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Abstract Atmospheric extreme heat is intensifying across terrestrial, marine, and coastal environments, impacting ecosystems, society, and other extremes, such as drought and marine heatwaves. We quantify the characteristics of contiguous near‐surface heatwaves using ERA5 (December 1940–November 2024) and find significant differences across these environments. Coastal heatwaves exhibit higher mean and peak intensity compared to terrestrial and atmospheric marine heatwaves in tropical and temperate regions, while peak intensity of polar coastal heatwaves is also significantly higher. We find that peak intensity decreases with distance from the coastline. We observe significant increases in frequency, concurrence, duration, and spatial extent, with more rapid increases during 1990–2024 compared to 1940–1989. The El Niño‐Southern Oscillation significantly influences interannual variations in heatwave frequency in tropical regions. Our findings provide important insights into extreme heat across terrestrial, marine, and coastal environments which can aid in societal adaptations under global warming. 

Abstract June 2023 witnessed the hottest, largest, and longest‐lasting heatwave across Mexico and Texas between 1940 and 2023. We apply constructed analogs with multiple linear regression models to quantify the contribution of different drivers to daily temperature anomalies during this heatwave. On the hottest day (20 June), circulation, soil moisture, and their interaction explained 3.82°C (90% CI: 2.72–4.91°C) of the 5.42°C observed anomaly with most of the residual attributed to the thermodynamic effects of long‐term warming. Using CESM2‐LENS2, we find that June 2023‐like patterns are not projected to increase in frequency but will become 1.9°C hotter by the mid‐21st century under SSP3‐7.0. The hottest simulated day with these patterns could produce temperatures >50°C (122°F) across south Texas, representing a low‐likelihood yet physically plausible worst‐case scenario that could inform disaster preparedness and adaptation planning. 

Abstract Lightning is a major source of wildfire ignition in the western United States (WUS). We build and train convolutional neural networks (CNNs) to predict the occurrence of cloud‐to‐ground (CG) lightning across the WUS during June–September from the spatial patterns of seven large‐scale meteorological variables from reanalysis (1995–2022). Individually trained CNN models at each 1° × 1° grid cell (n = 285 CNNs) show high skill at predicting CG lightning days across the WUS (median AUC = 0.8) and perform best in parts of the interior Southwest where summertime CG lightning is most common. Further, interannual correlation between observed and predicted CG lightning days is high (medianr = 0.87), demonstrating that locally trained CNNs realistically capture year‐to‐year variation in CG lightning activity across the WUS. We then use layer‐wise relevance propagation (LRP) to investigate the relevance of predictor variables to successful CG lightning prediction in each grid cell. Using maximum LRP values, our results show that two thermodynamic variables—ratio of surface moist static energy to free‐tropospheric saturation moist static energy, and the 700–500 hPa lapse rate—are the most relevant CG lightning predictors for 93%–96% of CNNs depending on the LRP variant used. As lightning is not directly simulated by global climate models, these CNNs could be used to parameterize CG lightning in climate models to assess changes in future CG lightning occurrence with projected climate change. Understanding changes in CG lightning risk and consequently lightning‐caused wildfire risk across the WUS could inform fire management, planning, and disaster preparedness. 

Abstract Recurving tropical cyclones (TC) in the Western North Pacific can affect the atmospheric circulation over Pacific‐Western North America (PWNA) via interactions with the midlatitude circulation. Using reanalysis and tropical cyclone best‐track data, we examine how recurving TCs that make extratropical transition modulate 500‐hPa ridge characteristics over PWNA during the peak (June‐September) and late (October–December) seasons. TCs recurving at lower latitudes are associated with more intense and poleward‐centered ridges relative to TCs recurving at higher latitudes, and TCs that recurve farther west are associated with relatively westward‐centered ridges. Characteristics of the prevailing midlatitude flow such as its amplitude and positioning relative to the recurving TCs also affect PWNA ridge characteristics, determine whether the flow is amplified or dampened following TC‐midlatitude interactions. Our study highlights multiple factors shaping the diversity of midlatitude circulation responses to recurving TCs, which are relevant for predicting downstream ridge characteristics and their associated surface extremes. 

