Union of Concerned Scientists Global Warming

Weatherwise, 2026’s warm season has been one for the record books in many parts of the Midwest. A seemingly endless barrage of severe and, at times, deadly thunderstorms and tornados have wreaked havoc on homes and businesses, hundreds of thousands of which experienced power outages as a result.

As climate change is projected to increase severe thunderstorm activity across much of the Midwest, the power sector should heed this year’s pummeling as a wake-up call and reflect on whether it’s ready to withstand more of the same. This year offers an opportunity to imagine more concretely into a climate changed-world, to consider where system vulnerabilities lie, and where investments are needed to ensure our grid is resilient and able to reliably and equitably provide electricity for homes and businesses across the region. 

2026 weather extremes blow past 30-year averages

Taking stock of this year’s weather extremes in the Midwest is personal for me. And not to bury the lede: my family is fine, but we just barely avoided landing in the crosshairs of some of the most dangerous storms that have hit my home state of Wisconsin.

In mid-June, my husband and daughter were hunkered down in a barn in Belleville, Wisconsin, waiting out a severe thunderstorm that produced a tornado down the road. The storm destroyed two homes and severely damaged several more in Belleville. 

On another occasion, my daughter spent her last hour of the school year sheltered in place in her school’s basement as a severe thunderstorm roared through the area, producing 80+ MPH wind gusts. It was such a strong storm that it was eventually classified as a derecho— a particularly extreme class of severe thunderstorms. 

Looking out from the personal to the broader pattern, this has been an astounding year for Wisconsin. This April was the most tornadic on record in 76 years, with 27 tornados touching down across the state versus the more typical single April tornado. May was a relatively calm month, but there were 58 percent more severe storms in June than average. 

Wisconsin is certainly not alone. Most states in the Midwest had above average tornado counts in April. However, Illinois has been the hardest hit, experiencing the most tornados of any state in the US this year. Illinois has already seen 212 tornadoes form—more than three times its annual average of the last thirty years. To date, the National Weather Service has issued a whopping 812 severe thunderstorm warnings in Illinois.

StateNWS Severe Thunderstorm WarningsNWS 30-Year Average Severe Thunderstorm Warnings (1996-2025)Tornados That Formed30-Year Average Tornado Counts (1996-2025)Illinois81260821264Wisconsin4743474625Michigan 3313612614Examples of 2026 year-to-date severe thunderstorm warnings issued in the Midwest by the National Weather Service (NWS) and tornado counts as compared with long-term, 30-year averages. (Numbers collected through 7/7/26.)  Consequences for our power system

The deadly and damaging severe storms that have hit the Midwest this year have been incredibly consequential for power outages, and things are not slowing down yet. On Independence Day weekend, deadly, climate change-driven extreme heat and severe thunderstorms drove prolonged power outages for hundreds of thousands of homes and businesses across the Midwest, leaving many in dangerous, hot conditions. 

Nearly two million homes and businesses lost power as a result of a series of severe thunderstorms that hit the Midwest and Ohio Valley in mid-June, according to an analysis by PowerOutage.us. Thousands of homes and businesses lost their power for multiple days on end as a result of the storms, including in my hometown of Madison, where the storms downed power lines and broke power poles. Check out this incredible simulation of the power outages caused by some of the severe thunderstorms rolling through on June 10. 

Unfortunately, this year is unlikely to be an anomaly with respect to severe storms causing power outages in the Midwest. Important aspects of severe thunderstorm activity are already strengthening as a result of human-caused climate change. 

In addition, warmer temperatures—and with them, thunderstorms—are expected to occur earlier in the Midwest as they did this spring, lengthening the timeframe within which severe thunderstorms can form. And climate change is forecast to increase the likelihood of extreme heat that can co-occur with severe storms and strain the power system as happened on Independence Day weekend, leaving communities in harm’s way.

It is therefore critical that power sector actors heed the warning that this year is giving them. As my colleagues and I recommend in our report Power After the Storm, detailed climate risk assessments must be carried out to understand what the grid is going to be up against and how risks should be mitigated and addressed. 

