Climate Whiplash and California Wildfires

Roger Caiazza

The difference between weather and climate is constantly mistaken by climate change advocates Recently Southern California wildfires have been blamed on climate change.  Patrick Brown addressed the question how much did “Climate Whiplash” impact the Los Angeles fires.  His excellent analysis raises concerns that I want to highlight.

Weather vs. Climate

Every time there is an extreme weather event proponents for eliminating fossil fuels confuse weather and climate when they claim the effects of GHG emissions on global warming are obvious today. According to the National Oceanic and Atmospheric Administration’s National Ocean Service “Weather reflects short-term conditions of the atmosphere while climate is the average daily weather for an extended period of time at a certain location.”  It goes on to explain “Climate is what you expect, weather is what you get.” 

Hydroclimate Volatility

Patrick Brown described the Swain et al. (2025): Hydroclimate Volatility on a Warming Earth Nature review paper. He quoted the first line of the UCLA Press Release for the paper: “Los Angeles is burning, and accelerating hydroclimate whiplash is the key climate connection”  and remarked: “Thanks in no small part to the huge journalistic audience that lead author Dr. Daniel Swain commands, the “climate whiplash” vernacular was immediately adopted in international headlines covering the recent Los Angeles fires.”  This is a classic example of an extreme weather event that is linked to climate change by organizations and individuals that have a vested interest in advancing the threat of climate change.

Brown noted that: “the paper has demonstrated incredible reach and is in the 99.99th percentile in terms of online attention for all research (not just climate research) of a similar age.”  However he echoes my concern: “But as is the case for so much high-profile climate science, there is a large gap between the impression conveyed by the coverage and the impression left from the observational data.”

Climate Whiplash

I have never heard of the concept of climate whiplash before this story broke.  Brown explains:

Dangerous, intense wildfires require dry vegetation. The idea behind the climate whiplash connection to the Los Angeles fires is that very wet winters in Southern California in 2022-2023 and 2023-2024 enabled a great deal of vegetation growth but that the very dry beginning of the 2024-2025 winter allowed that vegetation to dry out, resulting in a landscape primed for uncontrollable wildfires. Swain explains the mechanism in interviews with Adam Conover and Neil deGrasse Tyson.

In order for this to be a climate change problem, we need to know whether these events are increasing.  Brown noted that:

The idea being conveyed is that these climate whiplash events are dramatically increasing not just in Southern California, but globally.  “Every fraction of a degree of warming speeds the growing destructive power of the transitions” Swain said.

Brown described background for this concept:

Taking a step back, the fundamental theory undergirding changing “hydroclimate” (think water cycle where we are considering not just how precipitation provides moisture but also how evaporation takes moisture) whiplash is nothing new. It is a basic fact of atmospheric physics that a warmer atmosphere can “hold” more water vapor (about 7% more per °C of warming). This warming influence on the water cycle has been discussed in detail since at least the 1980s (e.g., Manabe, & Wetherald, 1986)). At first, most research discussed a general intensification of the water cycle, typically emphasizing that already dry areas would get drier and already wet areas would get wetter as the globe warmed. However, by the mid-2000s, studies like Trenberth et al. (2003), Chou & Neelin (2004), Meehl et al. (2005), and Held & Soden (2006) began pointing out that the same physics (warmer atmosphere holds more moisture) can drive larger variability in the same place—heavier rain events juxtaposed with prolonged and/or more intense dry spells.

These concepts are taught regularly as a part of Climate Change 101 classes, including my own, and they are accepted as consensus climate science, articulated with “high confidence” in the IPCC’s most recent assessment report:

“A warmer climate increases moisture transport into weather systems, which, on average, makes wet seasons and events wetter (high confidence)”

“Warming over land drives an increase in atmospheric evaporative demand and the severity of droughts (high confidence).”

The reason I wanted to highlight Brown’s analysis of this paper is because he highlights a key complication for the general public’s understanding of climate change.  It is accepted that a warmer climate increases moisture in the atmosphere and drought severity.  The implications of those mechanisms are important with respect to GHG emission reduction policies.  The question is so what? What is the magnitude of the change, what impacts might result from these mechanisms, and do we expect that changes in global temperatures due to GHG emissions will result in significant impacts from these mechanisms are all questions that should be addressed.

I fully endorse Brown’s explanation, especially the statement that I highlighted below:

However, I like to point out that it is useful to break down lines of evidence in climate science into categories of

1. Historical observations/trends
2. Fundamental theory
3. Mathematical modeling

I know from teaching the “wet gets wetter, dry gets drier” concept that the evidence for increased variability in the same location is much stronger in the theory and modeling categories than it is in observations. This is important because observations should take precedence over the other two. Focusing on observations tells us a lot about how big of an effect we’re talking about (i.e., do we see major trends emerge through the noise of the observation system and natural variability?). Furthermore, a fundamental point of doing science is to explain observations. The canonical order of operations is that first you observe some phenomenon, and then you use the tools of theory and modeling to make sense of it.

