Large Wildfires Research Articles

The effect of adjacent vegetation on fire severity in Afrotemperate forest along the southern Cape coast of South Africa

Recently two large wildfires (around the towns of Knysna in 2017 and George in 2018) jointly burnt over 80 000 ha in the southern Cape, South Africa. Here, patches of closed-canopy Afrotemperate forest occur within a matrix of fire-prone (native) fynbos shrublands or adjacent to commercial plantations of invasive alien Pinus trees (a transformed state). We compared the distances that fire penetrated into forest margins adjacent to fynbos to those adjacent to plantations. Furthermore, we used a satellite-derived index of fire severity, the differenced Normalised Burn Ratio (dNBR), to compare fire severity in forest margins adjacent to fynbos to those adjacent to plantations. Results were inconsistent between the two fires. In the Knysna fire, no significant difference was noted in fire penetration into forest, while forest margins adjacent to plantations burnt at significantly lower severity than those adjacent to fynbos. In the George fire, penetration into and fire severity in forest margins adjacent to plantations were significantly greater than in those adjacent to fynbos. Not only were fire severity and penetration in forest margins with plantations adjacent dissimilar between the George and Knysna fires, but variability in fire severity was greater in forest margins with plantation adjacent than in those with fynbos adjacent. Our study provides evidence that fire severity in forest margins is associated with the adjacent vegetation type and that plantations potentially expose forests to greater variability in fire severity and extent than the forest may experience under natural conditions. Other important factors that may affect the severity and extent of burn in forest margins are forest patch size and topographical position, the nature of the ecotone between forest and the adjacent vegetation, and the fuel load and structure of the adjacent vegetation which varies considerably in relation to stand age and management practices in plantations.

Investigating the drivers of the unprecedented Chernobyl Power Plant Wildfire in April 2020 and its effects on 137Cs dispersal

In this study, we explore the conditions that led to the unprecedented wildfire that occurred in the Chernobyl Exclusion Zone in April 2020 and the effect of this fire on 137Cs dispersal, as wildfires are important drivers of 137Cs resuspension, with potentially harmful consequences for the receiving ecosystems. We characterised the historical wildfire record between 2000 and 2020 using the MCD64A1.006 MODIS Burned Area Monthly Global 500 m dataset and assessed the climatic conditions associated with these wildfire events using ERA5-Land reanalysis data. We also examined fire danger indices at the time of these wildfires. We then explored the widespread effects of the April 2020 wildfire on 137Cs resuspension and subsequent deposition using the NOAA-HYSPLIT model, concluding that the impacts of such resuspension on areas further afield were minimal. Results show that climatic conditions leading to severe wildfires are increasing, especially during March and April. High soil moisture, relative humidity and extreme temperature anomalies are associated with the largest wildfires on record, and fire risk indices at the time of the April 2020 fire were higher than for other large fires on record. We have estimated that 3854 GBq of 137Cs resuspended during the CPPF, with atmospheric transport dominant over Russia, Ukraine, Moldova and Kazakhstan. The observed increase in large wildfires will have implications for wildfire-driven soil erosion processes, which will further exacerbate the effects of atmospheric-driven 137Cs redistribution.

Wildfires impact on ecosystem service delivery in fire-prone maritime pine-dominated forests

Alterations generated by intensified wildfire regimes are leading to unprecedented impacts in the supply of ecosystem services (ES). We investigated how a large wildfire affected the components of ES delivery (capacity, flow, and demand) in a fire-prone landscape. We selected a set of socio-ecologically and economically important provisioning ES and analysed temporal trends in and mismatches between ES flow and demand indicators over three spatial scales. Serotinous pine forests were the principal service providing units (SPUs) contributing to ES supply before fire. Fire interrupted their ES capacity, correspondingly reducing the ES flow of wood production, hunting, livestock, and mushroom harvesting for several years. Actual fire-driven losses in wood production were masked by the immediate removal and selling of the burned trees. We detected two new opportunities of ES delivery emerge as a result of post-fire natural vegetation dynamics that last until today: honey and resin collection. Finally, there were no spatial mismatches between ES flow and demand over time due to wildfire occurrence. These findings highlighted the need to promote the post-fire recovery of key SPUs, and identify new unforeseen opportunities of ES supply created by fire and by the natural post-fire dynamics of the vegetation, to, at least partially, reverse the losses.

