List of Publications

Systematically tracking the hourly progression of large wildfires using GOES satellite observations

Earth System Science Data | 2024 | IF 11.333

Liu, T., J. T. Randerson, Y. Chen, D. C. Morton, E. B. Wiggins, P. Smyth, E. Foufoula-Georgiou, R. Nadler, O. Nevo

In the western United States, prolonged drought, warming climate, and historical fuel build-up have contributed to larger and more intense wildfires, as well as longer fire seasons. As these costly wildfires become more common, new tools and methods are essential for improving our understanding of the evolution of fires and how extreme weather conditions, including heatwaves, windstorms, droughts, and varying levels of active fire suppression, influence fire spread. Here we develop the GOES-Observed Fire Event Representation (GOFER) algorithm to derive the hourly fire progression of large wildfires and create a dataset of hourly fire perimeters, active fire lines, and fire spread rates. Using GOES-East and GOES-West geostationary satellite detections of active fires, we test the GOFER algorithm on 28 large wildfires in California from 2019–2021. The GOFER algorithm includes parameter optimizations for defining the burned-to-unburned boundary and correcting for the parallax effect from elevated terrain. We evaluate GOFER perimeters with using 12-hourly data from the VIIRS-derived Fire Event Data Suite (FEDS) and final fire perimeters from California’s Fire and Resource Assessment Program (FRAP). Although the GOES imagery used to derive GOFER has coarser resolution (2 km at the equator), the final fire perimeters from GOFER correspond reasonably well with those obtained from FRAP, with a mean Intersection-over-Union (IoU) of 0.77, in comparison to 0.83 between FEDS and FRAP. GOFER fills a key temporal gap present in other fire tracking products that rely on low-earth-orbit imagery, where perimeters are available at 12-hour intervals or longer, or at ad hoc intervals from aircraft overflights. This is particularly relevant when a fire spreads rapidly, such as at maximum hourly spread rates of over 5 km/h. Our GOFER algorithm for deriving the hourly fire progression using GOES can be applied to large wildfires across North and South America and reveals considerable variability in rates of fire spread on diurnal time scales. The resulting GOFER dataset has a broad set of applications, including the development of predictive models for fire spread and improvement of atmospheric transport models for surface smoke estimates.

GloCAB: global cropland burned area from mid-2002 to 2020

Earth System Science Data | 2024 | IF 11.333

Hall, J. V., F. Argueta, M. Zubkova, Y. Chen, J. T. Randerson, L. Giglio

Burned area estimates are an essential component of cropland management systems, inventory-based fire emission calculations, and air quality models, and any inaccuracies in these estimates propagate into the final outputs and decision-making process. While satellite-based global burned area and fire emission datasets (e.g., GFED, FireCCI51, and MCD64A1) are frequently cited in the scientific literature and are employed by a range of users from atmospheric and carbon modelers to policy-makers, they are generally not optimized for cropland burning – a quintessential small-fire type. Here we describe a new dataset (GloCAB; global cropland area burned) which represents the first attempt at a global cropland-focused burned area product. The GloCAB dataset provides global, monthly cropland burned area at 0.25∘ spatial resolution from July 2002 to December 2020. Crop-specific burned area conversion factors for several widespread burnable crops (winter wheat, spring wheat, maize, rice, and sugarcane) were calculated from extensively mapped cropland reference regions spanning 191 560 fields over 5 different countries. We found global annual cropland burned area (2003–2020) ranged between 64 Mha (2018) and 102 Mha (2008) with an average of 81 Mha using our lower-bound estimates, which are substantially higher than the annual average of 32 Mha in the MCD64A1 C6 product. Region-specific trend analysis found some areas with significant increasing trends (northwest India), while the heterogeneity of many other regions showed no burned area trends.

Multi-decadal trends and variability in burned area from the fifth version of the Global Fire Emissions Database (GFED5)

Earth System Science Data | 2023 | IF 11.333

Chen, Y., J. Hall, D. Van Wees, N. Andela, S. Hantson, L. Giglio, G. R. Van Der Werf, D. C. Morton, J. T. Randerson

Long-term records of burned area are needed to understand wildfire dynamics, assess fire impacts on ecosystems and air quality, and improve fire forecasts. Here, we fuse multiple streams of remote sensing data to create a 24 year (1997–2020) dataset of monthly burned area as a component of the fifth version of the Global Fire Emissions Database (GFED5). During 2001–2020, we use the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD64A1 burned area product and adjust for the errors of commission and omission. Adjustment factors are estimated based on region, land cover, and tree cover fraction, using spatiotemporally aligned burned area from Landsat or Sentinel-2. Burned area in croplands, peatlands, and deforestation regions is estimated from MODIS active fire detections. Along-Track Scanning Radiometer (ATSR) and Visible and Infrared Scanner (VIRS) active fire data are used to extend the time series back to 1997. The global annual burned area during 2001–2020 is estimated to be 774 ± 63 Mha yr−1 or 5.9 ± 0.5 % of ice-free land. Burned area declined by 1.21 ± 0.66 % yr−1, a cumulative decrease of 24.2 ± 13.2 % over 20 years. The global reduction is primarily driven by a decrease in fires in savannas, grasslands, and croplands. Forest, peat, and deforestation fires did not exhibit significant long-term trends. The GFED5 global burned area is 93 % higher than MCD64A1, 61 % higher than GFED4s, and in closer agreement with products from higher-resolution satellite sensors. These data may reduce discrepancies between fire emission estimates from activity-based and atmospheric-based approaches, and improve our understanding of global fire impacts on the carbon cycle and climate system.

Evidence for multi-decadal fuel buildup in a large California wildfire from smoke radiocarbon measurements

Environmental Research Letters | 2023 | IF 6.947

Odwuor, A., Yañez, C. C., Chen, Y., Hopkins, F. M., Moreno, A., Xu, X., Czimczik, C. I., and Randerson, J. T.

In recent decades, there has been a significant increase in annual area burned in California's Sierra Nevada mountains. This rise in fire activity has prompted the need to understand how historical forest management practices affect fuel composition and emissions. Here we examined the total carbon (TC) concentration and radiocarbon abundance (Δ14C) of particulate matter (PM) emitted by the KNP Complex Fire, which occurred during California's 2021 wildfire season and affected several groves of giant sequoia trees in the southern Sierra Nevada. During a 26 h sampling period, we measured concentrations of fine airborne PM (PM2.5), as well as dry air mole fractions of carbon monoxide (CO) and methane (CH4), using a ground-based mobile laboratory. We also collected filter samples of PM2.5 for analysis of TC concentration and Δ14C. High correlation among PM2.5, CO, and CH4 time series confirmed that our PM2.5 measurements captured variability in wildfire emissions. Using a Keeling plot approach, we determined that the mean Δ14C of PM2.5 was 111.6 ± 7.7‰ (n = 12), which was considerably enriched relative to atmospheric carbon dioxide in the northern hemisphere in 2021 (−3.2 ± 1.4‰). Combining these Δ14C data with a steady-state one-box ecosystem model, we estimated that the mean age of fuels combusted in the KNP Complex Fire was 40 years, with a range of 29–57 years. These results provide evidence for emissions originating from woody biomass, larger-diameter fine fuels, and coarse woody debris that have accumulated over multiple decades. This is consistent with independent field observations that indicate high fire intensity contributed to widespread giant sequoia mortality. With the expanded use of prescribed fires planned over the next decade in California to mitigate wildfire impacts, our measurement approach has the potential to provide regionally-integrated estimates of the effectiveness of fuel treatment programs.

Attention-Based Wildland Fire Spread Modeling Using Fire-Tracking Satellite Observations

Fire | 2023 | IF 3.2

Zou, Y., Sadgedhi, M., Liu, Y., Puchko, A., Le, S., Chen, Y., Andela, N., Gentine. P.

Modeling the spread of wildland fires is essential for assessing and managing fire risks. However, this task remains challenging due to the partially stochastic nature of fire behavior and the limited availability of observational data with high spatial and temporal resolutions. Herein, we propose an attention-based deep learning modeling approach that can be used to learn the complex behaviors of wildfires across different fire-prone regions. We integrate optimized spatial and channel attention modules with a convolutional neural network (CNN) modeling architecture and train the attention-based fire spread models using a recently derived fire-tracking satellite observational dataset in conjunction with corresponding fuel, terrain, and weather conditions. The evaluation results and their comparison with benchmark models, such as a deeper and more complex autoencoder model and the semi-empirical FARSITE fire behavior model, demonstrate the effectiveness of the attention-based models. These new data-driven fire spread models exhibit promising modeling performances in both the next-step prediction (i.e., predicting fire progression from one timestep earlier) and recursive prediction (i.e., recursively predicting final fire perimeters from initial ignition points) of observed large wildfires in California, and they provide a foundation for further practical applications including short-term active fire spread prediction and long-term fire risk assessment.

A simplified machine learning based wildfire ignition model from insurance perspective

ICLR | 2023

Liu, Y., Le, S., Zou, Y., Sadgedhi, M., Chen, Y., Andela, N., Gentine. P.

In the context of climate change, wildfires are becoming more frequent, intense, and prolonged in the western US, particularly in California. Wildfires cause catastrophic socio-economic losses and are projected to worsen in the near future. Inaccurate estimates of fire risk put further pressure on wildfire (re)insurance and cause many homes to lose wildfire insurance coverage. Efficient and effective prediction of fire ignition is one step towards better fire risk assessment. Here we present a simplified machine learning-based fire ignition model at yearly scale that is well suited to the use case of one-year term wildfire (re)insurance. Our model yields a recall, precision, and the area under the precision-recall curve of 0.69, 0.86 and 0.81, respectively, for California, and significantly higher values of 0.82, 0.90 and 0.90, respectively, for the populated area, indicating its good performance. In addition, our model feature analysis reveals that power line density, enhanced vegetation index (EVI), vegetation optical depth (VOD), and distance to the wildland-urban interface stand out as the most important features determining ignitions. The framework of this simplified ignition model could easily be applied to other regions or genesis of other perils like hurricane, and it paves the road to a broader and more affordable safety net for homeowners.