Abstract Several recent widespread temperature extremes across the United States (U.S.) have been associated with power outages, disrupting access to electricity at times that are critical for the health and well-being of communities. Building resilience to such extremes in our energy infrastructure needs a comprehensive understanding of their spatial and temporal characteristics. In this study, we systematically quantify the frequency, extent, duration, and intensity of widespread temperature extremes and their associated energy demand in the six North American Electric Reliability Corporation regions using ERA5 reanalysis data. We show that every region has experienced hot or cold extremes that affected nearly their entire extent and such events were associated with substantially higher energy demand, resulting in simultaneous stress across the entire electric gird. The western U.S. experienced significant increases in the frequency (123%), extent (32%), duration (55%) and intensity (29%) of hot extremes and Texas experienced significant increases in the frequency (132%) of hot extremes. The frequency of cold extremes has decreased across most regions without substantial changes in other characteristics. Using power outage data, we show that recent widespread extremes in nearly every region have coincided with power outages, and such outages account for between 12%–52% of all weather-related outages in the past decade depending on the region. Importantly, we find that solar potential is significantly higher during widespread hot extremes in all six regions and during widespread cold extremes in five of the six regions. Further, wind potential is significantly higher during widespread hot or cold extremes in at least three regions. Our findings indicate that increased solar and wind capacity could be leveraged to meet the higher demand for energy during such widespread extremes, improving the resilience and reliability of our energy systems in addition to limiting carbon emissions. 

Abstract During the last week of June 2021, the Pacific Northwest region of North America experienced a record-breaking heatwave of historic proportions. All-time high temperature records were shattered, often by several degrees, across many locations, with Canada setting a new national record, the state of Washington setting a new record, and the state of Oregon tying its previous record. Here we diagnose key meteorology that contributed to this heatwave. The event was associated with a highly anomalous midtropospheric ridge, with peak 500-hPa geopotential height anomalies centered over central British Columbia. This ridge developed over several days as part of a large-scale wave train. Back trajectory analysis indicates that synoptic-scale subsidence and associated adiabatic warming played a key role in enhancing the magnitude of the heat to the south of the ridge peak, while diabatic heating was dominant closer to the ridge center. Easterly/offshore flow inhibited marine cooling and contributed additional downslope warming along the western portions of the region. A notable surface thermally induced trough was evident throughout the event over western Oregon and Washington. An eastward shift of the thermal trough, following the eastward migration of the 500-hPa ridge, allowed an inland surge of cooler marine air and dramatic 24-h cooling, especially along the western periphery of the region. Large-scale horizontal warm-air advection played a minimal role. When compared with past highly amplified ridges over the region, this event was characterized by much higher 500-hPa geopotential heights, a stronger thermal trough, and stronger offshore flow. 

Escalating wildfire activity in the western United States has accelerated adverse societal impacts. Observed increases in wildfire severity and impacts to communities have diverse anthropogenic causes—including the legacy of fire suppression policies, increased development in high-risk zones, and aridification by a warming climate. However, the intentional use of fire as a vegetation management tool, known as “prescribed fire,” can reduce the risk of destructive fires and restore ecosystem resilience. Prescribed fire implementation is subject to multiple constraints, including the number of days characterized by weather and vegetation conditions conducive to achieving desired outcomes. Here, we quantify observed and projected trends in the frequency and seasonality of western United States prescribed fire days. We find that while ~2 C of global warming by 2060 will reduce such days overall (−17%), particularly during spring (−25%) and summer (−31%), winter (+4%) may increasingly emerge as a comparatively favorable window for prescribed fire especially in northern states. 

Abstract Cloud‐to‐ground lightning with minimal rainfall (“dry” lightning) is a major wildfire ignition source in the western United States (WUS). Although dry lightning is commonly defined as occurring with <2.5 mm of daily‐accumulated precipitation, a rigorous quantification of precipitation amounts concurrent with lightning‐ignited wildfires (LIWs) is lacking. We combine wildfire, lightning and precipitation data sets to quantify these ignition precipitation amounts across ecoprovinces of the WUS. The median precipitation for all LIWs is 2.8 mm but varies with vegetation and fire characteristics. “Holdover” fires not detected until 2–5 days following ignition occur with significantly higher precipitation (5.1 mm) compared to fires detected promptly after ignition (2.5 mm), and with cooler and wetter environmental conditions. Further, there is substantial variation in precipitation associated with promptly‐detected (1.7–4.6 mm) and holdover (3.0–7.7 mm) fires across ecoprovinces. Consequently, the widely‐used 2.5 mm threshold does not fully capture lightning ignition risk and incorporating ecoprovince‐specific precipitation amounts would better inform WUS wildfire prediction and management.