Radar systems provide the most useful information about the intensity, movement, and characteristics of severe thunderstorms, but are expensive to maintain and require extensive maintenance. In South Africa, some areas are not covered by radar systems, while very few operational radar systems exist in other southern African countries. Despite these shortcomings, all meteorological centers still have to warn the public of pending severe weather events. The Nowcasting Satellite Application Facility (NWC SAF) in Europe developed software that utilizes satellite data to identify and track rapidly developing thunderstorms (RDT). The NWC software was installed at the South African Weather Service in 2014. Initially, the RDT product was validated against lightning data and the results showed that the RDT product could provide very useful information on possible severe or intense convective storms. This study focusses on the effects of including lightning as an ancillary dataset into the algorithms and then validating the RDT product against radar data. Twenty-five summer cases were considered to determine whether the inclusion of lightning data had a positive effect on the accuracy of the RDT product, when compared to radar data. The results of this study show that in the majority of the cases, the inclusion of lightning data was beneficial to the RDT product. On average the Probability of Detection (POD) improved by 6.6%, the Heidke Skill Score (HSS) by 4.6%, and the False alarm ratio (FAR) by 0.1%. To our knowledge, South Africa is the only African country which is running the NWC SAF software operationally and which has performed an evaluation of the product over Africa against observations from radar systems and lightning sensors. The outcomes of this study are very encouraging for other countries in Africa where convection and severe convection often occur and sophisticated data sources are absent. Initial studies over East Africa indicate that the RDT product can benefit operational practices for the nowcasting of severe convection events.

Severe weather events associated with strong winds and flooding can cause fatalities, injuries and damage to property. Detailed and accurate weather forecasts that are issued and communicated timeously, and actioned upon, can reduce the impact of these events. The responsibility to provide such forecasts usually lies with government departments or state-owned entities; in South Africa that responsibility lies with the South African Weather Service (SAWS). SAWS is also a regional specialised meteorological centre and therefore provides weather information to meteorological services within the Southern African Development Community (SADC). We evaluated SAWS weather information using near real-time observations and models on the nowcasting to short-range forecasting timescales during two extreme events. These are the Idai tropical cyclone in March 2019 which impacted Mozambique, Zimbabwe and Malawi resulting in over 1000 deaths, and the floods over the KwaZulu-Natal (KZN) province in April 2019 that caused over 70 deaths. Our results show that weather models gave an indication of these systems in advance, with warnings issued at least 2 days in advance in the case of Idai and 1 day in advance for the KZN floods. Nowcasting systems were also in place for detailed warnings to be provided as events progressed. Shortcomings in model simulations were shown, in particular on locating the KZN flood event properly and over/-underestimation of the event. The impacts experienced during the two events indicate that more needs to be done to increase weather awareness, and build disaster risk management systems, including disaster preparedness and risk reduction.Significance: This paper is relevant for all South Africans and the SADC region at large because it provides information on: the weather forecasting processes followed at the South African Weather Service, available early warning products in South Africa and for the SADC region made possible through the public purse, the performance of nowcasting and modelling systems in the case of predicting two extreme weather events that had adverse impacts on southern African society, and the dissemination of warnings of future extreme weather events.

Surface moisture boundaries or drylines are considered important role players on severe thunderstorm days by South African weather forecasters. On 11 December 2017 one of several thunderstorms which occurred along a dryline, developed into a supercell thunderstorm that resulted in a destructive tornado over the Vaal Marina south of Johannesburg. While the importance of drylines for convection initiation in the region is relatively well understood, the climatological characteristics of drylines and dryline related convection were unknown until recently. Making use of an objective dryline identification algorithm and ERA5 reanalysis data, a climatology of synoptic drylines for the subtropical southern African interior is developed for 1979-2021. The Southern African Plateau (SAP) domain falls within 16-32°S; 18-29°E. Subsequently cloud-to-ground lightning stroke data from the South African Weather Service’s lightning detection network are used to identify days where drylines result in convection between 2010-2021 for a smaller domain within 24-30ºS; 18-24.5ºE. This region is characterized by its high rainfall variability and has some of the highest dryline frequencies in southern Africa. Drylines are found to occur regularly during spring and summer (September - February), almost daily during December, but rarely in winter. Dryline frequencies show large interannual variability with as few as 47 drylines in the summer of 2015/16 of which 38 were convective dryline days, and as many as 73 drylines in the summer of 2016/17 of which 61 were convective. A westward shift in peak dryline frequency takes place through the summer. Drylines peak first over the eastern parts of the SAP during November, but over the central and western SAP during December. Synoptic composite maps are used to gain insight into the different formation environments of drylines that result in convection and those that do not.

Original article: https://doi.org/10.17159/sajs.2021/7911 The authors’ employment at the South African Weather Service (SAWS) was inadvertently omitted from the Competing Interests statement in the original article. All but one of the authors are employees of SAWS and were involved in the forecasting process or were in the section responsible for observations during the forecasting and observations of the weather events reported on.