Record-high CO₂ emissions from boreal fires in 2021

Science | 2023 | IF 63.714

Zheng, B., Ciais, P., Chevallier, F., Yang, H., Canadell, J. G., Chen, Y., et al.

Extreme wildfires are becoming more common and increasingly affecting Earth’s climate. Wildfires in boreal forests have attracted much less attention than those in tropical forests, although boreal forests are one of the most extensive biomes on Earth and are experiencing the fastest warming. We used a satellite-based atmospheric inversion system to monitor fire emissions in boreal forests. Wildfires are rapidly expanding into boreal forests with emerging warmer and drier fire seasons. Boreal fires, typically accounting for 10% of global fire carbon dioxide emissions, contributed 23% (0.48 billion metric tons of carbon) in 2021, by far the highest fraction since 2000. 2021 was an abnormal year because North American and Eurasian boreal forests synchronously experienced their greatest water deficit. Increasing numbers of extreme boreal fires and stronger climate–fire feedbacks challenge climate mitigation efforts. Carbon dioxide emissions from boreal forest fires have been increasing since at least the year 2000, reaching a new high in 2021, Zheng et al. report. Although boreal fires typically produce about 10% of global carbon dioxide emissions from wildfires, in 2021 they produced nearly one quarter of the total. This abnormally high total resulted from the concurrence of water deficits in North America and Eurasia, which was an unusual situation. The increasing number of extreme wildfires that is accompanying global warming presents a real challenge to global climate change mitigation efforts. —HJS Boreal fires in 2021 contributed their largest fraction of global fire carbon dioxide emissions since 2000.

Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED)

Geosci. Model Dev. | 2022 | IF 6.565

van Wees, D., G. R. van der Werf, J. T. Randerson, B. M. Rogers, Y. Chen, S. Veraverbeke, L. Giglio, and D. C. Morton

In fire emission models, the spatial resolution of both the modelling framework and the satellite data used to quantify burned area can have considerable impact on emission estimates. Consideration of this sensitivity is especially important in areas with heterogeneous land cover and fire regimes and when constraining model output with field measurements. We developed a global fire emissions model with a spatial resolution of 500 m using MODerate resolution Imaging Spectroradiometer (MODIS) data. To accommodate this spatial resolution, our model is based on a simplified version of the Global Fire Emissions Database (GFED) modelling framework. Tree mortality as a result of fire, i.e. fire-related forest loss, was modelled based on the overlap between 30 m forest loss data and MODIS burned area and active fire detections. Using this new 500 m model, we calculated global average carbon emissions from fire of 2.1±0.2 (±1σ interannual variability, IAV) Pg C yr−1 during 2002–2020. Fire-related forest loss accounted for 2.6±0.7 % (uncertainty range =1.9 %–3.3 %) of global burned area and 24±6 % (uncertainty range =16 %–31 %) of emissions, indicating that fuel consumption in forest fires is an order of magnitude higher than the global average. Emissions from the combustion of soil organic carbon (SOC) in the boreal region and tropical peatlands accounted for 13±4 % of global emissions. Our global fire emissions estimate was higher than the 1.5 Pg C yr−1 from GFED4 and similar to 2.1 Pg C yr−1 from GFED4s. Even though GFED4s included more burned area by accounting for small fires undetected by the MODIS burned area mapping algorithm, our emissions were similar to GFED4s due to higher average fuel consumption. The global difference in fuel consumption could mainly be explained by higher SOC emissions from the boreal region as constrained by additional measurements. The higher resolution of the 500 m model also contributed to the difference by improving the simulation of landscape heterogeneity and reducing the scale mismatch in comparing field measurements to model grid cell averages during model calibration. Furthermore, the fire-related forest loss algorithm introduced in our model led to more accurate and widespread estimation of high-fuel-consumption burned area. Recent advances in burned area detection at resolutions of 30 m and finer show a substantial amount of burned area that remains undetected with 500 m sensors, suggesting that global carbon emissions from fire are likely higher than our 500 m estimates. The ability to model fire emissions at 500 m resolution provides a framework for further improvements with the development of new satellite-based estimates of fuels, burned area, and fire behaviour, for use in the next generation of GFED.

Tracking and classifying Amazon fire events in near real time

Science Advances | 2022 | IF 13.117

Niels, A.,D.C. Morton, W. Schroeder, Y. Chen, P.M. Brando, J.T. Randerson

Exceptional fire activity in 2019 sparked concern about Amazon forest conservation. However, the inability to rapidly separate satellite fire detections by fire type hampered fire suppression and assessment of ecosystem and air quality impacts. Here, we describe the development of a near–real-time approach for tracking contributions from deforestation, forest, agricultural, and savanna fires to burned area and emissions and apply the approach to the 2019 fire season in South America. Across the southern Amazon, 19,700 deforestation fire events accounted for 39% of all satellite active fire detections and the majority of fire carbon emissions (63%; 69 Tg C). Multiday fires accounted for 81% of burned area and 92% of carbon emissions from the Amazon, with many forest fires burning uncontrolled for weeks. Most fire detections from deforestation fires were correctly identified within 2 days (67%), highlighting the potential to improve situational awareness and management outcomes during fire emergencies.

California wildfire spread derived using VIIRS satellite observations and an object-based tracking system

Scientific Data | 2022 | IF 6.444

Chen, Y, S. Hantson, N. Andela, S. R. Coffield, C. A. Graff, D. C. Morton, L. E. Ott, E. Foufoula-Georgiou, P. Smyth, M. L. Goulden, J. T. Randerson

Changing wildfire regimes in the western US and other fire-prone regions pose considerable risks to human health and ecosystem function. However, our understanding of wildfire behavior is still limited by a lack of data products that systematically quantify fire spread, behavior and impacts. Here we develop a novel object-based system for tracking the progression of individual fires using 375 m Visible Infrared Imaging Radiometer Suite active fire detections. At each half-daily time step, fire pixels are clustered according to their spatial proximity, and are either appended to an existing active fire object or are assigned to a new object. This automatic system allows us to update the attributes of each fire event, delineate the fire perimeter, and identify the active fire front shortly after satellite data acquisition. Using this system, we mapped the history of California fires during 2012–2020. Our approach and data stream may be useful for calibration and evaluation of fire spread models, estimation of near-real-time wildfire emissions, and as means for prescribing initial conditions in fire forecast models.

Future increases in lightning ignition efficiency and wildfire occurrence expected from drier fuels in boreal forest ecosystems of western North America

Environmental Research Letters | 2022 | IF 6.793

Hessilt, T. D., Abatzoglou, J. T., Chen, Y., Randerson, J. T., Scholten, R. C., van der Werf, G., & Veraverbeke, S.

Lightning-induced fire is the primary disturbance agent in boreal forests. Recent large fire years have been linked to anomalously high numbers of lightning-caused fire starts, yet the mechanisms regulating the probability of lightning ignition remain uncertain and limit our ability to project future changes. Here, we investigated the influence of lightning properties, landscape characteristics, and fire weather on lightning ignition efficiency – the likelihood that a lightning strike starts a fire - in Alaska, United States of America, and Northwest Territories, Canada, between 2001 and 2018. We found that short-term fuel drying associated with fire weather was the main driver of lightning ignition efficiency. Lightning was also more likely to ignite a wildfire in denser, evergreen forest areas. Under a high greenhouse gas emissions scenario, we predicted that changes in vegetation and fire weather increase lightning ignition efficiency by 14 ± 9 % in Alaska and 31 ± 28 % in the Northwest Territories per 1 ℃ warming by end-of-century. The increases in lightning ignition efficiency, together with a projected doubling of lightning strikes, result in a 39 to 65 % increase in lightning-caused fire occurrence per 1 ℃ warming. This implies that years with many fires will occur more frequently in the future, thereby accelerating carbon losses from boreal forest ecosystems.

Increasing forest fire emissions despite the decline in global burned area

Science Advances | 2021 | IF 13.117

Zheng,B., P. Ciais, F. Chevallier, E. Chuvieco, Y. Chen, and H. Yang

Satellites have detected a global decline in burned area of grassland, coincident with a small increase in burned forest area. These contrasting trends have been reported in earlier literature; however, less is known of their impacts on global fire emission trends due to the scarcity of direct observations. We use an atmospheric inversion system to show that global fire emissions have been stable or slightly decreasing despite the substantial decline in global burned area over the past two decades caused by the carbon dioxide emission increase from forest fires offsetting the decreasing emissions from grass and shrubland fires. Forest fires are larger carbon dioxide sources per unit area burned than grassland fires, with a slow or incomplete follow-up recovery—sometimes no recovery due to degradation and deforestation. With fires expanding over forest areas, the slow recovery of carbon dioxide uptake over burned forest lands weakens land sink capacity, implying positive feedback on climate change.

