Claims in “How Climate Migration Will Reshape America” vs. observational data

A few people asked me about the accuracy of a recent NY Times Magazine / NY Times Daily Podcast story “How Climate Migration Will Reshape America”. It contains plenty of interesting discussion on e.g., property insurance under a changing climate but it is very loose with the facts on current climate change in the US and it continuously errs on the side of hyperbole and exaggeration.

Below I take a look at observational data corresponding to some of the claims in the article. Overall, I think the data gives a very different impression of the state of climate change in the US than does the rhetoric in the piece.

This is important because this kind of exaggeration undermines the credibility of the NY Times / NY Times Daily Podcast at a time when people really need journalism they can trust.

Furthermore, the issue of human migration under climate change is important and thus it needs to be covered in a serious and fact-based way. We cannot afford for this kind of sloppiness to give people an excuse to dismiss the entire premise.

Most of this piece’s claims are about the future. It is difficult to fact-check claims about the future so I will just look at a few claims that can be easily put in context against historical observational data.

Claim: “August besieged California with a heat unseen in generations.”

Context on CA heat: August 2020 was the fourth hottest month on record in California. It’s average temperature was 79°F. Not as hot as July 2018 (79.6°F), July 2006 (79.3°F), or July 1931 (79.5°F). So it was hot but not “unseen in generations”.

Claim: “I am far from the only American facing such questions. This summer has seen more fires, more heat, more storms — all of it making life increasingly untenable in larger areas of the nation”

Context on fires: The nation has not seen more fires through August but when September numbers are tallied this will indeed go up and likely will set a record. Though it is important to note that there is not an obvious nationwide long-term trend in wildfires.

More context on fires: It is perhaps worth mentioning that global annual area-burned has decreased over the past 20 years. This illustrates that, thus far, climate is not a first-order influence on area-burned and its influence can be totally overwhelmed by other factors. https://www.weatherclimatehumansystems.org/faq-on-fires-humans-and-global-change

Context on US heat: It is true that this summer was hot in the US. It was the 4th warmest on record behind 2011, 2012 and 1936.

More context on heat: Rather than looking at summer means, we can look at indices that measure attributes of heatwaves like the “Warm Spell Duration Index”. Here’s what that looks like for the US. The 1920s and 1930s had higher values that what we have seen recently.

Context on storms: It is not clear what is meant by storms. But maximum 1-day precipitation might be a pretty good proxy for what most people think of as storms. There have been increases in this metric over recent decades but we are not at a historical maxima:

More context on storms: The author could also be referring to tropical storms. Below is a measure of tropical storms making landfall in the United States. We can see some increase in recent decades.

Claim: “Already, droughts regularly threaten food crops across the West…”

Context on droughts: The brown bars are the area in the US that are much more arid than normal. The US West has indeed seen bad droughts in the 2000s and 2010s. More on crops below.

More context on droughts: It is worth noting that we do not see long-term trends in droughts over the US overall.

Claim: “while destructive floods inundate towns and fields from the Dakotas to Maryland”

Context on floods: Here is the long-term change in an index of maximum 5-day precipitation. While not a direct measure of floods, this can be thought of as a rough proxy. By this measure, we are not currently at a historical maxima.

Claim: “Rising seas and increasingly violent hurricanes are making thousands of miles of American shoreline nearly uninhabitable.”

Context on rising seas: Global sea levels have risen about 3 inches since the mid 1990s. This will be a major problem as it continues but does 3 inches plus the change in tropical cyclones shown above amount to “thousands of miles of shoreline nearly uninhabitable”? Sorry, it does not.

http://sealevel.colorado.edu/

Claim: “Let’s start with some basics. Across the country, it’s going to get hot. Buffalo may feel in a few decades like Tempe, Ariz., does today”

Context: This is absolutely false. The average daily high temperature in July in Buffalo NY is near 79°F. The average daily high temperature in July in Tempe Arizona is near 106°F. That’s a 27°F difference.

Buffalo is projected to warm by roughly 2.3°F under a medium emissions scenario by 2050 (and by 5°F by 2100). So that would mean that the author claimed a warming of something like 27°F “in a few decades” when our best estimate is something closer to 10% of that.

Claim: “The Great Plains states today provide nearly half of the nation’s wheat, sorghum and cattle and much of its corn; the farmers and ranchers there export that food to Africa, South America and Asia. Crop yields, though, will drop sharply with every degree of warming.”