Widespread regeneration failure in forests of Greater Yellowstone under scenarios of future climate and fire.

Changing climate and disturbance regimes are increasingly challenging the resilience of forest ecosystems around the globe. A powerful indicator for the loss of resilience is regeneration failure, that is, the inability of the prevailing tree species to regenerate after disturbance. Regeneration failure can result from the interplay among disturbance changes (e.g., larger and more frequent fires), altered climate conditions (e.g., increased drought), and functional traits (e.g., method of seed dispersal). This complexity makes projections of regeneration failure challenging. Here we applied a novel simulation approach assimilating data-driven fire projections with vegetation responses from process modeling by means of deep neural networks. We (i) quantified the future probability of regeneration failure; (ii) identified spatial hotspots of regeneration failure; and (iii) assessed how current forest types differ in their ability to regenerate under future climate and fire. We focused on the Greater Yellowstone Ecosystem (2.9×106 ha of forest) in the Rocky Mountains of the USA, which has experienced large wildfires in the past and is expected to undergo drastic changes in climate and fire in the future. We simulated four climate scenarios until 2100 at a fine spatial grain (100m). Both wildfire activity and unstocked forest area increased substantially throughout the 21st century in all simulated scenarios. By 2100, between 28% and 59% of the forested area failed to regenerate, indicating considerable loss of resilience. Areas disproportionally at risk occurred where fires are not constrained by topography and in valleys aligned with predominant winds. High-elevation forest types not adapted to fire (i.e., Picea engelmannii-Abies lasiocarpa as well as non-serotinous Pinus contorta var. latifolia forests) were especially vulnerable to regeneration failure. We conclude that changing climate and fire could exceed the resilience of forests in a substantial portion of Greater Yellowstone, with profound implications for carbon, biodiversity, and recreation.

Deforestation, fires, and lack of governance are displacing thousands of jaguars in Brazilian Amazon

AbstractThe rate of deforestation and the number of large wildfires are increasing in the Amazon. Illegal loggers, miners, ranchers, and farmers all have contributed to this increase. Their activities have dramatic consequences for biodiversity, ecological services, and people. In this study, we estimated the number of jaguars affected by deforestation. We focused on the Brazilian Amazon from August 2016 to December 2019. Further, we analyzed the effects of socio‐geographic determinants of deforestation and state policies. To do so, we used deforestation data from DETER‐B satellite system. The number of jaguars within each deforested area was pulled from a previous study, which provided jaguar abundances for jaguar entire range. We assumed all jaguars within a deforested area were affected (displaced or killed). To determine the underlying causes of jaguar loss, we regressed the number of jaguars lost per state and year against the proportion of total forest area within reserves, distance to forest border, and monetary efficiency in cattle production. We estimate a total of 1,422 jaguars have been displaced/killed in recent years (2016: 488, 2017: 360, 2018: 268, 2019: 354). Only the proportion of protected area had an effect in reducing jaguar deforestation. We discuss how our work could result in near real‐time monitoring of jaguar displacement and how policies such as wood certification, more efficient cattle production, and centralizing governance may be solutions.

A multi-analysis approach for estimating regional health impacts from the 2017 Northern California wildfires

ABSTRACT Smoke impacts from large wildfires are mounting, and the projection is for more such events in the future as the one experienced October 2017 in Northern California, and subsequently in 2018 and 2020. Further, the evidence is growing about the health impacts from these events which are also difficult to simulate. Therefore, we simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling with WRF-CMAQ, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses. To demonstrate these analyses, we estimated the health impacts from smoke impacts during wildfires in October 8–20, 2017, in Northern California, when over 7 million people were exposed to Unhealthy to Very Unhealthy air quality conditions. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ system. Interestingly, this approach did not necessarily improve overall results, however it was key to simulating the initial 12-hr explosive fire activity and smoke impacts. To improve these results, we applied one data fusion and three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across all cases, the best Pearson correlation was 0.5. Overall, WRF-CMAQ simulations were biased high and the geostatistical methods were biased low. Finally, we applied the optimized PM2.5 exposure estimate in an exposure-response function. Estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% CI: 0, 196) with 47% attributable to wildland fire smoke. Implications: Large wildfires in the United States and in particular California are becoming increasingly common. Associated with these large wildfires are air quality and health impact to millions of people from the smoke. We simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses from the October 2017 Northern California wildfires. Temporary monitors deployed for the wildfires provided an important model evaluation dataset. Total estimated regional mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to the wildland fire smoke. This illustrates the profound effect that even a 12-day exposure to wildland fire smoke can have on human health.

