JFSP Fire Science Exchange Network
This study finds that the usefulness of several fire severity metrics (Composite Burn Index, RdNBR) depends on whether the land had burned recently and how severely.
Read MoreThis research brief provides an example of easy-to-understand conceptual modeling framework as applied to a Mediterranean-type ecosystem.
Read MoreRecent work by researchers from U.C. Berkeley and the U.S. Forest Service has produced a spatially-explicit predictive model that can be used to forecast where regeneration of (non-serotinous) conifers is most likely to occur after wildfire. This predictive model combines seed availability with climatic, topographic, and burn severity data to forecast the spatial patterns of post-fire conifer regeneration
Read MoreA comparison of two historical fire history data sets, the State of California Fire and Resource Protection (FRAP) database and a database based on annual state and federal written reports, found substantial differences between the two.
Read MorePresented at the Mojave Desert Fire Science and Management Workshop. Barstow, CA 2014.
This presentation discusses the process of model development to map the ignition probability and fire severity.
Presenter: Emma Underwood et al.
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From PSW website: "An efficient raster fire-spread model named HFire is introduced. HFire can simulate single-fire events or long-term fire regimes, using the same fire-spread algorithm. This paper describes the HFire algorithm, benchmarks the model using a standard set of tests developed for FARSITE, and compares historical and predicted fire spread perimeters for three southern California fires. HFire is available for download at http://firecenter.berkeley.edu/hfire/."
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Five fire simulation models used from all over the world were compared: EMBYR, FIRESCAPE, LANDSUM, SEM-‐LAND, and LA-‐MOS(DS).
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Janet Franklin and colleagues used LANDIS, a landscape disturbance and succession model to investigate how short, moderate and long fire return intervals (FRI's) in southern California affect persistence of different shrub life histories.
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In this study, two atmosphere-‐ocean general circulation models to explore shifts in Santa Ana occurrences.
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A study demonstrates some critically important flaws in some of the published studies and suggests approaches for increasing the credibility of studies using historical VTM data.
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This research project assessed the accuracy of three different smoke models (CALPUFF, DAYSMOKE, and CMAQ) at predicting PM2.5 emissions from prescrubed burn and wildfire events in the southeastern United States. Past fire events were modeled, and models were compared to observed data from the actual events.
Visit Firescience.gov to download full text PDFs >
In this study, prototype summaries are constructed for varying time intervals using California wildfire data from 1990 to 2006, as well as summaries of spatial patterns of fires within each wildfire season.
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A model has been developed to predict wildfire risk in northeastern Mojave Desert. The model incorporates remote sensing data as well as field sampling data to generate the predicted fire risk.
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The California Fire Science Consortium is divided into 4 geographic regions and 1 wildland-urban interface (WUI) team. Statewide coordination of this program is based at UC Berkeley.
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This regional Fire Science Exchange is one of 15 regional fire science exchanges sponsored by Joint Fire Science Program (JFSP).
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