We also urge the power sector to transition to electricity grids powered by clean energy so that we can prevent the worst impacts of climate change from manifesting. Finally, we encourage engagement with communities in order that investments and decisions reflect the needs of all customers that our electricity grids are meant to serve. 

By taking lived experiences from this year into account together with advances in climate science, we can make our electricity grid more resilient and ready to handle the more extreme weather that is headed our way.

The author would like to thank the Wisconsin State Climatology Office for their assistance with some of the statistics used in this blog.

In yet another year defined by record breaking weather events, attribution science can play an important role in articulating how climate change is both contributing to and worsening extremes. 

In broad strokes, attribution science identifies and quantifies human contributions to climate change and its related impacts. Attribution research has provided foundational understanding about climate change for over 30 years and has been a cornerstone of the United Nations’ Intergovernmental Panel on Climate Change (IPCC) assessments, which serve as the global authority on consensus climate change science. These studies are retrospective and distinct from climate impact time series because they isolate the role of climate change and address questions of causation. Similarly, they are separate from projection studies that model the impacts of climate change into the future. 

Attribution science includes four interrelated subfields—trend, source, impact, and extreme event—which provide different kinds of insight into the consequences of climate change. This blog, however, will focus specifically on what extreme event attribution can tell us about our world and discuss strategies to communicate both its findings and its limitations.

A brief history of extreme event attribution

Did climate change make this heatwave more likely?

Did climate change make this downpour more intense?

Extreme event attribution (EEA) answers research questions like these. Like so many scientific disciplines, attribution research has evolved over time, allowing scientists to answer new questions about the impacts of fossil-fueled climate change.

The first EEA study focused on a devastating heatwave that occurred in Europe in 2003, that led to 35,000 excess deaths and the creation of extreme heat warning programs in countries across Europe. The study, published by Peter Stott and colleagues in 2004, found that human influence had more than doubled the likelihood of this event. While attribution methods had previously shown how climate change had contributed to trends like rising global average surface temperatures, this study represented a huge methodological advance by isolating the role of climate change in an individual event for the first time.

Over the past 20+ years, the field has evolved rapidly, increasing our understanding of how climate change is driving extreme weather. This type of research has shown that during Hurricane Harvey, climate change tripled the likelihood of extreme rainfall and increased total rainfall by at least 19%, with a best estimate of 37%. Similarly, research on extreme heat has shown that climate change made the 2021 Pacific Northwest heatwave up to 3.6°F hotter.  

Sometimes this research finds that climate change did not play a role in a given extreme event. A study focused on May 2023 extreme rain in northern Italy, for instance, found that climate change didn’t affect the event’s likelihood or severity. Results like these affirm the rigor of this methodology, but are also rare given the fundamental changes to our atmosphere.

EEA studies have also become critical evidence in IPCC assessment reports, supporting key findings like:

“Human-caused climate change is already affecting many weather and climate extremes in every region across the globe” and “It is virtually certain that hot extremes (including heatwaves) have become more frequent and more intense across most land regions since the 1950s, with high confidence that human-induced climate change is the main driver of these changes.”

Each statement and figure included in the Summary for Policymakers section of IPCC reports (like those quoted above) are approved by every country that participates in the IPCC in collaboration with the report’s scientific authors. As a result, the inclusion of EEA research in IPCC reports and the Summaries for Policymakers underscores the robust methodology that underlies these studies as well as their role in shaping the consensus understanding of climate change.   

Innovative studies moved the field of EEA forward in 2025, with two high profile studies that addressed research questions about the contributions of emissions from the Carbon Majors, the largest fossil fuel producers and cement manufacturers in the world, to extreme heatwaves.

One study attributed the economic costs of several extreme heatwaves to the emissions of the Carbon Majors, finding that the emissions of single emitter, Chevron, have led to between $791 billion to $3.6 trillion USD in heat related losses over a 31 year period.

Another study systematically attributed 231 heatwaves to emissions from the Carbon Majors, finding that their emissions contributed to half of the increase in heatwave intensity over the last 120 years, and that between 16 and 53 of these heatwaves would not have occurred without emissions traced to these entities. Like the Stott study in 2004, these studies highlight major developments in extreme event attribution and foreshadow the exciting research on the horizon.

