A warm, dry spring has set the stage for above-average significant wildland fire risk across much of the southern and western United States this summer, and no part of the United States will have below-average fire potential through the end of August.
“It’s not necessarily a foregone conclusion that we’re going to have a really busy season, but everything is pointing that way.”
These predictions are part of a 4-month outlook produced monthly by the National Interagency Fire Center (NIFC), a group of wildland fire experts from eight federal agencies that coordinates wildland fire resources across the country.
The most recent outlook, published 1 May, projects the likelihood of significant fires (defined as those that require an NIFC response) from May to August using long-term forecasts from NOAA’s Climate Prediction Center, current precipitation and drought conditions, and an assessment of the fuels available in different regions (like grasses, brush, and timber).
This year, 1,848,210 acres across the country have already burned—nearly twice the annual average over the past 10 years.
“It’s not necessarily a foregone conclusion that we’re going to have a really busy season, but everything is pointing that way,” said Jim Wallmann, a meteorologist for the U.S. Forest Service at the NIFC and one of the outlook’s authors.
Significant wildland fire potential will be elevated across much of the West and Southeast this summer. Click image for larger version. Credit: National Interagency Coordination Center, Public Domain
Drought in the West
In the West, wildfire season typically peaks in late summer. This most recent outlook predicts an above-average significant fire potential for much of the West as the season peaks.
In May, the above-average risk is concentrated in eastern Arizona and western New Mexico, though that risk fades to normal by August as the Southwest’s monsoon season begins. In June, the above-average risk extends to western Colorado and parts of the Pacific Northwest. In July and August, that risk covers much of the Northwest, including Utah, Idaho, Oregon, Washington, and Northern California.
Above-average spring temperatures and a far-below-normal snowpack across the West are contributing to the elevated risk in Washington, Oregon, Idaho, and Northern California, in particular. Many river basins across the West contain less than 20% of their normal amount of snow, and some are already snow-free at all observed locations due to melting caused by warm temperatures in March.
As of May, many river basins in the West have a snow water equivalent—the amount of water held in their current snowpack—that is less than 50% (in red) of the 1991–2020 average level. Credit: USDA Natural Resources Conservation Service, Public Domain
“The snowpack being lower this time of year, and melting out, affects the soil moisture throughout the rest of the summer, which then affects the fuel moistures,” said Craig Clements, a meteorologist at San Jose State University’s Fire Weather Research Laboratory who was not involved in the outlook. Early snowmelt also uncovers fuels, like pine needles and leaf litter, that would typically be under snow, exposing them to the air to dry and catch fire.
Southern California and the Sierra Nevada mountain range, though, remain at an average significant fire risk throughout the summer, as a result of higher-than-average precipitation earlier in the year.
The Southeast and Beyond
Fire risk will also be elevated in the Southeast this summer. Florida, for example, remains at an above-average significant fire potential through the end of August. Southern Georgia, Mississippi, Louisiana, Arkansas, and the eastern halves of Virginia, North Carolina, and South Carolina will also have above-average significant fire potential.
The above-average risk is fueled, in part, by a worsening drought affecting the Southeast alongside the drought in the West. As of 1 May, nearly 63% of the country was experiencing drought, and 19% of the country was experiencing extreme or exceptional drought, according to the U.S. Drought Monitor.
The Midwest and the Northeast will remain at an average significant fire potential from May to August, though northwestern Minnesota faces an above-average potential in May.
No place in the United States is projected to have a below-average significant fire potential through the end of August.
Preparing Amid Uncertainty
A developing El Niño—a climate phenomenon that affects heat storage in the ocean—could alter the fire risk projections. Scientists expect that a strong El Niño could lead to a below-normal hurricane season, worsening drought in the Southeast. In the Pacific, a strong El Niño could intensify the hurricane season, which may lower wildfire risk.
However, a stronger El Niño could drive more lightning strikes in the Sierra Nevada, which could increase fire risk there, Clements said. In 2020, for example—a strong El Niño year—Hurricane Elida in the Pacific contributed to a lightning outbreak that supercharged wildfires in the West.
