From January to August 2022, there were a total of ** wildfires in California. Most of the fires in the U.S. state started in June. The Mosquito Fire was the largest fire that year based on the number of acres burned, which struck California on September 7, 2022. Overall, the monthly number of wildfires was higher in 2021 when compared to 2022.

The State of the Climate is a collection of periodic summaries recapping climate-related occurrences on both a global and national scale. The State of the Climate Monthly Overview-National Wildfires provides a summary of wildland fires in the U.S. and related weather and climate conditions. Statistical summaries such as the number of fires and acres burned are provided as are reports from the U.S. Drought Monitor and fire danger maps. Monthly reports for the summer "fire season" and annual summaries begin in July 2002. Depending on conditions, reporting was extended beyond the summer and fall seasons, and beginning in 2009 a summary was generated for each month. Following the July 2013 report, and until further notice, NCEI will no longer issue the Wildfire component of its Monthly Climate report. All previous Wildfire reports will be maintained online. Updated statistics will be updated on our Wildfire Societal Impacts webpage.

Oregon saw the largest area burned by wildfires across the United States in 2024. That year, about 2,232 individual wildfires burned in the northwestern state, ravishing almost 1.89 million acres. Texas followed second, with roughly 1.3 million acres burned due to wildfires that year. Fire season 2021 and California’s wildfire suppression costs As one of the most wildfire-prone states in the country, California spends a significant amount of money on their suppression. Estimates suggest wildfire suppression expenditure in California climbed to 1.2 billion U.S. dollars in the fiscal year ending June 2022. The fiscal year, which includes the summer and fall months of 2021, was among the most devastating fire seasons on record, with that year’s Dixie fire becoming the second-largest California wildfire by acres burned. The Dixie fire was responsible for over 963,000 acres burned across the state that year. Wildfire causes Wildfires are uncontrolled fires burning across any type of combustible vegetation such as grass- and brushland, forests, and agricultural fields. They are also referred to as wildland fires, forest fires, or bushfires, with the latter term particularly common in Australia. Wildfires regularly occur on all continents of the world, except for Antarctica, but are particularly common in dry regions with dense vegetation. As the rise in average global temperatures is changing weather patterns and resulting in more and more countries being affected by dry, hot weather conditions, the severity and rapid spread of wildfires have increased in recent years. The most common causes of wildfires are natural phenomena such as lightning strikes as well as human activity. The area burned due to human-caused wildfires in the U.S. surpassed 1.5 million acres in 2023.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (including wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a vector point shapefile of the _location of all currently inventoried fires occurring between calendar year 1984 and 2024 for CONUS, Alaska, Hawaii, and Puerto Rico. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires were not discernable from available imagery.

Historic Fire Perimeter Dataset Feedback (arcgis.com)

Current criteria for data collection are as follows:

CAL FIRE (including contract counties) submit perimeters ≥10 acres in timber, ≥50 acres in brush, or ≥300 acres in grass, and/or ≥3 impacted residential or commercial structures, and/or caused ≥1 fatality.

All cooperating agencies submit perimeters ≥10 acres.

Version update:

Firep24_1 was released in April 2025. Five hundred forty-eight fires from the 2024 fire season were added to the database (2 from BIA, 56 from BLM, 197 from CAL FIRE, 193 from Contract Counties, 27 from LRA, 8 from NPS, 55 from USFS and 8 from USFW). Six perimeters were added from the 2025 fire season (as a special case due to an unusual January fire siege). Five duplicate fires were removed, and the 2023 Sage was replaced with a more accurate perimeter. There were 900 perimeters that received updated attribution (705 removed “FIRE” from the end of Fire Name field and 148 replaced Complex IRWIN ID with Complex local incident number for COMPLEX_ID field). The following fires were identified as meeting our collection criteria but are not included in this version and will hopefully be added in a future update: Addie (2024-CACND-002119), Alpaugh (2024-CACND-001715), South (2024-CATIA-001375). One perimeter is missing containment date that will be updated in the next release.

Cross checking CALFIRS reporting for new CAL FIRE submissions to ensure accuracy with cause class was added to the compilation process. The cause class domain description for “Powerline” was updated to “Electrical Power” to be more inclusive of cause reports.

Includes separate layers filtered by criteria as follows:

California Fire Perimeters (All): Unfiltered. The entire collection of wildfire perimeters in the database. It is scale dependent and starts displaying at the country level scale.

Recent Large Fire Perimeters (≥5000 acres): Filtered for wildfires greater or equal to 5,000 acres for the last 5 years of fires (2020-January 2025), symbolized with color by year and is scale dependent and starts displaying at the country level scale. Year-only labels for recent large fires.