The Influence of Wildfire Smoke on Cloud Microphysics during the September 2020 Pacific Northwest Wildfires

AbstractDuring late summer 2020, large wildfires over the Pacific Northwest produced dense smoke that impacted the region for an extended period. During this period of poor air quality, persistent low-level cloud coverage was poorly forecast by operational numerical weather prediction models, which dissipated clouds too quickly or produced insufficient cloud coverage extent. This deficiency raises questions about the influence of wildfire smoke on low-level clouds in the marine environment of the Pacific Northwest.This paper investigates the effects of wildfire smoke on the properties of low-level clouds, including their formation, microphysical properties, and dissipation. A case study from 12-14 September 2020 is used as a testbed to evaluate the impact of wildfire smoke on such clouds. Observations from satellites and surface observing sites, coupled with mesoscale model simulations, are applied to understand the influence of wildfire smoke during this event. Results indicate that the presence of thick smoke over Washington led to decreased temperatures in the lower troposphere which enhanced low-level cloud coverage, with smoke particles altering the microphysical structure of clouds to favor high concentrations of small droplets. Thermodynamic changes due to smoke are found to be the primary driver of enhanced cloud lifetime during these events, with microphysical changes to clouds as a secondary contributing factor. However, both the thermodynamic and microphysical effects are necessary to produce a realistic simulation.

The current landscape fire management in Ukraine and strategy for its improvement

Abstract Recurrent wildfires in Ukraine exert severe impacts on the environment, human health and security as well as damage to private and public assets. From 2007 to 2020, the frequency of large wildfires has increased and reached a level that has not occurred previously. The period during April-October 2020 was the worst in modern Ukrainian history for the occurrence of catastrophic fires, e.g. in the Chernobyl Exclusion Zone (67 000 ha), Zhytomyr oblast (43 000 ha), Lugansk oblast (35 000 ha) and Kharkiv oblast (8 000 ha). In Ukraine there is the additional problem of open burning, mainly burning agriculture residues, which covers two million hectares (ha) annually. State forestry enterprises who are responsible for the management of 71% of the Ukrainian forests (7.6 million ha)and agricultural holdings are also responsible for the management of 41.3 million ha of croplands. The remaining forest users manage forest areas of 3.1 million ha within reserves and national nature parks. This article presents a brief overview of the problem of forest fires as well as of fires in other landscapes in Ukraine, and includes a critical reviews of the current wildfire management system and a description of the main features of the national wildfire management strategy. It also highlights the results of a survey of numerous stakeholders conducted on landscape fires in Ukraine. Based on the review of global and regional experiences, as well as existing fire risks in Ukraine, recommendations were developed for implementing an integrated landscape level national fire management approach.

Hot and cold flavors of southern California\u2019s Santa Ana winds: their causes, trends, and links with wildfire

Santa Ana winds (SAWs) are associated with anomalous temperatures in coastal Southern California (SoCal). As dry air flows over SoCal’s coastal ranges on its way from the elevated Great Basin down to sea level, all SAWs warm adiabatically. Many but not all SAWs produce coastal heat events. The strongest regionally averaged SAWs tend to be cold. In fact, some of the hottest and coldest observed temperatures in coastal SoCal are linked to SAWs. We show that hot and cold SAWs are produced by distinct synoptic dynamics. High-amplitude anticyclonic flow around a blocking high pressure aloft anchored at the California coast produces hot SAWs. Cold SAWs result from anticyclonic Rossby wave breaking over the northwestern U.S. Hot SAWs are preceded by warming in the Great Basin and dry conditions across the Southwestern U.S. Precipitation over the Southwest, including SoCal, and snow accumulation in the Great Basin usually precede cold SAWs. Both SAW flavors, but especially the hot SAWs, yield low relative humidity at the coast. Although cold SAWs tend to be associated with the strongest winds, hot SAWs tend to last longer and preferentially favor wildfire growth. Historically, out of large (> 100 acres) SAW-spread wildfires, 90% were associated with hot SAWs, accounting for 95% of burned area. As health impacts of SAW-driven coastal fall, winter and spring heat waves and impacts of smoke from wildfires have been recently identified, our results have implications for designing early warning systems. The long-term warming trend in coastal temperatures associated with SAWs is focused on January–March, when hot and cold SAW frequency and temperature intensity have been increasing and decreasing, respectively, over our 71-year record.