“We’re still not sure exactly how [El Niño] is going to impact the season.”
“We’re still not sure exactly how [El Niño] is going to impact the season,” Wallmann said. As late summer approaches, meteorologists will better understand how El Niño will develop and affect wildfire risk.
Weather patterns can change, and day-to-day conditions still play a role in fire occurrence. “If the weather shifts, or we get a really big heat wave, it can modify [the forecast]. Or if it remains relatively moderate, that might lessen the fire danger,” Clements said. “We’ll just have to see how the weather plays out.”
Wallmann and Clements emphasized that those living in areas with elevated fire risk should be aware of their surroundings and think ahead about where they might go for safety should a wildfire occur. “Having that situational awareness ahead of time can help you make better decisions,” Wallmann said.
Citation: van Deelen, G. (2026), Most of the U.S. West will face above-normal wildfire risk this summer, Eos, 107, https://doi.org/10.1029/2026EO260145. Published on 11 May 2026.
Thirty years ago, the blockbuster movie Twister featured a group of academics putting themselves at risk by chasing tornadoes in the name of science. Although the Hollywood story entailed a surfeit of sensationalism, special effects, and unrealistic stereotypes, the movie got a few things right. Specifically, the scientists were trying to study tornadoes using a large number of spatially distributed, home-built, low-cost (and potentially sacrificial) sensors.
Today, we commonly refer to the coordinated use of tens to hundreds of similar sensors that are spread out as “large-N” sensing. Such sensor distributions have led to important advances in seismology and infrasound science, where they have improved our understanding of seismic ground motion and helped shed light on volcanic eruption dynamics [e.g., Rosenblatt et al., 2022; Anderson et al., 2023].
The benefits of large-N networks and arrays include robust spatial sampling and signal extraction from noise. They are also advantageous for detecting small signals, sensing natural hazards in remote environments, and offering critical redundancies for sensors at risk from lava or debris flows, wildfire, weather, or even malicious mammals.
Since 2013, our research group in the Department of Geosciences at Boise State University (BSU) has worked to study infrasound from geophysical phenomena by capitalizing on the benefits of low-cost, large-N sensing technology [e.g., Slad and Merchant, 2021]. More than a decade on, this effort has yielded scientific successes from a variety of environments, and it is continuing to evolve.
Large-N Sensing for Infrasound
Many violent natural processes, including landslides, volcanic eruptions, earthquakes, avalanches, and meteors, produce infrasound.
Many violent natural processes, including landslides, volcanic eruptions, earthquakes, avalanches, and meteors, produce infrasound, defined as low-frequency sound below the threshold of human hearing (less than 20 Hertz). Such events may create audible sound as well, but the subaudible band is often much more energetic in terms of sound intensity, and it has long wavelengths that can propagate long distances with little attenuation. These characteristics make infrasound especially valuable for remote sensing of natural phenomena.
Our group at BSU grew more interested in developing our own inexpensive infrasound sensing solutions after costing out technology for commercial data logging systems, the compact electronic devices that record and store sensor data. These systems can be far more expensive than infrasound transducers—the sensors that actually detect sound—themselves.
The cost element became particularly relevant after we lost instrumentation deployed at the summit of Chile’s Villarrica volcano when it erupted a 2-kilometer-tall lava fountain on 3 March 2015 [Johnson et al., 2018]. In an instant, our hardware, including seismic and infrasonic sensors and their commercial multichannel data loggers, was entombed beneath falling lava. This financial loss incentivized our work to develop low-cost loggers that would match the technical specifications and fidelity of commercial systems.
The result was the customized Gem infrasound logger, which we created using the widely available and very economical Arduino open-source electronic prototyping platform and its low–power consumption microcontroller. The Gem is an all-in-one infrasound sensor and data logger with a high dynamic range (millipascals to 100 pascals), a 100-hertz sample rate appropriate for infrasound, and a built-in GPS for precise timing and synchronization [Anderson et al., 2018].