California Fire Perimeters (1950+): Filtered for wildfires that started in 1950-January 2025. Symbolized by decade, and display starting at country level scale.

Detailed metadata is included in the following documents:

Wildland Fire Perimeters (Firep24_1) Metadata

See more information on our Living Atlas data release here:

CAL FIRE Historical Fire Perimeters Available in ArcGIS Living Atlas

For any questions, please contact the data steward:

Kim Wallin, GIS Specialist

CAL FIRE, Fire & Resource Assessment Program (FRAP)

kimberly.wallin@fire.ca.gov

The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image of MTBS burn severity classes for all inventoried fires occurring in CONUS during calendar year 2024. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires were not discernable from available imagery.

The National Park Service (NPS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image of burn severity classes for all NPS-requested burn severity fires, occurring in CONUS. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires which were not discernable from available imagery.

This product is published on a provisional basis to provide necessary information to individuals assessing burn severity impacts on a time sensitive basis. This product was produced using the methods of the Monitoring Trends in Burn Severity (MTBS) Program; however, this fire may not meet the criteria for an MTBS initial assessment. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. MTBS typically maps fires using an initial assessment (immediately after the fire) or an extended assessment (peak of green the season after the fire) for low-biomass and high-biomass fires respectively. Refer to MTBS.gov for more information on MTBS methods and criteria. Fires reported as greater than 40,000 acres in burned area are mapped on a provisional basis, using an initial assessment strategy regardless of vegetation type or density, provided suitable imagery is available. Once imagery for an extended assessment is available, this fire will be assessed under the MTBS program and an official MTBS initial or extended assessment product will be published under that program. This map layer is a thematic raster image of burn severity classes for all currently inventoried Provisional Initial Assessment fires occurring in CONUS.

Historic Fire Perimeter Dataset Feedback (arcgis.com)

Current criteria for data collection are as follows:

CAL FIRE (including contract counties) submit perimeters ≥10 acres in timber, ≥50 acres in brush, or ≥300 acres in grass, and/or ≥3 impacted residential or commercial structures, and/or caused ≥1 fatality.

All cooperating agencies submit perimeters ≥10 acres.

Version update:

Firep24_1 was released in April 2025. Five hundred forty-eight fires from the 2024 fire season were added to the database (2 from BIA, 56 from BLM, 197 from CAL FIRE, 193 from Contract Counties, 27 from LRA, 8 from NPS, 55 from USFS and 8 from USFW). Six perimeters were added from the 2025 fire season (as a special case due to an unusual January fire siege). Five duplicate fires were removed, and the 2023 Sage was replaced with a more accurate perimeter. There were 900 perimeters that received updated attribution (705 removed “FIRE” from the end of Fire Name field and 148 replaced Complex IRWIN ID with Complex local incident number for COMPLEX_ID field). The following fires were identified as meeting our collection criteria but are not included in this version and will hopefully be added in a future update: Addie (2024-CACND-002119), Alpaugh (2024-CACND-001715), South (2024-CATIA-001375). One perimeter is missing containment date that will be updated in the next release.

Cross checking CALFIRS reporting for new CAL FIRE submissions to ensure accuracy with cause class was added to the compilation process. The cause class domain description for “Powerline” was updated to “Electrical Power” to be more inclusive of cause reports.

Includes separate layers filtered by criteria as follows:

California Fire Perimeters (All): Unfiltered. The entire collection of wildfire perimeters in the database. It is scale dependent and starts displaying at the country level scale.

Recent Large Fire Perimeters (≥5000 acres): Filtered for wildfires greater or equal to 5,000 acres for the last 5 years of fires (2020-January 2025), symbolized with color by year and is scale dependent and starts displaying at the country level scale. Year-only labels for recent large fires.

California Fire Perimeters (1950+): Filtered for wildfires that started in 1950-January 2025. Symbolized by decade, and display starting at country level scale.

Detailed metadata is included in the following documents:

Wildland Fire Perimeters (Firep24_1) Metadata

See more information on our Living Atlas data release here:

CAL FIRE Historical Fire Perimeters Available in ArcGIS Living Atlas

For any questions, please contact the data steward:

Kim Wallin, GIS Specialist

CAL FIRE, Fire & Resource Assessment Program (FRAP)

kimberly.wallin@fire.ca.gov

Historic Fire Perimeter Dataset Feedback (arcgis.com)

Current criteria for data collection are as follows:

CAL FIRE (including contract counties) submit perimeters ≥10 acres in timber, ≥50 acres in brush, or ≥300 acres in grass, and/or ≥3 impacted residential or commercial structures, and/or caused ≥1 fatality.

