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This work investigates the scalability of extreme temperatures over the European domain with global warming levels. We have used the EURO-CORDEX ensemble of regional model simulations at 0.11° resolution for daily minimum and maximum temperatures to analyze future changes in extreme weather daily events. Scaling with the annual mean global warming modeled by the driving GCM was applied to future extreme temperature indices changes. Regional changes in each index were scaled by corresponding global warming levels obtained from GCMs. This approach asserts that regional patterns of climate change and average global temperature change are linearly related. It can provide information regarding climate change for periods or emission scenarios when no simulations exist. According to the results, the annual minimum of the lowest temperature of the day (TNn) increases more than the annual maximum of the highest temperature of the day (TXx) for Europe. The multi-model mean of the changes in scaled patterns of extreme temperatures emerges early, around 2020, even before it becomes robust. Individual scaled patterns of TNn and TXx emerge from around 2040.

A considerable part of the skill in decadal forecasts often comes from the forcings, which are present in both initialized and uninitialized model experiments. This makes the added value from initialization difficult to assess. We investigate statistical tests to quantify if initialized forecasts provide skill over the uninitialized experiments. We consider three correlation-based statistics previously used in the literature. The distributions of these statistics under the null hy-pothesis that initialization has no added values are calculated by a surrogate data method. We present some simple exam-ples and study the statistical power of the tests. We find that there can be large differences in both the values and power for the different statistics. In general, the simple statistic defined as the difference between the skill of the initialized and uninitialized experiments behaves best. However, for all statistics the risk of rejecting the true null hypothesis is too high compared to the nominal value. We compare the three tests on initialized decadal predictions (hindcasts) of near-surface temperature performed with a climate model and find evidence for a significant effect of initializations for small lead times. In contrast, we find only little evidence for a significant effect of initializations for lead times longer than 3 years when the experience from the simple experiments is included in the estimation.

We investigate the forced response of the North Atlantic Oscillation (NAO)-calculated as the ensemble mean-in different large ensembles of climate models including simulations with historical forcings and initialized decadal hindcasts. The forced NAO in the CMIP6 historical ensemble correlates significantly with observations after 1970. However, the forced NAO shows an apparent nonstationarity with significant correlations to observations only in the period after 1970 and in the period before 1890. We demonstrate that such apparent nonstationarity can be due to chance even when models and observations are independent. For the period after 1970 the correlation to the observed NAO continues to increase while the amplitude of the forced signal continues to decrease-although both with some signs of saturation-when the ensemble size grows. This behavior can be explained by a simple statistical model assuming a very small signal-to-noise ratio in the models. We find only rather weak evidence that initialization improves the skill of the NAO on decadal time scales. The NAO in the historical ensembles including only natural forcings, well-mixed greenhouse gases, or anthropogenic aerosols show skill that is not significantly different from zero. The same holds for a large single-model ensemble. The skills of these ensembles, except for the well-mixed greenhouse gas ensemble, are also significantly different from the skill of the larger full historical ensemble even though their ensemble sizes are smaller. Taken together, our results challenge the possibility of useful NAO predictions on decadal time scales.

Intense convective storms can be hazardous when occurring over large populated cities. In a changing climate, decision makers and the general public increasingly need to be able to better understand if and to what extent these storms are influenced by anthropological climate change and what to expect as climate continues to warm. Unfortunately due to their limited ability to resolve small-scale features in models, convective storms remain a challenge to the modeling community. Here, we use a forecast-ensemble based method using a convection permitting model with full data-assimilation, to assess the risk of exceeding certain precipitation thresholds related to a critical cloudburst event that occurred over Copenhagen, Denmark. Our results show that this set-up is representing well the overall observed intensities. By adapting a pseudo-global warming approach, we show that both the risk for flooding and the risk for reaching unprecedented precipitation intensity increases resulting from further warming.

European climate is associated with variability and changes in the mid-latitude atmospheric circulation. In this study, we aim to investigate potential future change in circulation over Europe by using the EURO-CORDEX regional climate projections at 0.11 degrees grid mesh. In particular, we analyze future change in 500-hPa geopotential height (Gph), 500-hPa wind speed and mean sea level pressure (MSLP) addressing different warming levels of 1 degrees C, 2 degrees C and 3 degrees C, respectively. Simple scaling with the global mean temperature change is applied to the regional climate projections for monthly mean 500-hPa Gph and 500-hPa wind speed. Results from the ensemble mean of individual models show a robust increase in 500-hPa Gph and MSLP in winter over Mediterranean and Central Europe, indicating an intensification of anticyclonic circulation. This circulation change emerges robustly in most simulations within the coming decade. There are also enhanced westerlies which transport warm and moist air to the Mediterranean and Central Europe in winter and spring. It is also clear that, models showing different responses to circulation depend very much on the global climate model ensemble member in which they are nested. For all seasons, particularly autumn, the ensemble mean is much more correlated with the end of the century than most of the individual models. In general, the emergence of a scaled pattern appears rather quickly.

