Kholeka Mtshali

I spent many of my school holidays in Midrand – an area described as Johannesburg’s ‘in-between’ suburb. With its lavish gated communities, malls, and rapid developments, Midrand always felt removed from the grittier and more historic parts of the city. Having spent years in the suburban areas of Johannesburg, I had a vague sense of what the Central Business District (CBD) was like. I had ideas about its robustness and chaos, but I hardly ever went there…mostly as I was concerned about my safety.    

Then came my PhD. My doctoral research focused on how Urban Ecological Infrastructure (UEI) can be used as a tool to adapt to climate change impacts in the City of Johannesburg. Consequently, I spent much time in the CBD!

UEIs include green spaces/parks, wetlands, urban forests, and even green roofs. Essentially, UEIs are natural or semi-natural features within cities that provide environmental and social benefits to those living in them. I wanted to find out if such infrastructures exist within Jo’burg’s CBD. I also wanted to understand if and how these UEIs could aid with better responses to heatwaves, flooding, and other climatic threats.

To answer these research questions, I used a mixed-methods approach. As such, I incorporated the use of satellite imagery, climate data from the South African Weather Services (SAWS), and interviews with municipal stakeholders, private consultants, and researchers/academics who helped guide decisions on using UEIs for climate adaptation. I was keen to better understand how the city viewed UEIs and what their plans were for effective climate adaptation. Relatedly, I wanted to know what plans for UEIs were in motion, and how many UEIs existed, if any?

The analysis of my climate data from SAWS indicated that between 1993 – 2023, minimum and maximum temperatures in Johannesburg increased by 0.03 °C and 0.025 °C respectively. I attributed this increase to declining vegetation cover in the metro due to rapid urbanisation caused by a rising population. The unequal distribution of green UEIs across different economic and racial groups further contributed to the increasing temperatures. Annual precipitation over the period increased by 5.407 mm due to increased deforestation, land use changes, and the El Nino-Southern Oscillation (ENSO).

I am sure you want to know more about what I found! But for this blog, I actually want to focus more on my experience in the field and less about reporting on my findings.

My research involved interviews with various stakeholders, which meant I met with some very senior people. My interactions with city officials were interesting and felt daunting, as I was basically asking them if they were delivering on the policy promises they had made! I asked them for the locations of the UEIs, as well as who managed/maintained them? I was also asking them whether there were any inequalities amongst the upper and lower economic classes when it came to the distribution of UEIs in the city? For this doctoral researcher, being in these spaces and asking such direct questions to such senior officials felt bold and nerve wrecking, but also, empowering. And in one particular interaction, I knew that what I was doing was important, as my one participant remarked, “You researchers and academics think you know it all”. Under ordinary circumstances, such a statement would have offended me, but in that moment, I realised I was asking all the right questions. That feeling pushed me to persevere and conduct the research as best I could. Not only for the sake of my research integrity but also to critically engage with the matter at hand, “how (if at all) is the city preparing for and adapting to the increasing climate challenges?”

Through my time in the field, I began to realise something strange: the more I studied the city, the less I felt I truly knew it. My coming in as a researcher meant that I had to view the city through a new lens – one shaped by critical analysis, policy frameworks, and institutional interviews. The reality is I wasn’t merely observing it; I was interrogating it. Consequently, my experience, although necessary and fruitful, felt very alienating. The alienation came from the swift realisation that my doctoral work would expose serious challenges within the metro. Although unpublished as yet, my findings demonstrate that climate action is being sidelined. However, what stood out the most was that despite the weight of bureaucracy and inequality impacting on a swift response, I saw a city trying to be resilient. A most memorable example is the rehabilitation of the Jukskei River which is one of the ways they aim to harness UEIs for climate resilience in the area by scaling nature based solutions for climate resilience in the city. That got a thumbs up from me!

My experience also meant discovery as I began to understand that Johannesburg not only carried childhood memories, but it was a complex and living system that required remediation and urgent attention. I understood that being a researcher in your own city means sitting with the discomfort of certain realities.

I’ve come to learn that simplifying science doesn’t mean avoiding jargon; it means being honest about how science changes and influences us, how it unsettles us, and teaches us to see differently. For me, my fieldwork wasn’t about collecting data, it was about unlearning, relearning, and reconnecting with my city in a deeper and more meaningful way.

While much in the way of cross sector collaboration is needed to prioritise climate change, Johannesburg is still home and is, as far as I could ascertain from my research, ready to adapt to climate change through UEIs.

Zaine Perry

They rage across the ocean, tear through coastlines, and leave devastation in their wake but tropical cyclones (TCs), for all their fury, are surprisingly delicate creatures. They rely on a perfect mix of conditions to form, survive, intensify and when just one of those ingredients goes missing, the whole system can collapse. That’s what makes them so fascinating (and so difficult to predict).

