Evidence is provided of the successful application of a single atmospheric model code at time scales ranging from shortrange weather forecasting through to projections of future climate change, and at spatial scales that vary from relatively low-resolution global simulations, to ultra-high resolution simulations at the micro-scale. The model used for these experiments is a variable-resolution global atmospheric model, the conformal-cubic atmospheric model (CCAM). It is shown that CCAM may be used to obtain plausible projections of future climate change, as well as skilful forecasts at the seasonal and short-range time scales, over the Southern African region. The model is additionally applied for extended simulations of present-day climate at spatial scales ranging from global simulations at relatively low horizontal resolution, to the micro-scale at ultra-high (1 km) resolution. Applying the atmospheric model at the shorter time scales provides the opportunity to test its physical parameterisation schemes and its response to fundamental forcing mechanisms (e.g. ENSO). The existing skill levels at the shorter time scales enhance the confidence in the model projections of future climate change, whilst the related verification studies indicate opportunities for future model improvement.

Convective initiation is a challenge for convection‐permitting models due to its sensitivity to sub‐km processes. We evaluate the representation of convective storms and their initiation over South Africa during four summer months in Met Office Unified Model simulations at a 1.5‐km horizontal grid length. Storm size distributions from the model compare well with radar observations, but rainfall in the model is predominantly produced by large storms (50 km in diameter or larger) in the evening, whereas radar observations show that most rainfall occurs throughout the afternoon, from storms 10–50 km in diameter. In all months, the modelled maximum number of storm initiations occurs at least 2 hr prior to the radar‐observed maximum. However, the diurnal cycle of rainfall between the model and observations compares well, suggesting that the numerous storm initiations in the simulations do not produce much rainfall. Modelled storms are generally less intense than those in radar observations, especially in early summer. In February, when tropical influences dominate, the simulated storms are of similar intensity to observed storms. Simulated storms tend to reach their peak intensity in the first 15 min after initiation, then gradually become less intense as they grow. In radar observations, storms reach their peak intensity 15 min into their life cycle, stay intense as they grow larger, then gradually weaken after they have reached their maximum diameter. Two November case studies of severe convection are analysed in detail. A higher resolution grid length initiates convection slightly earlier (300 m as opposed to 1.5 km) with the same scientific settings. Two 1.5 km simulations that apply more subgrid mixing have delayed convective initiation. Analysis of soundings indicates little difference in the convective indices, suggesting that differences in convection may be attributed to the choice of subgrid mixing parameters.

The accurate prediction of rainfall events, in terms of their timing, location and rainfall depth, is important to a wide range of social and economic applications. At many operational weather prediction centres, as is also the case at the South African Weather Service, forecasters use deterministic model outputs as guidance to produce subjective probabilistic rainfall forecasts. The aim of this research was to determine the skill of a new objective multi-model, multi-institute probabilistic ensemble forecast system for South Africa. Such forecasts are obtained by combining the rainfall forecasts of 2 operational high-resolution regional atmospheric models in South Africa. The first model is the Unified Model (UM), which is operational at the South African Weather Service. The UM contributes 3 ensemble members, each with a different physics scheme, data assimilation techniques and horizontal resolution. The second model is the Conformal-Cubic Atmospheric Model (CCAM) which is operational at the Council for Scientific and Industrial Research, which in turn contributed 2 members to the ensemble system based on different horizontal resolutions. A single-model ensemble forecast, with each of the ensemble members having equal weights, was constructed for the UM and CCAM models, respectively. These UM and CCAM single-model ensemble predictions are then combined into a multi-model ensemble prediction, using simple un-weighted averaging. The probabilistic forecasts produced by the single-model system as well as the multi-model system have been tested against observed rainfall data over 3 austral summer 6-month periods from 2006/07 to 2008/09, using the Brier skill score, relative operating characteristics, and the reliability diagram. The forecast system was found to be more skilful than the persistence forecast. Moreover, the system outscores the forecast skill of the individual models.

Since 2016, the South African Weather Service (SAWS) has been running convective-scale simulations to assist with forecast operations across southern Africa. These simulations are run with a tropical configuration of the Met Office Unified Model (UM), nested in the Met Office global model, but without data assimilation. For November 2016, convection-permitting simulations at 4.4- and 1.5-km grid lengths are compared against a simulation at 10-km grid length with convection parameterization (the current UM global atmosphere configuration) to identify the benefits of increasing model resolution for forecasting convection across southern Africa. The simulations are evaluated against satellite rainfall estimates, CloudSat vertical cloud profiles, and SAWS radar data. In line with previous studies using the UM, on a monthly time scale, the diurnal cycle of convection and the distribution of rainfall rates compare better against observations when convection-permitting model configurations are used. The SAWS radar network provides a three-dimensional composite of radar reflectivity for northeast South Africa at 6-min intervals, allowing the evaluation of the vertical development of precipitating clouds and of the timing of the onset of deep convection. Analysis of four case study days indicates that the 4.4-km simulations have a later onset of convection than the 1.5-km simulations, but there is no consistent bias of the simulations against the radar observations across the case studies.