Ease of attributing the role of climate change depends on event type and geography

Extreme event attribution research builds on decades of peer-reviewed science. The available data and methodology, however, mean that scientists can attribute some types of events with higher confidence and that the geographic spread of these studies skews heavily towards events in the Global North.

The events that can be attributed with the most confidence are those that are most closely tied to temperature increases, like heatwaves. Isolating the contribution of climate change can be more complicated for more complex events,  like convective storms that involve more complex processes. This translates to different levels of confidence in the attribution of certain types of events, which is reflected in the published literature about these topics. The IPCC is very clear about this while also affirming the confidence and rigor of studies and event types where scientists have stronger confidence in their conclusions.

Extreme event attribution research is also not well distributed geographically, with lots of studies focused on events in the Global North and far fewer studies on events in the Global South. Systemic issues can make bridging this gap difficult. For example, long term data sets required to establish a baseline in this type of research are often more readily available the Global North, which carries important equity implications as attribution science becomes important in the accountability and litigation spaces.

EEA research is one important tool among many for understanding climate change. However, remaining cognizant of its limitations and working to overcome them will be key as the field continues to develop.

Communicating about climate change and extreme events

Attribution science is a broad field of research, but EEA research has become its poster child, in part, due to the work of World Weather Attribution which conducts rapid attribution studies using peer reviewed methods, often resulting in broad media coverage. While these studies have increased awareness of fossil fueled extreme events, they have also led to confusion about what types of questions attribution science can and can’t answer. answer.

Attribution science answers questions like: did climate change make this event more frequent or intense?

It does not answer the question: was climate change the sole contributor to this event?  

Similarly, we’re never going to have an attribution study for every event. But even without one, climate science—particularly trend attribution research—can inform our thinking about how climate change may have played a role.

For example, hurricanes are super complex events, and tropical cyclone formation is notoriously hard to model. As a result, I’m not aware of any EEA studies that demonstrate how climate change contributed to the formation of a specific hurricane. As discussed above, much research has established the connection between climate change extreme precipitation associated with hurricanes.

However, we also have robust trend attribution research that shows the key role of climate change in rising sea surface temperatures, which can allow storms to rapidly intensify. Similarly, sea level rise attributed to climate change can exacerbate flooding from hurricanes. When talking about hurricanes in the absence of an EEA study, highlighting these key pieces of information is key in contextualizing how climate change may be contributing to these events. This distinction matters because scientific integrity requires us to be clear about what we know and what we don’t. We can state with confidence that climate change is warming oceans and raising sea levels (both of which worsen hurricane impacts) while acknowledging that other aspects remain less certain. Being precise about this strengthens, rather than weakens, the science.

Wildfires represent another example of this. As individual events, they are incredibly difficult to attribute to climate change due to the range of factors that play a role like historical banning of cultural burning practices by Indigenous communities, forest management, and ignition source. But we have amazing trend attribution science that can allow us to say a lot about the role of climate change in these events. A 2016 study, for example, showed that climate change via increased dryness nearly doubled burned area in forests of western North America between 1986 and 2015. This study looked at many wildfires in aggregate to understand the role of climate change.

Following the devastating January 2025 wildfires in Los Angeles, one rapid attribution study found that climate change made the observed extreme fire weather—that drove the rapid spread of wildfires in the region—35% more likely. Together, this research shows that while event attribution studies allow us to quantify the specific contribution of climate change to a given event, we have a wide range of other science we can rely on to show how climate change is impacting our communities and ecosystems.

Moving forward: Five things to keep in mind when talking about attribution science

As attribution science continues to grow and find new applications—from IPCC assessments to courtroom evidence to help with city planning—how we talk about it matters. Here are key considerations for communicating about EEA and attribution science more broadly:

1. Be precise about the questions EEA can answer. Extreme event attribution tells us how climate change influenced an event’s likelihood or intensity, not whether climate change was the sole driver of an event. This distinction matters when framing EEA as answering “did climate change make this more likely or severe?” rather than “did climate change cause this?” and avoids overclaiming while still conveying meaningful information about climate change’s role.

