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This study proposes a dynamically downscaled climatology of Portugal, produced by a high resolution (9 km) WRF simulation, forced by 20 years of ERA-Interim reanalysis (1989–2008), nested in an intermediate domain with 27 km of resolution. The Portuguese mainland is characterized by large precipitation gradients, with observed mean annual precipitation ranging from about 400 to over 2,200 mm, with a very wet northwest and rather dry southeast, largely explained by orographic processes. Model results are compared with all available stations with continuous records, comprising daily information in 32 stations for temperature and 308 for precipitation, through the computation of mean climatologies, standard statistical errors on daily to seasonally timescales, and distributions of extreme events. Results show that WRF at 9 km outperforms ERA-Interim in all analyzed variables, with good results in the representation of the annual cycles in each region. The biases of minimum and maximum temperature are reduced, with improvement of the description of temperature variability at the extreme range of its distribution. The largest gain of the high resolution simulations is visible in the rainiest regions of Portugal, where orographic enhancement is crucial. These improvements are striking in the high ranking percentiles in all seasons, describing extreme precipitation events. WRF results at 9 km compare favorably with published results supporting its use as a high-resolution regional climate model. This higher resolution allows a better representation of extreme events that are of major importance to develop mitigation/adaptation strategies by policy makers and downstream users of regional climate models in applications such as flash floods or heat waves.

In recent years, research related to the occurrence of marine heatwave (MHW) events worldwide has been increasing, reporting severe impacts on marine ecosystems which led to losses of marine biodiversity or changes in world fisheries. Many of these studies, based on regional and global coupled models, show relevant biases in the MHW properties when compared with observations. In this study, the MHW frequency of occurrence, the duration and mean intensity over the global oceans are characterized, taking advantage of the new global climate model (GCM) dataset, from the Coupled Model Project Intercomparison Phase 6 (CMIP6). The MHWs result for the historical period are compared with observations, and the future projected changes are characterized under three socioeconomic pathways (SSPs) (SSP1, SSP2 and SSP5), for the middle and end of century (2041-2070 and 2071-2100). The results show a reasonable agreement between the modeled and observed MHW property trends, indicating increases in the frequency, duration and intensity of MHWs along the historical period. For the period 1982-2014, both the ∼2 mean observed events per year and the mean intensity of 0.35 °C above the threshold are underestimated by the multi-model ensemble (MME) mean by 21% and 31%, respectively, while the observed duration of ∼12 d are overestimated by 100%. The future MHWs are expected to increase in duration and intensity, where a near permanent MHW occurs with reference to the historical climate conditions, mainly by the end of the 21st century. The future MHWs intensity, projected by the MME mean, increases in the range of 0.2 °C to 1.5 °C, from the least to the most severe pathways. The GCMs biases obtained with CMIP6 revealed to be in line with the CMIP5 biases, reinforcing the need to use high spatial resolution models to characterize MHW.

Biases in climate model simulations introduce biases in subsequent impact simulations. Therefore, bias correction methods are operationally used to post-process regional climate projections. However, many problems have been identified, and some researchers question the very basis of the approach. Here we demonstrate that a typical cross-validation is unable to identify improper use of bias correction. Several examples show the limited ability of bias correction to correct and to downscale variability, and demonstrate that bias correction can cause implausible climate change signals. Bias correction cannot overcome major model errors, and naive application might result in ill-informed adaptation decisions. We conclude with a list of recommendations and suggestions for future research to reduce, post-process, and cope with climate model biases. Bias correction methods aim to remove introduced bias for climate model simulations; however, improper use can result in spurious climate signals. This Perspective considers the issues of bias correction and makes recommendations for research to overcome model biases.

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution ( ∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼  −40% at 12 km to ∼  −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales.

