Climate-driven changes in the fire regime within boreal forest ecosystems are likely to have important effects on carbon cycling and species composition. In the context of improving fire management options and developing more realistic scenarios of future change, it is important to understand how meteorology regulates different aspects of fire dynamics, including ignition, daily fire spread, and cumulative annual burned area. Here we combined Moderate-Resolution Imaging Spectroradiometer (MODIS) active fires (MCD14ML), MODIS imagery (MOD13A1) and ancillary historic fire perimeter information to produce a data set of daily fire spread maps for Alaska during 2002-2011. This approach provided a spatial and temporally continuous representation of fire progression and a precise identification of ignition and extinction locations and dates for each wildfire. The fire-spread maps were analyzed with daily vapor pressure deficit (VPD) observations from the North American Regional Reanalysis (NARR) and lightning strikes from the Alaska Lightning Detection Network (ALDN). We found a significant relationship between daily VPD and likelihood that a lightning strike would develop into a fire ignition. In the first week after ignition, above average VPD increased the probability that fires would grow to large or very large sizes. Strong relationships also were identified between VPD and burned area at several levels of temporal and spatial aggregation. As a consequence of regional coherence in meteorology, ignition, daily fire spread, and fire extinction events were often synchronized across different fires in interior Alaska. At a regional scale, the sum of positive VPD anomalies during the fire season was positively correlated with annual burned area during the NARR era (1979-2011; R2 = 0.45). Some of the largest fires we mapped had slow initial growth, indicating opportunities may exist for suppression efforts to adaptively manage these forests for climate change. The results of our spatiotemporal analysis provide new information about temporal and spatial dynamics of wildfires and have implications for modeling the terrestrial carbon cycle. © Author(s) 2014.

Floods and droughts frequently affect the Amazon River basin, impacting transportation, agriculture, and ecosystem processes within several South American countries. Here we examine how sea surface temperature (SST) anomalies influence interannual variability of terrestrial water storage anomalies (TWSAs) in different regions within the Amazon Basin and propose a statistical modeling framework for TWSA prediction on seasonal timescales. Three simple semi-empirical models forced by a linear combination of lagged spatial averages of central Pacific and tropical North Atlantic climate indices (Niño 4 and TNAI) were calibrated against a decade-long record of 3°, monthly TWSAs observed by the Gravity Recovery And Climate Experiment (GRACE) satellite mission. Niño 4 was the primary external forcing in the northeastern region of the Amazon Basin, whereas TNAI was dominant in central and western regions. A combined model using the two indices improved the fit significantly (p< 0.05) for at least 64% of the grid cells within the basin, compared to models forced solely with Niño 4 or TNAI. The combined model explained 66% of the observed variance in the northeastern region, 39% in the central and western region, and 43% for the Amazon Basin as a whole, with a 3-month lead time between the climate indices and the predicted TWSAs. Model performance varied seasonally: it was higher than average during the wet season in the northeastern Amazon and during the dry season in the central and western region. The predictive capability of the combined model was degraded with increasing lead times. Degradation rates were lower in the northeastern Amazon (where 49% of the variance was explained using an 8-month lead time versus 69% for a 1-month lead time) compared to the central and western Amazon (where 22% of the variance was explained at 8 months versus 43% at 1 month). These relationships may contribute to an improved understanding of the climate processes regulating the spatial patterns of flood and drought risk in South America.©Author(s) 2014.