All cooperating agencies submit perimeters ≥10 acres.

Version update:

Firep24_1 was released in April 2025. Five hundred forty-eight fires from the 2024 fire season were added to the database (2 from BIA, 56 from BLM, 197 from CAL FIRE, 193 from Contract Counties, 27 from LRA, 8 from NPS, 55 from USFS and 8 from USFW). Six perimeters were added from the 2025 fire season (as a special case due to an unusual January fire siege). Five duplicate fires were removed, and the 2023 Sage was replaced with a more accurate perimeter. There were 900 perimeters that received updated attribution (705 removed “FIRE” from the end of Fire Name field and 148 replaced Complex IRWIN ID with Complex local incident number for COMPLEX_ID field). The following fires were identified as meeting our collection criteria but are not included in this version and will hopefully be added in a future update: Addie (2024-CACND-002119), Alpaugh (2024-CACND-001715), South (2024-CATIA-001375). One perimeter is missing containment date that will be updated in the next release.

Cross checking CALFIRS reporting for new CAL FIRE submissions to ensure accuracy with cause class was added to the compilation process. The cause class domain description for “Powerline” was updated to “Electrical Power” to be more inclusive of cause reports.

Includes separate layers filtered by criteria as follows:

California Fire Perimeters (All): Unfiltered. The entire collection of wildfire perimeters in the database. It is scale dependent and starts displaying at the country level scale.

Recent Large Fire Perimeters (≥5000 acres): Filtered for wildfires greater or equal to 5,000 acres for the last 5 years of fires (2020-January 2025), symbolized with color by year and is scale dependent and starts displaying at the country level scale. Year-only labels for recent large fires.

California Fire Perimeters (1950+): Filtered for wildfires that started in 1950-January 2025. Symbolized by decade, and display starting at country level scale.

Detailed metadata is included in the following documents:

Wildland Fire Perimeters (Firep24_1) Metadata

See more information on our Living Atlas data release here:

CAL FIRE Historical Fire Perimeters Available in ArcGIS Living Atlas

For any questions, please contact the data steward:

Kim Wallin, GIS Specialist

CAL FIRE, Fire & Resource Assessment Program (FRAP)

kimberly.wallin@fire.ca.gov

The downloadable ZIP file contains an number of Esri shapefiles as described below. This data set provides the spatial information used to complete a post fire inventory and assessment for the 2015 Slide Fire in Clearwater County, Idaho. The fire burned 73 acres within Clearwater County, Idaho in August 2015. Data was prepared by several agencies including US Forest Service, and the Nez Perce Soil and Water Conservation District. Data was prepared for the North Central Idaho Wildfire Restoration Group as part of their efforts in preparing the North Central Idaho Wildfire Inventory and Assessment Report (2015).Several data sets are available and are described as follows:Fire Boundary: Data shows the 2015 fire boundary. Data generated by US Forest Service. File name: OldGreerFireBoundaryLand Cover: Land cover categories generated from National Land Cover Database (2011, USGS). Data processed by clipping NLCD by 2015 fire boundary. Fire boundary generated from InciWeb. Categories include; Developed, Open Space - Mix of constructed materials, but mostly lawn grasses. Impervious surfaces < 20% of total cover. Deciduous Forest - >20% deciduous trees. Evergreen Forest - >20% evergreen trees. Mixed Forest – >20% trees with mix of deciduous and evergreen trees. Shrub/Scrub >20% shrub vegetation. Grassland/Herbaceous - >80% grass /other herbaceous vegetation. Pasture/Hay - Areas of grasses, legumes, or grass-legume mixtures planted for livestock grazing or the production of seed or hay crops, typically on a perennial cycle. Cultivated Crops Areas used for the production of annual crops and/or being annually tilled. Woody Wetlands – Soils that are periodically saturated or covered with water and contain >20% forest or shrubland vegetation. Emergent Herbaceous Wetlands Soils that are periodically saturated or covered with water and vegetation is >80% herbaceous. Data generated by Nikki Lane, Nez Perce soil and Water Conservation District. Jan 2016. Files are named OldGreerLandCoverFINAL10_15_2015 or OldGreerLandCover.shpLand Ownership: Ownership layer for 2015 fire boundary. Source data is BLM Federal Land Status layer clipped to 2015 fire boundary obtained from InciWeb. Bureau of Land Management (BLM); Surface Management Agency (Federal Land Status) layer. 2011. (http://insideidaho.org). Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. Ownership categories: BLM – Bureau of Land Management, Private – private, USFS – US Forest Service, IR – Indian Reservation, State – State of Idaho. Files are named OldGreerLandownershipFINAL1_6_16 or OldGreerLandStatus.shp.Slope Class: Data generated from USGS Digital Elevation Model to identify slopes. Slopes were divided into 3 classes; 1-20, 21-40;>40. Data generated within 2015 fire boundary areas as identified by US Forest Service. Data generated by Nikki Lane, Nez Perce Soil and Water Conservation District. January 2016. Files are named oldgreerpoly or OldGreerSlope.Streams: Data shows streams (perennial and intermittent) within the Wash Complex 2015 fire boundary. Streams layer obtained from USGS. U.S. Rivers and Streams represent detailed rivers and streams in the United States. Data clipped and processed by Cody Dawes, Nez Perce Soil and Water Conservation District in January 2016. Files named OldGreerStreams.PrivateForestlandsBySlope: Data shows three slope classes (0-20, 20-40, >40) on private owned forestlands. Data generated from BLM ownership layer, USGS Digital Elevation Model, and the National Land Cover Database. Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. File name OldGreerPrivateForestlandSlopeClassFINAL_1_7_16Private land forested acres: Data shows privately owned forest acres burned during the 2015 event. Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. File name OldGreerForestAcres.