Although we initially conceived of the Gem as an alternative to commercial loggers to be deployed as single stations or in small arrays, we quickly realized its potential for use in high-density distributed sensing arrays that enabled new detection capabilities. In particular, its small package size (it has about the dimensions and weight of a paperback novel) and its ease of deployment—simply insert alkaline batteries, place it on the ground, and turn it on—have opened opportunities for rapid, large-N deployments in difficult-to-access environments.
Early Successes for the Gem
Volcán Villarrica, near Pucon, Chile, is seen in 2025 (left). The volcano regularly releases gas from a small lava lake recessed deep within the summit crater (right). Credit: Jeffrey B. Johnson
The Gem’s inaugural field mission came in January 2020 during a return to Villarrica, where activity had returned to normal following its 2015 paroxysmal eruption [Rosenblatt et al., 2022]. Typical activity in the volcano’s normal state includes open-vent degassing from a small lava lake recessed deep within the summit crater, which produces its famously powerful volcano infrasound [e.g., Johnson et al., 2012].
To capture Villarrica’s infrasound in detail, a four-person team from BSU climbed the 3,000-meter-tall glaciated volcano and quickly installed 16 sensors around the crater rim, as well as another 16 sensors along an 8-kilometer linear transect from the summit down the northern slope (Figure 1). This unique sensor distribution permitted us to capture the infrasound wavefield and how it interacts with topography in unprecedented detail.
Fig. 1. (a) Oblique and (b) plan views of Villarica’s summit region were created from structure-from-motion surveys in 2020. Red triangles and circles indicate locations of Gem sensing packages. (c) Also in 2020, Jake Anderson adjusts a cable suspended across the volcano’s crater that held a Gem sensor (circled). (d) In 2025, Jerry Mock unloads Gem systems at Villarica’s summit during another data collection campaign there. Click image for larger version. Credit: Jeffrey B. Johnson
Deploying such an array configuration using much heavier, larger, and power-intensive conventional instruments would have taken far more time and resources, as well as a bigger group. With the Gems, however, the installation was feasible for our small team, each member of which could easily carry eight instruments and the batteries needed to power them.
To monitor volcanoes with infrasound, it is necessary to understand the influence of atmospheric effects.
Once in place, these sensors collected continuous data during the 2-week study that were used to quantify the diffraction of sound coming out of the volcanic crater [Rosenblatt et al., 2022] and to measure the sound’s attenuation as it propagated away. Such studies are important for investigating time-varying atmospheric parameters such as changing temperatures and winds, which can affect infrasound transmission, diminishing its amplitude or even—in extreme cases—completely silencing it in an acoustic shadow zone [Johnson et al., 2012]. To monitor volcanoes with infrasound, it is necessary to understand the influence of atmospheric effects.
Months later, another opportunity arose to demonstrate the Gems’ capability for large-N infrasound sensing. During the early days of the COVID-19 pandemic, on 31 March 2020, a magnitude 6.5 earthquake occurred near Stanley, Idaho. The earthquake, the largest in the state since 1983, kicked off an energetic aftershock sequence, with more than 700 magnitude 3 or greater earthquakes occurring in 6 months. Most of these events produced significant local infrasound radiation, or “airquakes,” caused by ground-atmosphere coupling [e.g., Johnson et al., 2020].
Pandemic-related precautions inhibited a large team from venturing as a group into the field. However, a lone BSU researcher (coauthor Jacob Anderson), trudging through forest terrain and deep snow on skis, was able to deploy and activate 22 Gems in less than 4 hours in early April, thanks in part to the sensors’ compact size and ease of deployment.
This array captured hundreds of local infrasonic aftershocks within about 25 kilometers of their epicenters. It also recorded a far larger event 700 kilometers away, the 15 May magnitude 6.5 Monte Cristo earthquake in Nevada. The array detected the epicentral infrasound from the distant earthquake source, as well as infrasound from numerous secondary sources, including mountain ranges throughout the western United States that reradiated the ground motion as infrasound (Figure 2) [Anderson et al., 2023].