Context on crop yields: Historically it has warmed and crop yields have only increased. For one thing, there has been little detrimental climate stress on US crops so far, as measured by indices like the Crop Moisture Stress Index:

Further Context on crop yields: Yields of corn and other crops have only increased globally because changes in technology and agricultural practices have vastly outweighed any negative impact from climate. https://ourworldindata.org/crop-yields

Claim: “It was the kind of thing that might never have been possible if California’s autumn winds weren’t getting fiercer and drier every year”.

Context on CA autumn winds: The most infamous fire-enhancing autumn winds in CA are the “Santa Ana winds”. They are not increasing every year and projections suggest that their occurrence will be less frequent not more frequent under climate change.

https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018GL080261

Claim: “The 2018 National Climate Assessment also warns that the U.S. economy overall could contract by 10 percent.”

Context: This is a 10% contraction relative to a no-climate change scenario not 10% contraction relative to today. That distinction makes a huge difference. It means that the projection says that if GDP were to increase by 100% without climate change over the next 80 years (very conservative estimate) then climate change would cause GDP to “only” increase by 90%.

Claim: “Once you accept that climate change is fast making large parts of the United States nearly uninhabitable…”

Context: I am sorry but this is just not reconcilable with the data above.

I could go on with other claims made in this piece but I’ll stop here for now. You should get the idea. It paints a picture of current climate change in the US that is very different than the story that is told from looking at the actual observational data and all the errors are in the direction of overstating the negative impact on the US today.

The editors at NY Times Magazine / The Daily Podcast must think that being cavalier with the facts is OK because ‘sending the right message’ on climate change is more important than accuracy. I could not disagree more.

At a time when trust in institutions like the New York Times is faltering, and the right calls them fake news – they cannot afford to confirm that narrative. It makes it too easy for those who want to be dismissive of climate change to feel vindicated in that belief.

Plots above are mostly from: https://ncdc.noaa.gov/cag/ and https://climdex.org/access/

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Tipping Points in the Climate System

Lecture on tipping points in the climate system from my frosh, general education level Global Warming course.

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Seasonal Prediction of Particularly-Impactful Hot Days

Screen Shot 2020-01-03 at 11.45.26 AM

My talk on this research at the American Meteorological Society’s Annual Meeting.

PTBrown_AGU_2019_Poster

AGU E-Poster

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Net Economic Impact of UN Global Warming Mitigation Targets

PTBrown_AGU_2018.png

PTBrown_AGU_2018_Poster

 

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This video is a visual explanation of meteorological Skew-T, Log-P sounding diagrams (aka thermodynamic diagrams)

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Why is concern about global warming so politically polarized?

As a climate scientist, I often hear it bemoaned that the public discussion of human-caused global warming is so politically polarized (Pew Research, 2019). The argument goes that global warming is simply a matter of pure science and thus there should be no divisions of opinion along political lines. Since it tends to be the political Right that opposes policies designed to address global warming, the reason for the political division is often placed solely on the ideological stubbornness of the Right.

This is a common theme in research on political divides regarding scientific questions. These divides are often studied from the perspective of researchers on the Left who, rather self-servingly, frame the research question as something like “Our side came to its conclusions from pure reason, so what exactly makes the people who disagree with us so biased and ideologically motivated?” I would put works like The Republican Brain: The Science of Why They Deny Science — and Reality in this category.

Works like The Republican Brain correctly point out that those most dismissive of global warming tend to be on the Right, but they incorrectly assume that the Left’s position is therefore informed by dispassionate logic. If the Left was motivated by pure reason then the Left would not be just as likely as the Right to deny science on the safety of vaccines and genetically modified foods. Additionally, as Mooney has argued elsewhere, the Left is more eager than the Right to deny mainstream science when it doesn’t support a blank-slate view of human nature. This suggests that fidelity to science and logic are not what motivates the Left’s concern about global warming.

Rather than thinking of the political divide on global warming as being the result of logic vs. dogma, a much better explanation is that people tend to accept conclusions, be they scientific or otherwise, that support themes, ideologies, and narratives that are a preexisting component of their worldview (e.g., Washburn and Skitka, 2017). It just so happens that the themes, ideologies, and narratives associated with human-caused global warming and its proposed solutions align well with archetypal worldviews of the Left and create great tension with archetypal worldviews of the Right.