This map layer is a thematic raster image of MTBS burn severity classes for all inventoried fires occurring in CONUS during calendar year 2022 that do not meet standard MTBS size criteria. These data are published to augment the data that are available from the MTBS program. This product was produced using the methods of the Monitoring Trends in Burn Severity Program (MTBS), however these fires do not meet the size criteria for a standard MTBS assessment. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. MTBS typically maps fires using an initial assessment (immediately after the fire) or an extended assessment (peak of green the season after the fire) for low-biomass and high-biomass fires respectively. Refer to MTBS.gov for more information on MTBS methods and criteria. Standard MTBS mappings must meet the size criteria of at least 500 acres for the eastern states and territories and 1,000 acres for the western states and territories to be eligible for mapping. Undersized MTBS fires are those fires that do not meet the standard MTBS size criteria but are otherwise mapped using standard MTBS methodologies.

Several data sets are available and are described as follows:Burn Severity: This data set reflects the fire burn severity and classifies intensity into three categories. Data field verified and processed by the US Forest Service, Nez Perce and Clearwater National Forests, Kamiah, Idaho. Shape files and KMZ files are included. Files are named fisherfirepoly_barc_reclass2 or FisherBurnSeverityFINAL10_15_2015.Fire Boundary: Data shows the 2015 fire boundary. Data generated by US Forest Service. File name contains the FisherBoundaryHillslope Erosion: Within the fire boundary, hillslope erosion rates were identified. Data was organized into one of four categories; low (0-1 tons/acre), moderate (1-10 tons/acre), high (10-50 tons/acre), and very high (>50 tons/acre). Potential hillslope erosion was estimated using the GeoWEPP model. GeoWEPP is a geo-spatial interface for WEPP (Water Erosion Prediction Project). GeoWEPP Model Runs completed by Mary Miller, Michigan Tech Research Institute and USFS Rocky Mountain Research Station, Moscow, Idaho. Map Generated by Nikki Lane, Nez Perce Soil and Water Conservation District. June 2016. Files named FisherGeoWeppLand Cover: Land cover categories generated from National Land Cover Database (2011, USGS). Data processed by clipping NLCD by 2015 fire boundary. Categories include; Developed, Open Space - Mix of constructed materials, but mostly lawn grasses. Impervious surfaces < 20% of total cover. Deciduous Forest - >20% deciduous trees. Evergreen Forest - >20% evergreen trees. Mixed Forest – >20% trees with mix of deciduous and evergreen trees. Shrub/Scrub >20% shrub vegetation. Grassland/Herbaceous - >80% grass /other herbaceous vegetation. Pasture/Hay - Areas of grasses, legumes, or grass-legume mixtures planted for livestock grazing or the production of seed or hay crops, typically on a perennial cycle. Cultivated Crops Areas used for the production of annual crops and/or being annually tilled. Woody Wetlands – Soils that are periodically saturated or covered with water and contain >20% forest or shrubland vegetation. Emergent Herbaceous Wetlands - Soils that are periodically saturated or covered with water and vegetation is >80% herbaceous. Data generated by Nikki Lane, Nez Perce Soil and Water Conservation District. Jan 2016. Files are named FisherLandCover_FINAL_12_22_15.Land ownership: Land ownership layer for 2015 fire boundary. Source data is BLM Federal Land Status layer clipped to 2015 fire boundary. Bureau of Land Management (BLM); Surface Management Agency (Federal Land Status) layer. 2011. (http://insideidaho.org). Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. Ownership categories: BLM – Bureau of Land Management, Private – private, USFS – US Forest Service, IR – Indian Reservation, State – State of Idaho. Files are named FisherLandownershipFINAL1_6_16.Slope Class: Data generated from USGS Digital Elevation Model to identify slopes. Slopes were divided into three classes; 1-20, 21-40;>40. Data generated within 2015 fire boundary areas as identified by US Forest Service. Data generated by Nikki Lane, Nez Perce Soil and Water Conservation District. January 2016. Files are named fisslope or FisherSlopeClassesFINAL1_7_2016.Streams: Data shows streams (perennial and intermittent) within the Woodrat Complex 2015 fire boundary. Streams layer obtained from USGS. U.S. Rivers and Streams represent detailed rivers and streams in the United States. Data clipped and processed by Cody Dawes, Nez Perce Soil and Water Conservation District in January 2016. Files named FisherStreamNames or FisherStreams.Private land forested acres: Data shows privately owned forest acres burned during the 2015 event. Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. File name FisherForestedAcresOnPrivateLand