Boreal fires burn into carbon-rich organic soils, thereby releasing large quantities of trace gases and aerosols that influence atmospheric composition and climate. To better understand the factors regulating boreal fire emissions, we developed a statistical model of carbon consumption by fire for Alaska with a spatial resolution of 450 m and a temporal resolution of 1 day. We used the model to estimate variability in carbon emissions between 2001 and 2012. Daily burned area was mapped using imagery from the Moderate Resolution Imaging Spectroradiometer combined with perimeters from the Alaska Large Fire Database. Carbon consumption was calibrated using available field measurements from black spruce forests in Alaska. We built two nonlinear multiplicative models to separately predict above- and belowground carbon consumption by fire in response to environmental variables including elevation, day of burning within the fire season, pre-fire tree cover and the differenced normalized burn ratio (dNBR). Higher belowground carbon consumption occurred later in the season and for mid-elevation forests. Topographic slope and aspect did not improve performance of the belowground carbon consumption model. Aboveground and belowground carbon consumption also increased as a function of tree cover and the dNBR, suggesting a causal link between the processes regulating these two components of carbon consumption. Between 2001 and 2012, the median carbon consumption was 2.54 kg C m-2. Burning in land-cover types other than black spruce was considerable and was associated with lower levels of carbon consumption than for pure black spruce stands. Carbon consumption originated primarily from the belowground fraction (median Combining double low line 2.32 kg C m-2 for all cover types and 2.67 kg C m-2 for pure black spruce stands). Total carbon emissions varied considerably from year to year, with the highest emissions occurring during 2004 (69 Tg C), 2005 (46 Tg C), 2009 (26 Tg C), and 2002 (17 Tg C) and a mean of 15 Tg C year-1 between 2001 and 2012. Mean uncertainty of carbon consumption for the domain, expressed as 1 standard deviation (SD), was 0.50 kg C m-2. Uncertainties in the multiplicative regression model used to estimate belowground consumption in black spruce stands and the land-cover classification were primary contributors to uncertainty estimates. Our analysis highlights the importance of accounting for the spatial heterogeneity of fuels and combustion when extrapolating emissions in space and time, and the need for of additional field campaigns to increase the density of observations as a function of tree cover and other environmental variables influencing consumption. The daily emissions time series from the Alaskan Fire Emissions Database (AKFED) presented here creates new opportunities to study environmental controls on daily fire dynamics, optimize boreal fire emissions in biogeochemical models, and quantify potential feedbacks from changing fire regimes.

We describe a climate mode synchronizing forest carbon losses from North and South America by analyzing time series of tropical North Atlantic sea surface temperatures (SSTs), landfall hurricanes and tropical storms, and Amazon fires during 1995-2013. Years with anomalously high tropical North Atlantic SSTs during March-June were often followed by a more active hurricane season and a larger number of satellite-detected fires in the southern Amazon during June-November. The relationship between North Atlantic tropical cyclones and southern Amazon fires (r = 0.61, p < 0.003) was stronger than links between SSTs and either cyclones or fires alone, suggesting that fires and tropical cyclones were directly coupled to the same underlying atmospheric dynamics governing tropical moisture redistribution. These relationships help explain why seasonal outlook forecasts for hurricanes and Amazon fires both failed in 2013 and may enable the design of improved early warning systems for drought and fire in Amazon forests.

Warming during late winter and spring in recent decades has been credited with increasing high northern latitude CO2 uptake, but it is unclear how different species and plant functional types contribute to this response. To address this, we measured net ecosystem exchange (NEE) at a deciduous broadleaf (aspen and willow) forest and an evergreen conifer (black spruce) forest in interior Alaska over a 3-year period. We partitioned NEE into gross primary production (GPP) and ecosystem respiration (Re) components, assessing the impact of interannual climate variability on these fluxes during spring and summer. We found that interannual variability in both spring and summer NEE was greatest at the deciduous forest. Increases in spring air temperatures between 2002 and 2004 caused GPP to increase during the early part of the growing season (April, May, and June), with a 74% increase at the deciduous forest and a 16% increase at the evergreen forest. Re increased in parallel, by 61% and 15%, respectively. In contrast, a summer drought during 2004 caused GPP during August to decrease by 12% at the deciduous forest and by 9% at the evergreen forest. Concurrent increases in Re, by 21% and 2% for the two forests, further contributed to a reduction in net carbon uptake during the drought. Over the growing season (April-September) net carbon uptake increased by 40% at the deciduous forest and 3% at the evergreen forest in 2004 as compared with 2002. These results suggest that deciduous forests may contribute disproportionately to variability in atmospheric CO2 concentrations within the northern hemisphere and that the carbon balance of deciduous forests may have a greater sensitivity to future changes in climate. © 2007 Elsevier B.V. All rights reserved.

