A recent Associated Press (AP) story titled “Records shattered as summer heat hits Southwest in March; ‘This is what climate change looks like’” claims the recent Southwest heatwave is the latest proof that climate change is driving “ultra extremes.” [some emphasis, links added]
This is highly misleading and unsupported by real-world data. The story and the study it cites rely primarily on speculative modeling and reanalysis data rather than direct long-term observational comparisons.
Further, the Southwestern United States is an arid, naturally hot region of the country, with long-term droughts and used-up resources, [which is] likely one of the reasons multiple accomplished native peoples abandoned the area during different periods over time.
Heatwaves have been common throughout history, with “record” heatwaves having occurred long before “climate change” became a political buzzword and a darling topic of the media.
The AP’s report relies heavily on a single attribution study from the World Weather Attribution (WWA) group titled “Record-shattering March temperatures in Western North America virtually impossible without climate change.” As the AP reports, WWA asserts that the event was “virtually impossible without human-induced climate change.”
But reading the study, one finds that its conclusions are driven by the theory that humans are definitely causing dangerous climate change applied to climate model ensembles and reanalysis products, with assumptions built in.
In other words, it is an exercise in circular reasoning, driven by models calibrated against recent warming trends. That is not the same as direct historical proof.
Heatwaves are not new in the Southwestern United States or even across the country as a whole. The United States experienced extraordinary heatwaves in the 1930s during the Dust Bowl era, decades before large-scale postwar industrial emissions.
According to the National Oceanic and Atmospheric Administration (NOAA), the 1936 North American heatwave set all-time high-temperature state records that still stand today for nearly half the states in America.
The summer of 1936 remains one of the most extreme in the instrumental record. Likewise, the 1954 and 1980 U.S. heatwaves produced widespread triple-digit temperatures across the Southwest and Plains.
These all occurred when the Earth was cooler and human greenhouse gas emissions were small relative to today (See figure 1 below).
Globally, Europe’s 2003 heatwave and Russia’s 2010 heatwave occurred before the recent surge in attribution studies and were widely discussed in terms of atmospheric blocking patterns and natural variability.
Persistent high-pressure “heat dome” systems, like the one described in the WWA report, are well-known meteorological features that have driven extreme heat events for as long as weather has been recorded.
The relevant question is not whether heatwaves occur; they always have. The question is whether their frequency or intensity is increasing beyond natural variability. That requires long-term observational records, not model back-casting.
We have roughly 150 years of reasonably reliable global temperature measurements. Compared to the timescale of human existence—or even the Holocene epoch—that is a statistical blink of an eye.
In any sufficiently long dataset, new records are expected to occur occasionally, particularly in a warming recovery from the Little Ice Age. Setting a record does not automatically prove human causation.
The WWA study acknowledges that the event is so extreme that it is difficult to estimate a return period, defaulting to a one-in-100-year benchmark for analysis.
It further admits that model estimates vary widely, with probability ratios ranging from modest to effectively infinite, depending on weighting and assumptions. When a study produces probability ratios spanning orders of magnitude, that reflects uncertainty, not certainty.
Most importantly, the WWA method blends observational datasets with climate models, then adjusts statistical distributions based on global mean surface temperature. That is a modeling framework; it does not demonstrate that greenhouse gases physically “caused” the heat dome.
It estimates how model-generated worlds change under different assumed forcing scenarios.
Model output is not observation, and climate models are definitely not thermometers. They incorporate assumptions about feedbacks, aerosols, ocean-atmosphere coupling, and internal variability. Small changes in parameterization can yield very different probability ratios, as seen in the wide uncertainty bounds reported in the WWA report.
Furthermore, urban heat island effects, land-use changes, and expanding metropolitan areas in places like Phoenix and Las Vegas amplify measured heat extremes locally. Rapid population growth across the Southwest means more pavement, more infrastructure, and more heat retention.
That is a measurable, well-documented effect independent of global greenhouse gas concentrations.
A single five-day March heat event, no matter how uncomfortable, does not redefine long-term climatology. Blocking highs, jet stream shifts, and regional atmospheric circulation patterns remain primary drivers of short-term extremes.
The WWA report itself notes the role of a persistent high-pressure “heat dome.” That is meteorology, not carbon dioxide physics.
Climate Realism has refuted WWA’s studies multiple times in the past. The main problem with attribution studies – studies assembled quickly and lack peer review to glom onto headlines – is that they assume from the outset what they should be attempting to prove.
Statistician Dr. William Briggs provided a good, simple summary of how attribution models work:
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 are 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 exist now 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 modeled accurately to the degree attribution scientists claim because of the interconnectedness and chaotic nature of the different systems.
Chaos Theory itself sprang up from the findings of an individual attempting to generate computer models for weather.
Extreme heat deserves preparedness, planning, and adaptation. But conflating statistical model outputs with physical inevitability is scientifically illegitimate and misleads readers.
Bigger heatwaves have occurred in U.S. history before climate attribution became a media staple. Records are expected to be set during a 150-year dataset from time to time.
Attribution modeling is not the same thing as observational proof.
Calling this event “virtually impossible without climate change” is not a scientifically determined conclusion. The statement is grounded in probabilistic modeling, not grounded in data and real-world observations.
That is not careful climate science; it is a false narrative built on unjustified attribution.
Read more at Climate Realism