The definitional distinction between the political Right and the political Left originates from the French Revolution and is most fundamentally about the desirability and perceived validity of social hierarchies. Definitionally, those on the Right see hierarchies as natural, meritocratic and justified while those on the Left see hierarchies more as a product of luck and exploitation. A secondary distinction, at least contemporarily in the West, is that those on the Right tend to emphasize individualism at the expense of collectivism and those on the Left prefer the reverse.

There are several aspects of the contemporary human-caused global warming narrative that align well with an anti-hierarchy, collectivist worldview. This makes the issue gratifying to the sensibilities of the Left and offending to the sensibilities of the Right.

The most fundamental of these themes is the degree to which humanity itself can be placed at the top of the hierarchy of life on the planet. Those on the Right would be more likely to articulate that it is justified to privilege the interests of humanity over the interests of other species or the “interests” of the planet as a whole (to the degree that there is such a thing). On the other hand, those on the Left would be more likely to emphasize across-species egalitarianism and advocate for reduced impact on the environment, even if it is against the interest of humans.

Within humanity, there are also at least two levels for which narratives about hierarchies influence thinking on global warming. One is the issue of developed vs. developing countries. The blame for global warming falls disproportionately on developed countries (in terms of historical greenhouse gas emissions) and thus proposed solutions often call on developed countries to bear the brunt of the cost of reducing emissions going forward. (Additionally, it is argued that developed countries have the luxury of being able to afford the associated increases in the cost of energy.) Overall, the solutions proposed for global warming imply that wealthy countries owe a debt to the rest of humanity that should come due sooner rather than later.

Those on the Right are more likely to see the wealth of developed countries as being rightfully earned through their own industriousness while those on the Left are more likely to view the disproportionate wealth of different countries as being fundamentally unjust and likely originating from exploitation. Thus, the story that wealthy countries are to blame for the global warming problem and that the solution is to penalize wealthy countries and subsidize poor countries is one that aligns well with preexisting narratives on the Left but not those on the Right. An accentuating factor is the tendency of the Right to be more in favor of national autonomy and thus opposed to global governance and especially international redistribution.

The third level for which hierarchy narratives couple with political divides on global warming relates to the wealth of corporations and individuals. On the Right, the story of oil and gas companies (as well as electric utilities that utilize fossil fuels) is one of innovation and wealth creation: The smartest and most deserving people and organizations found the most efficient ways to transform idle fossil fuel resources into the power that runs society and greatly enhances human wellbeing. Under such a narrative, it is fundamentally unjust to point a finger of blame at those entities (both corporations and individuals) that have done so much for human progress. The counter-narrative from the Left is that greedy corporations and individuals exploited natural resources for their own gain at the expense of the planet and the general public. Under this narrative, policies that blame and punish those in the fossil fuel industry are seen as bringing about a cosmic justice that is necessary for them to atone for their sins.

The other major overlapping theme that defines the divide between the Left and the Right on global warming is the degree to which collectivism is emphasized compared to individualism. Global warming is fundamentally a tragedy of the commons problem in which logical agents act in such a way that ends up being in the worst interest for everyone in the long term. These types of ‘collective-action problems’ almost necessarily call for top-down government intervention and thus they are inevitably associated with collectivism at the expense of individualism. Also, global warming’s long term nature calls for the embracement of collectivism across generations. Again, this natural alignment of the global warming problem with collectivist themes makes the issue much more palatable for the Left than for the Right.

In addition to these fundamental ideological issues, there are a number of more circumstantial characteristics that’s I believe have contributed to polarization regarding global warming.

One is that, in the U.S. at least, Al Gore was the primary actor that brought global warming into the national consciousness. If one wanted the issue to be “non-political” one couldn’t have conceived of a worse person than a former vice president and presidential nominee to be the main flagbearer for the movement.

Also, there is the longstanding claim by those on the Right that the global warming issue is just a Trojan Horse intended as an excuse to bring about all the desired policies of the Left. Books like This Changes Everything: Capitalism vs. The Climate and plans like the Green New Deal do little to dispel this narrative. For example, the Green New Deal Resolution contained the following proposals:

“Providing all people of the United States with— (i) high-quality health care; (ii) affordable, safe, and adequate housing; (iii) economic security; and (iv) access to clean water, clean air, healthy and affordable food, and nature.”