2. Acknowledge varying confidence levels without undermining the science Confidence in attribution findings varies by event type. Heatwaves, which tie closely to temperature increases, can be attributed with high confidence. More complex events like extreme precipitation or hurricanes involve additional factors that complicate isolation of climate change’s contribution. Attribution science still has a lot to say about most event types, but communicating these differences transparently strengthens credibility while still affirming the robust methodology underlying the research. These methodological constraints represent opportunities for the research to further develop.

3. Absence of an attribution study doesn’t mean absence of a climate connection. Not every event will have a dedicated attribution study, and that’s okay. Trend attribution research can inform our understanding even when event-specific studies don’t exist. For hurricane formation and intensification, for example, we can point to robust science on rising sea surface temperatures and sea level rise to contextualize climate change’s role without needing a specific EEA study for each storm.

4. Extreme event attribution exists within the broader attribution science research field. Extreme event attribution is one of four interrelated subfields,alongside trend, source, and impact attribution. Communicating EEA as part of this broader toolkit helps highlight that multiple lines of evidence can inform conclusions about climate change’s contributions, even when one type of study isn’t available.

5. Attribution science is robust and continues to evolve. From the first 2004 European heatwave study to 2025 Carbon Majors research attributing economic costs and heatwave occurrence to specific emitters, EEA has rapidly expanded the questions it can answer. Pointing to these advances signals that attribution science is dynamic and continues to develop new tools for understanding climate impacts.

Attribution science has come a long way in two decades and continues to develop. By communicating its findings and its boundaries clearly and constructively, we can help ensure this research continues to inform the decisions, policies, and accountability efforts that shape our climate future.

Scientists are increasingly able to determine how human-caused emissions have increased the risks of particular events and the harms they produce—advances that are critical as communities experience ever more costly and dangerous extreme weather. This work is known as attribution science: a robust and growing field that examines the role fossil-fueled climate change plays in specific weather events, long-term climate trends, and their real-world consequences.

As my colleague Dr. Delta Merner explains, attribution science includes several connected areas of research. The first, “event attribution,” asks whether climate change made a particular weather event more likely or more intense. The second, “source attribution,” traces climate change and associated hazards back to emissions sources or sectors. And third, “impact attribution” examines the resulting harms, including damage to homes and infrastructure, lost livelihoods, health impacts, and deaths.

Attribution science utilizes a suite of tools to understand these connections: earth observations, statistical methods, emissions data, and climate models. Climate models are a central tool of attribution science through their ability to develop modeled counterfactuals—that is, simulations of what our world might have been without human-induced warming.

Climate models and attribution science have both advanced rapidly over recent decades, making both critical tools for understanding how climate change is progressing and fossil fuel companies’ responsibility for its worsening effects.

So, how exactly are climate models used in attribution science, and why can we have confidence in the conclusions they help produce?

What is a climate model, and why does it matter for attribution?

Climate models are among the main tools scientists use to simulate how Earth will respond to increasing concentrations of heat-trapping pollutants in the atmosphere. When scientists refer to climate models, they generally talk about a general circulation model, or GCM. These models simulate how the atmosphere, oceans, land, and cryosphere respond to changes in internal climate dynamics, such as the El Niño-Southern Oscillation (ENSO) and Atlantic Multidecadal Oscillation, and external drivers, including greenhouse gas emissions.

Climate models are some of the most reliable tools for understanding our earth-climate system because they have been improved, tested, and updated for decades. 

Modern climate models are made up of connected component models for the atmosphere, ocean, land surface, and cryosphere. An atmospheric model, for example, simulates circulation, radiation, clouds, and aerosols. Ocean models simulate circulation and heat uptake. Land models represent processes such as soil moisture, vegetation, snow cover, evapotranspiration, and carbon storage.

When these components are connected, or coupled, they exchange information with one another, allowing models to represent the feedbacks and interactions that shape the real-world climate system. These coupled models are often compared through coordinated international efforts such as the Coupled Model Intercomparison Project, or CMIP, which allows scientists to evaluate results across many models, institutions, and experimental designs.

CMIP simulations are also a major source of evidence for national and international climate assessments, including reports from the Intergovernmental Panel on Climate Change (IPCC), where they help scientists assess past climate change, project future risks, and evaluate confidence across different concentration scenarios and model results.