Machine Learning Methods and Synthetic Data Generation to Predict Large Wildfires.

Wildfires are becoming more frequent in different parts of the globe, and the ability to predict when and where they will occur is a complex process. Identifying wildfire events with high probability of becoming a large wildfire is an important task for supporting initial attack planning. Different methods, including those that are physics-based, statistical, and based on machine learning (ML) are used in wildfire analysis. Among the whole, those based on machine learning are relatively novel. In addition, because the number of wildfires is much greater than the number of large wildfires, the dataset to be used in a ML model is imbalanced, resulting in overfitting or underfitting the results. In this manuscript, we propose to generate synthetic data from variables of interest together with ML models for the prediction of large wildfires. Specifically, five synthetic data generation methods have been evaluated, and their results are analyzed with four ML methods. The results yield an improvement in the prediction power when synthetic data are used, offering a new method to be taken into account in Decision Support Systems (DSS) when managing wildfires.

Environmental and political implications of underestimated cropland burning in Ukraine

Open burning is illegal in Ukraine, yet Ukraine has, on average, 300 times more fire activity per year (2001–2019) than most European countries. In 2016 and 2017, 47% of Ukraine was identified as cultivated area, with a total of 70% of land area dedicated to agricultural use. Over 57% of all active fires in Ukraine detected using space-borne Visible Infrared Imaging Radiometer Suite (VIIRS) during 2016 and 2017 were associated with pre-planting field clearing and post-harvest crop residue removal, meaning that the majority of these fires are preventable. Due to the small size and transient nature of cropland burns, satellite-based burned area (BA) estimates are often underestimated. Moreover, traditional spectral-based BA algorithms are not suitable for distinguishing burned from plowed fields, especially in the black soil regions of Ukraine. Therefore, we developed a method to estimate agricultural BA by calibrating VIIRS active fire data with exhaustively mapped cropland reference areas (42 958 fields). Our study found that cropland BA was significantly underestimated (by 30%–63%) in the widely used Moderate Resolution Imaging Spectroradiometer-based MCD64A1 BA product, and by 95%–99.9% in Ukraine’s National Greenhouse Gas Inventory. Although crop residue burns are smaller and emit far less emissions than larger wildfires, reliable monitoring of crop residue burning has a number of important benefits, including (a) improving regional air quality models and the subsequent understanding of human health impacts due to the proximity of crop residue burns to urban locations, (b) ensuring an accurate representation of predominantly smaller fires in regional emission inventories, and (c) increasing awareness of often illegal managed open burning to provide improved decision-making support for policy and resource managers.

Drought-driven wildfire impacts on structure and dynamics in a wet Central Amazonian forest.

While the climate and human-induced forest degradation is increasing in the Amazon, fire impacts on forest dynamics remain understudied in the wetter regions of the basin, which are susceptible to large wildfires only during extreme droughts. To address this gap, we installed burned and unburned plots immediately after a wildfire in the northern Purus-Madeira (Central Amazon) during the 2015 El-Niño. We measured all individuals with diameter of 10 cm or more at breast height and conducted recensuses to track the demographic drivers of biomass change over 3 years. We also assessed how stem-level growth and mortality were influenced by fire intensity (proxied by char height) and tree morphological traits (size and wood density). Overall, the burned forest lost 27.3% of stem density and 12.8% of biomass, concentrated in small and medium trees. Mortality drove these losses in the first 2 years and recruitment decreased in the third year. The fire increased growth in lower wood density and larger sized trees, while char height had transitory strong effects increasing tree mortality. Our findings suggest that fire impacts are weaker in the wetter Amazon. Here, trees of greater sizes and higher wood densities may confer a margin of fire resistance; however, this may not extend to higher intensity fires arising from climate change.

