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Climate change has the potential to influence many aspects of wildfire behavior and risk. During the last decade, Greece has experienced large-scale wildfire phenomena with unprecedented fire behavior and impacts. In this study, thousands of wildfire events were simulated with the Minimum Travel Time (MTT) fire growth algorithm (called Randig) and resulted in spatial data that describe conditional burn probabilities, potential fire spread and intensity in Messinia, Greece. Present (1961-1990) and future (2071-2100) climate projections were derived from simulations of the KNMI regional climate model RACMO2, under the SRES A1B emission scenario. Data regarding fuel moisture content, wind speed and direction were modified for the different projection time periods to be used as inputs in Randig. Results were used to assess the vulnerability changes for certain values-at-risk of the natural and human-made environment. Differences in wildfire risk were calculated and results revealed that larger wildfires that resist initial control are to be expected in the future, with higher conditional burn probabilities and intensities for extensive parts of the study area. The degree of change in the modeled Canadian Forest Fire Weather Index for the two time periods also revealed an increasing trend in frequencies of higher values for the future. [ABSTRACT FROM AUTHOR]

Wildfires are a global phenomenon that in some circumstances can result in human casualties, economic loss, and ecosystem service degradation. In this article we spatially identify wildfire risk transmission pathways and locate the areas of highest exposure of human populations to wildland fires under severe, but not uncommon, weather events. We quantify varying levels of exposure in terms of population potentially affected and tie the exposure back to the spatial source of the risk for the Front Range of Colorado, USA. We use probabilistic fire simulation modeling to address where fire ignitions are most likely to cause the highest impact to human communities, and to explore the role that various landowners play in that transmission of risk. Our results indicated that, given an ignition and the right fire weather conditions, large areas along the Front Range in Colorado could be exposed to wildfires with high potential to impact human populations, and that overall private ignitions have the potential to impact more people than federal ignitions. These results can be used to identify high-priority areas for wildfire risk mitigation using various mitigation tools. [ABSTRACT FROM AUTHOR]

Wildfires are a global phenomenon that in some circumstances can result in human casualties, economic loss, and ecosystem service degradation. In this article we spatially identify wildfire risk transmission pathways and locate the areas of highest exposure of human populations to wildland fires under severe, but not uncommon, weather events. We quantify varying levels of exposure in terms of population potentially affected and tie the exposure back to the spatial source of the risk for the Front Range of Colorado, USA. We use probabilistic fire simulation modeling to address where fire ignitions are most likely to cause the highest impact to human communities, and to explore the role that various landowners play in that transmission of risk. Our results indicated that, given an ignition and the right fire weather conditions, large areas along the Front Range in Colorado could be exposed to wildfires with high potential to impact human populations, and that overall private ignitions have the potential to impact more people than federal ignitions. These results can be used to identify high-priority areas for wildfire risk mitigation using various mitigation tools., (© 2014 Society for Risk Analysis Published 2014. This article is a U.S. government work and is in the public domain for the USA.)