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Background. Since the mid-20th century, massive dieback of coniferous forests has been observed in the temperate and boreal zones across North America and Northern Eurasia. The first hypotheses explaining forest dieback were associated with industrial air pollution (acid rain). At the end of the century, new hypotheses emerged that supported critical climate-induced aridization to explain forest dieback. Many studies were based on the SPEI (Standardized Precipitation Evapotranspiration Index) drought index. Our goals were to investigate if the SPEI drought index was a suitable metric to reflect drought conditions in wet and moist dark-needled forests in the South Siberian Mountains (Mts) and if droughts trigger the dieback of those forests. Methods. We calculated the SPEI drought index, the annual moisture index AMI, potential evapotranspiration PET, and water balance dynamics for the period 1961–2019 for four transects in the South Siberian Mts. where decline/dieback of dark-needled Siberian pine and fir forests were identified in situ. Climate data from nine weather stations located at lower and upper elevations of each transect were used to calculate climatic index dynamics for the 1961–2019 period to identify dry and wet phases of the period. Results. Our findings showed that climatic moisture/dryness indices have rarely gone down to high risk levels during the last 60 years (1961–2019). AMI did not reach the critical limit, 2.25, characteristic of the lower border for the dark-needled taiga. SPEI values < −1.5 represent drought stress conditions for dark-needled conifers at the lower border, and these conditions occurred 3–4 times during the 60-year period. However, the annual water balance stayed positive in those years in wet and moist forests at mid-to-high elevations. Trees are known to survive occasional (1–2) dry years. We found that dark-needled conifer dieback often occurs in wet years with plentiful rain rather than in drought years. We found forest dieback was associated with the westerlies that bring atmospheric pollution from the west at 50–56 N latitudes, where the air masses cross populated regions that have widespread industrial complexes. Conclusions. We concluded that the observed decline of dark-needled conifers at middle-to-high elevations across South Siberia’s Mts was conditioned by several plausible causes, among which air pollution seems to be more credible than dry climatic conditions, as cited in the literature. Results are essential for understanding these ecosystems and others as our planet changes. Other causes and mechanisms should be further investigated, which would necessitate creating infrastructure that supports the teamwork of plant physiologists, foresters, chemists, etc. 

Abstract Injections of wildfire smoke plumes into the free troposphere impact air quality, yet model forecasts of injections are poor. Here, we use aircraft observations obtained during the 2019 western US wildfires (FIREX-AQ) to evaluate a commonly used smoke plume rise parameterization in two atmospheric chemistry-transport models (WRF-Chem and HRRR-Smoke). Observations show that smoke injections into the free troposphere occur in 35% of plumes, whereas the models forecast 59–95% indicating false injections in the simulations. False injections were associated with both models overestimating fire heat flux and terrain height, and with WRF-Chem underestimating planetary boundary layer height. We estimate that the radiant fraction of heat flux is 0.5 to 25 times larger in models than in observations, depending on fuel type. Model performance was substantially improved by using observed heat flux and boundary layer heights, confirming that models need accurate heat fluxes and boundary layer heights to correctly forecast plume injections. 

Abstract Wildfire emissions are a key contributor of carbonaceous aerosols and trace gases to the atmosphere. Induced by buoyant lifting, smoke plumes can be injected into the free troposphere and lower stratosphere, which by consequence significantly affects the magnitude and distance of their influences on air quality and radiation budget. However, the vertical allocation of emissions when smoke escapes the planetary boundary layer (PBL) and the mechanism modulating it remain unclear. We present an inverse modeling framework to estimate the wildfire emissions, with their temporal and vertical evolution being constrained by assimilating aerosol extinction profiles observed from the airborne Differential Absorption Lidar‐High Spectral Resolution Lidar during the Fire Influence on Regional to Global Environments and Air Quality field campaign. Three fire events in the western U.S., which exhibit free‐tropospheric injections are examined. The constrained smoke emissions indicate considerably larger fractions of smoke injected above the PBL (f_>PBL, 80%–94%) versus the column total, compared to those estimated by the WRF‐Chem model using the default plume rise option (12%–52%). The updated emission profiles yield improvements for the simulated vertical structures of the downwind transported smoke, but limited refinement of regional smoke aerosol optical depth distributions due to the spatiotemporal coverage of flight observations. These results highlight the significance of improving vertical allocation of fire emissions on advancing the modeling and forecasting of the environmental impacts of smoke. 