The relationship between the polar jet stream and extreme wildfire events in North America

AbstractNorthern hemisphere mid-latitudeweather is strongly influenced by the polar jet stream (PJS), which dictates the position of storm tracks; this influence also extends to weather patterns conducive to the ignition and growth of large wildfires. We examined the role of the PJS on extreme wildfire events in North America (NA) between 40° and 70°N latitude, using fire spread events (FSEs) for 2002—2016. Climatologies of the 300-hPa wind components and derived quantities show that the PJS weakens and moves northward in the Boreal summer coincident with the fire season. We use spatio-temporal compositing of 300-hPa winds and 500-hPa geopotential height anomalies to show that FSEs are associated with an upper-level ridge and high centered over events, except eastern Canada where patterns are displaced westward. Ridge patterns persist longer for FSEs in western NA compared with Eastern NA, as well as for May to August compared with April, September and October. These tropospheric patterns also occur concomitantly with surface weather drivers of fire spread including positive daily mean temperature and vapor pressure deficit anomalies and negative precipitation anomalies. Distributions of maximum and minimum latitudinal jet stream peak, ridge and trough positions, relative to FSEs, confirm that events occur predominantly southward of the jet stream core and near a ridge for low split flow configurations but not necessarily for high split flow configurations. These findings have wide-reaching implications for better understanding NA fire regimes and potential fire management strategies (eg. resource pre-positioning and tactical suppression) through improved forecasting of fire weather.

Relationship between circum-Arctic atmospheric wave patterns and large-scale wildfires in boreal summer

Long-term assessment of severe wildfires and associated air pollution and related climate patterns in and around the Arctic is essential for assessing healthy human life status. To examine the relationships, we analyzed the National Aeronautics and Space Administration (NASA) modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Our investigation based on this state-of-the-art atmospheric reanalysis data reveals that 13 out of the 20 months with the highest PM2.5 (corresponding to the highly elevated organic carbon in the particulate organic matter [POM] form) monthly mean mass concentration over the Arctic for 2003–2017 were all in summer (July and August), during which POM of 0.5 μg m−3 and PM2.5 were positively correlated. This correlation suggests that high PM2.5 in the Arctic is linked to large wildfire contributions and characterized by significant anticyclonic anomalies (i.e. clockwise atmospheric circulation) with anomalous surface warmth and drier conditions over Siberia and subpolar North America, in addition to Europe. A similar climate pattern was also identified through an independent regression analysis for the July and August mean data between the same atmospheric variables and the sign-reversed Scandinavian pattern index. We named this pattern of recent atmospheric circulation anomalies the circum-Arctic wave (CAW) pattern as a manifestation of eastward group-velocity propagation of stationary Rossby waves (i.e. large-scale atmospheric waves). The CAW induces concomitant development of warm anticyclonic anomalies over Europe, Siberia, Alaska, and Canada, as observed in late June 2019. Surprisingly, the extended regression analysis of the 1980–2017 period revealed that the CAW pattern was not prominent before 2003. Understanding the CAW pattern under future climate change and global warming would lead to better prediction of co-occurrences of European heatwaves and large-scale wildfires with air pollution over Siberia, Alaska, and Canada in and around the Arctic in summer.

Evidence that post‐fire recovery of small mammals occurs primarily via in situ survival

AbstractAimAs climate change intensifies and wildfire frequency and scale increase, it is critical we develop a robust understanding of how species recover from these major disturbances. Here, we aim to determine whether source populations for recovery following large‐scale intense wildfires are derived from either in situ survival, or immigration from surrounding unburnt areas (ex situ). Secondly, we sought to determine whether habitat elements (e.g., logs) within the landscape facilitate in situ survival of small mammals during fires.LocationGrampians National Park, south‐eastern Australia.MethodsWe used long‐term post‐fire small mammal monitoring to investigate sources of recovery for small mammals, and camera trapping and habitat surveys immediately following large intense wildfires to assess evidence for and drivers of post‐fire survival.ResultsWe found no relationship between distance to unburnt vegetation and the occurrence of any native species, suggesting that in situ survival is the probable mechanism for recovery of post‐fire mammal populations, compared with immigration from external unburnt areas. We also show that key habitat elements such as rocks and large trees were associated with the occurrence of several species immediately post‐fire, suggesting a role for these features in facilitating the survival of species during and following fire.Main conclusionsWe present evidence for post‐fire recovery being driven by in situ survival. In situ survival is facilitated by small unburnt patches and habitat elements in burnt areas. These surviving individuals become the founders for subsequent post‐fire population recovery. Given that globally we are seeing increasingly frequent large‐scale wildfires driven by climate change, the capacity for in situ survival will help mitigate some of the fire‐related impacts of climate change.