Fig. 2. This map shows source region(s) of infrasound associated with the May 2020 Monte Cristo earthquake in Nevada that was detected by an array of Gem infrasound sensors deployed at the PARK site near Stanley, Idaho. Click image for larger version. Credit: Adapted from Anderson et al. [2023], CC BY 4.0
Detecting all these distinct signals was possible because of the enhanced array processing capabilities provided by the large number of sensors. Anderson et al. [2023] showed that when the data were processed from 3-sensor subsets of the 20+-sensor array—instead of from the whole array—it was possible to detect only the most intense earthquake infrasound arrivals. In other words, the larger array had much greater fidelity and sensing capabilities than smaller distributions of sensors.
During its 2-month deployment, the Stanley array also detected sounds from other distant nonearthquake sources, including waterfalls 195 kilometers away and thunder more than 900 kilometers away [Scamfer and Anderson, 2023]. Such enhanced detections, facilitated by large-N sensing, demonstrate an improved capacity to monitor a range of Earth phenomena continuously over a wide range of distances.
Putting Sensors in Harm’s Way
Since those proof-of-concept deployments, Gems have been used to monitor snow avalanches, lahars, river flow discharge, stratospheric sounds (while mounted aboard a solar balloon), and numerous volcanoes during field experiments [e.g., Tatum et al., 2023; Bosa et al., 2024; Rosenblatt et al., 2022; Brissaud et al., 2021]. Given their ease of use, small size, and low replacement cost, they’ve also been tested in hazardous environments where the risk to more expensive hardware could be considered unreasonable.
The motivation to put sensors in harm’s way is to gain insight into geophysical phenomena by recording subtle signals close to the source that may not be detectable from farther away.
The motivation to put sensors in harm’s way is to gain insight into geophysical phenomena by recording subtle signals close to the source that may not be detectable from farther away. For example, at Villarrica, Rosenblatt et al. [2022] suspended a Gem on a cable 100 meters above a lava lake to collect infrasound data from a unique, bird’s-eye perspective over the crater (Figure 1c). (Stringing the cable across the crater proved far more challenging than deploying the sensor itself, which slid down the cable until finding its resting place at the bottom of the cable’s arc.)
In another case, we landed a pair of Gems on the ground near a frequently exploding crater at Fuego volcano in Guatemala using a drone (see video below). We later retrieved one of the sensors from high on the volcano’s flanks. Another was lost because high winds initially posed too great a risk to fly the drone back for it. Then the following day after the wind subsided, we could not locate the stranded Gem, which was probably a casualty of a nighttime explosion.
Drone footage and infrasound recordings were collected during an explosion of Fuego volcano on 4 February 2024. Pa = pascals. Credit: video: Jerry C. Mock; animation and infrasound: Jeffrey B. Johnson
Our group at BSU also has nascent interest in using Gems to study fire in natural environments. Wildfires produce infrasound from a spatially extensive source region corresponding to actively burning areas. Because of the source complexity and the fact that fire infrasound is low amplitude and tremor-like [Johnson et al., 2025], enhancing signal-to-noise ratios in recorded infrasound is critical. This enhancement is enabled by using large-N monitoring networks, making infrasound wildfire surveillance a promising area of investigation.
Low-cost, rapid infrasound deployments could one day be used as an effective operational tool.
Toward this objective, our group installed 76 sensors ahead of a prescribed burn in Reynolds Creek, Idaho, in October 2023 to begin developing infrasound as a tool for monitoring and mapping wildfire. We have also deployed Gems for infrasound studies of naturally occurring wildfires, such as the Emigrant wildfire in Oregon in August and September 2025 (Figure 3). During that active wildfire response, a team safely and quickly installed tens of sensors within a matter of hours in an area facing dynamic hazards from the rapidly expanding fire, which eventually covered 33,000 acres (about 13,354 hectares). Luckily, no instruments were lost, and the data have shown the potential to track a wildfire as it advances.
