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 rainfall 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 rainfall quantiles all intensify, while in the Mediterranean the low-medium quantiles are mostly decreasing as extremes intensify. 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 parameter 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 rainfall), 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’, 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 contribution to all-days change of wet-days distribution change is much smaller than the one of dry-days frequency. Therefore, in the Mediterranean the increase of dry-days frequency is crucial for all-days trends, even when looking at heavy precipitations.

Two assumptions commonly applied in convection schemes—the diagnostic and quasi-equilibrium assumptions—imply that convective activity (e.g., convective precipitation) is controlled only by the large-scale (macrostate) environment at the time. In contrast, numerical experiments indicate a “memory” or dependence of convection also on its own previous activity whereby subgrid-scale (microstate) structures boost but are also boosted by convection. In this study we investigated this memory by comparing single-column model behavior in two idealized tests previously executed by a cloud-resolving model (CRM). Conventional convection schemes that employ the diagnostic assumption fail to reproduce the CRM behavior. The memory-capable org and LMDZ cold pool schemes partially capture the behavior, but fail to fully exhibit the strong reinforcing feedbacks implied by the CRM. Analysis of this failure suggests that it is because the CRM supports a linear (or superlinear) dependence of the subgrid structure growth rate on the precipitation rate, while the org scheme assumes a sublinear dependence. Among varying versions of the org scheme, the growth rate of the org variable representing subgrid structure is strongly associated with memory strength. These results demonstrate the importance of parameterizing convective memory, and the ability of idealized tests to reveal shortcomings of convection schemes and constrain model structural assumptions.

The elimination of rain evaporation in the planetary boundary layer (PBL) has been found to lead to convective self-aggregation (CSA) even without radiative feedback, but the precise mechanisms underlying this phenomenon remain unclear. We conducted cloud-resolving simulations with two domain sizes and progressively reduced rain evaporation in the PBL. Surprisingly, CSA only occurred when rain evaporation was almost completely removed. The additional convective heating resulting from the reduction of evaporative cooling in the moist patch was found to be the trigger, thereafter a dry subsidence intrusion into the PBL in the dry patch takes over and sets CSA in motion. Temperature and moisture anomalies oppose each other in their buoyancy effects, hence explaining the need for almost total rain evaporation removal. We also found radiative cooling and not cold pools to be the leading cause for the comparative ease of CSA to take place in the larger domain.

Radiative cooling on the lowest atmospheric levels is of strong importance for modulating atmospheric circulations and organizing convection, but detailed observations and a robust theoretical understanding are lacking. Here we use unprecedented observational constraints from subsidence regimes in the tropical Atlantic to develop a theory for the shape and magnitude of low-level longwave radiative cooling in clear-sky, showing large peaks at the top of the boundary layer. A suite of novel scaling approximations is first developed from simplified spectral theory, in close agreement with the measurements. The radiative cooling peak height is set by the maximum lapse rate in water vapor path, and its magnitude is mainly controlled by the ratio of column relative humidity above and below the peak. We emphasize how elevated intrusions of moist air can reduce low-level cooling, by sporadically shading the spectral range which effectively cools to space. The efficiency of this spectral shading depends both on water content and altitude of moist intrusions; its height dependence cannot be explained by the temperature difference between the emitting and absorbing layers, but by the decrease of water vapor extinction with altitude. This analytical work can help to narrow the search for low-level cloud patterns sensitive to radiative-convective feedbacks: the most organized patterns with largest cloud fractions tend to occur in atmospheres below 10% relative humidity and feel the strongest low-level cooling. This motivates further assessment of these favorable conditions for radiative-convective feedbacks and a robust quantification of corresponding shallow cloud dynamics in current and warmer climates.

In observations and cloud-resolving model (CRM) simulations, large-scale domains where convection is more aggregated (clustered into a smaller number of clouds) are associated with a drier troposphere. What mechanisms explain this drying? Hypotheses involve dynamical and microphysical processes. The goal of this study is to quantify the relative importance of these processes. We use a series of CRM simulations with different dynamical regimes and different kinds of convective organization forced by external forcings (isolated cumulonimbi, tropical cyclones, squall lines). We interpret the simulation results in the light of a hierarchy of simpler models (last-saturation model, analytical model). In CRM simulations, the troposphere is drier in the environment of more aggregated convection (tropical cyclones and squall lines). A last-saturation model is able to reproduce the drier troposphere even in absence of any microphysical processes or horizontal motions. Cloud intermittence is the key factor explaining this drying: when clouds are more intermittent, subsiding air parcels are more likely to encounter a cloud. An analytical model highlights the key role of the duration of convective systems. Remoistening by microphysical processes contributes to the moister troposphere when convection is less aggregated, though its importance is secondary smaller than that of intermittence. We suggest that the observed anti-correlation between convective aggregation and relative humidity may, at least partially, be mediated by the duration of convective systems.