The National Park Service (NPS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image of burn severity classes for all NPS-requested burn severity fires, occurring in CONUS during calendar year 1998. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires which were not discernable from available imagery.

In the face of recent wildfires across the Western United States, it is essential that we understand both the dynamics that drive the spatial distribution of wildfire, and the major obstacles to modeling the probability of wildfire over space and time. However, it is well documented that the precise relationships of local vegetation, climate, and ignitions, and how they influence fire dynamics, may vary over space and among local climate, vegetation, and land use regimes. This raises questions not only as to the nature of the potentially nonlinear relationships between local conditions and the fire, but also the possibility that the scale at which such models are developed may be critical to their predictive power and to the apparent relationship of local conditions to wildfire. In this study we demonstrate that both local climate – through limitations posed by fuel dryness (CWD) and availability (AET) – and human activity – through housing density, roads, electrical infrastructure, and agriculture, play important roles in determining the annual probabilities of fire throughout California. We also document the importance of previous burn events as potential barriers to fire in some environments, until enough time has passed for vegetation to regenerate sufficiently to sustain subsequent wildfires. We also demonstrate that long-term and short-term climate variations exhibit different effects on annual fire probability, with short-term climate variations primarily impacting fire probability during periods of extreme climate anomaly. Further, we show that, when using nonlinear modeling techniques, broad-scale fire probability models can outperform localized models at predicting annual fire probability. Finally, this study represents a powerful tool for mapping local fire probability across the state of California under a variety of historical climate regimes, which is essential to avoided emissions modelling, carbon accounting, and hazard severity mapping for the application of fire-resistant building codes across the state of California.

Methods Climate data used in this study was drawn from the California Basin Characterization Model v8, and consists of monthly estimates of cumulative water deficit (CWD) and actual evapotranspiration (AET) from 1951 – 2016. This dataset represents a 270-m grid-based model of water balance calculations that incorporates climate inputs through PRISM data in addition to solar radiation, topographic shading, cloudiness, and soil properties to estimate evapotranspiration. Using these monthly values, we calculated the 1980 – 2009 mean CWD and AET normals, as well as mean deviations from those normals over a three-year period preceding each year of interest.

Cultivated and agricultural areas were identified using the 2016 National Land Cover Database data, which estimated dominant land cover throughout North America at 30-m resolution. The proportion of cultivated area and of water features that covered each 1-km pixel were then calculated by resampling to 1-km scale. Mean housing density data was drawn from the Integrated Climate and Land-Use Scenarios (ICLUS) dataset, which provides decadal estimates of housing density throughout the United states from 1970 - 2020. As precise continuous estimates of housing density were not available, housing density within each pixel was set to the mean of its class. Annual values were estimated from decadal data using linear interpolation. Ecoregions within California (hereafter referred to as “regions”) were delineated using CalVeg ecosystem provinces data.

Road data were drawn from 2018 TIGER layer data, and consisted of all primary and secondary roads across California. Electrical infrastructure data was drawn from 2020 transmission lines data. In both cases, the distance of nearest roads or transmission lines to each pixel were then calculated. Pixels which contained roads or electrical infrastructure were assigned distances of 0 km.

