Forecasting Global Fire Emissions on Subseasonal to Seasonal (S2S) Time Scales
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Casey A. Graff | J. Randerson | Padhraic Smyth | E. Foufoula‐Georgiou | D. Morton | L. Giglio | G. R. van der Werf | N. Andela | Yang Chen | L. Ott | S. Coffield
[1] M. Chin,et al. Six global biomass burning emission datasets: intercomparison and application in one global aerosol model , 2019 .
[2] Padhraic Smyth,et al. Machine learning to predict final fire size at the time of ignition , 2019, International journal of wildland fire.
[3] A. Russell,et al. Global Fire Forecasts Using Both Large‐Scale Climate Indices and Local Meteorological Parameters , 2019, Global Biogeochemical Cycles.
[4] A. P. Williams,et al. Observed Impacts of Anthropogenic Climate Change on Wildfire in California , 2019, Earth's Future.
[5] M. Andreae. Emission of trace gases and aerosols from biomass burning – an updated assessment , 2019, Atmospheric Chemistry and Physics.
[6] J. Randerson,et al. The Global Fire Atlas of individual fire size, duration, speed and direction , 2018, Earth System Science Data.
[7] Lynn M. Johnston,et al. Wildland-Urban Interface , 2019, Encyclopedia of Wildfires and Wildland-Urban Interface (WUI) Fires.
[8] N. Unger,et al. Fire air pollution reduces global terrestrial productivity , 2018, Nature Communications.
[9] Michael V. Saha,et al. Climate seasonality as an essential predictor of global fire activity , 2018, Global Ecology and Biogeography.
[10] J. Randerson,et al. Smoke radiocarbon measurements from Indonesian fires provide evidence for burning of millennia-aged peat , 2018, Proceedings of the National Academy of Sciences.
[11] A. P. Williams,et al. Global patterns of interannual climate–fire relationships , 2018, Global change biology.
[12] Mian Chin,et al. Connecting Indonesian Fires and Drought With the Type of El Niño and Phase of the Indian Ocean Dipole During 1979–2016 , 2018, Journal of Geophysical Research: Atmospheres.
[13] J. Randerson,et al. A pan-tropical cascade of fire driven by El Niño/Southern Oscillation , 2017, Nature Climate Change.
[14] J. Randerson,et al. Global fire emissions estimates during 1997–2016 , 2017 .
[15] J. Randerson,et al. A human-driven decline in global burned area , 2017, Science.
[16] J. Randerson,et al. Lightning as a major driver of recent large fire years in North American boreal forests , 2017 .
[17] Bin Zhao,et al. The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). , 2017, Journal of climate.
[18] Yuzhong Zhang,et al. Top-of-atmosphere radiative forcing affected by brown carbon in the upper troposphere , 2017 .
[19] Jennifer K. Balch,et al. Human-started wildfires expand the fire niche across the United States , 2017, Proceedings of the National Academy of Sciences.
[20] Michael G. Bosilovich,et al. Atmospheric Water Balance and Variability in the MERRA-2 Reanalysis , 2017 .
[21] A. P. Williams,et al. Impact of anthropogenic climate change on wildfire across western US forests , 2016, Proceedings of the National Academy of Sciences.
[22] Douglas C. Morton,et al. How much global burned area can be forecast on seasonal time scales using sea surface temperatures? , 2016 .
[23] A. Arneth,et al. Climate, CO 2 and human population impacts on global wildfire emissions , 2016 .
[24] Y. Ishikawa,et al. A new Approach to El Niño Prediction beyond the Spring Season , 2015, Scientific Reports.
[25] R. Seager,et al. Climatology, Variability, and Trends in the U.S. Vapor Pressure Deficit, an Important Fire-Related Meteorological Quantity* , 2015 .
[26] Grant J. Williamson,et al. Climate-induced variations in global wildfire danger from 1979 to 2013 , 2015, Nature Communications.
[27] Malcolm P. North,et al. Water balance and topography predict fire and forest structure patterns , 2015 .
[28] Daniel Crawl,et al. Towards an Integrated Cyberinfrastructure for Scalable Data-driven Monitoring, Dynamic Prediction and Resilience of Wildfires , 2015, ICCS.
[29] A. Jalalkamali,et al. Application of several artificial intelligence models and ARIMAX model for forecasting drought using the Standardized Precipitation Index , 2015, International Journal of Environmental Science and Technology.
[30] Nicolas Faivre,et al. Controls on the spatial pattern of wildfire ignitions in Southern California , 2014 .
[31] Florian Pappenberger,et al. Seasonal forecasting of fire over Kalimantan, Indonesia , 2014 .
[32] J. Randerson,et al. Multi-scale influence of vapor pressure deficit on fire ignition and spread in boreal forest ecosystems , 2014 .
[33] W. Schroeder,et al. The New VIIRS 375 m active fire detection data product: Algorithm description and initial assessment , 2014 .
[34] J. Randerson,et al. Long-term trends and interannual variability of forest, savanna and agricultural fires in South America , 2013 .
[35] Douglas G. Woolford,et al. Wildfire Prediction to Inform Fire Management: Statistical Science Challenges , 2013, 1312.6481.
[36] George Athanasopoulos,et al. Forecasting: principles and practice , 2013 .
[37] G. Faluvegi,et al. Direct top‐down estimates of biomass burning CO emissions using TES and MOPITT versus bottom‐up GFED inventory , 2013 .
[38] R. DeFries,et al. Understorey fire frequency and the fate of burned forests in southern Amazonia , 2013, Philosophical Transactions of the Royal Society B: Biological Sciences.