Hi, I’m a 2^nd year MSc student studying at the University of Cape Town (UCT), trying to understand one of the strangest TCs ever recorded: TC Freddy. I use numerical models to see how storms like Freddy form, move, intensify and impact regions over the South West Indian Ocean to improve forecasting and better protect vulnerable communities. I first encountered this storm – or at least the early parts of it – during my Honours in Ocean and Atmosphere Science at UCT, around two years ago.

Freddy formed northwest of Australia on 6 February 2023 and went on to travel over 8 000 km across the southern Indian Ocean, lasting until 14 March – over a month later. It made its first landfall in Madagascar on 21 February 2023 and went onto cross Mozambique a few days later. It brought catastrophic flooding, damages and death across Madagascar, Mozambique, and Malawi, and is now remembered as one of the most intense and persistent cyclones ever recorded in the region.

What I didn’t expect, however, was how familiar Freddy would become to me.

At the time, Freddy had recently occurred and gained a lot of attention for its unusual behaviour. My supervisors flagged it as a system worth looking into for my Honours research. Little did I know I’d still be talking about Freddy in my MSc thesis, still trying to make sense of what kept it alive for so long. It’s almost like Freddy refused to go quietly, both in the atmosphere and in my academic life.

Its record-breaking lifespan caught the attention of many in the scientific community, with researchers across the globe working to understand how a single storm could last so long. My work is one contribution to this wider effort. Here is my 2 cents worth.

At first glance, Freddy had the basics of a TC: warm sea surface temperatures and relatively low wind shear, the kind of ingredients researchers usually expect when a storm spins up. However, as I dug deeper into the data, I realised there was so much more going on and some of it was hiding beneath the surface.

One of the biggest surprises was ocean heat content (OHC). Freddy’s track overlapped with areas of high OHC, which I like to think of as the ocean’s energy reserve for fuelling storms. The friendly petrol attendant at the Engine garage, if you will. That hidden warmth beneath the surface gave Freddy the energy to keep going, even when you’d think it would start running low.

Another curveball was the influence of TC Dingani – a separate system swirling to the west of Freddy in mid-February 2023. On paper, the two storms were far apart, but they ended up indirectly shaping each other’s paths. Dingani interacted with the Mascarene High, a major subtropical pressure system, splitting it into two separate high-pressure cells. This split Mascarene High, altered the steering flow in the region and helped push Freddy westward, right across the southern Indian Ocean and into Madagascar.

Even more fascinating was the role of moisture. Dingani may have helped funnel moisture toward Freddy, effectively feeding it from a distance. Moisture is the lifeblood of a TC, and Freddy managed to maintain a rich supply throughout most of its journey by getting a blood transfusion from the guest to the west (Dingani). Weather data showed strong moisture fluxes from the lower and middle atmosphere, particularly in the lead-up to landfall events.

Speaking of landfalls, did you know that only 5% of TCs that reach Madagascar go on to make landfall in Mozambique? Freddy didn’t just make landfall, it did so twice with a “ping-pong” motion in between. After crossing Madagascar, Freddy moved into the Mozambique Channel, weakened overland, re-emerged over warm waters, and then re-intensified. That kind of behaviour isn’t unheard of, but it’s certainly unusual and hard to do numerical modelling on, especially when storms interact with both land and ocean environments in such complex ways.

In fact, modelling Freddy was one of the biggest challenges researchers faced. Weather models struggled to simulate its intensity and track with much accuracy. Even widely used datasets like IBTrACS, used by researchers and disaster agencies, missed parts of Freddy’s path, especially when it weakened over land. This is a big problem for studies that look at where storms go and what damage they cause, particularly in parts of southeastern Africa. These kinds of studies help us understand how often communities are hit, how severe the impacts are, and where support may be needed most. If the data says the cyclone wasn’t there… well, good luck claiming from insurance for the damage it caused. No track, no storm. No storm, no support. For vulnerable communities, that missing data can mean missing out on recovery aid they desperately need.

So, what does Freddy teach us?

For one, it shows that TCs are fragile beasts, sensitive to a range of atmospheric and oceanic conditions, many of which change from day to day. They’re not just wind and rain; they’re dynamic systems shaped by pressure patterns, ocean eddies, moisture transport, and even the presence of other storms.

Most weather models only simulate the atmosphere, but Freddy’s case suggests that leaving out the ocean, especially things like OHC, can be a big oversight. To better understand storms like Freddy, researchers need better tracking algorithms, more detailed ocean data, and coupled models that can simulate the feedback between ocean and atmosphere in real time. Only then can we improve our forecasting and give vulnerable communities the information they need before the next Freddy arrives.

Until then, I’ll probably still be thinking (and talking) about Freddy because some storms just leave a mark that’s hard to shake.

This map shows how large-scale pressure systems helped steer Cyclone Freddy (dots) and Dingani (triangles) across the Indian Ocean. Think of it as the atmospheric ‘roadmap’ that guided their paths (Perry et al., 2024).