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The Mediterranean region is experiencing pronounced aridification and in certain areas higher occurrence of intense precipitation. In this work, we analyze the evolution of the precipitation probability distribution in terms of precipitating days (or "wet‐days") and all‐days quantile trends, in Europe and the Mediterranean, using the ERA5 reanalysis. Looking at the form of wet‐days quantile trends curves, we identify four regimes. Two are predominant: in most of northern Europe the precipitation quantiles all intensify, while in the Mediterranean the low‐medium quantiles are mostly decreasing as extremes intensify or decrease. The wet‐days distribution is then modeled by a Weibull law with two parameters, whose changes capture the four regimes. Assessing the significance of the parameters' changes over 1950–2020 shows that a signal on wet‐days distribution has already emerged in northern Europe (where the distribution shifts to more intense precipitation), but not yet in the Mediterranean, where the natural variability is stronger. We extend the results by describing the all‐days distribution change as the wet‐days' change plus a contribution from the dry‐days frequency change, and study their relative contribution. In northern Europe, the wet‐days distribution change is the dominant driver, and the contribution of dry‐days frequency change can be neglected for wet‐days percentiles above about 50%. In the Mediterranean, however, the change of precipitation distribution comes from the significant increase of dry‐days frequency instead of an intensity change during wet‐days. Therefore, in the Mediterranean the increase of dry‐days frequency is crucial for all‐days trends, even for heavy precipitation. Plain Language Summary: The Mediterranean region is facing increased dryness alongside more intense rainfall in certain areas. We delved into the change of precipitation frequency and intensity across Europe and the Mediterranean using ERA5 reanalysis data from 1950 to 2020. Our analysis revealed four distinct patterns in how rainfall is evolving. In much of northern Europe, heavy rainfall events are becoming more frequent, while in the Mediterranean, lighter precipitation is decreasing while heavy rain is either increasing or decreasing. To understand these changes better, we used a mathematical model with two parameters. This model helped us track the types of changes in precipitation patterns. We found that in northern Europe, the increase in rainfall intensity is the primary driver of change, while in the Mediterranean, it's more about the increase of the dry‐days frequency. These findings underscore the importance of considering both the frequency and intensity of precipitation when studying climate change impacts. By understanding these shifts, we can better prepare for future weather extremes in these regions and adapt to the changing climate. Key Points: Four regimes of change for daily precipitation distribution are identified, and are captured by a two parameters analytical modelIn northern Europe, a signal of increasing mean and extreme precipitation has emergedIn the Mediterranean, the changes of precipitation appears dominated by changes in dry‐days frequency [ABSTRACT FROM AUTHOR]

Deep convection occurs periodically in the Gulf of Lion, in the northwestern Mediterranean Sea, driven by the seasonal atmospheric change and Mistral winds. To determine the variability and drivers of both forcings, multiple 1 year ocean simulations were run, spanning from 1993 to 2013. Two sets of simulations were performed: a control and seasonal set, the first forced by unfiltered atmospheric forcing and the other by filtered forcing. The filtered forcing was bandpass filtered, retaining the seasonal and intraday aspects but removing the high frequency phenomena. Comparing the two sets allows for distinguishing the effects of the high frequency component of the Mistral on the ocean response. During the preconditioning phase, the seasonal forcing was found to be the main destratifying process, removing on average 46% of the stratification needed for deep convection to occur, versus the 28% removed by the Mistral. Despite this, each forcing triggered deep convection in roughly half of the deep‐convection events. Sensible and latent heat fluxes were found to be the main drivers of the seasonal forcing during deep‐convection years, removing 0.17 and 0.43 m2s−2 of stratification, respectively. They were themselves driven by increased wind speeds, believed to be the low frequency signal of the Mistral, as more Mistral events occur during deep‐convection winters (34% vs. 29% of the preconditioning period days). An evolving seasonal forcing in a changing climate may have significant effects on the future deep convection cycle of the western Mediterranean Sea. Plain Language Summary: Deep convection occurs periodically in the Gulf of Lion (located in the northwestern Mediterranean Sea), when water at the surface of the ocean is cooled enough to mix freely with the deeper water below, sometimes reaching the sea floor. It's an important part of the overall circulation of the Mediterranean Sea that leads to an explosion in the phytoplankton population in the following spring. In the gulf, the surface cooling is caused by the atmospheric transition from summer to winter and the Mistral winds. The latter is a cool, dry northerly wind that flows through the Rhône Valley out over the gulf. In our study, we ran ocean simulations that included and excluded the non‐seasonal effects of the Mistral to determine the importance of the seasonal and Mistral forcing on deep convection. The seasonal forcing was found to have a larger role, and contained a low frequency part of the Mistral, elevating the average wind speeds during the winter. Changes in the seasonal forcing and ocean water composition will need to be studied to understand the evolution of deep convection in the Gulf of Lion and its consequences on the Mediterranean Sea dynamics and biology in a changing climate. Key Points: The seasonal atmospheric change is the main driver of destratificationWinters with deep convection have below average levels of stratification that the atmospheric forcing has to overcomeThe Mistral winds have a low frequency signature that elevates the seasonal wind speeds in the winter [ABSTRACT FROM AUTHOR]

Morocco, as a Mediterranean and North African country, is acknowledged as a climate change hotspot, where increased drought and related water resource shortages present a real challenge for human and natural systems. However, its geographic position and regional characteristics make the simulation of the distribution and variability of precipitation particularly challenging in the region. In this study, we propose an approach where the Laboratoire de Météorologie Dynamique Zoom (LMDZ) GCM is run with a stretched grid configuration developed with enhanced resolution (35 km) over the region, and we apply run‐time bias correction to deal with the atmospheric model's systematic errors on large‐scale circulation. The bias‐correction terms for wind and temperature are built using the climatological mean of the adjustment terms on tendency errors in an LMDZ simulation relaxed towards ERA5 reanalyses. The free reference run with the zoomed configuration is compared to two bias‐corrected runs. The free run exhibits noticeable improvements in mean low‐level circulation, high frequency variability and moisture transport and compares favourably to precipitation observations at the local scale. The mean simulated climate is substantially improved after bias correction w.r.t. to the uncorrected runs. At the regional scale, the bias‐correction showed improvements in moisture transport and precipitation distribution, but no noticeable effect was observed in mean precipitation amounts, interannual variability and extreme events. To address the latter, model tuning after grid refinement and developing more "scale‐aware" parameterizations are necessary. The observed improvements on the large‐scale circulation suggest that the run‐time bias correction can be used to drive regional climate models for a better representation of regional and local climate. It can also be combined with "a posteriori" bias correction methods to improve local precipitation simulation, including extreme events. [ABSTRACT FROM AUTHOR]