The influence of fire aerosols on surface climate and gross primary production in the Energy Exascale Earth System Model (E3SM)

Journal of Climate | 2021 | IF 5.148

Xu, L., Q. Zhu, W. J. Riley, Y. Chen, H. Wang, P.-L. Ma, and J. T. Randerson

Fire-emitted aerosols play an important role in influencing Earth’s climate, directly by scattering and absorbing radiation and indirectly by influencing cloud microphysics. The quantification of fire-aerosol interactions, however, remains challenging and subject to uncertainties in emissions, plume parameterizations, and aerosol properties. Here we optimized fire-associated aerosol emissions in the Energy Exascale Earth System Model (E3SM) using the Global Fire Emissions Database (GFED) and AERONET aerosol optical depth (AOD) observations during 1997-2016. We distributed fire emissions vertically using smoke plume heights from Multi-angle Imaging SpectroRadiometer (MISR) satellite observations. From the optimization, we estimate that global fires emit 45.5 Tg y-1 of primary particulate organic matter and 3.9 Tg y-1 of black carbon. We then performed two climate simulations with and without the optimized fire emissions. We find that fire aerosols significantly increase global AOD by 14 ± 7% and contribute to a reduction in net shortwave radiation at the surface (-2.3 ± 0.5 W m-2). Together, fire-induced direct and indirect aerosol effects cause annual mean global land surface air temperature to decrease by 0.17 ± 0.15°C, relative humidity to increase by 0.4 ± 0.3%, and diffuse light fraction to increase by 0.5 ± 0.3%. In response, GPP declines by 2.8 Pg C y-1, as a result of large positive drivers (decreases in temperature and increases in humidity and diffuse light) nearly cancelling out large negative drivers (decreases shortwave radiation and soil moisture). Our analysis highlights the importance of fire aerosols in modifying surface climate and photosynthesis across the tropics.

Climate influence on the 2019 fires in Amazonia

Science of the Total Environment | 2021 | IF 7.963

Dong, X., F. Li, Z. Lin, S. P. Harrison, Y. Chen, J.-S. Kugg

Amazonia experienced unusually devastating fires in August 2019, leading to huge regional and global environmental and economic losses. The increase in fires has been largely attributed to anthropogenic deforestation, but anomalous climate conditions could also have contributed. This study investigates the climate influence on Amazonia fires in August 2019 and underlying mechanisms, based on statistical correlation and multiple linear regression analyses of 2001–2019 satellite-based fire products and multiple observational or reanalyzed climate datasets. Positive fire anomalies in August 2019 were mainly located in southern Amazonia. These anomalies were mainly driven by low precipitation and relative humidity, which increased fuel dryness and contributed to 38.9 ± 9.5% of the 2019 anomaly in pyrogenic carbon emissions over the southern Amazonia. The dry conditions were associated with southerly wind anomalies over southern Amazonia that suppressed the climatological southward transport of water vapor originating from the Atlantic. The southerly wind anomalies were caused by the combination of a Gill-type cyclonic response to the warmer North Atlantic sea surface temperature (SST), and enhancement of the Walker and Hadley circulations over South America due to the colder SST in the eastern Pacific, and a mid-latitude wave train triggered by the warmer condition in the western Indian Ocean. Our study highlights, for the first time, the important role of Indian Ocean SST for fires in Amazonia. It also reveals how cold SST anomalies in the tropical eastern Pacific link the warm phase of the El Niño-Southern Oscillation (ENSO) in the preceding December–January to the dry-season fires in Amazonia. Our findings can develop theoretical basis of global tropical SST-based fire prediction, and have potential to improve prediction skill of extreme fires in Amazonia and thus to take steps to mitigate their impacts which is urgency given that dry conditions led to the extreme fires are becoming common in Amazonia.

Future increases in Arctic lightning and fire risk for permafrost carbon

Nature Climate Change | 2021 | IF 25.290

Chen, Y., D. M. Romps, J. T. Seeley, S. Veraverbeke, W. J. Riley, Z. A. Mekonnen and J. T. Randerson

Lightning is an indicator and a driver of climate change. Here, using satellite observations of lightning flash rate and ERA5 reanalysis, we find that the spatial pattern of summer lightning over northern circumpolar regions exhibits a strong positive relationship with the product of convective available potential energy (CAPE) and precipitation. Applying this relationship to Climate Model Intercomparison Project Phase 5 climate projections for a high-emissions scenario (RCP8.5) shows an increase in CAPE (86 ± 22%) and precipitation (17 ± 2%) in areas underlain by permafrost, causing summer lightning to increase by 112 ± 38% by the end of the century (2081–2100). Future flash rates at the northern treeline are comparable to current levels 480 km to the south in boreal forests. We hypothesize that lightning increases may induce a fire–vegetation feedback whereby more burning in Arctic tundra expedites the northward migration of boreal trees, with the potential to accelerate the positive feedback associated with permafrost soil carbon release.

The role of fire in global forest loss dynamics

Global Change Biology | 2021 | IF 10.863

van Wees, D., G. R. van der Werf, J. T. Randerson, N. Andela, Y. Chen, D. C. Morton

Fires, among other forms of natural and anthropogenic disturbance, play a central role in regulating the location, composition and biomass of forests. Understanding the role of fire in global forest loss is crucial in constraining land‐use change emissions and the global carbon cycle. We analysed the relationship between forest loss and fire at 500 m resolution based on satellite‐derived data for the 2003–2018 period. Satellite fire data included burned area and active fire detections, to best account for large and small fires, respectively. We found that, on average, 38 ± 9% (± range) of global forest loss was associated with fire, and this fraction remained relatively stable throughout the study period. However, the fraction of fire‐related forest loss varied substantially on a regional basis, and showed statistically significant trends in key tropical forest areas. Decreases in the fraction of fire‐related forest loss were found where deforestation peaked early in our study period, including the Amazon and Indonesia while increases were found for tropical forests in Africa. The inclusion of active fire detections accounted for 41%, on average, of the total fire‐related forest loss, with larger contributions in small clearings in interior tropical forests and human‐dominated landscapes. Comparison to higher‐resolution fire data with resolutions of 375 and 20 m indicated that commission errors due to coarse resolution fire data largely balanced out omission errors due to missed small fire detections for regional to continental‐scale estimates of fire‐related forest loss. Besides an improved understanding of forest dynamics, these findings may help to refine and separate fire‐related and non‐fire‐related land‐use change emissions in forested ecosystems.

Forecasting global fire emissions on sub‐seasonal to seasonal (S2S) timescales

JAMES | 2020 | IF 6.660

Chen, Y., J. T. Randerson, S. R. Coffield, E. Foufoula‐Georgiou, P. Smyth, C. A. Graff, D. C. Morton, N. Andela, G. R. van der Werf, L. Giglio, and L. E. Ott

Fire emissions of gases and aerosols alter atmospheric composition and have substantial impacts on climate, ecosystem function, and human health. Warming climate and human expansion in fire‐prone landscapes exacerbate fire impacts and call for more effective management tools. Here we developed a global fire forecasting system that predicts monthly emissions using past fire data and climate variables for lead times of 1 to 6 months. Using monthly fire emissions from the Global Fire Emissions Database (GFED) as the prediction target, we fit a statistical time series model, the Autoregressive Integrated Moving Average model with eXogenous variables (ARIMAX), in over 1300 different fire regions. Optimized parameters were then used to forecast future emissions. The forecast system took into account information about region‐specific seasonality, long‐term trends, recent fire observations, and climate drivers representing both large‐scale climate variability and local fire weather. We cross‐validated the forecast skill of the system with different combinations of predictors and forecast lead times. The reference model, which combined endogenous and exogenous predictors with a 1 month forecast lead time, explained 52% of the variability in the global fire emissions anomaly, considerably exceeding the performance of a reference model that assumed persistent emissions during the forecast period. The system also successfully resolved detailed spatial patterns of fire emissions anomalies in regions with significant fire activity. This study bridges the gap between the efforts of near‐real time fire forecasts and seasonal fire outlooks, and represents a step toward establishing an operational global fire, smoke, and carbon cycle forecasting system.

Forecasting Daily Wildfire Activity Using Poisson Regression

IEEE TGRS | 2020 | IF 5.600

Graff, C. A., S. R. Coffield, Y. Chen, E. Foufoula-Georgiou, J. T. Randerson, and P. Smyth

Wildfires and their emissions reduce air quality in many regions of the world, contributing to thousands of premature deaths each year. Smoke forecasting systems have the potential to improve health outcomes by providing future estimates of surface aerosol concentrations (and health hazards) over a period of several days. In most operational smoke forecasting systems, fire emissions are assumed to remain constant during the duration of the weather forecast and are initialized using satellite observations. Recent work suggests that it may be possible to improve these models by predicting the temporal evolution of emissions. Here, we develop statistical models to predict fire activity one to five days into the future using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite fire counts and weather data from ERA-interim reanalysis. Our predictive framework consists of two-Poisson regression models that separately represent new ignitions and the dynamics of existing fires on a coarse resolution spatial grid. We use ten years of active fire detections in Alaska to develop the model and use a cross-validation approach to evaluate model performance. Our results show that regression methods are significantly more accurate in predicting daily fire activity than persistence-based models (which suffer from an overestimation of fire counts by not accounting for fire extinction), with vapor pressure deficit being particularly effective as a single weather-based predictor in the regression approach.

