A review of the experimental protocol and motivation for DYAMOND, the first intercomparison project of global storm-resolving models, is presented. Nine models submitted simulation output for a 40-day (1 August–10 September 2016) intercomparison period. Eight of these employed a tiling of the sphere that was uniformly less than 5 km. By resolving the transient dynamics of convective storms in the tropics, global storm-resolving models remove the need to parameterize tropical deep convection, providing a fundamentally more sound representation of the climate system and a more natural link to commensurately high-resolution data from satellite-borne sensors. The models and some basic characteristics of their output are described in more detail, as is the availability and planned use of this output for future scientific study. Tropically and zonally averaged energy budgets, precipitable water distributions, and precipitation from the model ensemble are evaluated, as is their representation of tropical cyclones and the predictability of column water vapor, the latter being important for tropical weather.

A climatological approach is developed to characterize the mesoscale environment in which heavily precipitating events (HPEs) grow over a mountainous Mediterranean area. This climatology that is based on three-dimensional variational data assimilation (3D-Var) mesoscale analyses is performed for a 5-yr period, considering cases with daily precipitation of .150 mm occurring over southern France during autumn. Different diagnostics are used to document the time evolution of mesoscale features associated with the HPEs for initiation, mature, and dissipation stages. To underline differences according to the location of precipitation, four subdomains are also considered: Languedoc-Roussillon, Cé vennes-Vivarais, South Alps, and Corsica. Composite analyses show that these events are driven by some common features (slowly evolving trough-ridge pattern and diffluent midlevel flow). Instability and moisture are transported by the low-level jet (LLJ) toward the target area from their sources, which are located upstream over the Mediterranean Sea. Strong moisture convergence is located within the left exit of the LLJ. These parameters reach a maximum during the mature stage. During the life cycle of the HPEs, the low-level winds rotate clockwise. Composite analyses also show that the synoptic and mesoscale patterns can differ greatly as a function of the location of the precipitation. Indeed, the LLJ varies from southeasterly to southwesterly. The midlevel flow varies from southerly to southwesterly. The areas of high moisture and instability are stretched in different orientations. Long-lasting events are associated with a more pronounced quasi-stationary trough-ridge pattern, higher values of CAPE, a wetter troposphere, and faster LLJ. The most-heavily precipitating events are found to be in general associated with higher values of these parameters or with a low-level inflow that is closer to perpendicular to the relief.

SUMMARYWe present an overview of the 3D-Var data assimilation in the framework of the ALADIN/France model. The purpose of this system is to provide improved precipitation forecasts at mesoscale and in the short range, up to 18 hours. The goal of the paper is threefold. Firstly, we present initial considerations for the design of the 3D-Var system. Secondly, we discuss in more detail the specification of the background-error covariance matrix, by comparing three different error simulation techniques, namely two variants of the NMC method and an ensemble-based approach. The formal, diagnostic and impact studies have led to the selection of the ensemblebased covariances for the ALADIN/France assimilation. Thirdly, scores of quantitative precipitation forecasts are shown in order to illustrate the robustness and the preliminary meteorological performance of the ALADIN/France assimilation suite. The results indicate that the tested configuration improves some aspects of the precipitation forecast, while being neutral for others, when compared with the spin-up model.We conclude the paper by providing a more explicit insight into the future evolution of limited-area variational analysis towards convective-scale data assimilation.

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