Abstract
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.
Highlights
Nowcasting is the science of anticipating the ordinary and severe weather events in the few hours (0–6 h) [1]
The average of all the time steps for this day indicate that there was a 7% improvement in the the false alarm ratio (FAR), and a 7% improvement in the Heidke skill score (HSS) from 0.53 to 0.6 when lightning data is Probability of Detection (POD), a 2% improvement in the FAR, and a 7% improvement in included in the rapidly developing thunderstorms (RDT) software
The dark green solid line shows the HSS when lightning was excluded from the software and the dotted light green line when lightning data was added as auxiliary input
Summary
Nowcasting is the science of anticipating the ordinary and severe weather events in the few hours (0–6 h) [1]. Severe convective weather events can include heavy rainfall, strong winds, hail, and/or tornadoes [2]. The issuing of weather-related warnings for such events in South Africa is the mandate of the South African Weather Service (SAWS). Radar systems provide the most useful information about the intensity, movement, and characteristics of severe weather events, but these data sources are expensive to obtain and require extensive maintenance. In South Africa, radar systems do not provide coverage of the entire country and this leaves gaps between radar systems. In other southern African countries, very few operational
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