Valley fever is endemic to the southwestern United States. Humans contract this fungal disease by inhaling spores of Coccidioides spp. Changes in the environment can influence the abundance and dispersal of Coccidioides spp., causing fluctuations in valley fever incidence. We combined county-level case records from state health agencies to create a regional valley fever database for the southwestern United States, including Arizona, California, Nevada, New Mexico, and Utah. We used this data set to explore how environmental factors influenced the spatial pattern and temporal dynamics of valley fever incidence during 2000-2015. We compiled climate and environmental geospatial data sets from multiple sources to compare with valley fever incidence. These variables included air temperature, precipitation, soil moisture, surface dust concentration, normalized difference vegetation index, and cropland area. We found that valley fever incidence was greater in areas with warmer air temperatures and drier soils. The mean annual cycle of incidence varied throughout the southwestern United States and peaked following periods of low precipitation and soil moisture. From year-to-year, however, autumn incidence was higher following cooler, wetter, and productive springs in the San Joaquin Valley of California. In southcentral Arizona, incidence increased significantly through time. By 2015, incidence in this region was more than double the rate in the San Joaquin Valley. Our analysis provides a framework for interpreting the influence of climate change on valley fever incidence dynamics. Our results may allow the U.S. Centers for Disease Control and Prevention to improve their estimates of the spatial pattern and intensity of valley fever endemicity.

An improved understanding of the mechanisms that regulate wildfire risk at local to regional scales is needed for the design of effective fire and ecosystem management. We investigated the spatial distribution of burned area in Southern California during 1960-2009 using five different data-driven methods: multiple linear regression, generalized additive models (GAMs), GAMs with spatial autocorrelation, non-linear multiplicative models, and random forest models. We used each method to separately develop burned area risk maps for Southern California's two distinct wildfire regimes: Santa Ana (SA fires), which occur during high wind events mostly in autumn, and non-Santa Ana fires (non-SA fires), which occur mostly during the hot and dry Mediterranean-climate summer. The different methods explained 38-63% of the spatial variance in burned area for SA fires and 21-48% for non-SA fires. The two fire regimes had contrasting drivers, with Fosberg fire weather index, relative humidity, minimum temperature, and distance to housing most important for SA fires, and shrub cover, road density, and distance to minor and major roads most important for non-SA fires. Our modeling framework carries implications for the strategic placement of fire suppression resources, and for prevention planning in areas facing increasing human and climate pressures.

Land clearing for crops, plantations and grazing results in anthropogenic burning of tropical forests and peatlands in Indonesia, where images of fire-generated aerosol plumes have been captured by the Multi-angle Imaging SpectroRadiometer (MISR) since 2001. Here we analyze the size, shape, optical properties, and age of distinct fire-generated plumes in Borneo from 2001-2009. The local MISR overpass at 10:30 a.m. misses the afternoon peak of Borneo fire emissions, and may preferentially sample longer plumes from persistent fires burning overnight. Typically the smoke flows with the prevailing southeasterly surface winds at 3-4 m s-1, and forms ovoid plumes whose mean length, height, and cross-plume width are 41 km, 708 m, and 27% of the plume length, respectively. 50% of these plumes have length between 24 and 50 km, height between 523 and 993 m and width between 18% and 30% of plume length. Length and cross-plume width are lognormally distributed, while height follows a normal distribution. Borneo smoke plume heights are similar to previously reported plume heights, yet Borneo plumes are on average nearly three times longer than previously studied plumes. This could be due to sampling or to more persistent fires and greater fuel loads in peatlands than in other tropical forests. Plume area (median 169 km2, with 25th and 75th percentiles at 99 km 2 and 304 km2, respectively) varies exponentially with length, though for most plumes a linear relation provides a good approximation. The MISR-estimated plume optical properties involve greater uncertainties than the geometric properties, and show patterns consistent with smoke aging. Optical depth increases by 15-25% in the down-plume direction, consistent with hygroscopic growth and nucleation overwhelming the effects of particle dispersion. Both particle single-scattering albedo and top-of-atmosphere reflectance peak about halfway down-plume, at values about 3% and 10% greater than at the origin, respectively. The initially oblong plumes become brighter and more circular with time, increasingly resembling smoke clouds. Wind speed does not explain a significant fraction of the variation in plume geometry. We provide a parameterization of plume shape that can help atmospheric models estimate the effects of plumes on weather, climate, and air quality. Plume age, the age of smoke furthest down-plume, is lognormally distributed with a median of 2.8 h (25th and 75th percentiles at 1.3 h and 4.0 h), different from the median ages reported in other studies. Intercomparison of our results with previous studies shows that the shape, height, optical depth, and lifetime characteristics reported for tropical biomass burning plumes on three continents are dissimilar and distinct from the same characteristics of non-tropical wildfire plumes. © Author(s) 2012.

