The South African Weather Service gave the clearest sign yet on 1 September: this El Niño is on course to become the strongest event in living memory, with sea surface temperatures already tracking past 3°C above normal.
A national outlook can’t say which town or farming district takes the hardest hit. AfriGIS has started overlaying that seasonal forecast onto its own cadastral, municipal boundary and demographic data, turning a national warning into a localised risk map.
Antonie Peens, GISSA national director at AfriGIS, has been mapping what that means at ground level. Overlaying the seasonal outlook onto AfriGIS’s cadastral, suburb and municipal boundary data shows the risk isn’t spread evenly. “It splits out into the central interior and the far northeast,” he says. “The municipalities set to be hit hardest include the North West, Free State, Eastern Cape, Northern Cape, Limpopo, and parts of Mpumalanga. It sounds like it’s all over, but that’s genuinely what a below-normal rainfall forecast looks like across a Super El Niño.” KwaZulu-Natal, by contrast, is showing up as the most lightly affected region, though he’s careful to note that’s still forecast data, not certainty.
Above: Antonie Peens, GISSA national director at AfriGIS (photo supplied)
Ease of access to data can help determine risk
That data isn’t AfriGIS’s own model. The company describes itself as the technology provider and delivery mechanism for South African Weather Service data, made available via a series of API services. “We’re the vehicle that makes SAWS data available,” he explains. “You query what the forecast data is and get it back immediately. You’re not waiting on someone to send you a text file. It’s 100% South African Weather Service data, and we’ve built it so users can pull it straight into their own systems with automation, as a ready-made solution.”
Who needs to watch that data closely depends on what their use cases are. Farmers, businesses, and insurers all draw on it, but for different reasons: irrigation planning for farmers tracking whether evapotranspiration is outpacing water supply, storm and lightning data for insurers, dam-level tracking for anyone reliant on a specific water source.
The power of visualisation
Peens points to South Africa coming off an unusually good rainfall year. Full dams can create a false sense of security. “Last year we had really good rainfall. Dams are relatively full, so there’s less of a sense of urgency to conserve. But that comfort can actually put us in a difficult position.” The question, he says, isn’t whether the buffer exists, it’s how quickly it drains if the Super El Niño intensifies as forecast.
A single forecast layers in more than temperature and rainfall, Peens notes, from wind and fire-danger scoring to UV index and tidal data from coastal stations. El Niño itself is fundamentally a sea surface temperature signal, and he flags sea level rise as a risk worth watching alongside drought and heat.
“On its own, data is just a set of coordinates and values,” he says. “The moment you put that on a map and someone can see this is where they are and this is what it looks like, it turns data into insights – it becomes information that means something to them. Colour that data from blue to red, and if someone sees they’re sitting in a red zone, they’re simply more aware than if they were looking at a blue one.”
That picture will keep getting clearer as time marches forward. Peens expects the forecast to firm up through spring as the event develops, with each update redrawing which municipalities sit closest to red on the map. “Proper planning will be a key component in traversing difficult times ahead successfully,” says Peens. “But proper planning is a continuous and adaptive process as opposed to a once-off event. Events such as those driving El Niño are dynamic, and the data around it is too. Crucial decisions need to be made and they will have to be recalibrated just as continuously as the data insights around them change, too.
Photo by Domenico Adornato on Unsplash