“Guaranteeing a job with a family-sustaining wage, adequate family and medical leave, paid vacations, and retirement security to all people of the United States.”

“Providing resources, training, and high-quality education, including higher education, to all people of the United States, with a focus on frontline and vulnerable communities, so those communities may be full and equal participants in the Green New Deal mobilization”.

These are objectives that clearly seek to satisfy goals of the Left but it is much less clear how directly related these objectives are to global warming.

So, it should really not be particularly mysterious that opinions on global warming tend to divide along political lines. It is not because one side embraces pure reason while the other remains obstinately wedded to political dogmatism. It is simply that the problem and its proposed solutions align more comfortably with the dogma of one side than the other. That does not mean, however, that the Left is equally out-of-step with the science of global warming as the Right. It really is the case that the Right is more likely to deny the most well-established aspects of the science. But, if skeptical conservatives are to be convinced, the Left must learn to reframe the issue in a way that is more palatable to their worldview.

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Daily, Seasonal, Annual and Decadal Temperature Variability on a Single Graph

New York Daily Seasonal Annual and Decadal Temperature

The graph above is a record of temperature from 1950-2017 for New York City.

What is unique about this graph is that it shows daily, seasonal, annual and decadal temperature variability on a single Y-axis, revealing how their magnitudes compare.

The daily temperature cycle is represented by the three colored lines in each panel, where red, black and blue represent the daily maximum, daily average and daily minimum for each season and year. For example, the red dots in the far left panel represent the average of all the daily maximum temperatures for the spring of each year.

We can see that in New York, the daily minimum temperature tends to be around 13 degrees C (23 degrees F) lower than the daily maximum temperature.

The annual temperature cycle is illustrated by the variation across the four panels with each panel representing one of the four canonical seasons.

We can see that in New York, the summer tends to be about 22 degrees C (40 degrees F) warmer than the winter.

Interannual temperature variability is illustrated by the year-to-year wiggles in each line.

We can see that in New York, there can be year-to-year swings in temperature (for a given season) of several degrees C. For example, the summer of 1999 had a daily average temperature of 24 C (75 F) and the summer of 2000 had a daily average temperature of 21 C (70 F). It is also notable that year-to-year variability in winter temperature is substantially larger than year-to-year variability in summer temperature.

Decadal temperature changes are represented by the linear trend lines. We can see long term warming which is primarily driven by increases in greenhouse gasses (i.e., this is the local manifestation of global warming). The long term warming is generally more prominent in the daily minimum temperature compared to the daily maximum temperature and more prominent in the winter compared to the summer. In other words, global warming is shrinking both the daily and seasonal temperature cycles.

In terms of absolute magnitude, the seasonal cycle is the dominant mode of variability, followed by the daily cycle, year-to-year variability and finally, long term warming.

Thus, while Global Warming is very pronounced on global spatial scales and centennial and greater timescales, we can see that, thus far, it has had a modest influence on the temperature in New York relative to the typical variability at the daily, seasonal and annual timescales.

Data here is from Berkeley Earth.

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El Nino’s influence the upcoming season’s global land temperatures

The El-Niño Southern Oscillation (ENSO) is the preeminent mode of global climate variability on timescales of months to several years. El Niño events cause temporary elevations in global average temperatures, and in the context of background global warming from increasing greenhouse gas concentrations, El Niño events are often associated with setting new global temperature records. El Niños cause warmer than typical global average temperatures because they are associated with a great amount of heat release from the equatorial Pacific to the atmosphere which is then distributed globally. This release of heat also imprints on the structure of the atmosphere and shifts the tendencies of typical atmospheric circulations. In certain locations, advection from climatologically colder locations (e.g., flow from the north in the Northern Hemisphere) becomes more prominent than normal during El Niño events which can cause a local tendency for temperatures to cool during El Niños, despite elevated temperatures globally. The large scale atmospheric circulation is also influenced by the state of ENSO differently depending on the time of the year.

This all means that if you want to translate the state of ENSO into a seasonal forecast (e.g., a forecast for 3-month average temperatures) at a particular location, you have to be careful to examine both the specific relationship between ENSO and climate variability at the location you are interested in as well as how that relationship depends on the time of the year. This is the purpose of the Simple ENSO Regression Forecast (SERF).

