NH34C:
Wildfires: Triggers, Predictability, and Impact Assessment


Submit an Abstract to this Session


Session ID#: 62882

Session Description:
Wildfire risks in a human-natural system continuum have become more concerning in the recent years, especially along wildland-urban interfaces and in densely populated and industrial areas. For example, the 2018 Mendocino Complex Fire has become the largest fire in Californian history; and the 2016 Fort McMurray wildfires scaled down Canadian oil production for two months affecting global oil. Meanwhile, wildfires remain one the least predictable perils due to both their aleatory uncertainty component mainly associated with wildfire ignition triggers, and their epistemic uncertainty component reflecting the lack of knowledge about fire fuel availability and its moisture content, physical setting, weather, and variability in climate. This interdisciplinary session covers topics related to wildfire including drivers/triggers, trends and anomalies, detection and monitoring, risk management and assessment, evaluation of socio-economic and ecological impacts. It also illustrates application of numerical modeling, machine learning, remote sensing, and laboratory or field data in this research field.
Primary Convener:  Christian Klose, Swiss Re, Data Science and Hazard Resilience, Armonk, NY, United States
Conveners:  Son V Nghiem, NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States, Seung Hee Kim, Chapman University, Institute for Earth, Computing, Human and Observing (ECHO), Orange, CA, United States and Nataliya Le Vine, Swiss Re, Armonk, NY, United States
Primary Liaison:  Nataliya Le Vine, Swiss Re, Armonk, NY, United States
Chairs:  Amber Jeanine Soja, National Institute of Aerospace, Hampton, United States and Jinwon Kim, National Institute of Meteorological Sciences, Seogwipo-si, South Korea
OSPA Liaison:  Jia Shenyue, Chapman University, Institute for Earth, Computing, Human and Observing (ECHO), Orange, CA, United States
Co-Organized with:
Natural Hazards, and GeoHealth

Proposed Co-Organized Session with:
  • A - Atmospheric Sciences
  • GC - Global Environmental Change
  • GH - GeoHealth
  • SI - Societal Impacts and Policy Sciences
Index Terms:

1616 Climate variability [GLOBAL CHANGE]
1920 Emerging informatics technologies [INFORMATICS]
4313 Extreme events [NATURAL HAZARDS]
4341 Early warning systems [NATURAL HAZARDS]

Abstracts Submitted to this Session:

The Deadly Montecito Post-Fire Debris Flow of January 9, 2018 and the Successes and Challenges of Post-Fire Debris-Flow Prediction and Early Warning (Invited) (396043)
Mark E Jackson, NOAA National Weather Service, Oxnard, CA, United States and Dennis M Staley, U.S. Geologic Survey, Volcano Science Center, Alaska Volcano Observatory, Anchorage, United States
Concentrations of heavy metals and polycyclic aromatic hydrocarbons in indoor house dust after 2016 Fort McMurray Wildfires (415443)
Arthur W. H. Chan1, Lukas Kohl2, Meng Meng1, Joan Sadio De Vera3, Bridget A Bergquist4, Colin A. Cooke5, Sarah Hustins6, Brian Jackson6, Chung-Wai Chow7 and Greg Wentworth8, (1)University of Toronto, Department of Chemical Engineering and Applied Chemistry, Toronto, ON, Canada, (2)University of Helsinki, Department of Agricultural Science and Institute for Atmospheric and Earth System Research / Forest Sciences, Faculty of Agriculture and Forestry, Helsinki, Finland, (3)University of Toronto, Earth Sciences, Toronto, ON, Canada, (4)University of Toronto, Department of Earth Sciences, Toronto, ON, Canada, (5)Alberta Environment and Parks, Edmonton, AB, Canada, (6)Alberta Environment and Parks, Environmental Monitoring and Science Division, Edmonton, AB, Canada, (7)University of Toronto, Division of Respirology, Department of Medicine, Faculty of Medicine, Toronto, ON, Canada, (8)Alberta Environment and Parks, Environmental Monitoring and Science Division, Edmonton, Canada
The Fire Climate that Preceded the Largest Fire in California History: A Statistical Anomaly or Wave of the Future? (419844)
Francis Fujioka1, Shyh Chen2, John Benoit2, Charles Jones3 and Seung Hee Kim4, (1)Chapman University, CEESMO, Orange, CA, United States, (2)USDA Forest Service, Pacific Southwest Research Station, Riverside, CA, United States, (3)University of California, Santa Barbara, Department of Geography, Santa Barbara, United States, (4)Chapman University, Institute for Earth, Computing, Human and Observing (ECHO), Orange, CA, United States
THE FIREHUB: A PROTOTYPE OPERATIONAL EARLY WARNING, FIRE DETECTION AND BURNED AREA MAPPING SYSTEM (Invited) (415815)
Charalambos Kontoes, National Observatory of Athens, Institute for Astronomy and Astrophysics, Space Applications and Remote Sensing - BEYOND Center of Earth Observation Research and Satellite Remote Sensing, Athens, Greece
Reducing California Homeowners’ Wildfire Risk on Their Property and in Their Community: Willingness to Pay Results of a Choice Experiment (423324)
Armando Gonzalez-Caban, Chapman University, Orange, CA, United States, Jose J. Sanchez, USDA Forest Service, Vallejo, CA, United States, John B. Loomis, Professor, Department of Agricultural and Resource Economics, Fort Collins, CO, United States and Thomas Holmes, Research Forester, Forest Economics and Policy, Research Triangle Park, NC, United States
ECMWF Perspective on the Big Data Challenge for Fire Forecasting (Invited) (352634)
Francesca Di Giuseppe, ECMWF, Reading, United Kingdom, Claudia Vitolo, ECMWF, Reading, United States and ECMWF fire forecasting team
Seasonal to decadal prediction of fire danger (Invited) (352725)
Etienne Tourigny1, Joaqun Bedia2, Raul Marcos1, Balakrishnan Solaraju1, Francesca Di Giuseppe3 and Francisco J. Doblas-Reyes1,4, (1)Barcelona Supercomputing Center, Barcelona, Spain, (2)Predictia Intelligent Data Solutions, Cantabria, Spain, (3)ECMWF, Reading, United Kingdom, (4)Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
Improvement Wild Fire Detection Algorithm using Time-series Himawari-8 IR Images (429475)
Sung-Hwan Park, University of Seoul, Seoul, Korea, Republic of (South), Hyung-Sup Jung, University of Seoul, Department of Geoinformatics, Seoul, South Korea and Wook Park, Yonsei University, Seoul, Korea, Republic of (South)

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