[39] J. Randerson,et al. Satellite observations of terrestrial water storage provide early warning information about drought and fire season severity in the Amazon , 2013 .
[40] J. Pausas,et al. The global fire–productivity relationship , 2013 .
[41] M. Flannigan,et al. Global wildland fire season severity in the 21st century , 2013 .
[42] J. Randerson,et al. Analysis of daily, monthly, and annual burned area using the fourth‐generation global fire emissions database (GFED4) , 2013 .
[43] B. Abish,et al. A stochastic model for predicting aerosol optical depth over the north Indian region , 2013 .
[44] J. Randerson,et al. The changing radiative forcing of fires: global model estimates for past, present and future , 2012 .
[45] James Durbin,et al. Time Series Analysis by State Space Methods: Second Edition , 2012 .
[46] Michael Brauer,et al. Estimated Global Mortality Attributable to Smoke from Landscape Fires , 2012, Environmental health perspectives.
[47] Christopher I. Roos,et al. The human dimension of fire regimes on Earth , 2011, Journal of biogeography.
[48] J. Randerson,et al. Forecasting Fire Season Severity in South America Using Sea Surface Temperature Anomalies , 2011, Science.
[49] John S. Kimball,et al. Evaluation of MERRA Land Surface Estimates in Preparation for the Soil Moisture Active Passive Mission , 2011 .
[50] Krista M. Gebert,et al. Spatially explicit forecasts of large wildland fire probability and suppression costs for California , 2011 .
[51] Dong Eun Lee,et al. North Tropical Atlantic influence on western Amazon fire season variability , 2011 .
[52] Charles W. McHugh,et al. A Method for Ensemble Wildland Fire Simulation , 2011 .
[53] A. Fernández-Manso,et al. Forecast of NDVI in coniferous areas using temporal ARIMA analysis and climatic data at a regional scale , 2011 .
[54] D. Shindell,et al. Driving forces of global wildfires over the past millennium and the forthcoming century , 2010, Proceedings of the National Academy of Sciences.
[55] H. Juang,et al. NCEP–ECPC monthly to seasonal US fire danger forecasts , 2010 .
[56] Y. Shimabukuro,et al. The Incidence of Fire in Amazonian Forests with Implications for REDD , 2010, Science.
[57] Matthieu Lengaigne,et al. Influence of the state of the Indian Ocean Dipole on the following year’s El Niño , 2010 .
[58] P. Webster,et al. Beyond the spring barrier , 2010 .
[59] R. DeFries,et al. Deforestation driven by urban population growth and agricultural trade in the twenty-first century , 2010 .
[60] Christopher I. Roos,et al. Fire in the Earth System , 2009, Science.
[61] F. Joos,et al. Erratum: Climate and human influences on global biomass burning over the past two millennia , 2009 .
[62] D. Roy,et al. What limits fire? An examination of drivers of burnt area in Southern Africa , 2009 .
[63] J. Randerson,et al. Climate regulation of fire emissions and deforestation in equatorial Asia , 2008, Proceedings of the National Academy of Sciences.
[64] F. Joos,et al. Climate and human influences on global biomass burning over the past two millennia , 2008 .
[65] Daniel Peña,et al. Autoregressive Integrated Moving Average (ARIMA) Modeling , 2008 .
[66] Robert Pardo,et al. The Evaluation and Optimization of Trading Strategies , 2008 .
[67] S. Ly,et al. What limits fire? An examination of drivers of burnt area in Southern Africa , 2008 .
[68] David Riaño,et al. Burned area forecasting using past burned area records and Southern Oscillation Index for tropical Africa (1981–1999) , 2007 .
[69] S. Lavorel,et al. Vulnerability of land systems to fire: Interactions among humans, climate, the atmosphere, and ecosystems , 2006 .
[70] T. Swetnam,et al. Warming and Earlier Spring Increase Western U.S. Forest Wildfire Activity , 2006, Science.
[71] F. Achard,et al. Ecology: Human role in Russian wild fires , 2006, Nature.
[72] Susan I. Stewart,et al. The wildland-urban interface in the United States based on 125 million building locations. , 2005, Ecological applications : a publication of the Ecological Society of America.
[73] A. Weaver,et al. Detecting the effect of climate change on Canadian forest fires , 2004 .
[74] T. H. Clutton-Brock,et al. Why large-scale climate indices seem to predict ecological processes better than local weather , 2004, Nature.
[75] Lei Ji,et al. Forecasting vegetation greenness with satellite and climate data , 2004, IEEE Geoscience and Remote Sensing Letters.
[76] Thomas M. Smith,et al. An Improved In Situ and Satellite SST Analysis for Climate , 2002 .
[77] E. F. Ledrew,et al. ARMA time series modelling of remote sensing imagery: A new approach for climate change studies , 2002 .
[78] M. Hoerling,et al. ENSO variability, teleconnections and climate change , 2001 .
[79] K. Hadri. Testing The Null Hypothesis Of Stationarity Against The Alternative Of A Unit Root In Panel Data With Serially Correlated Errors , 1999 .
[80] M. Finney. FARSITE : Fire Area Simulator : model development and evaluation , 1998 .
[81] P. Phillips,et al. Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? , 1992 .
[82] M. E. Alexander,et al. Canadian Forest Fire Danger Rating System: An Overview , 1989 .
[83] David Bolton. The Computation of Equivalent Potential Temperature , 1980 .
[84] H. Akaike. A new look at the statistical model identification , 1974 .
[85] P. Young,et al. Time series analysis, forecasting and control , 1972, IEEE Transactions on Automatic Control.