Abstract. Fires emit sufficient sulfur to affect local and regional airquality and climate. This study analyzes SO2 emission factors andvariability in smoke plumes from US wildfires and agricultural fires, as well as theirrelationship to sulfate and hydroxymethanesulfonate (HMS) formation.Observed SO2 emission factors for various fuel types show goodagreement with the latest reviews of biomass burning emission factors,producing an emission factor range of 0.47–1.2 g SO2 kg−1 C.These emission factors vary with geographic location in a way that suggeststhat deposition of coal burning emissions and application ofsulfur-containing fertilizers likely play a role in the larger observedvalues, which are primarily associated with agricultural burning. A 0-D boxmodel generally reproduces the observed trends of SO2 and total sulfate(inorganic + organic) in aging wildfire plumes. In many cases, modeled HMSis consistent with the observed organosulfur concentrations. However, acomparison of observed organosulfur and modeled HMS suggests that multipleorganosulfur compounds are likely responsible for the observations but thatthe chemistry of these compounds yields similar production and loss rates asthat of HMS, resulting in good agreement with the modeled results. Weprovide suggestions for constraining the organosulfur compounds observedduring these flights, and we show that the chemistry of HMS can alloworganosulfur to act as an S(IV) reservoir under conditions of pH > 6 and liquid water content>10−7 g sm−3. This canfacilitate long-range transport of sulfur emissions, resulting in increasedSO2 and eventually sulfate in transported smoke. 

Abstract The NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX‐AQ) experiment was a multi‐agency, inter‐disciplinary research effort to: (a) obtain detailed measurements of trace gas and aerosol emissions from wildfires and prescribed fires using aircraft, satellites and ground‐based instruments, (b) make extensive suborbital remote sensing measurements of fire dynamics, (c) assess local, regional, and global modeling of fires, and (d) strengthen connections to observables on the ground such as fuels and fuel consumption and satellite products such as burned area and fire radiative power. From Boise, ID western wildfires were studied with the NASA DC‐8 and two NOAA Twin Otter aircraft. The high‐altitude NASA ER‐2 was deployed from Palmdale, CA to observe some of these fires in conjunction with satellite overpasses and the other aircraft. Further research was conducted on three mobile laboratories and ground sites, and 17 different modeling forecast and analyses products for fire, fuels and air quality and climate implications. From Salina, KS the DC‐8 investigated 87 smaller fires in the Southeast with remote and in‐situ data collection. Sampling by all platforms was designed to measure emissions of trace gases and aerosols with multiple transects to capture the chemical transformation of these emissions and perform remote sensing observations of fire and smoke plumes under day and night conditions. The emissions were linked to fuels consumed and fire radiative power using orbital and suborbital remote sensing observations collected during overflights of the fires and smoke plumes and ground sampling of fuels. 

Abstract. Wildfire smoke is one of the most significant concerns ofhuman and environmental health, associated with its substantial impacts onair quality, weather, and climate. However, biomass burning emissions andsmoke remain among the largest sources of uncertainties in air qualityforecasts. In this study, we evaluate the smoke emissions and plumeforecasts from 12 state-of-the-art air quality forecasting systemsduring the Williams Flats fire in Washington State, US, August 2019, whichwas intensively observed during the Fire Influence on Regional to GlobalEnvironments and Air Quality (FIREX-AQ) field campaign. Model forecasts withlead times within 1 d are intercompared under the same framework basedon observations from multiple platforms to reveal their performanceregarding fire emissions, aerosol optical depth (AOD), surface PM2.5,plume injection, and surface PM2.5 to AOD ratio. The comparison ofsmoke organic carbon (OC) emissions suggests a large range of daily totalsamong the models, with a factor of 20 to 50. Limited representations of thediurnal patterns and day-to-day variations of emissions highlight the needto incorporate new methodologies to predict the temporal evolution andreduce uncertainty of smoke emission estimates. The evaluation of smoke AOD(sAOD) forecasts suggests overall underpredictions in both the magnitude andsmoke plume area for nearly all models, although the high-resolution modelshave a better representation of the fine-scale structures of smoke plumes.The models driven by fire radiativepower (FRP)-based fire emissions or assimilating satellite AODdata generally outperform the others. Additionally, limitations of thepersistence assumption used when predicting smoke emissions are revealed bysubstantial underpredictions of sAOD on 8 August 2019, mainly over thetransported smoke plumes, owing to the underestimated emissions on7 August. In contrast, the surface smoke PM2.5 (sPM2.5) forecastsshow both positive and negative overall biases for these models, with mostmembers presenting more considerable diurnal variations of sPM2.5.Overpredictions of sPM2.5 are found for the models driven by FRP-basedemissions during nighttime, suggesting the necessity to improve verticalemission allocation within and above the planetary boundary layer (PBL).Smoke injection heights are further evaluated using the NASA LangleyResearch Center's Differential Absorption High Spectral Resolution Lidar(DIAL-HSRL) data collected during the flight observations. As the firebecame stronger over 3–8 August, the plume height became deeper, with aday-to-day range of about 2–9 km a.g.l. However, narrower ranges arefound for all models, with a tendency of overpredicting the plume heights forthe shallower injection transects and underpredicting for the days showingdeeper injections. The misrepresented plume injection heights lead toinaccurate vertical plume allocations along the transects corresponding totransported smoke that is 1 d old. Discrepancies in model performance forsurface PM2.5 and AOD are further suggested by the evaluation of theirratio, which cannot be compensated for by solely adjusting the smoke emissionsbut are more attributable to model representations of plume injections,besides other possible factors including the evolution of PBL depths andaerosol optical property assumptions. By consolidating multiple forecastsystems, these results provide strategic insight on pathways to improvesmoke forecasts. 

Abstract Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the “firehose” of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways towards mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.