Fire history data was drawn from FRAP fire perimeter data, which incorporates perimeters of all known timber fires >10 acres (>0.04 km2), brush fires >30 acres (>0.12 km2), and grass fires >300 acres (>1.21 km2) from 1878 – 2017. Using this data, the presence of fire in each 1-km pixel was classified in a binary fashion (e.g. 1 for burned, 0 for unburned) for each year of interest. Due to computational limits and the quantity of data involved in this study, we did not calculate the burned area within each pixel, or distinguish pixels in which a single fire occurred in a given year from those in which multiple fires occurred. This data was also used to calculate the number of years since the most recent fire within any pixel, prior to each year in which fire probability was projected. Thus, locations in which no fire was observed throughout the fire record were treated as having gone a maximum of 100 years without a fire event for the purposes of model construction. These pixels comprised 29% - 33% of data annually (depending on year), and included both locations in which fire would not be expected (such as highly xeric regions) as well as locations in fire-prone areas in which no fire had been documented within the FRAP fire perimeter data used in this study.

The downloadable ZIP file contains an number of Esri shapefiles as described below. This data set provides the spatial information used to complete a post fire inventory and assessment for the 2015 Woodrat Fire in Idaho County, Idaho. The fire burned 6,471 acres within Idaho County, Idaho in August 2015. Data was prepared by several agencies including US Forest Service, USDA Natural Resources Conservation Service, US Geological Survey, and the Nez Perce Soil and Water Conservation District. Data was prepared for the North Central Idaho Wildfire Restoration Group as part of their efforts in preparing the North Central Idaho Wildfire Inventory and Assessment Report (2015).Several data sets are available and are described as follows:Burn Severity: This data set reflects the fire burn severity and classifies intensity into three categories. Data field verified and processed by the US Forest Service, Nez Perce and Clearwater National Forests, Kamiah, Idaho. Shape files and KMZ files are included. Files are named woodrat.Fire Boundary: Data shows the 2015 fire boundary. Data generated by US Forest Service. File name contains the words heat perimeter.Hillslope Erosion: Within the fire boundary, hillslope erosion rates were identified. Data was organized into one of four categories; low (0-1 tons/acre), moderate (1-10 tons/acre), high (10-50 tons/acre), and very high (>50 tons/acre). Potential hillslope erosion was estimated using the GeoWEPP model. GeoWEPP is a geo-spatial interface for WEPP (Water Erosion Prediction Project). GeoWEPP Model Runs completed by Mary Miller, Michigan Tech Research Institute and USFS Rocky Mountain Research Station, Moscow, Idaho. Map Generated by Nikki Lane, Nez Perce Soil and Water Conservation District. June 2016. Files named WoodratGeoWeppLand Cover: Land cover categories generated from National Land Cover Database (2011, USGS). Data processed by clipping NLCD by 2015 fire boundary. Categories include; Developed, Open Space - Mix of constructed materials, but mostly lawn grasses. Impervious surfaces < 20% of total cover. Deciduous Forest - >20% deciduous trees. Evergreen Forest - >20% evergreen trees. Mixed Forest – >20% trees with mix of deciduous and evergreen trees. Shrub/Scrub >20% shrub vegetation. Grassland/Herbaceous - >80% grass /other herbaceous vegetation. Pasture/Hay - Areas of grasses, legumes, or grass-legume mixtures planted for livestock grazing or the production of seed or hay crops, typically on a perennial cycle. Cultivated Crops Areas used for the production of annual crops and/or being annually tilled. Woody Wetlands – Soils that are periodically saturated or covered with water and contain >20% forest or shrubland vegetation. Emergent Herbaceous Wetlands - Soils that are periodically saturated or covered with water and vegetation is >80% herbaceous. Data generated by Nikki Lane, Nez Perce Soil and Water Conservation District. Jan 2016. Files are named WoodratLandcoverFINAL_12_22_15.Land ownership: Land ownership layer for 2015 fire boundary. Source data is BLM Federal Land Status layer clipped to 2015 fire boundary. Bureau of Land Management (BLM); Surface Management Agency (Federal Land Status) layer. 2011. (http://insideidaho.org). Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. Ownership categories: BLM – Bureau of Land Management, Private – private, USFS – US Forest Service, IR – Indian Reservation, State – State of Idaho. Files are named WoodratLandownershipFINAL1_6_16Slope Class: Data generated from USGS Digital Elevation Model to identify slopes. Slopes were divided into three classes; 1-20, 21-40;>40. Data generated within 2015 fire boundary areas as identified by US Forest Service. Data generated by Nikki Lane, Nez Perce Soil and Water Conservation District. January 2016. Files are named woodratpoly.Streams: Data shows streams (perennial and intermittent) within the Woodrat Complex 2015 fire boundary. Streams layer obtained from USGS. U.S. Rivers and Streams represent detailed rivers and streams in the United States. Data clipped and processed by Cody Dawes, Nez Perce Soil and Water Conservation District in January 2016. Files named WoodratStreams.Private land forested acres: Data shows privately owned forest acres burned during the 2015 event. Data generated by intersecting the National Land Cover Database, with the 2015 burn boundary and the BLM Land Status Database, then filtering for forest land cover and private land. Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. File name WoodratForestedAcresonPrivateLand.Post Fire Debris Flow Analysis for stream segments: This data set represents a post fire debris flow hazard analysis for stream segments within the 2015 fire boundary. Debris flow hazard classified as low (stream segments with low probability of debris flow occurrence and smallest debris flow volume), moderate (stream segments with relatively low probability of occurrence and larger debris flow volume estimates) and high (high probability of occurrence and large debris flow volume estimate). The analysis was completed by Dennis Staley, US Geological Survey. File names contain the wording wrt2015_segment.Post Fire Debris Flow Analysis for basins: This data set represents a post fire debris flow hazard analysis for basins within the 2015 fire boundary. Debris flow hazard classified as low ( basins with low probability of debris flow occurrence and smallest debris flow volume), moderate (basins with relatively low probability of occurrence and larger debris flow volume estimates) and high (high probability of occurrence and large debris flow volume estimate). The analysis was completed by Dennis Staley, US Geological Survey. File names contain the wording wrt2015_basin.Planting Groups: Data layer contains forest planting groups as identified by USDA Natural Resources Conservation Service. Data reflects private lands within the 2015 burned area that were forest land cover. Data generated by Frank Gariglio and Brian Gardner, USDA Natural Resources Conservation Service. GIS layer processed by Nez Perce Soil and Water Conservation District. Data layer generated January 2016. Files named woodratplantinggroups. Planting Group Descriptions:Group 0 - burned areas that are assumed to be PIPO (Pinus Ponderosa)Group 1 - PIPO (Pinus ponderosa) onlyGroup 2 - PIPO (Pinus ponderosa) dominant, with some PSMEC (Pseudotsuga menziesii (Mirb.) Franco var. glauca (Beissn.)) Rocky Mountain Douglas-firGroup 3 - PSMEG( Pseudotsuga menziesii) Rocky Mtn Douglas Fir and PIPO (Pinus ponderosa) with some LAOC (Larix occidentalis Nutt.) western larchGroup 4 - PSMEG (Pseudotsuga menzeisii), LAOC (Larix occidentalis) and possibly PIPO (Pinus ponderosa) and PICO (Pinus contorta) Lodgepole PineGroup 5 - PSMEG (Pseudotsuga menzeisii), LAOC (Larix occidentalis) and possible PIEN (Picea engelmannii Parry ex Engelm.) Engelmann spruce and PICO (Pinus contorta) Lodgepole Pine