Widespread tree mortality events occur during periods of severe drought in temperate conifer forests and are expected to become more frequent in many areas due to climate change. Improved mapping of individual tree mortality is needed to identify risk factors and design effective conservation strategies. In this study, we used National Ecological Observatory Network (NEON) lidar and multispectral reflectance airborne observations to map individual tree mortality over a 160 km2 area during and after the 2012–2016 drought for two sites in California's Sierra National Forest. We used NEON lidar to derive tree locations and crown perimeters and multispectral data to map tree mortality for more than 1 million trees. We found that 25.4% of the trees in our study area died between 2013 and 2017, with considerably higher mortality at the lower-elevation Soaproot Saddle site. Between 2017 and 2019, an additional 2.0%–2.8% of the trees died each year. Two wildfires in 2020 and 2021 increased tree mortality within burned area perimeters by 49%–89% between 2019 and 2021. Consistent with previous work, we found that tree mortality risk increased as a function of tree height. Tree mortality was positively associated with distance from rivers, trees per hectare, and decreasing slope at the lower elevation site. In contrast, increasing slope was positively associated with tree mortality at the higher elevation site. Our approach and dataset provide a means to study the combined effects of drought and wildfire on tree mortality and may improve projections of forest resilience under a changing climate.

Aerosol source apportionment remains a critical challenge for understanding the transport and aging of aerosols, as well as for developing successful air pollution mitigation strategies. The contributions of fossil and non-fossil sources to organic carbon (OC) and elemental carbon (EC) in carbonaceous aerosols can be quantified by measuring the radiocarbon (14C) content of each carbon fraction. However, the use of 14C in studying OC and EC has been limited by technical challenges related to the physical separation of the two fractions and small sample sizes. There is no common procedure for OC/EC 14C analysis, and uncertainty studies have largely focused on the precision of yields. Here, we quantified the uncertainty in 14C measurement of aerosols associated with the isolation and analysis of each carbon fraction with the Swiss-4S thermal-optical analysis (TOA) protocol. We used an OC/EC analyzer (Sunset Laboratory Inc., OR, USA) coupled to a vacuum line to separate the two components. Each fraction was thermally desorbed and converted to carbon dioxide (CO2) in pure oxygen (O2). On average, 91 % of the evolving CO2 was then cryogenically trapped on the vacuum line, reduced to filamentous graphite, and measured for its 14C content via accelerator mass spectrometry (AMS). To test the accuracy of our setup, we quantified the total amount of extraneous carbon introduced during the TOA sample processing and graphitization as the sum of modern and fossil (14C-depleted) carbon introduced during the analysis of fossil reference materials (adipic acid for OC and coal for EC) and contemporary standards (oxalic acid for OC and rice char for EC) as a function of sample size. We further tested our methodology by analyzing five ambient airborne particulate matter (PM2.5) samples with a range of OC and EC concentrations and 14C contents in an interlaboratory comparison. The total modern and fossil carbon blanks of our setup were 0.8 ± 0.4 and 0.67 ± 0.34 μg C, respectively, based on multiple measurements of ultra-small samples. The extraction procedure (Swiss-4S protocol and cryo-trapping only) contributed 0.37 ± 0.18 μg of modern carbon and 0.13 ± 0.07 μg of fossil carbon to the total blank of our system, with consistent estimates obtained for the two laboratories. There was no difference in the background correction between the OC and EC fractions. Our setup allowed us to efficiently isolate and trap each carbon fraction with the Swiss-4S protocol and to perform 14C analysis of ultra-small OC and EC samples with high accuracy and low 14C blanks.