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California has experienced enhanced extreme wildfire behaviour in recent years 1 – 3 , leading to substantial loss of life and property 4 , 5 . Some portion of the change in wildfire behaviour is attributable to anthropogenic climate warming, but formally quantifying this contribution is difficult because of numerous confounding factors 6 , 7 and because wildfires are below the grid scale of global climate models. Here we use machine learning to quantify empirical relationships between temperature (as well as the influence of temperature on aridity) and the risk of extreme daily wildfire growth (>10,000 acres) in California and find that the influence of temperature on the risk is primarily mediated through its influence on fuel moisture. We use the uncovered relationships to estimate the changes in extreme daily wildfire growth risk under anthropogenic warming by subjecting historical fires from 2003 to 2020 to differing background climatological temperatures and aridity conditions. We find that the influence of anthropogenic warming on the risk of extreme daily wildfire growth varies appreciably on a fire-by-fire and day-by-day basis, depending on whether or not climate warming pushes conditions over certain thresholds of aridity, such as 1.5 kPa of vapour-pressure deficit and 10% dead fuel moisture. So far, anthropogenic warming has enhanced the aggregate expected frequency of extreme daily wildfire growth by 25% (5–95 range of 14–36%), on average, relative to preindustrial conditions. But for some fires, there was approximately no change, and for other fires, the enhancement has been as much as 461%. When historical fires are subjected to a range of projected end-of-century conditions, the aggregate expected frequency of extreme daily wildfire growth events increases by 59% (5–95 range of 47–71%) under a low SSP1–2.6 emissions scenario compared with an increase of 172% (5–95 range of 156–188%) under a very high SSP5–8.5 emissions scenario, relative to preindustrial conditions. Quantification of climate warming in California using machine learning shows increased daily wildfire growth risk by 25%, with an expected increase of 59% and 172% in 2100, for low- and very-high-emissions scenarios, respectively.

In this paper we present the first direct observational evidence that the condensation level in pyrocumulus and pyrocumulonimbus clouds can be significantly higher than the ambient lifted condensation level. In addition, we show that the environmental thermodynamic profile, day-to-day variations in humidity, and ambient wind shear all exert significant influence over the onset and development of pyroconvective clouds. These findings are established using a scanning Doppler lidar and mobile radiosonde system during two large wildfires in northern California, the Bald Fire and the Rocky Fire. The lidar is used to distinguish liquid water from smoke backscatter during the plume rise, and thus provides a direct detection of plume condensations levels. Plume tops are subsequently determined from both the lidar and nearby radar observations. The radiosonde data, obtained adjacent to the fires, contextualize the lidar and radar observations, and enable estimates of the plume ascent, convective available potential energy, and equilibrium level. A noteworthy finding is that in these cases, the convective condensation level, not the lifted condensation level, provides the best estimate of the pyrocumulus initiation height.

The time-mean and time-varying smoke and velocity structure of a wildfire convective plume is examined using a high-resolution scanning Doppler lidar. The mean plume is shown to exhibit the archetypal form of a bent-over plume in a crosswind, matching the well-established Briggs plume-rise equation. The plume cross section is approximately Gaussian and the plume radius increases linearly with height, consistent with plume-rise theory. The Briggs plume-rise equation is subsequently inverted to estimate the mean fire-generated sensible heat flux, which is found to be 87kWm−2. The mean radial velocity structure of the plume indicates flow convergence into the plume base and regions of both convective overshoot and sinking flow in the upper plume. The updraft speed in the lower plume is estimated to be 13.5ms−1 by tracking the leading edge of a convective element ascending through the plume. The lidar data also reveal aspects of entrainment processes during the plume rise. For example, the covariation of the radial velocity and smoke perturbations are shown to dilute the smoke concentration with height.

Remote sensing techniques have been used to study and track wildfire smoke plume structure and evolution; however, knowledge gaps remain because of the limited availability of observational datasets aimed at understanding fine-scale fire–atmosphere interactions and plume microphysics. Meteorological radars have been used to investigate the evolution of plume rise in time and space, but highly resolved plume observations are limited. In this study, we present a new mobile millimeter-wave (Ka band) Doppler radar system acquired to sample the fine-scale kinematics and microphysical properties of active wildfire smoke plumes from both wildfires and large prescribed fires. Four field deployments were conducted in autumn of 2019 during two wildfires in California and one prescribed burn in Utah. Radar parameters investigated in this study include reflectivity, radial velocity, Doppler spectrum width, differential reflectivity Z DR , and copolarized correlation coefficient ρ HV . Observed radar reflectivity ranged between −15 and 20 dB Z in plume, and radial velocity ranged from 0 to 16 m s −1 . Dual-polarimetric observations revealed that scattering sources within wildfire plumes are primarily nonspherical and oblate-shaped targets as indicated by Z DR values measuring above 0 and ρ HV values below 0.8 within the plume. Doppler spectrum width maxima were located near the updraft core region and were associated with radar reflectivity maxima.