Several data sets are available and are described as follows:Burn Severity: This data set reflects the fire burn severity and classifies intensity in to three categories. Data field verified and processed by the US Forest Service, Nez Perce and Clearwater National Forests, Orofino, Idaho. Shape files and KMZ files are included. Files are named SlideBurnSeverityFire Boundary: Data shows the 2015 fire boundary. Data generated by US Forest Service. File name: Slide Fire Boundary or contains the words heat perimeter.Hillslope Erosion: Within the fire boundary, hillslope erosion rates were identified. Data was organized into one of four categories; low (0-1 tons/acre), moderate (1-10 tons/acre), high (10-50 tons/acre), and very high (>50 tons/acre). Potential hillslope erosion was estimated using the GeoWEPP model. GeoWEPP is a geo-spatial interface for WEPP (Water Erosion Prediction Project). GeoWEPP Model Runs completed by Mary Miller, Michigan Tech Research Institute and USFS Rocky Mountain Research Station, Moscow, Idaho. Map Generated by Nikki Lane, Nez Perce Soil and Water Conservation District. June 2016. Files named SlideGeoWeppLand Cover: Land cover categories generated from National Land Cover Database (2011, USGS). Data processed by clipping NLCD by 2015 fire boundary. Fire boundary generated from InciWeb. Categories include; Developed, Open Space - Mix of constructed materials, but mostly lawn grasses. Impervious surfaces < 20% of total cover. Deciduous Forest - >20% deciduous trees. Evergreen Forest - >20% evergreen trees. Mixed Forest – >20% trees with mix of deciduous and evergreen trees. Shrub/Scrub >20% shrub vegetation. Grassland/Herbaceous - >80% grass /other herbaceous vegetation. Pasture/Hay - Areas of grasses, legumes, or grass-legume mixtures planted for livestock grazing or the production of seed or hay crops, typically on a perennial cycle. Cultivated Crops Areas used for the production of annual crops and/or being annually tilled. Woody Wetlands – Soils that are periodically saturated or covered with water and contain >20% forest or shrubland vegetation. Emergent Herbaceous Wetlands Soils that are periodically saturated or covered with water and vegetation is >80% herbaceous. Data generated by Nikki Lane, Nez Perce soil and Water Conservation District. Jan 2016. Files are named SlideLandCoverFINAL12_24_2015Land Ownership: Ownership layer for 2015 fire boundary. Source data is BLM Federal Land Status layer clipped to 2015 fire boundary obtained from InciWeb. Bureau of Land Management (BLM); Surface Management Agency (Federal Land Status) layer. 2011. (http://insideidaho.org). Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. Ownership categories: BLM – Bureau of Land Management, Private – private, USFS – US Forest Service, IR – Indian Reservation, State – State of Idaho. Files are named SlideLandownerhipFINAL1_6_16Slope Class: Data generated from USGS Digital Elevation Model to identify slopes. Slopes were divided into 3 classes; 1-20, 21-40;>40. Data generated within 2015 fire boundary areas as identified by US Forest Service. Data generated by Nikki Lane, Nez Perce Soil and Water Conservation District. January 2016. Files are named slidepoly or SlideSlopeClassFINAL1_7_2016Streams: Data shows streams (perennial and intermittent) within the Wash Complex 2015 fire boundary. Streams layer obtained from USGS. U.S. Rivers and Streams represent detailed rivers and streams in the United States. Data clipped and processed by Cody Dawes, Nez Perce Soil and Water Conservation District in January 2016. Files named SlideStreamNames or SlideStreamsPrivateForestlandsBySlope: Data shows three slope classes (0-20, 20-40, >40) on private owned forestlands. Data generated from BLM ownership layer, USGS Digital Elevation Model, and the National Land Cover Database. Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. File name SlideForestedAcresOnPrivateLandBySlopePrivate land forested acres: Data shows privately owned forest acres burned during the 2015 event. Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. File name SlideForestedAcresOnPrivateLandPost Fire Debris Flow Analysis for stream segments: USGS post fire debris flow hazard analysis for stream segments within the 2015 fire boundary. Debris flow hazard classified as low (stream segments with low probability of debris flow occurrence and smallest debris flow volume), moderate (stream segments with relatively low probability of occurrence and larger debris flow volume estimates) and high (high probability of occurrence and large debris flow volume estimate). File names contain the wording slide2015_segment_dfpredictions_25yr or Slide25yrSegmentHazardRatingFINAL12_22_2015.Post Fire Debris Flow Analysis for basins: USGS post fire debris flow hazard analysis for basins within the 2015 fire boundary. Debris flow hazard classified as low (basins with low probability of debris flow occurrence and smallest debris flow volume), moderate (basins with relatively low probability of occurrence and larger debris flow volume estimates) and high (high probability of occurrence and large debris flow volume estimate). File names contain the wording slide2015_basin_dfpredictions_25yr or Slide25yrBasinHazardRatingFINAL12_22_2015.