Preliminary results suggest that low-cost, rapid infrasound deployments could one day be used as an effective operational tool. For example, in firefighting responses, infrasound might complement intermittent aerial observations, from aircraft or drones, because it provides a continuous record of fire activity. Infrasound surveillance might also be able to “hear” combustion sources within a burn area that is obscured to optical sensing because of clouds or nightfall.
Fig. 3. (a) The spread and severity of the 2025 Emigrant Fire in Oregon, as calculated from prefire (21 August) and postfire (18 October) Sentinel-2 satellite images, are shown. Inset maps show the distribution of 37 Gem sensors rapidly deployed in three arrays. (b) Smoke from the fire rises from the landscape on 31 August during deployment of the sensors. (c) Following the fire, one sensor that had been melted by the fire was recovered with its data card still intact (red circle). dNBR = differenced normalized burn ratio. Click image for larger version. Credit: (a) and (b): Madeline A. Hunt; (c): Jacob F. Anderson
The Evolution of Low-Cost Sensors
Five years ago, the single-sensor Gem was a cutting-edge infrasound logging solution. While it remains a powerful and economical tool for large-N arrays and for sensing in hostile environments, it is evolving.
Boise State University researchers (left to right) Madeline Hunt, Owen Walsh, Jerry Mock, and Jacob Anderson prepare to deploy Gem sensors in Idaho’s Sawtooth Mountains in January 2024. Credit: Jeffrey B. Johnson
We have now developed the Gem into an even more versatile version called the Aspen, which can log four independent sensors at a sample rate of 200 hertz, double that of the Gem. The Aspen retains the small size, low weight, low power consumption, and low cost of the Gem, but with the capability to record higher-resolution 24-bit, time-synchronized data from a triaxial seismic sensor and an infrasound transducer.
Recording synchronous seismoinfrasonic data on the same logging platform offers the advantage of sensing both ground shaking and infrasonic oscillations. The ability to measure waves propagating in the ground and in the air simultaneously could facilitate work in the growing field of environmental seismology, which focuses on geophysical sources at Earth’s surface like debris flows and volcanoes.
Although we have focused on seismoacoustic geophysical measurements in our work, the concept of gathering data with low-cost instrumentation in harm’s way or from coordinated arrays of numerous sensors holds promise across Earth and environmental sciences. Such approaches could be used, for example, with tiltmeters (which measure slope changes), gravity meters, or near-infrared thermometers (e.g., optical pyrometers), all of which would offer additional data streams complementing seismoacoustic observations in geophysical studies of volcanoes.
With the diversity of emerging uses, it’s clear that large-N sensing—infeasible or cost prohibitive in many cases until recently—could transform how we measure many facets of Earth, helping to reveal the inner workings of volatile volcanoes, twisting tornadoes, and more.
Acknowledgments
More information about low-cost infrasound sensing solutions can be found at https://sites.google.com/boisestate.edu/infravolc/home. Development of the Gem infrasound logging platform was supported by a grant from the National Science Foundation (EAR-2122188).
References
Anderson, J. F., et al. (2018), The Gem infrasound logger and custom‐built instrumentation, Seismol. Res. Lett., 89(1), 153–164, https://doi.org/10.1785/0220170067.
Anderson, J. F., et al. (2023), Remotely imaging seismic ground shaking via large-N infrasound beamforming, Commun. Earth Environ., 4(1), 399, https://doi.org/10.1038/s43247-023-01058-z.
Bosa, A. R., et al. (2024), Dynamics of rain-triggered lahars and destructive power inferred from seismo-acoustic arrays and time-lapse camera correlation at Volcán de Fuego, Guatemala, Nat. Hazards, 121, 3,431–3,472, https://doi.org/10.1007/s11069-024-06926-1.
