We evaluate the performance of a large ensemble of Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) over South America for a recent past reference period and examine their projections of twenty-first century precipitation and temperature changes. The future changes are computed for two time slices (2040–2059 and 2080–2099) relative to the reference period (1995–2014) under four Shared Socioeconomic Pathways (SSPs, SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5). The CMIP6 GCMs successfully capture the main climate characteristics across South America. However, they exhibit varying skill in the spatiotemporal distribution of precipitation and temperature at the sub-regional scale, particularly over high latitudes and altitudes. Future precipitation exhibits a decrease over the east of the northern Andes in tropical South America and the southern Andes in Chile and Amazonia, and an increase over southeastern South America and the northern Andes—a result generally consistent with earlier CMIP (3 and 5) projections. However, most of these changes remain within the range of variability of the reference period. In contrast, temperature increases are robust in terms of magnitude even under the SSP1–2.6. Future changes mostly progress monotonically from the weakest to the strongest forcing scenario, and from the mid-century to late-century projection period. There is an increase in the seasonality of the intra-annual precipitation distribution, as the wetter part of the year contributes relatively more to the annual total. Furthermore, an increasingly heavy-tailed precipitation distribution and a rightward shifted temperature distribution provide strong indications of a more intense hydrological cycle as greenhouse gas emissions increase. The relative distance of an individual GCM from the ensemble mean does not substantially vary across different scenarios. We found no clear systematic linkage between model spread about the mean in the reference period and the magnitude of simulated sub-regional climate change in the future period. Overall, these results could be useful for regional climate change impact assessments across South America.

A multi‐millennia simulation performed with a three‐dimensional climate model under constant forcing shows abrupt climate events lasting for several centuries caused by a spontaneous transition to an infrequently visited state of the oceanic thermohaline circulation. This state is characterized by a more southern location of the main area of deep ocean convection in the North Atlantic and implies a large cooling in the mid and high latitudes of the northern hemisphere. This transition of the thermohaline circulation occurs spontaneously less than once in 5000 years in the model, but such transitions can also be triggered by a reduction of the solar irradiance.

Abstract. 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 degree for the ocean, alongside with a standard resolution version of the model, EC-Earth3P (80 km atmosphere, 1.0 degree ocean). The model forcing and simulations follow the 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 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 to reach 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.

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 (2015–2050) 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 ∼25km. At high resolution, multireanalysis-mean 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.

<p>Atmospheric rivers (AR) are associated with flooding events in Norway, like the flood that impacted Flåm in 2014. We assess trends in Norwegian AR characteristics, and the influence of AR variability on extreme precipitation in Norway. After evaluating the global climate model, EC-Earth, compared to the ERA-Interim reanalysis, we show that ARs increase in both intensity and frequency by the end of the century. In two regions on the west coast, the majority of winter precipitation maxima are associated with AR events (> 80% of cases). 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. Finally, we find 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 snow, can have severe impacts on flooding and water resource management in Norway.</p>

Starting to resolve the oceanic mesoscale in climate models is a step change in model fidelity. This study examines how certain obstinate biases in the midlatitude North Atlantic respond to increasing resolution (from 1° to 0.25° in the ocean) and how such biases in sea surface temperature (SST) affect the atmosphere. Using a multi-model ensemble of historical climate simulations run at different horizontal resolutions, it is shown that a severe cold SST bias in the central North Atlantic, common to many ocean models, is significantly reduced with increasing resolution. The associated bias in the time-mean meridional SST gradient is shown to relate to a positive bias in low-level baroclinicity, while the cold SST bias causes biases also in static stability and diabatic heating in the interior of the atmosphere. The changes in baroclinicity and diabatic heating brought by increasing resolution lead to improvements in European blocking and eddy-driven jet variability. Across the multi-model ensemble a clear relationship is found between the climatological meridional SST gradients in the broader Gulf Stream Extension area and two aspects of the atmospheric circulation: the frequency of high-latitude blocking and the southern-jet regime. This relationship is thought to reflect the two-way interaction (with a positive feedback) between the respective oceanic and atmospheric anomalies. These North Atlantic SST anomalies are shown to be important in forcing significant responses in the midlatitude atmospheric circulation, including jet variability and the stormtrack. Further increases in oceanic and atmospheric resolution are expected to lead to additional improvements in the representation of Euro-Atlantic climate.

In this study, we perform an evaluation of PRIMAVERA high-resolution (25-50 km) Global Climate Models (GCMs) relative to CORDEX Regional Climate Models (RCMs) over Europe (12-50 km resolutions). It is the first time such assessment is performed for regional climate information using ensembles of GCMs and RCMs at similar horizontal resolutions. We perform this exercise for the distribution of daily precipitation contributions to rainfall bins over Europe 25 under current climate conditions. Both ensembles are evaluated against high quality national gridded observations in terms of resolution and station density. We show that PRIMAVERA GCMs simulate very similar distribution to CORDEX RCMs that CMIP5 cannot because of their coarse resolutions. PRIMAVERA and CORDEX ensembles generally show similar strengths and weaknesses. They are of good quality in summer and autumn in most European regions, but tend to overestimate precipitation in winter and spring. PRIMAVERA show improvements in the latter bias by reducing mid-rain 30 rate biases in Central and Eastern Europe. Moreover, CORDEX simulate less light rainfall than PRIMAVERA in most regions and seasons, which improves this common GCM bias. Finally, PRIMAVERA simulate less heavy precipitation than CORDEX in most regions and seasons, especially in summer. PRIMAVERA appear to be closer to observations. However, when we apply an averaged precipitation undercatch error of 20%, CORDEX become closer to these synthetic datasets.Considering 50 km resolution GCM or RCM datasets over Europe results in large benefits compared to CMIP5 models for 35 impact studies at the regional scale. The effect of increasing resolution from 50 km to 12 km in CORDEX simulations is, in comparison, small in most regions and seasons outside mountainous regions (due to the importance of orography) and coastal regions (mostly depending on the resolution of the land-sea contrast). Now that GCMs are able to reach the level of information provided by CORDEX RCMs run at similar resolutions, there is an opportunity to better coordinate GCM and RCM simulations for future model intercomparison projects. 1 IntroductionClimate models are essential tools to provide information on the evolution of climate quantities, their variability and interactions with various components of the Earth System. There have been two main streams of development in the climate modelling community: Global Climate Models (GCMs) and Regional Climate Models (RCMs). GCMs are complex models that account for interactions at the global scale between various components of the Earth System (e.g. atmosphere, ocean, sea 45 ice, vegetation). They are designed to balance model resolution, physics complexity and computational requirements, and are therefore commonly run at coarse spatial resolution. RCMs are complex models that dynamically downscale GCM results to obtain fine climate information at the regional scale. The main advantages of the dynamical downscaling approach are that: 1) RCMs are computationally cheaper and use a higher horizo...

Linking Global to Regional Climate Change Chapter 10 10 are introduced and assessed in Section 10.3. Section 10.3 also addresses the performance of models in simulating relevant climate characteristics as needed to estimate the credibility of future projections. Section 10.4 assesses the interplay between anthropogenic causes and internal variability at regional scales, and its relevance for the attribution of regional climate changes and the emergence of regional climate change signals. Section 10.5 tackles the issue of how regional climate information is distilled from different sources taking into account the context and the values of both the producer and the user. Section 10.6 illustrates the distillation approach using three comprehensive examples. Finally, Section 10.7 lists some limitations to the assessment of regional climate information.