By Paul Homewood
An excellent exposé by Linnea Lueken of the weather attribution fraud:
A recent post at Phys.org claims that a recent attribution study shows that climate change made April 2022’s flooding in South Africa, “significantly” worse. This is an unfalsifiable (not able to be proven or disproven experimentally or observationally) claim that ignores the complexities of weather, and relies on distinctly unreliable computer modelling.
The article, titled “Climate change significantly worsened deadly 2022 Durban floods, study shows,” goes over an attribution study that focused on flooding in Durban, South Africa, three years ago. Phys.org claims the study “shows that rainfall during the storm of 11–12 April 2022 was between 40 percent and 107 percent heavier than it would have been in a cooler, pre-industrial climate.”
How do they know this? They don’t, rather they claim it based on computer model outputs.
Unlike most coverage of attribution science, Phys.org vaguely hints at the fact that the modelling is less than bulletproof, explaining that the models “simulated the storm in both today’s warmed climate and a counterfactual world without human-induced global warming.”
Climate Realism has explained at length why attribution modelling is not evidence, but it may be helpful to point out that Phys.org is only half right here. It is true that they used a counterfactual world with no warming, but the warmed model is also counterfactual. A number of assumptions, some more robustly backed by available data and evidence than others, go into modelling the “current world.” Statistician Dr. William Briggs has what I consider the best simple summary of how attribution modelling works:
A model of the climate as it does not exist, but which is claimed to represent what the climate would look like had mankind not ‘interfered’ with it, is run many times. The outputs from these runs is examined for some ‘bad’ or ‘extreme’ event, such as higher temperatures or increased numbers of hurricanes making landfall, or rainfall exceeding some amount. The frequency with which these bad events occur in the model is noted. Next, a model of the climate as it is said to now exist is run many times. This model represents global warming. The frequencies from the same bad events in the model are again noted. The frequencies between the models are then compared. If the model of the current climate has a greater frequency of the bad event than the imaginary (called ‘counterfactual’) climate, the event is said to be caused by global warming, in whole or in part.
Both the “counterfactual” and the “current conditions” models can be massaged and changed to obtain nearly any result desired. It all depends on what assumptions are programmed in. There is no guarantee that the “real world” model is actually accurate. In fact, there is good reason to believe the Earth’s climate and weather systems cannot be modelled accurately to the degree attribution scientists claim because of the interconnectedness and chaotic nature of the different systems. In fact Chaos Theory itself sprung up from the findings of an individual attempting to generate computer models for weather.
Rainfall, for example, and flooding, are not as connected as climate scientists often claim. Even the IPCC, while noting that precipitation has generally increased in some parts of the world, acknowledges that flooding is not directly correlated to rainfall trends. In this case, human intervention on the natural world has a larger influence than rainfall alone. The construction of non-permeable surfaces like roads and foundations for buildings, for example, can exacerbate flooding even in places where rainfall trends have not changed. This is particularly true for places that have seen significant population growth and development.
This is certainly the case for Durban, South Africa, which has seen a 24% spike in population over just the last decade, adding nearly a million people since 2011.
Durban also has a long history of flooding. A study from the University of Witwatersrand notes that a “ . . . reconstructed the history of floods in KZN since the 1840s . . . a flooding event in September 1987 affected a larger geographic area of KZN and destroyed more homes than the 2022 event . . . [s]imilarly, a catastrophic flooding event in Durban, 1856 – also in April – produced a greater quantity of rainfall over a three-day period than last year’s floods.”
The 2022 flood was so catastrophic because more people and larger amounts of poorly designed homes and infrastructure were located in the area historically prone to flooding – the rainfall itself was not as severe as in the past. It’s likely that if attribution models had been around in the aftermath of the 1856 event, they would have attributed the flooding to climate change as a result of the assumptions built into the models and the way they are “tuned.”
Ironically, the Phys.org post bemoans the lack of immediate attribution, which they claim would somehow help save lives, However, at the time of the 2022 flooding, World Weather Attribution did respond and attribute the floods to climate change, as my colleague H. Sterling Burnett covered at the time. They were, of course, also incorrect. Burnett showed that Durban was already prone to historic flooding, which only would get worse with urbanization and insufficient water handling infrastructure.
Dedicated and widespread rainfall measurements have only existed in South Africa since 1960. There is not a whole lot of “recorded history” to go through when it comes to meteorology data in South Africa. There just isn’t enough data to say with such confidence that any of the flood events in recent years were unprecedented. Widespread satellite coverage for weather monitoring has existed only since the 1980s.
Instead of beginning with the assumption that climate change is making flooding worse in places like Durban, scientists should approach the issue more modestly. It is worthwhile to try to improve drainage and install better alarm systems in regions prone to flooding, but there is no reason to make global warming the focus of the arguments for better alerts. The truth at its most basic is sufficient: flooding happens and is especially deadly in heavily populated areas prone to flooding with inadequate warming systems and poorly designed infrastructure. People who persist in living in regions prone to flooding should be prepared, regardless of climate change.
https://climaterealism.com/2025/07/attribution-studies-dont-prove-anything-about-south-africas-floods-phys-org/
The key message here is that weather attribution models don’t only model the past climate, they also model the present one. As Linnea notes:
Both the “counterfactual” and the “current conditions” models can be massaged and changed to obtain nearly any result desired. It all depends on what assumptions are programmed in. There is no guarantee that the “real world” model is actually accurate. In fact, there is good reason to believe the Earth’s climate and weather systems cannot be modelled accurately to the degree attribution scientists claim because of the interconnectedness and chaotic nature of the different systems. In fact Chaos Theory itself sprung up from the findings of an individual attempting to generate computer models for weather.
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August 3, 2025 at 04:00AM
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