Machine learning to predict final fire size at the time of ignition

IJWF | 2019 | IF 3.200

Coffield, S. R., C. A. Graff, Y. Chen, P. Smyth, E. Foufoula-Georgiou, and J. T. Randerson

Fires in boreal forests of Alaska are changing, threatening human health and ecosystems. Given expected increases in fire activity with climate warming, insight into the controls on fire size from the time of ignition is necessary. Such insight may be increasingly useful for fire management, especially in cases where many ignitions occur in a short time period. Here we investigated the controls and predictability of final fire size at the time of ignition. Using decision trees, we show that ignitions can be classified as leading to small, medium or large fires with 50.4 ± 5.2% accuracy. This was accomplished using two variables: vapour pressure deficit and the fraction of spruce cover near the ignition point. The model predicted that 40% of ignitions would lead to large fires, and those ultimately accounted for 75% of the total burned area. Other machine learning classification algorithms, including random forests and multi-layer perceptrons, were tested but did not outperform the simpler decision tree model. Applying the model to areas with intensive human management resulted in overprediction of large fires, as expected. This type of simple classification system could offer insight into optimal resource allocation, helping to maintain a historical fire regime and protect Alaskan ecosystems.

Modeling Study of the Air Quality Impact of Record‐Breaking Southern California Wildfires in December 2017

JGR atmosphere | 2019 | IF 4.261

Shi, H., Z. Jiang, B. Zhao, Z. Li, Y. Chen, Y. Gu, J. H. Jiang, M. Lee, K.‐N. Liou, J. L. Neu, V. H. Payne, H. Su, Y. Wang, M. Witek, and J. Worden

We investigate the air quality impact of record‐breaking wildfires in Southern California during 5–18 December 2017 using the Weather Research and Forecasting model with Chemistry in combination with satellite and surface observations. This wildfire event was driven by dry and strong offshore Santa Ana winds, which played a critical role in fire formation and air pollutant transport. By utilizing fire emissions derived from the high‐resolution (375 × 375 m2) Visible Infrared Imaging Radiometer Suite active fire detections, the simulated magnitude and temporal evolution of fine particulate matter (PM2.5) concentrations agree reasonably well with surface observations (normalized mean bias = 4.0%). Meanwhile, the model could generally capture the spatial pattern of aerosol optical depth from satellite observations. Sensitivity tests reveal that using a high spatial resolution for fire emissions and a reasonable treatment of plume rise (a fair split between emissions injected at surface and those lifted to upper levels) is important for achieving decent PM2.5 simulation results. Biases in PM2.5 simulation are relatively large (about 50%) during the period with the strongest Santa Ana wind, due to a possible underestimation of burning area and uncertainty in wind field variation. The 2017 December fire event increases the 14‐day averaged PM2.5 concentrations by up to 231.2 μg/m3 over the downwind regions, which substantially exceeds the U.S. air quality standards, potentially leading to adverse health impacts. The human exposure to fire‐induced PM2.5 accounts for 14–42% of the annual total PM2.5 exposure in areas impacted by the fire plumes.

The Global Fire Atlas of individual fire size, duration, speed, and direction

Earth System Science Data | 2019 | IF 11.333

Andela, N., D.C.Morton, L. Giglio, R. Paugam, Y. Chen, S. Hantson, G.R. van der Werf, and J. T. Randerson

Natural and human-ignited fires affect all major biomes, altering ecosystem structure, biogeochemical cycles and atmospheric composition. Satellite observations provide global data on spatiotemporal patterns of biomass burning and evidence for the rapid changes in global fire activity in response to land management and climate. Satellite imagery also provides detailed information on the daily or sub-daily position of fires that can be used to understand the dynamics of individual fires. The Global Fire Atlas is a new global dataset that tracks the dynamics of individual fires to determine the timing and location of ignitions, fire size and duration, and daily expansion, fire line length, speed, and direction of spread. Here, we present the underlying methodology and Global Fire Atlas results for 2003–2016 derived from daily moderate-resolution (500 m) Collection 6 MCD64A1 burned-area data. The algorithm identified 13.3 million individual fires over the study period, and estimated fire perimeters were in good agreement with independent data for the continental United States. A small number of large fires dominated sparsely populated arid and boreal ecosystems, while burned area in agricultural and other human-dominated landscapes was driven by high ignition densities that resulted in numerous smaller fires. Long-duration fires in boreal regions and natural landscapes in the humid tropics suggest that fire season length exerts a strong control on fire size and total burned area in these areas. In arid ecosystems with low fuel densities, high fire spread rates resulted in large, short-duration fires that quickly consumed available fuels. Importantly, multiday fires contributed the majority of burned area in all biomass burning regions. A first analysis of the largest, longest and fastest fires that occurred around the world revealed coherent regional patterns of extreme fires driven by large-scale climate forcing. Global Fire Atlas data are publicly available through http://www.globalfiredata.org (last access: 9 August 2018) and https://doi.org/10.3334/ORNLDAAC/1642, and individual fire information and summary data products provide new information for benchmarking fire models within ecosystem and Earth system models, understanding vegetation–fire feedbacks, improving global emissions estimates, and characterizing the changing role of fire in the Earth system.

Soil Moisture Variability Intensifies and Prolongs Eastern Amazon Temperature and Carbon Cycle Response to El Niño–Southern Oscillation

Journal of Climate | 2019 | IF 5.148

Levine, P.A., J.T. Randerson, Y. Chen, M.S. Pritchard, M. Xu, and F.M. Hoffman

El Niño–Southern Oscillation (ENSO) is an important driver of climate and carbon cycle variability in the Amazon. Sea surface temperature (SST) anomalies in the equatorial Pacific drive teleconnections with temperature directly through changes in atmospheric circulation. These circulation changes also impact precipitation and, consequently, soil moisture, enabling additional indirect effects on temperature through land–atmosphere coupling. To separate the direct influence of ENSO SST anomalies from the indirect effects of soil moisture, a mechanism-denial experiment was performed to decouple their variability in the Energy Exascale Earth System Model (E3SM) forced with observed SSTs from 1982 to 2016. Soil moisture variability was found to amplify and extend the effects of SST forcing on eastern Amazon temperature and carbon fluxes in E3SM. During the wet season, the direct, circulation-driven effect of ENSO SST anomalies dominated temperature and carbon cycle variability throughout the Amazon. During the following dry season, after ENSO SST anomalies had dissipated, soil moisture variability became the dominant driver in the east, explaining 67%–82% of the temperature difference between El Niño and La Niña years, and 85%–91% of the difference in carbon fluxes. These results highlight the need to consider the interdependence between temperature and hydrology when attributing the relative contributions of these factors to interannual variability in the terrestrial carbon cycle. Specifically, when offline models are forced with observations or reanalysis, the contribution of temperature may be overestimated when its own variability is modulated by hydrology via land–atmosphere coupling.

Smoke radiocarbon measurements from Indonesian fires provide evidence for burning of millennia-aged peat

PNAS | 2018 | IF 11.205

E. B. Wiggins, C. I. Czimczik, G. M. Santos, Y. Chen, X. Xu, S. R. Holden, J. T. Randerson, C. F. Harvey, F. M. Kai, and L. E. Yu

In response to a strong El Niño, fires in Indonesia during September and October 2015 released a large amount of carbon dioxide and created a massive regional smoke cloud that severely degraded air quality in many urban centers across Southeast Asia. Although several lines of evidence indicate that peat burning was a dominant contributor to emissions in the region, El Niño-induced drought is also known to increase deforestation fires and agricultural waste burning in plantations. As a result, uncertainties remain with respect to partitioning emissions among different ecosystem and fire types. Here we measured the radiocarbon content (14C) of carbonaceous aerosol samples collected in Singapore from September 2014 through October 2015, with the aim of identifying the age and origin of fire-emitted fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm). The Δ14C of fire-emitted aerosol was −76 ± 51‰, corresponding to a carbon pool of combusted organic matter with a mean turnover time of 800 ± 420 y. Our observations indicated that smoke plumes reaching Singapore originated primarily from peat burning (∼85%), and not from deforestation fires or waste burning. Atmospheric transport modeling confirmed that fires in Sumatra and Borneo were dominant contributors to elevated PM2.5 in Singapore during the fire season. The mean age of the carbonaceous aerosol, which predates the Industrial Revolution, highlights the importance of improving peatland fire management during future El Niño events for meeting climate mitigation and air quality commitments.

Future Drying in Central America and Northern South America Linked With Atlantic Meridional Overturning Circulation

Geophysical Research Letters | 2018 | IF 4.720

Chen, Y., Langenbrunner, B., and J. T. Randerson

Many climate models from the fifth phase of the Coupled Model Intercomparison Project predict decreases in precipitation in Central America and northern South America by the year 2100 for the Representative Concentration Pathway 8.5 scenario. Here we show that the fifth phase of the Coupled Model Intercomparison Project models able to more accurately simulate warm North Atlantic sea surface temperatures (SSTs) for the present climate (strong Atlantic meridional overturning circulation models) are more likely to project a larger precipitation decrease. Drought amplification from the slowdown of Atlantic meridional overturning circulation is more significant during the wet season in the Northern Hemisphere, with an SST‐constrained model estimate yielding a 73% larger decrease in precipitation (−1.11 mm/day) than the multimodel mean (−0.64 mm/day). Since most Earth system models underestimate contemporary SSTs in the North Atlantic, the use of the multimodel mean for impact analysis likely underestimates drought stress and the vulnerability of neotropical forests to increasing drought from climate change.

Forest response to rising CO2 drives zonally asymmetric rainfall change over tropical land

Nature Climate Change | 2018 | IF 25.290

Kooperman, G.J., Y. Chen, F. M. Hoffman, C. D. Koven, K. Lindsay, M. S. Pritchard, A. L. S. Swann and J. T. Randerson

Understanding how anthropogenic CO2 emissions will influence future precipitation is critical for sustainably managing ecosystems, particularly for drought-sensitive tropical forests. Although tropical precipitation change remains uncertain, nearly all models from the Coupled Model Intercomparison Project Phase 5 predict a strengthening zonal precipitation asymmetry by 2100, with relative increases over Asian and African tropical forests and decreases over South American forests. Here we show that the plant physiological response to increasing CO2 is a primary mechanism responsible for this pattern. Applying a simulation design in the Community Earth System Model in which CO2 increases are isolated over individual continents, we demonstrate that different circulation, moisture and stability changes arise over each continent due to declines in stomatal conductance and transpiration. The sum of local atmospheric responses over individual continents explains the pan-tropical precipitation asymmetry. Our analysis suggests that South American forests may be more vulnerable to rising CO2 than Asian or African forests.

