the coming decades, coastal flooding will become more frequent due to sea‐level rise and potential changes in storms. To produce global storm surge projections from 1950 to 2050, we force the Global Tide and Surge Model with a ∼25‐km resolution climate model ensemble from the Coupled Model Intercomparison Project Phase 6 High Resolution Model Intercomparison Project (HighResMIP). This is the first time that such a high‐resolution ensemble is used to assess changes in future storm surges across the globe. We validate the present epoch (1985–2014) against the ERA5 climate reanalysis, which shows a good overall agreement. However, there is a clear spatial bias with generally a positive bias in coastal areas along semi‐enclosed seas and negative bias in equatorial regions. Comparing the future epoch (2021–2050) against the historical epoch (1951–1980), we project ensemble‐median changes up to 0.1 (or 20%) in the 1 in 10‐year storm surge levels. These changes are not uniform across the globe with decreases along the coast of Mediterranean and northern Africa and southern Australia and increases along the south coast of Australia and Alaska. There are also increases along (parts) of the coasts of northern Caribbean, eastern Africa, China and the Korean peninsula, but with less agreement among the HighResMIP ensemble. Information resulting from this study can be used to inform broad‐scale assessment of coastal impacts under future climate change. Plain Language Summary In the next few decades, coastal flooding is expected to become more frequent due to rising sea levels and changes in storms. To understand and prepare for these changes, we use a global hydrodynamic and multiple climate models to investigate how storm surges (a temporarily rise in water level during a storm) will respond to a warmer climate. These are the first global projections of storm surges based on highly detailed climate models (25–50 km). We compare the model output for recent years (1985–2014) with real‐world weather data, known as reanalysis data, and find a good overall agreement. However, the comparison also shows relatively large differences with larger or smaller values in certain areas. For the future (2021–2050), results show storm surge changes up to 20%. These changes vary around the world. Some areas (Mediterranean, northern Africa, and southern Australia) might experience lower storm surges, whereas other areas (South Australia, Alaska, the northern Caribbean, eastern Africa, China, and the Korean Peninsula) might experience higher storm surges. By using advanced computer models as done here, we are able to better understand how climate change could impact coastal area and thus make informed decisions for the future. Key Points Storm surge projections from 1950 to 2050 based on the Global Tide and Surge Model and a ∼25 km‐resolution High Resolution Model Intercomparison Project climate model ensemble Validation against ERA5 reanalysis (1985–2014) shows that the model performs well globally, but also reveals a clear spatial bias The median‐ensemble change of the 1 in 10‐year storm surge levels from 2021–2050 compared to 1951–1980 shows changes up to 0.1 m or 20%

Bomb cyclones, or explosive cyclones, are rapidly-intensifying extratropical weather systems that are often associated with extreme wind and precipitation. The projection of bomb cyclones is crucial for climate change risk assessment given their severe impacts on society and environment. This study investigates the projected changes in bomb cyclone activity between historical (1950–2014) and future (2015–2050) periods using the HighResMIP-PRIMAVERA multimodel ensemble. In the North Pacific (NP), the ensemble projects a 0.40° northward shift of bomb cyclone activity, with notably less events around Japan. An eastward shift of bomb cyclone activity is projected in the North Atlantic (NA) with a marked decline in the northwestern part. In the Southern Hemisphere (SH), bomb cyclones are projected to shift poleward by 0.49°, with little change in the total number of events. In all three analysis regions, the projected changes in bomb cyclone activity are associated with changes in lower-tropospheric baroclinicity, with the major contributor being vertical wind shear and static stability in the NP and the SH, respectively. Furthermore, we identify close relationships between the projected bomb cyclone changes and mean-flow changes in the NP and SH, with the shift of mid-latitude jet latitude significantly correlated with the projected decline and poleward shift of bomb cyclone activity. In the SH, the cooling of the polar lower stratosphere also contributes to the projected poleward movement. These results are not strongly dependent on model horizontal resolution, although higher-resolution models generally have a larger number of bomb cyclones.