At their core, climate models use well-established physical laws to calculate how energy, momentum, water, and other properties move through the climate system. They divide the planet into a three-dimensional grid and calculate how conditions such as temperature, moisture, winds, and rainfall change over time and from place to place.

Attribution science: Comparing what is with what could’ve been

For attribution science, knowing how each of these factors contributes to our climate matters enormously. Event attribution compares the climate in which an event occurred (usually today’s climate) with a counterfactual climate that is identical except for the added influence of human-caused warming. By running climate model simulations with—and without—observed human influences, researchers can quantify how greenhouse gas emissions changed the probability or intensity of an event.

For example, a heatwave may have occurred because of a particular weather pattern, but human-caused warming can raise the baseline temperature on which that weather pattern acts, making an extreme heat event more likely, hotter, longer lasting, or all three. The 2021 Pacific Northwest heatwave illustrates this clearly: the region has already warmed by 1°-1.5°C, and event-specific attribution studies found that the heatwave would have been virtually impossible without human-caused climate change and was about 1°C hotter because of it. The relevant question is therefore how much climate change shifted the odds, intensity, or consequences of any given event.  

Climate models have a strong track record for simulating global warming

Climate models are some of the most reliable tools for understanding our earth-climate system because they have been improved, tested, and updated for decades. Their development spans generations of scientists and computational advances, and they continue to improve.

In fact, a recent study found that climate models that were developed over 50 years ago have correctly predicted the Earth’s warming. The fact that models developed decades ago broadly projected the warming trajectory we are now living through is strong evidence that they capture the core physics of global warming.

Furthermore, climate models have evolved in both scale and resolution, improving our ability to understand regional and localized changes to our earth-system. While global climate models are essential for understanding large-scale warming and circulation patterns, regional models can provide more detailed information about how those changes interact with local geography, land surfaces, coastlines, mountains, cities, and weather systems. This is especially useful when studying events such as convective storms, storm surge, flooding, and wildfires, where local and regional processes can strongly influence the severity of an event.

The advances by climate models and their proven record for simulating our earth system are important in the attribution of science. Climate models allow scientists to translate that physical understanding into quantitative estimates of how human-caused warming has changed the likelihood, intensity, or impacts of specific weather extremes.

Climate models address scientific uncertainty

Attribution scientists use multiple robust methods to test, constrain, and quantify uncertainty. One of the most important methods is the use of climate-model ensembles, which help scientists distinguish the role of natural variability from the influence of human-caused warming when assessing extreme weather events and their impacts.

First, scientists use initial-condition ensembles to understand internal climate variability. In these experiments, researchers run the same climate model many times with nearly identical conditions, changing only very small differences in the initial state of the atmosphere or ocean. Because the climate system is complex and chaotic, these tiny differences can lead to different weather patterns and different sequences of natural variability over time.

This allows attribution scientists to simulate the range of outcomes that could occur under the same external conditions. When researchers compare a world with human-caused emissions to a counterfactual world without them across many simulations for each scenario, they can see whether the climate-change signal consistently shifts the likelihood or severity of an event beyond the range expected from natural variability alone.

Second, scientists use multi-model ensembles to evaluate structural uncertainty, which originates in the scientific choices made by developers of each model. Different modeling centers make different scientific and technical choices about numerical schemes, parameterizations, spatial resolution, and how to represent processes such as clouds, aerosols, land-atmosphere interactions, and ocean circulation because the climate system is complex and no single model can perfectly capture every process at every scale. Comparing results across models helps scientists determine whether a finding is robust across multiple plausible representations of the climate system.

That said, some models can be similar in their representation of certain interactions in the climate system, mainly due to the fact that a few were developed using the same computer code and parameterizations. Regardless of the choice, researchers use methods that account for both model performance and model interdependence, giving less weight to structurally similar models or models that perform less well against observations.

The purpose of ensembles is to understand and constrain uncertainty in a transparent way. And what is clear is that, with both types of ensembles, there is greater confidence in the climate-change signals on a variety of weather extremes and impacts.