The SERF is based on an ensemble of dynamical and statistical model forecasts that predict the future state of ENSO, combined with the historical relationships between the state of ENSO and concurrent local surface air temperature departures from average (as a function of location and time of the year).

At ClimateAi, we are developing considerably more sophisticated machine learning techniques for application to seasonal forecasting that are able to achieve enhanced skill over this simple method. Nevertheless, this simple method is transparent and serves as a useful benchmark for more sophisticated methods to be compared to.

Below is the Simple ENSO Regression Forecast (SERF) for the 2019 Northern Hemisphere summer and Southern Hemisphere winter (June-July-August 2019). A weak El-Niño like state is expected to persist throughout the upcoming season. This translates into an expectation for below normal temperatures over northern/central Canada, the US upper Midwest and much of Russia. Above average temperatures are expected over the US Pacific Northwest, Mexico, much of South America, Africa, India, the Middle East and Europe (see Figure 1 and Figure 2 below). One reason that the tropics shows more consistent warming is that the background global warming has a higher signal-to-noise ratio there which means it is more likely that any given season will be above its 1971-2000 average, regardless of the state of ENSO.

global_SERF_JJA_2019

Figure 1. Top) SERF forecast of the average temperature for June-July-August 2019 relative to the long term average (from 1971-2000) for each location. Bottom) Chance that the average temperature over June-July-August will be above the long term average (from 1971-2000) for June-July-August at that location.

regional_SERF_JJA_2019

Figure 2. Same as the bottom of figure 1 but zoomed in to particular regions.

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Does the IPCC say we have until 2030 to avoid catastrophic global warming?

In late 2018 the Intergovernmental Panel on Climate Change (IPCC) released a report on the impacts associated with global warming of 1.5°C (2.7°F) above preindustrial levels (as of 2019 we are at about 1.0°C above pre-industrial levels) as well as the technical feasibility of limiting global warming to such a level. The media coverage of the report immediately produced a meme that continues to persist. The meme is some kind of variation of the following:

The IPCC concluded that we have until 2030 (or 12 years) to avoid catastrophic global warming

Below is a sampling of headlines from coverage that propagated this meme.

However, these headlines are essentially purveying a myth. I think it is necessary to push back against this meme for two main reasons:

1) It is false.

2) I believe that spreading this messaging will ultimately undermine the credibility of the IPCC and climate science more generally.

Taking these two points in turn:

1) The IPCC did not conclude that society has until 2030 to avoid catastrophic global warming.

First of all, the word “catastrophic” does not appear in the IPCC report. This is because the report was not tasked with defining a level of global warming which might be considered to be catastrophic (or any other alarming adjective). Rather, the report was tasked with evaluating the impacts of global warming of 1.5°C (2.7°F) above preindustrial levels, and comparing these to the impacts associated with 2.0°C (3.6°F) above preindustrial levels as well as evaluating the changes to global energy systems that would be necessary in order to limit global warming to 1.5°C.

In the report, the UN has taken the strategy of defining temperature targets and then evaluating the impacts at these targets rather than asking what temperature level might be considered to be catastrophic. This is presumably because the definition of a catastrophe will inevitably vary from country to country and person to person, and there is not robust evidence that there is some kind of universal temperature threshold where a wide range of impacts suddenly become greatly magnified. Instead, impacts seem to be on a continuum where they simply get worse with more warming.

So what did the IPCC conclude regarding the impacts of global warming of 1.5°C? The full IPCC report constituted an exhaustive literature review but the main conclusions were boiled down in the relatively concise summary for policymakers. There were six high-level impact-related conclusions:

So to summarize the summary, the IPCC’s literature review found that impacts of global warming at 2.0°C are worse than at 1.5°C.

The differences in tone between the conclusions of the actual report and the media headlines highlighted above are rather remarkable. But can some of these impacts be considered to be catastrophic even if the IPCC doesn’t use alarming language? Again, this would depend entirely on the definition of the word catastrophic.

If one defines catastrophic as a substantial decline in the extent of artic sea ice, then global warming was already catastrophic a couple decades ago. If global warming intensified a wild fire to the extent that it engulfed your home (whereas it would not have without global warming) then global warming has already been catastrophic for you.