National Park Service fire restoration, policies versus results: What went wrong

In the 1960s the US National Park Service developed a policy designed to restore the natural ecological role of wildland fire. The policy was driven by growing understanding of ecosystem management benefits, as reflected in the 1963 Leopold Report on wildlife management in national parks. The new policy was designed to reverse decades of aggressive wildfire suppression that had caused disruptions in habitats and vegetative communities, and unnaturally high wildland fuel accumulation. More than 50 years later, the policy has largely failed to achieve its goals. This failure is due not just to climate change and the rise of new fire regimes dominated by mega-fires. It also was due to a lack of clear and unified organizational commitment by many parks, along with continued administrative comfort with fire suppression-oriented thinking, particularly during the window of opportunity between 1970 and 2000. During this time program emphasis shifted from ecosystem restoration to hazard fuels reduction, and program direction from Natural Resources staff to Emergency Services personnel. Efforts to establish a balance between emergency response thinking and resource management thinking largely failed due to institutional barriers and funding/staffing decisions driven by the threat of large wildfires. Park managers became wary of natural fire regime restoration efforts after the 1988 Yellowstone fires and the 2000 Cerro Grande Fire. This accelerated the demise of the Leopold Report vision of restoring and maintaining the ecological role of natural fire. In its place, wildfire suppression philosophy again became predominant, as reflected in the National Fire Plan with its focus away from ecological fire use and toward hazard fuel reduction in support of protecting the wildland urban interface. Restoring the Leopold Report vision requires an interdivisional commitment by Park emergency response and resources management organizations, guided by leadership at all organizational levels. It now may be timely to establish an NPS advisory board on wildland fire management similar to the one that produced the Leopold Report. This Board should review wildland fire policy implementation over the past 58 years, determine whether the ecosystem restoration paradigm is still valid, and if so, then the types of leadership and organizational changes required to achieve it.

Deep stratospheric intrusion and Russian wildfire induce enhanced tropospheric ozone pollution over the northern Tibetan Plateau

By using ozonesonde measurements during July–August in 2016, 2019, and 2020 at Golmud and Qaidam, European Centre for Medium-Range Weather Forecasts (ECMWF) next-generation reanalysis ERA5 data, satellite-borne Moderate Resolution Imaging Spectrometer data products, and backward trajectory calculations from the chemical Lagrangian model of the stratosphere (CLaMS) model, this study analyzes vertical ozone distributions and explores the influence of deep stratospheric intrusions and wildfires on ozone variation in the northern Tibetan Plateau (TP) during the Asian summer monsoon period. Large ozone partial pressures were observed between 20 and 30 km, with a maximum of ~16 mPa at approximately 27 km latitude. The comparisons between the vertical ozone profiles with and without the occurrence of stratospheric intrusions showed that their relative ozone difference was up to 72.4% in the tropopause layer (15.8 km), and a secondary maximum of 66.7% existed in the middle troposphere (10.1 km). The stratospheric intrusions dried the atmosphere by 52.9% and enhanced the ozone columns by 26.1% below the upper troposphere and lower stratosphere. A case study of deep stratospheric intrusion exhibited the occurrence of large ozone partial pressure in the middle troposphere in detail, with an ozone peak of ~6 mPa at 10 km, which was caused by a tropopause fold associated with the westerly wind jet at the north flank of the Asian summer monsoon anticyclone. The stratospheric intrusion processes effectively transported the cold and dry air mass with high ozone in the stratosphere downward to the middle troposphere over the northern TP. This study also confirmed that by long-range transport processes, large wildfire smoke occurred around central and eastern Russia on 19–26 July 2016 greatly caused ozone pollution in the troposphere (6 km depth from the surface) over the northern TP.