A pan-tropical cascade of fire driven by El Niño/Southern Oscillation

Nature Climate Change | 2017 | IF 25.290

Chen, Y., D. C. Morton, N. Andela, G. R. van der Werf, L. Giglio, and J. T. Randerson

The El Niño/Southern Oscillation (ENSO) has a pronounced influence on year-to-year variations in climate. The response of fires to this forcing is complex and has not been evaluated systematically across different continents. Here we use satellite data to create a climatology of burned-area and fire-emissions responses, drawing on six El Niño and six La Niña events during 1997–2016. On average, reductions in precipitation and terrestrial water storage increased fire emissions in pan-tropical forests by 133% during and following El Niño as compared with La Niña. Fires peaked in equatorial Asia early in the ENSO cycle when El Niño was strengthening (Aug–Oct), before moving to southeast Asia and northern South America (Jan–Apr), Central America (Mar–May) and the southern Amazon (Jul–Oct) during the following year. Large decreases in fire occurred across northern Australia during Sep–Oct of the second year from a reduced fuel availability. Satellite observations of aerosols and carbon monoxide provided independent confirmation of the spatiotemporal evolution of fire anomalies. The predictable cascade of fire across different tropical continents described here highlights an important time delay in the Earth system’s response to precipitation redistribution. These observations help to explain why the growth rate of atmospheric CO2 increases during El Niño 3 and may contribute to improved seasonal fire forecasts.

Global fire emissions estimates during 1997–2016

Earth System Science Data | 2017 | IF 11.333

van der Werf, G.R., J. T. Randerson, L. Giglio, T. T. van Leeuwen, Y. Chen, B. M. Rogers, M. Mu, M. J. E. van Marle, D. C. Morton, G. J. Collatz, R. J. Yokelson, and P. S. Kasibhatla

Climate, land use, and other anthropogenic and natural drivers have the potential to influence fire dynamics in many regions. To develop a mechanistic understanding of the changing role of these drivers and their impact on atmospheric composition, long-term fire records are needed that fuse information from different satellite and in situ data streams. Here we describe the fourth version of the Global Fire Emissions Database (GFED) and quantify global fire emissions patterns during 1997–2016. The modeling system, based on the Carnegie–Ames–Stanford Approach (CASA) biogeochemical model, has several modifications from the previous version and uses higher quality input datasets. Significant upgrades include (1) new burned area estimates with contributions from small fires, (2) a revised fuel consumption parameterization optimized using field observations, (3) modifications that improve the representation of fuel consumption in frequently burning landscapes, and (4) fire severity estimates that better represent continental differences in burning processes across boreal regions of North America and Eurasia. The new version has a higher spatial resolution (0.25°) and uses a different set of emission factors that separately resolves trace gas and aerosol emissions from temperate and boreal forest ecosystems. Global mean carbon emissions using the burned area dataset with small fires (GFED4s) were 2.2  ×  1015 grams of carbon per year (Pg C yr−1) during 1997–2016, with a maximum in 1997 (3.0 Pg C yr−1) and minimum in 2013 (1.8 Pg C yr−1). These estimates were 11 % higher than our previous estimates (GFED3) during 1997–2011, when the two datasets overlapped. This net increase was the result of a substantial increase in burned area (37 %), mostly due to the inclusion of small fires, and a modest decrease in mean fuel consumption (−19 %) to better match estimates from field studies, primarily in savannas and grasslands. For trace gas and aerosol emissions, differences between GFED4s and GFED3 were often larger due to the use of revised emission factors. If small fire burned area was excluded (GFED4 without the s for small fires), average emissions were 1.5 Pg C yr−1. The addition of small fires had the largest impact on emissions in temperate North America, Central America, Europe, and temperate Asia. This small fire layer carries substantial uncertainties; improving these estimates will require use of new burned area products derived from high-resolution satellite imagery. Our revised dataset provides an internally consistent set of burned area and emissions that may contribute to a better understanding of multi-decadal changes in fire dynamics and their impact on the Earth system. GFED data are available from http://www.globalfiredata.org.

A human-driven decline in global burned area

Science | 2017 | IF 47.728

N. Andela, D. C. Morton, L. Giglio, Y. Chen, G. R. van der Werf, P. S. Kasibhatla, R. S. DeFries, G. J. Collatz, S. Hantson, S. Kloster, D. Bachelet, M. Forrest, G. Lasslop, F. Li, S. Mangeon, J. R. Melton, C. Yue, J. T. Randerson

Fire is an essential Earth system process that alters ecosystem and atmospheric composition. Here we assessed long-term fire trends using multiple satellite data sets. We found that global burned area declined by 24.3 ± 8.8% over the past 18 years. The estimated decrease in burned area remained robust after adjusting for precipitation variability and was largest in savannas. Agricultural expansion and intensification were primary drivers of declining fire activity. Fewer and smaller fires reduced aerosol concentrations, modified vegetation structure, and increased the magnitude of the terrestrial carbon sink. Fire models were unable to reproduce the pattern and magnitude of observed declines, suggesting that they may overestimate fire emissions in future projections. Using economic and demographic variables, we developed a conceptual model for predicting fire in human-dominated landscapes.

Fire event prediction for improved regional smoke forecasting

Proceedings of the 7th International Workshop on Climate Informatics: CI 2017 | 2017

Butler, Z., Y. Chen, J. T. Randerson, and P. Smyth

Smoke from wildfires is a significant public health concern with over 300,000 people dying annually worldwide. Given these large health impacts an important goal is to forecast fire emissions on multi-day time scales, for example, to provide higher quality forecasts for operational smoke forecasting systems. In this paper we describe initial work on statistical predictive modeling techniques that use historical satellite and weather data to predict fire activity on daily time-scales and for a regional spatial domain. Prediction results from 10 years of wildfire data in Alaska illustrate how local weather information can be used to improve the quality of multiday fire forecasts.

How much global burned area can be forecast on seasonal time scales using sea surface temperatures?

Environmental Research Letters | 2016 | IF 6.793

Chen Y., D. C. Morton, N. Andela, L. Giglio and J. T. Randerson

Large-scale sea surface temperature (SST) patterns influence the interannual variability of burned area in many regions by means of climate controls on fuel continuity, amount, and moisture content. Some of the variability in burned area is predictable on seasonal timescales because fuel characteristics respond to the cumulative effects of climate prior to the onset of the fire season. Here we systematically evaluated the degree to which annual burned area from the Global Fire Emissions Database version 4 with small fires (GFED4s) can be predicted using SSTs from 14 different ocean regions. We found that about 48% of global burned area can be forecast with a correlation coefficient that is significant at a p < 0.01 level using a single ocean climate index (OCI) 3 or more months prior to the month of peak burning. Continental regions where burned area had a higher degree of predictability included equatorial Asia, where 92% of the burned area exceeded the correlation threshold, and Central America, where 86% of the burned area exceeded this threshold. Pacific Ocean indices describing the El Niño-Southern Oscillation were more important than indices from other ocean basins, accounting for about 1/3 of the total predictable global burned area. A model that combined two indices from different oceans considerably improved model performance, suggesting that fires in many regions respond to forcing from more than one ocean basin. Using OCI—burned area relationships and a clustering algorithm, we identified 12 hotspot regions in which fires had a consistent response to SST patterns. Annual burned area in these regions can be predicted with moderate confidence levels, suggesting operational forecasts may be possible with the aim of improving ecosystem management.

Tropical North Atlantic ocean-atmosphere interactions synchronize forest carbon losses from hurricanes and Amazon fires

Geophys. Res. Lett. | 2015 | IF 4.720

Chen Y., J. T. Randerson, and Douglas C. Morton

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 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.

Long-term trends and interannual variability of forest, savanna and agricultural fires in South America

Carbon Management | 2013 | IF 3.182

Chen Y., D. Morton, Y. Jin, G. J. Collatz, P.S. Kasibhatla, G.R. van der Werf, R.S. DeFries, and J. T. Randerson

Background: Landscape fires in South America have considerable impacts on ecosystems, air quality and the climate system. We examined long-term trends and interannual variability of forest, savanna and agricultural fires for the continent during 2001–2012 using multiple satellite-derived fire products. Results: The annual number of active fires in tropical forests increased significantly during 2001–2005. Several satellite-derived metrics, including fire persistence, indicated that this trend was mostly driven by deforestation. Fires between 2005 and 2012 had a small decreasing trend and large year-to-year changes that were associated with climate extremes. Fires in savannas and evergreen forests increased in parallel during drought events in 2005, 2007 and 2010, suggesting similar regional climate controls on fire behavior. Deforestation fire intensity (the number of fires per unit of deforested area) increased significantly within the Brazilian Amazon in areas with small-scale deforestation. Conclusion: Fires associated with forest degradation are becoming an increasingly important component of the fire regime and associated carbon emissions.