Using a sub-selection of regional climate models at 0.11 degrees (approximate to 12 km) grid resolution from the EURO-CORDEX ensemble, we investigate how the spatial extent of areas associated with the most intensive daily precipitation events changes as a consequence of global warming. We address this by analysing three different warming levels: 1 degrees C, 2 degrees C and 3 degrees C. We find that not only does the intensity of such events increase, but their size will also change as a function of the warming: larger systems becomes more frequent and larger, while systems of lesser extent are reduced in numbers.

The interior of western Canada, up to and including the Arctic, has experienced rapid change in its climate, hydrology, cryosphere, and ecosystems, and this is expected to continue. Although there is general consensus that warming will occur in the future, many critical issues remain. In this first of two articles, attention is placed on atmospheric-related issues that range from large scales down to individual precipitation events. Each of these is considered in terms of expected change organized by season and utilizing mainly “business-as-usual” climate scenario information. Large-scale atmospheric circulations affecting this region are projected to shift differently in each season, with conditions that are conducive to the development of hydroclimate extremes in the domain becoming substantially more intense and frequent after the mid-century. When coupled with warming temperatures, changes in the large-scale atmospheric drivers lead to enhancements of numerous water-related and temperature-related extremes. These include winter snowstorms, freezing rain, drought, forest fires, as well as atmospheric forcing of spring floods, although not necessarily summer convection. Collective insights of these atmospheric findings are summarized in a consistent, connected physical framework.

Winter weather events with temperatures near 0 degrees C are often associated with freezing rain. They can have major impacts on the society by causing power outages and disruptions to the transportation networks. Despite the catastrophic consequences of freezing rain, very few studies have investigated how their occurrences could evolve under climate change. This study aims to investigate the change of freezing rain and ice pellets over southern Québec using regional climate modeling at high resolution. The fifth-generation Canadian Regional Climate Model with climate scenario RCP 8.5 at 0.11 degrees grid mesh was used. The precipitation types such as freezing rain, ice pellets or their combination are diagnosed using five methods (Cantin and Bachand, Bourgouin, Ramer, Czys and, Baldwin). The occurrences of the diagnosed precipitation types for the recent past (1980–2009) are found to be comparable to observations. The projections for the future scenario (2070–2099) suggested a general decrease in the occurrences of mixed precipitation over southern Québec from October to April. This is mainly due to a decrease in long-duration events (≥6h). Overall, this study contributes to better understand how the distribution of freezing rain and ice pellets might change in the future using high-resolution regional climate model.

In regional climate modelling, it is well known that domains should be neither too large to avoid a large departure from the driving data, nor too small to provide a sufficient distance from the lateral inflow boundary to allow the full development of the small-scale (SS) features permitted by the finer resolution. Although most practitioners of dynamical downscaling are well aware that the jump of resolution between the lateral boundary condition (LBC) driving data and the nested regional climate model affects the simulated climate, this issue has not been fully investigated. In principle, as the jump of resolution becomes larger, the region of interest in the limited-area domain should be located further away from the lateral inflow boundary to allow the full development of the SS features. A careless choice of domain might result in a suboptimal use of the full finer resolution potential to develop fine-scale features. To address this issue, regional climate model (RCM) simulations using various resolution driving data are compared following the perfect-prognostic Big-Brother protocol. Several experiments were carried out to evaluate the width of the spin-up region (i.e. the distance between the lateral inflow boundary and the domain of interest required for the full development of SS transient eddies) as a function of the RCM and LBC resolutions, as well as the resolution jump. The spin-up distance turns out to be a function of the LBC resolution only, independent of the RCM resolution. When varying the RCM resolution for a given resolution jump, it is found that the spin-up distance corresponds to a fixed number of RCM grid points that is a function of resolution jump only. These findings can serve a useful purpose to guide the choice of domain and RCM configuration for an optimal development of the small scales allowed by the increased resolution of the nested model.