Application of Facebook’s Prophet Model for Forecasting Meteorological Data

The wildfire risk index was calculated based on current meteorological information, for example, temperature, humidity, and wind speed. Thus, meteorological data forecasting could help estimate the probability of fire occurrence or spreading speed to prevent large wildfires. This study predicts meteorological data (e.g., temperature, humidity, and wind speed) using Facebook's Prophet library. We trained the Prophet model using meteorological data between 2016 and 2018 in Goseong, Gangwon-do (where the wildfire occurred in 2019) and predicted meteorological data for the first four months in 2019. We obtained that Facebook's Prophet model was effective in computing speed and predicting the overall trend. However, it could not predict sudden irregular changes satisfactorily. Considering its rapidity, these results could play an important role in future research, especially as a basic research for time-series forecasting.

Association of Wildfire Air Pollution and Health Care Use for Atopic Dermatitis and Itch

Air pollution is a worldwide public health issue that has been exacerbated by recent wildfires, but the relationship between wildfire-associated air pollution and inflammatory skin diseases is unknown. To assess the associations between wildfire-associated air pollution and clinic visits for atopic dermatitis (AD) or itch and prescribed medications for AD management. This cross-sectional time-series study assessed the associations of air pollution resulting from the California Camp Fire in November 2018 and 8049 dermatology clinic visits (4147 patients) at an academic tertiary care hospital system in San Francisco, 175 miles from the wildfire source. Participants included pediatric and adult patients with AD or itch from before, during, and after the time of the fire (October 2018 through February 2019), compared with those with visits in the same time frame of 2015 and 2016, when no large wildfires were near San Francisco. Data analysis was conducted from November 1, 2019, to May 30, 2020. Wildfire-associated air pollution was characterized using 3 metrics: fire status, concentration of particulate matter less than 2.5 μm in diameter (PM2.5), and satellite-based smoke plume density scores. Weekly clinic visit counts for AD or itch were the primary outcomes. Secondary outcomes were weekly numbers of topical and systemic medications prescribed for AD in adults. Visits corresponding to a total of 4147 patients (mean [SD] age, 44.6 [21.1] years; 2322 [56%] female) were analyzed. The rates of visits for AD during the Camp Fire for pediatric patients were 1.49 (95% CI, 1.07-2.07) and for adult patients were 1.15 (95% CI, 1.02-1.30) times the rate for nonfire weeks at lag 0, adjusted for temperature, relative humidity, patient age, and total patient volume at the clinics for pediatric patients. The adjusted rate ratios for itch clinic visits during the wildfire weeks were 1.82 (95% CI, 1.20-2.78) for the pediatric patients and 1.29 (95% CI, 0.96-1.75) for adult patients. A 10-μg/m3 increase in weekly mean PM2.5 concentration was associated with a 7.7% (95% CI, 1.9%-13.7%) increase in weekly pediatric itch clinic visits. The adjusted rate ratio for prescribed systemic medications in adults during the Camp Fire at lag 0 was 1.45 (95% CI, 1.03-2.05). This cross-sectional study found that short-term exposure to air pollution due to the wildfire was associated with increased health care use for patients with AD and itch. These results may provide a better understanding of the association between poor air quality and skin health and guide health care professionals' counseling of patients with skin disease and public health practice.

Compound Extremes Drive the Western Oregon Wildfires of September 2020

AbstractSeveral very large high‐impact fires burned nearly 4,000 km2 of mesic forests in western Oregon during September 7–9, 2020. While infrequent, very large high‐severity fires have occurred historically in western Oregon, the extreme nature of this event warrants analyses of climate and meteorological drivers. A strong blocking pattern led to an intrusion of dry air and strong downslope east winds in the Oregon Cascades following a warm‐dry 60‐day period that promoted widespread fuel flammability. Viewed independently, both the downslope east winds and fuel dryness were extreme, but not unprecedented. However, the concurrence of these drivers resulted in compound extremes and impacts unmatched in the observational record. We additionally find that most large wildfires in western Oregon since 1900 have similarly coincided with warm‐dry summers during at least moderate east wind events. These results reinforce the importance of incorporating a multivariate lens for compound extremes in assessing wildfire hazard risk.