Satellite observations of terrestrial water storage provide early warning information about drought and fire season severity in the Amazon

J. Geophys. Res. - Biogeosciences | 2013 | IF 3.822

Chen Y., I. Velicogna, J. S. Famiglietti, and J. T. Randerson

Fire risk in the Amazon can be predicted several months before the onset of the dry season using sea surface temperatures in the tropical north Atlantic and tropical Pacific. The lead times between ocean state and the period of maximum burning (4–11 months) may enable the development of forecasts with benefits for forest conservation, yet the underlying physical and biological mechanisms responsible for these temporal offsets are not well known. Here, we examined the hypothesis that year-to-year variations in soil water recharge during the wet season modify atmospheric water vapor and fire behavior during the following dry season. We tested this hypothesis by analyzing terrestrial water storage observations from the Gravity Recovery and Climate Experiment (GRACE), active fires from the Moderate Resolution Imaging Spectroradiometer (MODIS), and several other satellite and atmospheric reanalysis datasets during 2002–2011. We found that terrestrial water storage deficits preceded severe fire seasons across the southern Amazon. The most significant relationships between monthly terrestrial water storage and the sum of active fires during the dry season occurred during April–August (p<0.02), corresponding to 1–5 month lead times before the peak month of burning (September). Analysis of other datasets provided evidence for a cascade of processes during drought events, with lower cumulative precipitation (and higher cumulative evapotranspiration) in the wet season substantially reducing terrestrial water storage, and subsequently, surface and column atmospheric water vapor. Our results suggest that terrestrial water storage observations from GRACE have the potential to improve fire season forecasts for the southern Amazon.

El Niño and health risks from landscape fire emissions in southeast Asia

Nature Climate Change | 2013 | IF 25.290

Marlier E. M., R. S. DeFries, A. Voulgarakis, P. L. Kinney, J. T. Randerson, D. T. Shindell, Y. Chen, G. Faluvegi

Emissions from landscape fires affect both climate and air quality1. Here, we combine satellite-derived fire estimates and atmospheric modelling to quantify health effects from fire emissions in southeast Asia from 1997 to 2006. This region has large interannual variability in fire activity owing to coupling between El Niño-induced droughts and anthropogenic land-use change2, 3. We show that during strong El Niño years, fires contribute up to 200 μg m−3 and 50 ppb in annual average fine particulate matter (PM2.5) and ozone surface concentrations near fire sources, respectively. This corresponds to a fire contribution of 200 additional days per year that exceed the World Health Organization 50 μg m−3 24-hr PM2.5 interim target4 and an estimated 10,800 (6,800–14,300)-person (~ 2%) annual increase in regional adult cardiovascular mortality. Our results indicate that reducing regional deforestation and degradation fires would improve public health along with widely established benefits from reducing carbon emissions, preserving biodiversity and maintaining ecosystem services.

Satellite-based assessment of climate controls on US burned area

Biogeosciences | 2013 | IF 34.295

Morton, D. C., G. J. Collatz, D. Wang, J. T. Randerson, L. Giglio, Y. Chen

Climate regulates fire activity through the buildup and drying of fuels and the conditions for fire ignition and spread. Understanding the dynamics of contemporary climate–fire relationships at national and sub-national scales is critical to assess the likelihood of changes in future fire activity and the potential options for mitigation and adaptation. Here, we conducted the first national assessment of climate controls on US fire activity using two satellite-based estimates of monthly burned area (BA), the Global Fire Emissions Database (GFED, 1997–2010) and Monitoring Trends in Burn Severity (MTBS, 1984–2009) BA products. For each US National Climate Assessment (NCA) region, we analyzed the relationships between monthly BA and potential evaporation (PE) derived from reanalysis climate data at 0.5° resolution. US fire activity increased over the past 25 yr, with statistically significant increases in MTBS BA for the entire US and the Southeast and Southwest NCA regions. Monthly PE was strongly correlated with US fire activity, yet the climate driver of PE varied regionally. Fire season temperature and shortwave radiation were the primary controls on PE and fire activity in Alaska, while water deficit (precipitation – PE) was strongly correlated with fire activity in the Plains regions and Northwest US. BA and precipitation anomalies were negatively correlated in all regions, although fuel-limited ecosystems in the Southern Plains and Southwest exhibited positive correlations with longer lead times (6–12 months). Fire season PE increased from the 1980's–2000's, enhancing climate-driven fire risk in the southern and western US where PE–BA correlations were strongest. Spatial and temporal patterns of increasing fire season PE and BA during the 1990's–2000's highlight the potential sensitivity of US fire activity to climate change in coming decades. However, climate-fire relationships at the national scale are complex, based on the diversity of fire types, ecosystems, and ignition sources within each NCA region. Changes in the seasonality or magnitude of climate anomalies are therefore unlikely to result in uniform changes in US fire activity.

Global burned area and biomass burning emissions from small fires

J. Geophys. Res. - Biogeosciences | 2012 | IF 3.822

Randerson, J. T., Y. Chen, G. R. van der Werf, B. M. Rogers, and D. C. Morton,

In several biomes, including croplands, wooded savannas, and tropical forests, many small fires occur each year that are well below the detection limit of the current generation of global burned area products derived from moderate resolution surface reflectance imagery. Although these fires often generate thermal anomalies that can be detected by satellites, their contributions to burned area and carbon fluxes have not been systematically quantified across different regions and continents. Here we developed a preliminary method for combining 1-km thermal anomalies (active fires) and 500 m burned area observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the influence of these fires. In our approach, we calculated the number of active fires inside and outside of 500 m burn scars derived from reflectance data. We estimated small fire burned area by computing the difference normalized burn ratio (dNBR) for these two sets of active fires and then combining these observations with other information. In a final step, we used the Global Fire Emissions Database version 3 (GFED3) biogeochemical model to estimate the impact of these fires on biomass burning emissions. We found that the spatial distribution of active fires and 500 m burned areas were in close agreement in ecosystems that experience large fires, including savannas across southern Africa and Australia and boreal forests in North America and Eurasia. In other areas, however, we observed many active fires outside of burned area perimeters. Fire radiative power was lower for this class of active fires. Small fires substantially increased burned area in several continental-scale regions, including Equatorial Asia (157%), Central America (143%), and Southeast Asia (90%) during 2001–2010. Globally, accounting for small fires increased total burned area by approximately by 35%, from 345 Mha/yr to 464 Mha/yr. A formal quantification of uncertainties was not possible, but sensitivity analyses of key model parameters caused estimates of global burned area increases from small fires to vary between 24% and 54%. Biomass burning carbon emissions increased by 35% at a global scale when small fires were included in GFED3, from 1.9 Pg C/yr to 2.5 Pg C/yr. The contribution of tropical forest fires to year-to-year variability in carbon fluxes increased because small fires amplified emissions from Central America, South America and Southeast Asia—regions where drought stress and burned area varied considerably from year to year in response to El Nino-Southern Oscillation and other climate modes.

Estimated global mortality attributable to smoke from landscape fires

Environmental Health Perspectives | 2012 | IF 9.031

Johnston, F. H., S. B. Henderson, Y. Chen, J. R. Randerson, M. Marlier, R. S. DeFries, P. Kinney, D. M. Bowman, M. Brauer

Background: Forest, grass, and peat fires release approximately 2 petagrams of carbon into the atmosphere each year, influencing weather, climate, and air quality. Objective: We estimated the annual global mortality attributable to landscape fire smoke (LFS). Methods: Daily and annual exposure to particulate matter ≤ 2.5 μm in aerodynamic diameter (PM2.5) from fire emissions was estimated globally for 1997 through 2006 by combining outputs from a chemical transport model with satellite-based observations of aerosol optical depth. In World Health Organization (WHO) subregions classified as sporadically affected, the daily burden of mortality was estimated using previously published concentration–response coefficients for the association between short-term elevations in PM2.5 from LFS (contrasted with 0 μg/m3 from LFS) and all-cause mortality. In subregions classified as chronically affected, the annual burden of mortality was estimated using the American Cancer Society study coefficient for the association between long-term PM2.5 exposure and all-cause mortality. The annual average PM2.5 estimates were contrasted with theoretical minimum (counterfactual) concentrations in each chronically affected subregion. Sensitivity of mortality estimates to different exposure assessments, counterfactual estimates, and concentration–response functions was evaluated. Strong La Niña and El Niño years were compared to assess the influence of interannual climatic variability. Results: Our principal estimate for the average mortality attributable to LFS exposure was 339,000 deaths annually. In sensitivity analyses the interquartile range of all tested estimates was 260,000–600,000. The regions most affected were sub-Saharan Africa (157,000) and Southeast Asia (110,000). Estimated annual mortality during La Niña was 262,000, compared with 532,000 during El Niño. Conclusions: Fire emissions are an important contributor to global mortality. Adverse health outcomes associated with LFS could be substantially reduced by curtailing burning of tropical rainforests, which rarely burn naturally. The large estimated influence of El Niño suggests a relationship between climate and the burden of mortality attributable to LFS.

Forecasting fire season severity in South America using sea surface temperature anomalies

Science | 2011 | IF 47.728

Chen, Y., J. T. Randerson, D. C. Morton, R. S. DeFries, G. J. Collatz, P. S. Kasibhatla, L. Giglio, Y. Jin, M. E. Marlier

Fires in South America cause forest degradation and contribute to carbon emissions associated with land use change. We investigated the relationship between year-to-year changes in fire activity in South America and sea surface temperatures. We found that the Oceanic Niño Index was correlated with interannual fire activity in the eastern Amazon, whereas the Atlantic Multidecadal Oscillation index was more closely linked with fires in the southern and southwestern Amazon. Combining these two climate indices, we developed an empirical model to forecast regional fire season severity with lead times of 3 to 5 months. Our approach may contribute to the development of an early warning system for anticipating the vulnerability of Amazon forests to fires, thus enabling more effective management with benefits for climate and air quality.