Portugal, which is located in the west limit of the Mediterranean subtropics, is a small region with a complex orography with large precipitation gradients and interannual variability. In this study, the newer and higher resolution regional climate simulations, covering Portugal, are evaluated in present climate and used to investigate the rainfall projections for the end of the twenty-first century, following the RCP4.5 and RCP8.5 emission scenarios. The EURO-CORDEX historical simulations, at 0.11° and at 0.44° resolution, are evaluated against gridded observations of precipitation, which allows the assembly of four multi-model ensembles. An extra simulation, at even higher resolution (9 km) with WRF is also analysed. In present climate, the models are able to describe the precipitation temporal and spatial patterns as well its distributions, although there is a large spread and an overestimation of larger rainfall quantiles. The multi-model ensembles show that selecting the best performing models adds quality to the overall representation of rainfall. The high-resolution simulations augment the spatial details of precipitation, but objectively do not seem to add value with respect to the coarse resolution. Regarding the RCP8.5 scenario, WRF and the multi-model ensembles consistently predict important losses of precipitation in Portugal in spring, summer and autumn, ranging from −10% and −50%. For all seasons, the changes are more severe in the southern basins. The precipitation distributions show, for all models, important reductions of the contribution from low to moderate/high precipitation bins and augments of days with strong rainfall. Furthermore, a prominent growth of high-ranking percentiles is predicted reaching values over 70% in some regions. Generally, the changes associated with the RCP4.5 scenario have the same signal and features, but with smaller magnitudes.

A global quantitative characterization of offshore wind power density is presented over the economic exclusive zones (EEZs), at annual and seasonal scales, based on the recently released ECMWF ERA-5 reanalysis. Compared to its predecessors, ERA-5 features increased spatial and temporal resolutions, along with improved model parameterizations and data assimilation methodologies. Consequently, the present study represents an updated benchmark of wind resources over the global oceans. Further robustness to this argument is provided by our results showing that of the EEZs with large wind energy potential are characterized by regional-scale circulation features (coastal jets and breezes, land-sea and topographic circulations), known require high model resolution to be accurately simulated. Additionally, it is demonstrated that larger errors (up to 50%) can result from estimating wind power density from logarithmically extrapolated near-surface wind speed when compared to using high-resolution model level information. Coarser (daily) temporal resolution is also found to cause widespread increases in offshore wind power density errors between 10% and 30% compared to higher (hourly) resolution data. Further leveraging on the high vertical resolution of ERA-5, we show the large benefit of future increases in hub-heights from 100 m to 250 m for global offshore wind resources. Such technological advance results in widespread gains (ranging between +5% and +50%) throughout the global EEZs and no losses for all seasons. Moreover, the gains are >+10% for all regions with large wind energy potential at 100 m and >+40% over the Arctic Pacific sector and in regions characterized by the presence of coastal low-level jets.

In this work we performed an analysis on the impacts of blocking episodes on seasonal and annual European precipitation and the associated physical mechanisms. Distinct domains were considered in detail taking into account different blocking center positions spanning between the Atlantic and western Russia. Significant positive precipitation anomalies are found for southernmost areas while generalized negative anomalies (up to 75 % in some areas) occur in large areas of central and northern Europe. This dipole of anomalies is reversed when compared to that observed during episodes of strong zonal flow conditions. We illustrate that the location of the maximum precipitation anomalies follows quite well the longitudinal positioning of the blocking centers and discuss regional and seasonal differences in the precipitation responses. To better understand the precipitation anomalies, we explore the blocking influence on cyclonic activity. The results indicate a split of the storm-tracks north and south of blocking systems, leading to an almost complete reduction of cyclonic centers in northern and central Europe and increases in southern areas, where cyclone frequency doubles during blocking episodes. However, the underlying processes conductive to the precipitation anomalies are distinct between northern and southern European regions, with a significant role of atmospheric instability in southern Europe, and moisture availability as the major driver at higher latitudes. This distinctive underlying process is coherent with the characteristic patterns of latent heat release from the ocean associated with blocked and strong zonal flow patterns. We also analyzed changes in the full range of the precipitation distribution of several regional sectors during blocked and zonal days. Results show that precipitation reductions in the areas under direct blocking influence are driven by a substantial drop in the frequency of moderate rainfall classes. Contrarily, southwards of blocking systems, frequency increases in moderate to extreme rainfall classes largely determine the precipitation anomaly in the accumulated totals. In this context, we show the close relationship between the more intrinsic torrential nature of Mediterranean precipitation regimes and the role of blocking systems in increasing the probability of extreme events.