However, I do not believe that changes in arctic sea ice extent and marginal changes in damages from forest fires (or droughts, floods etc.) are what most people envision when they think of the word catastrophic in this context. I believe that the imagery evoked in most peoples’ minds is much more at the scale of a global apocalyptic event. This idea is exemplified in Michael Barbaro’s question about the IPCC report that he asked on The New York Times’ The Daily:

“If we overshoot, if we blow past 1.5°C and 2°C degree warming, is it possible at that point that we’ve lost so much infrastructure, so much of the personnel and the resources required to fix this that it can’t be done anymore? Will there be enough of the world left to implement this in a way that could be effective?”

-Michael Barbaro, New York Times, The Daily, 10/19/2018

It is also articulated in a tweet from prominent climate science communicator Eric Holthaus:

If catastrophe is defined as global-scale devastation to human society then I do not see how it could be possible to read the IPCC report and interpret it as predicting catastrophe at 1.5°C or 2°C of warming. It simply makes no projections approaching such a level of alarm.

2. Undermining credibility.

Some will object to me pointing out that the IPCC has not predicted a global-scale societal catastrophe by 2030. They will inevitably suggest that whether or not the meme is strictly true, it is useful for motivating action on climate policy and therefore it is counterproductive to push back against it. I could not disagree more with this line of thinking.

The point of a document like the IPCC report should be to inform the public and policy makers in a dispassionate and objective way, not to make a case in order to inspire action. The fundamental reason for trusting science in general (and the IPCC in particular) is the notion that the enterprise will be objectively evaluating our best understanding of reality, not arguing for a predetermined outcome. I believe that the IPCC report has adhered to the best scientific standards but the meme of a predicted catastrophe makes it seem as though it has veered into full advocacy mode – making it appear untrustworthy.

An on-the-record prediction that may come back to haunt us

Apart from the inaccurate characterization that the IPCC has projected a catastrophe at 1.5°C, the other potentially harmful aspect of the media headlines above is that they put a timetable on the catastrophe that is very much in the near-term (2030). The year 2030 comes from the idea that we could first cross the 1.5°C threshold (at the annual mean level) in 2030, as is articulated in the report:

Now, if we immediately implement the global climate policies necessary to avoid 1.5°C of warming, then the prediction of a catastrophe will never be put to the test. However, as the IPCC report makes clear, achieving the cuts in emissions necessary to limit global warming to 1.5°C represents a truly massive effort:

Given that this effort would likely be massively expensive and represents a large technical challenge, it is unlikely to occur. This means that we are likely to pass 1.5°C of warming sometime in the 2030s, 2040s or 2050s. At this point – assuming that nothing resembling what most people would consider to be a global societal catastrophe has occurred – the catastrophe meme associated with the 2018 IPCC report will be dredged up and used as ammunition against the credibility of climate science and the IPCC. I fear that it will be used to undermine any further scientific evaluation of impacts from global warming.

In my experience, the primary reason that people skeptical of climate science come to their skepticism is that they believe climate scientists are acting as advocates rather than dispassionate evaluators of evidence. They believe climate scientists are acting as lawyers, making the case for climate action, rather than judges objectively weighing facts. The meme of a global catastrophe by 2030 seems to put a prediction on the record that is likely to be proven false and thus likely to reinforce this notion of ‘climate scientists as untrustworthy activists’ and thus harm the credibility of climate science thereafter.

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California fires and Global Warming’s influence on lack of moisture

This autumn has been very dry in California and this has undoubtedly increased the chance of occurrence of the deadly wildfires that the state is seeing.

When assessing the influence of global warming (from human burning of fossil fuels) on these fires, it is relevant to look at climate model projections of extremely dry autumn conditions in California. Below is an animation that uses climate models to calculate the odds that any given November in California will be extremely dry.

Here, extremely dry is defined as a California statewide November that is characterized by soil moisture content three standard deviations below the mean, where the mean and standard deviation is defined over the period 1860-1900.

We can see that these extremely dry Novembers in California go from being exceptionally rare early in the period (by definition), to being more likely now (~1% chance), and much more likely by the end of the century (~7% chance).

In terms of an odds ratio, this would indicate that “extremely dry” conditions are approximately 7 times more likely now than they were at the end of the 19th century and that these “extremely dry” conditions would be approximately 50 times more likely at the end of the century under an RCP8.5 scenario.

 

*chance is calculated by looking at the frequency of California Novembers below the 3 standard deviation threshold across all CMIP5 ensemble members (70) and using a moving window of 40 years.

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