Observations

Brown goes on to evaluate observations of the whiplash where increased precipitation enabled a great deal of vegetation growth followed by a period of decreased precipitation that allowed that vegetation to dry out, “resulting in a landscape primed for uncontrollable wildfires”.  I am only going to summarize two of the results.

Brown evaluated observations of year-to-year water cycle variability following the methodology of the Swain et al. (2025) paper. Note that he only evaluated the effect over land because it has no effect on wildfires if it occurs over the ocean.  He did not find any compelling evidence for an increase in these events in California.  The results for global land were described:

So, over all global land, at the timescale that is most relevant to the Los Angeles fires (annual), in the premiere observational dataset (ERA5), using Swain et al. (2025)’s own data, we have seen a long-term decrease in whiplash frequency (this, by the way, is acknowledged in passing in the text of Swain et al. (2025) on page 37).

Let’s pause for a second to recall the first line of the UCLA press release (“Los Angeles is burning, and accelerating hydroclimate whiplash is the key climate connection.”) and the global news coverage it generated. Would any reader of this coverage have any idea about the incredibly important caveats above? Not that I can tell.

In the next section Brown discussed the magnitude of changes in annual water cycle variability.  He stated that:

Now, to be fair, Swain et al. (2025) purport to show evidence of increasing whiplash frequency at multiple timescales, spatial extents (over the ocean, for example), and in other datasets.

However, highlighting changes in arbitrarily-defined “event” frequency without reporting changes in “event” magnitude is misleading, and it goes against one of the core recommendations of the National Academies of Sciences 2016 report on Attribution of Extreme Weather Events in the Context of Climate Change. As Ted Shepherd recently put it in his presentation to the committee responsible for the next such report: “Frequency is the more impressive number, but magnitude is perhaps the more physically interpretable number.”

Brown’s analysis of the magnitude of the changes found: “1 we see no long-term increase in water cycle variability at the location and timescale relevant to the Los Angeles fires.”

Patrick Brown Summary

Brown’s summary is important.  He notes that the choice of analysis data used affects the conclusion:

While “climate whiplash events” may be increasing in frequency under most of the very specific, selected definitions used and datasets investigated in Swain et al. (2025), the general idea that annual precipitation (or more generally, the water cycle, which includes evaporation) is becoming dramatically more variable is not supported when a broader set of datasets and definitions are used.

Brown worries that this analysis and the publicity it received is a problem:

Would a reader of Swain et al. (2025), or especially its coverage, have any idea about the weakness of its broader conclusions or the lack of robustness of its results to different definitions and datasets? Almost certainly not, and I contend that this is a major problem for public understanding and trust in climate science.

One of my over-arching issues with the existential threat narrative is that the accepted science is distorted with respect to reality of natural variability.  Brown explains:

Why don’t we see a robust increase in water cycle variability given the strong theory underpinning “wet gets wetter, dry gets drier”? For one thing, the theoretical size of the effect is known to be quite small relative to natural, unforced variability, making it inherently difficult to detect. For example, we see in Figure 7 above that year-to-year rainfall in Los Angeles naturally varies by as much as 300%, yet the signal we are looking for is one to two orders of magnitude less than this. It is also apparently the case that observational uncertainty is larger than the signal (or there would not be such disagreement between datasets). Physically, perhaps increasing mean precipitation is offsetting the increase in calculated evaporation in the SPEI index, reducing its variability. Maybe reduced temperature variability (via arctic amplification) is reducing calculated evaporation variability.

I agree with Brown’s concluding remark:

My main discomfort with Swain et al. (2025) and its rollout is that it appears that the primary goal was to create and disseminate the “climate whiplash” meme rather than conduct a truly rigorous evaluation of the evidence, including countervailing evidence. Ultimately, this makes the research a much larger advance in marketing than an advance in science.

Conclusion

Patrick Brown does an excellent job eviscerating the climate whiplash headlined stories based on Swain et al. (2025)’s recent paper.  It is frustrating that biased analyses that confirm pre-conceived get so much attention.  It will require many evaluations like Brown’s to address the misinformation.

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Roger Caiazza blogs on New York energy and environmental issues at Pragmatic Environmentalist of New York.  He has been a practicing meteorologist for nearly 50 years, was a Certified Consulting Meteorologist, and has B.S. and M.S. degrees in meteorology.  The opinions expressed in this post do not reflect the position of any of his previous employers or any other organization he has been associated with.