After extensive efforts over the course of a decade, convective-scale weather forecasts with horizontal grid spacings of 1–5 km are now operational at national weather services around the world, accompanied by ensemble prediction systems (EPSs). However, though already operational, the capacity of forecasts for this scale is still to be fully exploited by overcoming the fundamental difficulty in prediction: the fully three-dimensional and turbulent nature of the atmosphere. The prediction of this scale is totally different from that of the synoptic scale (10³ km), with slowly evolving semigeostrophic dynamics and relatively long predictability on the order of a few days. Even theoretically, very little is understood about the convective scale compared to our extensive knowledge of the synoptic-scale weather regime as a partial differential equation system, as well as in terms of the fluid mechanics, predictability, uncertainties, and stochasticity. Furthermore, there is a requirement for a drastic modification of data assimilation methodologies, physics (e.g., microphysics), and parameterizations, as well as the numerics for use at the convective scale. We need to focus on more fundamental theoretical issues—the Liouville principle and Bayesian probability for probabilistic forecasts—and more fundamental turbulence research to provide robust numerics for the full variety of turbulent flows. The present essay reviews those basic theoretical challenges as comprehensibly as possible. The breadth of the problems that we face is a challenge in itself: an attempt to reduce these into a single critical agenda should be avoided.

Blocking occurrence and its impacts on European temperature have been studied in the last decade. However, most previous studies on blocking impacts have focused on winter only, disregarding its fingerprint in summer and differences with other synoptic patterns that also trigger temperature extremes. In this work, we provide a clear distinction between high-latitude blocking and sub-tropical ridges occurring in three sectors of the Euro-Atlantic region, describing their climatology and consequent impacts on European temperature during both winter and summer. Winter blocks (ridges) are generally associated to colder (warmer) than average conditions over large regions of Europe, in some areas with anomalies larger than 5 °C, particularly for the patterns occurring in the Atlantic and Central European sectors. During summer, there is a more regional response characterized by above average temperature for both blocking and ridge patterns, especially those occurring in continental areas, although negative temperature anomalies persist in southernmost areas during blocking. An objective analysis of the different forcing mechanisms associated to each considered weather regime has been performed, quantifying the importance of the following processes in causing the temperature anomalies: horizontal advection, vertical advection and diabatic heating. While during winter advection processes tend to be more relevant to explain temperature responses, in summer radiative heating under enhanced insolation plays a crucial role for both blocking and ridges. Finally, the changes in the distributions of seasonal temperature and in the frequencies of extreme temperature indices were also examined for specific areas of Europe. Winter blocking and ridge patterns are key drivers in the occurrence of regional cold and warm extreme temperatures, respectively. In summer, they are associated with substantial changes in the frequency of extremely warm days, but with different signatures in southern Europe. We conclude that there has been some misusage of the traditional blocking definition in the attribution of extreme events.

Large temperature spatio-temporal gradients are a common feature of Mediterranean climates. The Portuguese complex topography and coastlines enhances such features, and in a small region large temperature gradients with high interannual variability is detected. In this study, the EURO-CORDEX high-resolution regional climate simulations (0.11° and 0.44° resolutions) are used to investigate the maximum and minimum temperature projections across the twenty-first century according to RCP4.5 and RCP8.5. An additional WRF simulation with even higher resolution (9 km) for RCP8.5 scenario is also examined. All simulations for the historical period (1971–2000) are evaluated against the available station observations and the EURO-CORDEX model results are ranked in order to build multi-model ensembles. In present climate models are able to reproduce the main topography/coast related temperature gradients. Although there are discernible differences between models, most present a cold bias. The multi-model ensembles improve the overall representation of the temperature. The ensembles project a significant increase of the maximum and minimum temperatures in all seasons and scenarios. Maximum increments of 8 °C in summer and autumn and between 2 and 4 °C in winter and spring are projected in RCP8.5. The temperature distributions for all models show a significant increase in the upper tails of the PDFs. In RCP8.5 more than half of the extended summer (MJJAS) has maximum temperatures exceeding the historical 90th percentile and, on average, 60 tropical nights are projected for the end of the century, whilst there are only 7 tropical nights in the historical period. Conversely, the number of cold days almost disappears. The yearly average number of heat waves increases by seven to ninefold by 2100 and the most frequent length rises from 5 to 22 days throughout the twenty-first century. 5% of the longest events will last for more than one month. The amplitude is overwhelming larger, reaching values which are not observed in the historical period. More than half of the heat waves will be stronger than the extreme heat wave of 2003 by the end of the century. The future heatwaves will also enclose larger areas, approximately 100 events in the 2071–2100 period (more than 3 per year) will cover the whole country. The RCP4.5 scenario has in general smaller magnitudes.