Bottom line: Climate models are important tools for attribution science

Climate models are essential tools for attribution science because they are grounded in well-established physics, tested against observations, and used alongside multiple lines of evidence. Attribution science brings together physical understanding, observations, statistical analysis, emissions data, and climate-model experiments to test how human-caused warming is changing the risks people face today. The use of multiple datasets, models and methods is what makes the field robust, allowing scientists to compare the world as it exists now to a counterfactual world without human-caused warming, quantify uncertainty, and assess how much climate change has shifted the likelihood, intensity, or impacts of specific events.

After a winter with little snowpack, high winds and temperatures have led to conflagrations in Utah and Colorado that have burned hundreds of thousands of acres. Governor Spencer Cox of Utah describes the current burning as the “most destructive fire in the state’s history;” Colorado governor Jared Polis has declared the wildfires a disaster, mobilizing the National Guard.

Beginning in the mid-1980s, the Western US has been stunned almost annually by destructive and often deadly wildland fires. It has become increasingly clear that we are in a new era of destructive megafires, due a combination of climate change, vegetation changes from widespread fire suppression, and development at the wildland-urban interface. In this post, I’ll touch briefly on the history of wildland fire and human response in the West, on some climate metrics that are related to the trends in wildland megafires, and identify possible mitigation and adaptation measures to respond to the fire-climate crises.

The first era of megafires

As the timber industry pushed west and north in the late 19th and early 20th centuries, large and destructive forest fires followed, since logging and land clearing for agriculture left large accumulation of debris. Some of the notorious and destructive fires included:

• The 2,400 square-mile Peshtigo fire in Wisconsin, October 1871, which killed over 2,000 people;
• The 3-million acre Big Blowup in Washington, Idaho and Montana, 1910, which killed 85 people. The story of that fire is told in Timothy Eagan’s book, The Big Burn.  It marked a turning point for staff of the young US Forest Service, who went from pariahs who were trying to control illegal logging and grazing against strong resistance, to local heroes in the fight to stop the fire; and
• The Tillamook Burn, Oregon, was a series of four fires that burned between 1933 and 1958, consuming 350,000 acres of mostly old-growth Douglas-fir.

Fire prevention and suppression techniques put in place

For generations, Indigenous peoples used fire management techniques such as controlled burns, harnessing the power of fire to shape the landscape for their survival. European colonizers banned and criminalized many of these practices when they arrived in the Americas.

During the 1930s and after World War II, under the New Deal, the US Forest Service and Bureau of Land Management, relying on Civilian Conservation Corps workers, built a network of fire lookouts in the West. Fire stations were built and staffed at the district level. An aggressive educational campaign was launched, using slogans like Smokey the Bear’s famous “Only you can prevent forest fires.” Smokejumpers were trained to parachute into otherwise inaccessible terrain to fight forest fires that mostly originated from lightning strikes.

The anti-fire campaign was successful for a time, but was marred by an incident in 1949, when 13 smokejumpers died fighting the Mann Gulch fire in west Montana. That tragic accident, memorialized in Norman Maclean’s book Young Men and Fire,  provided the impetus for the US Forest Service to establish a program of research on fire behavior, with Fire Science Laboratories now at Missoula, MT, Riverside, CA, and Seattle, WA, as well as projects at research stations throughout the US. Research was directed, for example, on understanding how local topography and microclimates could cause sudden and dangerous shifts in fire behavior.

Unfortunately, this March, the US Forest Service announced that it will close the majority of its research stations in 31 states, and consolidate its research division in a centralized office in Fort Collins, Colorado. When the Bureau of Land Management imposed a similar relocation plan during the first Trump administration, more than 87 percent of the Bureau of Land Management employees in the main Washington, DC, office resigned.

This relocation and downsizing of the Forest Service research program will have a devastating effect on ongoing and well-established research programs that are addressing the impacts of climate change on wildfires and forest health. It is hard to see this move by the Trump administration as anything but an ideological attack on science; it will likely take years for the research program to recover.