Impacts of 2006 Indonesian fires on tropical upper tropospheric carbon monoxide and ozone

Atmos. Chem. Phys. | 2011 | IF 6.133

Zhang, L., Q. Li, J. Jin, H. Liu, N. Livesey, J.H. Jiang, Y. Mao, D. Chen, M. Luo, Y. Chen

We investigate the relative impacts of biomass burning emissions and dynamics on tropical upper tropospheric carbon monoxide (CO) and ozone (O3) over western and central Indonesia during the August–November 2006 fires in equatorial Asia by using a global three-dimensional model of tropospheric chemistry (GEOS-Chem) and by comparing model results with Microwave Limb Sounder (MLS) observations of upper tropospheric CO and O3. GEOS-Chem CO and O3 show similarities with MLS observed enhancements from convective lifting of fire emissions. In the tropical upper troposphere (UT), fire effluents from equatorial Asia are primarily transported southwestward to the eastern tropical Indian Ocean, driven by the high-pressure systems along 10° N–15° N and 10° S–15° S latitudes, and northeastward to southeast Asia and beyond, driven by the western North Pacific subtropical high. A characteristic feature of these CO enhancements is that they lag behind biomass burning emissions (by 2–3 weeks) at the three pressure levels 215, 147 and 100 hPa, resulting from the decreasing influence of deep convective lifting with altitude in the tropical UT. Inclusion of biomass burning injection height significantly improves model comparison with observations. We estimate the fire influences by contrasting one model simulation with year-specific and another with climatological biomass burning emissions. Biomass burning accounts for about 50–150 ppbv of CO and 5–15 ppbv of O3 in the tropical UT below 100 hPa during October and November, with temporal variations driven by biomass burning and deep convection. We estimate the dynamic impacts by examining the difference between a model simulation for 2006 (El Niño) and another for 2005 (neutral). The dynamic impacts are far more complex and account for up to 100 ppbv of CO and 30 ppbv of O3 in the tropical UT below 100 hPa. The temporal variation of the dynamic impact on CO is driven by deep convection. The variation of the dynamic impact on O3 depends on deep convection as well as the associated lightning NOx emissions and also reflects non-linearity of O3 chemistry.

Biomass burning contribution to black carbon in the western United States mountain ranges

Atmos. Chem. Phys. | 2011 | IF 6.133

Mao, Y., Q. Li, L. Zhang, Y. Chen, J. T. Randerson, D. Chen, K.-N. Liou

Forest fires are an important source to carbonaceous aerosols in the Western United States (WUS). We quantify the relative contribution of biomass burning to black carbon (BC) in the WUS mountain ranges by analyzing surface BC observations for 2006 from the Interagency Monitoring of PROtected Visual Environment (IMPROVE) network using the GEOS-Chem global chemical transport model. Observed surface BC concentrations show broad maxima during late June to early November. Enhanced potassium concentrations and potassium/sulfur ratios observed during the high-BC events indicate a dominant biomass burning influence during the peak fire season. Model surface BC reproduces the observed day-to day and synoptic variabilities in regions downwind of but near urban centers. Major discrepancies are found at elevated mountainous sites during the July-October fire season when simulated BC concentrations are biased low by a factor of two. We attribute these low biases largely to the underestimated (by more than a factor of two) and temporally misplaced biomass burning emissions of BC in the model. Additionally, we find that the biomass burning contribution to surface BC concentrations in the USA likely was underestimated in a previous study using GEOS-Chem (Park et al., 2003), because of the unusually low planetary boundary layer (PBL) heights in the GEOS-3 meteorological reanalysis data used to drive the model. PBL heights from GEOS-4 and GEOS-5 reanalysis data are comparable to those from the North American Regional Reanalysis (NARR). Model simulations show slightly improved agreements with the observations when driven by GEOS-5 reanalysis data, but model results are still biased low. The use of biomass burning emissions with diurnal cycle, synoptic variability, and plume injection has relatively small impact on the simulated surface BC concentrations in the WUS.

Nitrogen deposition in tropical forests from savanna and deforestation fires

Global Change Biology | 2010 | IF 10.863

Chen, Y., J. T. Randerson, G. van der Werf, D. Morton, M. Mu, P. Kasibhatla,

We used satellite-derived estimates of global fire emissions and a chemical transport model to estimate atmospheric nitrogen (N) fluxes from savanna and deforestation fires in tropical ecosystems. N emissions and reactive N deposition led to a net transport of N equatorward, from savannas and areas undergoing deforestation to tropical forests. Deposition of fire-emitted N in savannas was only 26% of emissions – indicating a net export from this biome. On average, net N loss from fires (the sum of emissions and deposition) was equivalent to approximately 22% of biological N fixation (BNF) in savannas (4.0 kg N ha−1 yr−1) and 38% of BNF in ecosystems at the deforestation frontier (9.3 kg N ha−1 yr−1). Net N gains from fires occurred in interior tropical forests at a rate equivalent to 3% of their BNF (0.8 kg N ha−1 yr−1). This percentage was highest for African tropical forests in the Congo Basin (15%; 3.4 kg N ha−1 yr−1) owing to equatorward transport from frequently burning savannas north and south of the basin. These results provide evidence for cross-biome atmospheric fluxes of N that may help to sustain productivity in some tropical forest ecosystems on millennial timescales. Anthropogenic fires associated with slash and burn agriculture and deforestation in the southern part of the Amazon Basin and across Southeast Asia have substantially increased N deposition in these regions in recent decades and may contribute to increased rates of carbon accumulation in secondary forests and other N-limited ecosystems.

The sensitivity of CO and aerosol transport to the temporal and vertical distribution of North American boreal fire emissions

Atmos. Chem. Phys. | 2009 | IF 6.133

Chen, Y., Q. Li, J. T. Randerson, E. A. Lyons, R. A. Kahn, D. L. Nelson, and D. J. Diner

Forest fires in Alaska and western Canada represent important sources of aerosols and trace gases in North America. Among the largest uncertainties when modeling forest fire effects are the timing and injection height of biomass burning emissions. Here we simulate CO and aerosols over North America during the 2004 fire season, using the GEOS-Chem chemical transport model. We apply different temporal distributions and injection height profiles to the biomass burning emissions, and compare model results with satellite-, aircraft-, and ground-based measurements. We find that averaged over the fire season, the use of finer temporal resolved biomass burning emissions usually decreases CO and aerosol concentrations near the fire source region, and often enhances long-range transport. Among the individual temporal constraints, switching from monthly to 8-day time intervals for emissions has the largest effect on CO and aerosol distributions, and shows better agreement with measured day-to-day variability. Injection height substantially modifies the surface concentrations and vertical profiles of pollutants near the source region. Compared with CO, the simulation of black carbon aerosol is more sensitive to the temporal and injection height distribution of emissions. The use of MISR-derived injection heights improves agreement with surface aerosol measurements near the fire source. Our results indicate that the discrepancies between model simulations and MOPITT CO measurements near the Hudson Bay can not be attributed solely to the representation of injection height within the model. Frequent occurrence of strong convection in North America during summer tends to limit the influence of injection height parameterizations of fire emissions in Alaska and western Canada with respect to CO and aerosol distributions over eastern North America.

Possible influence of anthropogenic aerosols on cirrus clouds and anthropogenic forcing

Atmos. Chem. Phys. | 2009 | IF 6.133

Penner, J. E., Y. Chen, M. Wang, and X. Liu

Cirrus clouds have a net warming effect on the atmosphere and cover about 30% of the Earth's area. Aerosol particles initiate ice formation in the upper troposphere through modes of action that include homogeneous freezing of solution droplets, heterogeneous nucleation on solid particles immersed in a solution, and deposition nucleation of vapor onto solid particles. Here, we examine the possible change in ice number concentration from anthropogenic soot originating from surface sources of fossil fuel and biomass burning, from anthropogenic sulfate aerosols, and from aircraft that deposit their aerosols directly in the upper troposphere. We use a version of the aerosol model that predicts sulfate number and mass concentrations in 3-modes and includes the formation of sulfate aerosol through homogeneous binary nucleation as well as a version that only predicts sulfate mass. The 3-mode version best represents the Aitken aerosol nuclei number concentrations in the upper troposphere which dominated ice crystal residues in the upper troposphere. Fossil fuel and biomass burning soot aerosols with this version exert a radiative forcing of −0.3 to −0.4 Wm−2 while anthropogenic sulfate aerosols and aircraft aerosols exert a forcing of −0.01 to 0.04 Wm−2 and −0.16 to −0.12 Wm−2, respectively, where the range represents the forcing from two parameterizations for ice nucleation. The sign of the forcing in the mass-only version of the model depends on which ice nucleation parameterization is used and can be either positive or negative. The magnitude of the forcing in cirrus clouds can be comparable to the forcing exerted by anthropogenic aerosols on warm clouds, but this forcing has not been included in past assessments of the total anthropogenic radiative forcing of climate.