Brissaud, Q., et al. (2021), The first detection of an earthquake from a balloon using its acoustic signature, Geophys. Res. Lett., 48, e2021GL093013, https://doi.org/10.1029/2021GL093013.
Johnson, J. B., et al. (2012), Probing local wind and temperature structure using infrasound from Volcan Villarrica (Chile), J. Geophys. Res., 117, D17107, https://doi.org/10.1029/2012JD017694.
Johnson, J. B., et al. (2018), Forecasting the eruption of an open-vent volcano using resonant infrasound tones, Geophys. Res. Lett., 45, 2,213–2,220, https://doi.org/10.1002/2017GL076506.
Johnson, J. B., et al. (2020), Mapping the sources of proximal earthquake infrasound, Geophys. Res. Lett., 47, e2020GL091421 , https://doi.org/10.1029/2020GL091421.
Rosenblatt, B. B., et al. (2022), Controls on the frequency content of near-source infrasound at open-vent volcanoes: A case study from Volcán Villarrica, Chile, Bull. Volcanol., 84(12), 103, https://doi.org/10.1007/s00445-022-01607-y.
Scamfer, L. T., and J. F. Anderson (2023), Exploring background noise with a large‐N infrasound array: Waterfalls, thunderstorms, and earthquakes, Geophys. Res. Lett., 50, e2023GL104635, https://doi.org/10.1029/2023GL104635.
Slad, G., and B. Merchant (2021), Evaluation of Low Cost Infrasound Sensor Packages, Sandia Rep. SAND2021-13632, Sandia Natl. Lab., Albuquerque, N.M., https://doi.org/10.2172/1829264.
Tatum, T., J. F. Anderson, and T. J. Ronan (2023), Whitewater sound dependence on discharge and wave configuration at an adjustable wave feature, Water Resour. Res., 59, e2023WR034554, https://doi.org/10.1029/2023WR034554.
Author Information
Jeffrey B. Johnson (jeffreybjohnson@boisestate.edu), Jacob F. Anderson, Madeline A. Hunt, Owen A. Walsh, and Jerry C. Mock, Department of Geosciences, Boise State University, Idaho
Citation: Johnson, J. B., J. F. Anderson, M. A. Hunt, O. A. Walsh, and J. C. Mock (2026), Sensing the sounds from Earth’s hazardous environments, Eos, 107, https://doi.org/10.1029/2026EO260142. Published on 8 May 2026.
Urbanization, climate change, and fire suppression practices are contributing to increased wildfire risk at the densely populated wildland-urban interface. These factors make fires more unpredictable and harder to manage. In January 2025, this was made devastatingly clear in Los Angeles, when massive wildfires engulfed entire hillsides and canyons, destroying neighborhoods and damaging surrounding ecosystems.
The Mediterranean climate region of California, which stretches up most of the state’s coastline, is a naturally fire-prone landscape because its dry conditions support vegetation growth and also allow for fire to spread easily. As wildfires become more intense, better modeling and understanding of their drivers is crucial in efforts to predict risk.
Ward-Baranyay et al. looked at three of the January 2025 Los Angeles wildfires by analyzing preburn conditions, such as fuel characteristics, topography (including elevation and slope), and wind speed. Satellite observations gathered from the Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and the Earth Surface Mineral Dust Source Investigation (EMIT)—precursors to a recently announced NASA mission, the Explorer for Artemis Geology Lunar and Earth (EAGLE)—provided detailed information about the vegetation’s condition before the fires began. The researchers then built a random forest regression model to predict burn severity based on these conditions, ultimately demonstrating that prefire fuel conditions were a key driver of the destructive wildfires’ immediate effects on wildlands.
The model used in the study was able to accurately capture about 60% of the patterns in burn severity. It was most accurate for the Palisades and Hughes fires, but less accurate for the Eaton Fire. This discrepancy could be because the area burned by the Eaton Fire was more topographically variable, meaning its burn severity drivers may not have been fully captured by the model, the researchers suggest. Vegetation type was also a strong performance indicator: Terrain with shrub or scrub cover, the dominant vegetation type, offered the most accurate predictions for burn severity. The burn patterns of forests and other landscape types were less accurately captured.