A pyrocumulonimbus cloud from the Creek Fire in the Sierra National Forest as seen on September 5, 2020. Passenger Thalia Dockery took this photo on a Southwest Airlines flight, from San Jose to Las Vegas. Photo credit: Thalia Dockery The Angora Fire at Lake Tahoe, 2007. Photo credit: Steve DeVries Megafires in the era of climate change

Records since the mid-1980s show marked increases in both the number of large wildland fires (“large” defined as >400 hectares) and total area that they burned. The increases are sharpest in the northern Rocky Mountains, and are attributable to the earlier onset of spring and increasing summer moisture deficit (or vapor pressure deficit). Historic moisture deficit data are based on climate records, and future projections of vapor pressure deficit are derived from general circulation models. The evidence is very strong that increasing summer temperatures and atmospheric water deficit are the primary cause of the upward trend in megafires.

In addition to moisture (or vapor pressure deficit), climatic variables that have been related to changes in longer fire seasons and greater overall burned areas include:

• The percent of annual water-year precipitation falling as snow
• The maximum annual snowpack, in inches of stored water
• The snowpack water storage on April 1, the date of an important snow survey
• The onset date of spring snowmelt
• The center timing of snowmelt—that is, the date by which half the annual water-year snowmelt has passed a stream gage
• The Palmer Drought Severity Index
• The Forest Drought Severity Index

Mitigation and adaptation

For people who live in a wildlife-urban interface area—that is, is an area where homes and businesses are located that are adjacent to undeveloped land, forests and grasslands—adaptation to extreme forest fire might mean keeping a “go bag” close at hand in the short term. For decision-makers thinking about the longer term, modifying design standards will help make buildings more fire resistant.  

Mitigation might mean reducing forest fuel loads with prescribed burning, or cutting and removing vegetation. This approach often focuses on “ladder fuels,” small trees and shrubs that can conduct flame from the ground into the higher tree canopy. Fuel load reduction—or eliminating the vegetation most likely to burn—can help firefighters to protect certain assets, but it can be expensive. Average costs for prescribed burning in California range from to $140 to $170 per acre, and for cutting and removing vegetation, from $6,500 to $8,500 per acre.

To date, more than 100,000 acres in California’s Lake Tahoe region have been treated for fuel load reduction. Of course, these treatments will have to be repeated as vegetation re-grows.

Unfortunately, climate change is closing the window on opportunities for safely using prescribed fire—controlled burns—as a vegetation management strategy. This point was driven home in 2022 when a prescribed fire in New Mexico escaped control to become the 345,000-acre Hermit’s Peak Fire.

Before (l) and after (r) fuel load reduction at the Tunnel Creek project in the Tahoe Basin. Photos from the Nevada Division of State Lands. Photo credit: Anna Higgins A prescribed fire in the Lake Tahoe Basin. Photo credit: Rich Adams

Recent and accurate information on forest conditions is essential for planning and implementing fuel load reduction and prescribed burning. From the 1970s until last year, the US Forest Service’s Aerial Detection Survey mapped areas of forest mortality in California associated with insects, disease, drought and wildfire using low-elevation flights with trained observers. Last year, the Trump administration ended funding for the survey, and the US Forest Service was forced to lay off key staff and terminate the program. 

Widening cooperation to address the megafire crisis

Ecologists have long known that many Indigenous Tribes/nations have been using fire for millennia, managing vegetation to enhance forage for deer, keeping forests relatively open to facilitate hunting, and to promote the growth of plants useful for food, dye, medicine, ceremonies and weaving. Finally, staff at public agencies have begun to realize the value of this Indigenous knowledge and to seek opportunities for collaboration.

Although the forest management vocabularies of Tribes and agency staff are quite different, and distrust on the Tribal side is deep (with good reason), both sides are discovering the benefits of working together. The experience of the Yurok and Karuk tribes in working with the US Forest Service using prescribed fire as a vegetation management tool is a good example.

Of course, the best ways to address wildfires are to stop burning fossil fuels, hold fossil fuel companies accountable for the damages their products have caused, restore funding and create new investments into wildfire research and prevention, and allow the US to proceed on a trajectory toward clean, renewable energy and sustainable land management. With the Trump administration working against these goals, we’re in for a long summer of dangerous wildfires. You can help by asking your member of Congress to prevent the restructuring of the US Forest Service, to keep intact this agency’s crucial insights on wildfire prevention. And follow the advice of your local agencies and officials if you live in a wildfire-prone area.