Quantifying aerosol direct radiative effect with Multiangle Imaging Spectroradiometer observations: Top-of-atmosphere albedo change by aerosols based on land surface types

J. Geophys. Res. | 2009 | IF 4.261

Chen, Y., Q. Li, R. A. Kahn, J. T. Randerson, and D. J. Diner

Using internally consistent albedo, aerosol, cloud, and surface data from the Multiangle Imaging Spectroradiometer (MISR) instrument onboard the Terra satellite, top-of-atmosphere (TOA) spectral albedo change (dα) in the presence of aerosols over land is estimated and its dependence on aerosol and surface properties is analyzed. Linear regressions between spectral TOA albedo and aerosol optical depth (AOD) for different surface types are examined to derive the aerosol-free TOA albedo. MISR surface BiHemispherical Reflectance (BHR) values are used to differentiate surface types. We find relatively high correlations between spectral TOA albedo and AOD for BHR-stratified data in 2° × 2° grid cells. The global mean values of cloud-free dα over land for June–September 2007 are estimated to be 0.018 ± 0.003 (blue), 0.010 ± 0.003 (green), 0.007 ± 0.003 (red), and 0.008 ± 0.006 (near-infrared). Individual regions show large variations from these values. Global patterns of dα are determined mainly by AOD and aerosol radiative efficiency. Large positive values of dα are observed over regions with high aerosol loading and large single-scattering albedo, where the aerosol scattering effect is dominant. The presence of light-absorbing aerosols reduces aerosol radiative efficiency and dα. Surface reflectance influences both aerosol scattering and absorbing effects. Generally, the aerosol radiative efficiency decreases with increasing BHR. We also examined dα-AOD correlations over different vegetation types. We find the smallest dα values are over needleleaf forests and shrublands, whereas the largest values are over cropland and barren regions. The aerosol radiative efficiencies are lowest over needleleaf forests and barren regions and highest over grasslands and croplands.

Example applications of the MISR INteractive eXplorer (MINX) software tool to wildfire smoke plume analyses

Proc. of SPIE | 2008

Nelson D. L., Y. Chen, R. A. Kahn, D. J. Diner, and D. Mazzoni

The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard Terra acquires imagery at 275-m resolution at nine angles ranging from 0° to 70° off-nadir. This multi-angle capability facilitates the stereoscopic retrieval of smoke heights associated with near-source plumes. A new visualization and analysis program called MISR INteractive eXplorer (MINX) takes advantage of wind-direction information inherent in smoke plumes from active fires to determine plume heights and wind speeds at higher resolution and with greater accuracy than provided by the standard, operational MISR product. Among the software tool's many features are several designed for in-depth study of plumes, including animations of the nine MISR camera images that provide a visual 3-D perspective, and interactive digitization of plumes in order to automatically retrieve heights and winds. Aerosol properties from MISR, and fire power based on infrared brightness temperatures from MODIS (also on Terra) are archived along with the retrieved height and wind data. MINX retrievals have sufficient spatial detail to provide valuable input to studies of plume dynamics as well as large-scale climatological studies. Current efforts are focusing on fires in North America, but application to other areas of the world is also envisioned. Case study examples will be presented to illustrate MINX capabilities.

Quantitative studies of wildfire smoke injection heights with the Terra Multi-angle Imaging SpectroRadiometer

Proc. of SPIE | 2008

Diner, D. J., D. L. Nelson, Y. Chen, R. A. Kahn, J. Logan, F. T. Leung, and M. Val Martin

The Multi-angle Imaging SpectroRadiometer (MISR) is in its ninth year of operation aboard NASA's Terra satellite. MISR acquires imagery at nine view angles between 70.5° forward and backward of nadir. Stereoscopic image matching of red band data at 275-m horizontal spatial resolution provides measurements of aerosol plume heights in the vicinity and downwind of wildfires. We are supplementing MISR's standard stereo product with more detailed, higher vertical spatial resolution stereo retrievals over individual smoke plumes, using the MISR INteractive eXplorer (MINX) analysis tool. To limit the amount of data that must be processed, MODIS (Moderate resolution Imaging Spectroradiometer) thermal anomaly data are used to identify fire locations. Data over North America are being analyzed to generate a climatology of smoke injection heights and to derive a general parameterization for the injection heights that can be used within non-plume-resolving chemical transport models. In 2002, we find that up to about 30% of fire plumes over North America reached the free troposphere. Sufficiently buoyant plumes tend to become trapped near stratified stable layers within the atmospheric vertical profile, supporting a result first obtained on a more limited set of MISR data [1]. Data from other years are being processed to further establish the robustness of these conclusions.

Wildfire smoke injection heights – two perspectives from space

Geophys. Res. Lett. | 2008 | IF 4.720

Kahn, R. A., Y. Chen, D. L. Nelson, F. T. Leung, Q. Li, D. J. Diner, and J. A. Logan

The elevation at which wildfire smoke is injected into the atmosphere has a strong influence on how the smoke is dispersed, and is a key input to aerosol transport models. Aerosol layer height is derived with great precision from space-borne lidar, but horizontal sampling is very poor on a global basis. Aerosol height derived from space-borne stereo imaging is limited to source plumes having discernable features. But coverage is vastly greater, and captures the cores of major fires, where buoyancy can be sufficient to lift smoke above the near-surface boundary layer. Initial assessment of smoke injection from the Alaska-Yukon region during summer 2004 finds at least about 10% of wildfire smoke plumes reached the free troposphere. Modeling of smoke environmental impacts can benefit from the combined strengths of the stereo and lidar observations.

Aerosol indirect effects on clouds and global climate

PhD dissertation | 2006

Yang Chen

Advisor: Joyce Penner

There is large complexity and uncertainty in the study of aerosol indirect e®ect and the estimation of aerosol indirect forcing. However, accurately quantifying this effect is crucial to the projection of future climate change. If the aerosol indirect effect is very large, as some models predict, then the total forcing by aerosol and GHGs which have caused the 0.6 ‰average temperature increase of the past 100 years must be small. So the climate sensitivity (which relates the forcing and the response) of the models is large if the models are confined to the previous record of temperature. As Penner (2004) pointed out, the future, then, might be more at the upper range of climate projections. But if aerosols do not have much impact on the clouds and do not cool the temperature much, then greenhouse gases may be only slightly masked by aerosol-induced cloud changes, and projections of future climate might follow the more benign path. In this study, we will address these problems: 1. Is there any observational evidence showing that the aerosols can change the cloud radiative properties and the radiative balance of the earth? Can we separate other effects from the aerosol indirect effect? 2. What is the uncertainty in the estimation of the aerosol indirect effect? Which parameters contribute most to this uncertainty? 3. How do nitrate aerosols and nitric acid gas affect the cloud nucleation process? What is their influence on the aerosol indirect effect? Can we derive a parameterization considering this effect? 4. Have human beings induced aerosol affects on the cirrus clouds at high altitudes? What are the mechanisms behind the ice nucleation process? Can we give an estimation of the global forcing of this effect?

Uncertainty analysis for estimates of the first indirect aerosol effect

Atmos. Chem. Phys. | 2005 | IF 6.133

Chen, Y. and J. E. Penner

The IPCC has stressed the importance of producing unbiased estimates of the uncertainty in indirect aerosol forcing, in order to give policy makers as well as research managers an understanding of the most important aspects of climate change that require refinement. In this study, we use 3-D meteorological fields together with a radiative transfer model to examine the spatially-resolved uncertainty in estimates of the first indirect aerosol forcing. The global mean forcing calculated in the reference case is -1.30 Wm-2. Uncertainties in the indirect forcing associated with aerosol and aerosol precursor emissions, aerosol mass concentrations from different chemical transport models, aerosol size distributions, the cloud droplet parameterization, the representation of the in-cloud updraft velocity, the relationship between effective radius and volume mean radius, cloud liquid water content, cloud fraction, and the change in the cloud drop single scattering albedo due to the presence of black carbon are calculated. The aerosol burden calculated by chemical transport models and the cloud fraction are found to be the most important sources of uncertainty. Variations in these parameters cause an underestimation or overestimation of the indirect forcing compared to the base case by more than 0.6 Wm-2. Uncertainties associated with aerosol and aerosol precursor emissions, uncertainties in the representation of the aerosol size distribution (including the representation of the pre-industrial size distribution), and uncertainties in the representation of cloud droplet spectral dispersion effect cause uncertainties in the global mean forcing of 0.2~0.6 Wm-2. There are significant regional differences in the uncertainty associated with the first indirect forcing with the largest uncertainties in industrial regions (North America, Europe, East Asia) followed by those in the major biomass burning regions.

Observational evidence of a change in radiative forcing due to the indirect aerosol effect

Nature | 2005 | IF 49.962

Penner, J. E., X. Dong, and Y. Chen

Anthropogenic aerosols enhance cloud reflectivity by increasing the number concentration of cloud droplets, leading to a cooling effect on climate known as the indirect aerosol effect. Observational support for this effect is based mainly on evidence that aerosol number concentrations are connected with droplet concentrations, but it has been difficult to determine the impact of these indirect effects on radiative forcing1, 2, 3. Here we provide observational evidence for a substantial alteration of radiative fluxes due to the indirect aerosol effect. We examine the effect of aerosols on cloud optical properties using measurements of aerosol and cloud properties at two North American sites that span polluted and clean conditions—a continental site in Oklahoma with high aerosol concentrations, and an Arctic site in Alaska with low aerosol concentrations. We determine the cloud optical depth required to fit the observed shortwave downward surface radiation. We then use a cloud parcel model to simulate the cloud optical depth from observed aerosol properties due to the indirect aerosol effect. From the good agreement between the simulated indirect aerosol effect and observed surface radiation, we conclude that the indirect aerosol effect has a significant influence on radiative fluxes.

Review on the mechanism and law of urban photochemical air pollution

Shanghai Environmental Sciences | 2000

Chen, Y., L. Fu, and J. Hao

Photochemical mechanism and law are the bases of photochemical modeling and pollution control. The studies on photochemical pollution sources, photochemical mechanism, transportation, diffusion and deposition were summarized in this paper. In addition, based on the "ozone creation potential", the relationships between ozone and its precursors were analyzed. This paper indicated that in order to establish ozone control strategies, photochemical mechanism fitted for Chinese urban atmosphere is demanded.