Fuel conditions emerged as the dominant driver of burn severity, more so than topography or weather. In particular, how abundant, wet, dry, or stressed vegetation is can hint at how severe future fires may be. Tracking and monitoring these fuel conditions, researchers suggest, may be a way to monitor wildfire hazard in California and other fire-prone regions. (AGU Advances, https://doi.org/10.1029/2025AV002179, 2026)
Citation: Owen, R. (2026), Want to predict wildfire severity? Look to the state of vegetation, Eos, 107, https://doi.org/10.1029/2026EO260130. Published on 4 May 2026.
Wildfires can increase flooding risks in and downstream of burned areas by removing vegetation and disturbing hydrologic processes. As the climate changes, the severity of both wildfires and heavy rainfall events is increasing, meaning flooding is likely to become more severe in the near future. Better understanding how, and by how much, wildfires change flood risk is important for disaster and infrastructure planning for communities around the country.
To make the most of the limited data on flooding in the years following wildfires, the researchers created a paired-storms framework: They identified postfire peak flows (PFPFs), defined as the five highest peak flows within 3 years of a wildfire across seven watersheds. Then, for each precipitation event causing a PFPF, they looked for storms with similar characteristics (or paired storms) that occurred before the wildfire. Storm characteristics used for pairing included the season in which the storm occurred, recent precipitation, and precipitation depth, duration, and peak intensity.
The researchers found significantly elevated peak flows after wildfires in many cases, underlining the risks to communities following wildfires and validating their approach for use elsewhere.
Altogether, the authors found 26 PFPF events, including 20 with paired storms occurring before wildfires. For 75% of the postfire storms, their peak flows were 2 or more times greater than prefire peak flows. PFPFs were most likely to happen in the first year after a wildfire and typically occurred following storms that were centered upstream of the watershed centroid, were uniform in shape, and fully covered the watershed and burned area, the authors reported. They also found some evidence that the first storm in the year immediately following a fire has a higher-than-expected chance of producing a PFPF.
Future work could look more deeply at the characteristics of storms occurring over burned areas, such as storm direction and watershed recovery, and could apply the automated methods to more burned watersheds and storm events to enhance the robustness of the work, the authors say. (Water Resources Research, https://doi.org/10.1029/2025WR040693, 2026)
Source: Journal of Geophysical Research: Atmospheres
The 2018 Camp Fire was the deadliest and most destructive wildfire in California history. The Camp Fire spread extremely rapidly, driven by strong winds and dry fuels, but also by organized long-range spotting, i.e. lofting and downwind fallout of burning embers to ignite new fires.
Using operational Doppler radar and satellite observations, Lareau [2026] provides the first high resolution depiction of spotting behavior during an extreme wildfire. Observations show that spot fire events for the Camp Fire occurred 5-10 kilometers ahead of the fire front, quickly merging into new fire lines. Spot fires are not random but aligned within coherent fallout zones that are shaped by plume dynamics and background winds. These results show that operational weather radar can identify lofting and fallout regions in real time, providing a new way to anticipate spotting-driven fire spread and improve early warnings for fast-moving wildfires.
(a) Along wind cross section of Camp Fire plume reflectivity observed by radar measurements, showing distinct updrafts (white arrows) and ashfall regions (blue dashed arrow). Spot fires within 10 minutes of these radar measurements are shown as filled cyan triangles. (b) Map of column maximum radar reflectivity and fire perimeter. In both panels the black dashed line indicates the eastern edge of the town of Paradise, California. Credit: Lareau [2026], Figure 6ab
Citation: Lareau, N. P. (2026). Plume-coupled long-range spotting drove the explosive spread of the 2018 Camp Fire. Journal of Geophysical Research: Atmospheres, 131, e2025JD045798. https://doi.org/10.1029/2025JD045798
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