Increasing fuel aridity due to climate warming has and will continue to increase wildfire danger in California. In addition to reducing global greenhouse gas emissions, one of the primary proposals for counteracting this increase in wildfire danger is a widespread expansion of hazardous fuel reductions. Here, we quantify the potential for fuel reduction to reduce wildfire intensity using empirical relationships derived from historical observations with a novel combination of spatiotemporal resolution (0.375 km, instantaneous) and extent (48 million acres, 9 years). We use machine learning to quantify relationships between sixteen environmental conditions (including ten fuel characteristics and four temperature-affected aridity characteristics) and satellite-observed fire radiative power. We use the derived relationships to create fire intensity potential (FIP) maps for sixty historical weather snapshots at a 2 km and hourly resolution. We then place these weather snapshots in differing background climatological temperature and fuel characteristic conditions to quantify their independent and combined influence on FIP. We find that in order to offset the effect of climate warming under the SSP2-4.5 emissions scenario, fuel reduction would need to be maintained perpetually on ∼3 million acres (or 600 000 acres per year, 1% of our domain, at a 5 year return frequency) by 2050 and ∼8 million acres (or 1.6 million acres per year, 3% of our domain, at a 5 year return frequency) by 2090. Overall, we find substantial potential for fuel reduction to negate the effects of climate warming on FIP.

The second largest fire shelter deployment in U.S. history occurred in August 2003 during the Devil Fire, which was burning in a remote and rugged region of the San Francisco Bay Area, when relative humidity abruptly dropped in the middle of the night, causing rapid fire growth. Nocturnal drying events in the higher elevations along California’s central coast are a unique phenomenon that poses a great risk to wildland firefighters. Single-digit relative humidity with dewpoints below −25°C is not uncommon during summer nights in this region. To provide the fire management community with knowledge of these hazardous conditions, an event criterion was established to develop a climatology of nocturnal drying and to investigate the synoptic patterns associated with these events. A lower-tropospheric source region of dry air was found over the northeastern Pacific Ocean corresponding to an area of maximum low-level divergence and associated subsidence. This dry air forms above a marine inversion and advects inland overnight with the marine layer and immerses higher-elevation terrain with warm and dry air. An average of 15–20 nocturnal drying events per year occur in elevations greater than 700 m in the San Francisco Bay Area, and their characteristics are highly variable, making them a challenge to forecast.

A simple field experiment was conducted to measure and quantify fire–atmosphere interactions during a grass fire spreading up a hill under a moderate cross-slope wind. The observed fire intensity measured by passive radiometers and calculated sensible heat fluxes ranged between 90 and 120 kW m - 2 . Observations from this experiment showed that convective heat generated from the fire front was transported downwind in the lowest 2 m and the highest plume temperatures remained in this shallow layer, suggesting the fire spread was driven primarily by the advection of near-ignition temperature gases, rather than by radiation of the tilted flame. Fire-induced circulations were present with upslope flows occurring during the fire-front passage helping to transport heat up the slope and perpendicular to the fire front. A decrease in atmospheric pressure of 0.4 hPa occurred at the fire front and coincided with a strong updraft core of nearly 8 m s - 1 . These observations provide evidence that, even under moderately windy conditions, the pressure minimum in the fire remains rather close to the combustion zone and plume. The turbulence associated with the fire front was characterized by isotropic behaviour at 12.0 m above the ground, while less isotropic conditions were found closer to the ground due to higher horizontal variances associated with fire-induced flow at the fire front. From analysis of the turbulence kinetic energy budget terms, it was found that buoyancy production, rather than shear generation, had a larger contribution to the generation of turbulence kinetic energy, even during a highly sheared and moderate ambient wind.

The vertical turbulent transfer of heat and momentum in the lower atmospheric boundary layer is accomplished through intermittent sweep, ejection, outward interaction, and inward interaction events associated with turbulent updrafts and downdrafts. These events, collectively referred to as sweep–ejection dynamics, have been studied extensively in forested and nonforested environments and reported in the literature. However, little is known about the sweep–ejection dynamics that occur in response to turbulence regimes induced by wildland fires in forested and nonforested environments. This study attempts to fill some of that knowledge gap through analyses of turbulence data previously collected during three wildland (prescribed) fires that occurred in grassland and forested environments in Texas and New Jersey. Tower-based high-frequency (10 or 20 Hz) three-dimensional wind-velocity and temperature measurements are used to examine frequencies of occurrence of sweep, ejection, outward interaction, and inward interaction events and their actual contributions to the mean vertical turbulent fluxes of heat and momentum before, during, and after the passage of fire fronts. The observational results suggest that wildland fires in these environments can substantially change the sweep–ejection dynamics for turbulent heat and momentum fluxes that typically occur when no fires are present, especially the relative contributions of sweeps versus ejections in determining overall heat and momentum fluxes.

The FireFlux II experiment was conducted in a tall grass prairie located in south-east Texas on 30 January 2013 under a regional burn ban and high fire danger conditions. The goal of the experiment was to better understand micrometeorological aspects of fire spread. The experimental design was guided by the use of a coupled fire–atmosphere model that predicted the fire spread in advance. Preliminary results show that after ignition, a surface pressure perturbation formed and strengthened as the fire front and plume developed, causing an increase in wind velocity at the fire front. The fire-induced winds advected hot combustion gases forward and downwind of the fire front that resulted in acceleration of air through the flame front. Overall, the experiment collected a large set of micrometeorological, air chemistry and fire behaviour data that may provide a comprehensive dataset for evaluating and testing coupled fire–atmosphere model systems.

Letter to the Editor