This map layer is a thematic raster image of MTBS burn severity classes for all inventoried fires occurring in CONUS during calendar year 2022 that do not meet standard MTBS size criteria. These data are published to augment the data that are available from the MTBS program. This product was produced using the methods of the Monitoring Trends in Burn Severity Program (MTBS), however these fires do not meet the size criteria for a standard MTBS assessment. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. MTBS typically maps fires using an initial assessment (immediately after the fire) or an extended assessment (peak of green the season after the fire) for low-biomass and high-biomass fires respectively. Refer to MTBS.gov for more information on MTBS methods and criteria. Standard MTBS mappings must meet the size criteria of at least 500 acres for the eastern states and territories and 1,000 acres for the western states and territories to be eligible for mapping. Undersized MTBS fires are those fires that do not meet the standard MTBS size criteria but are otherwise mapped using standard MTBS methodologies.

Several data sets are available and are described as follows:Burn Severity: This data set reflects the fire burn severity and classifies intensity in to three categories. Data field verified and processed by the US Forest Service, Nez Perce and Clearwater National Forests, Orofino, Idaho. Shape files and KMZ files are included. Files are named ClearwaterComplexFireBurnSeverity or ClearwaterComplex_SBS.Fire Boundary: Data shows the 2015 fire boundary. Data generated by US Forest Service. File name: 20150826_0002_MDT_ClearwaterComplex_IR_HeatPerimeter or Clearwater Complex Fire Boundary.Hillslope Erosion: Within the fire boundary, hillslope erosion rates were identified. Data was organized into one of four categories; low (0-1 tons/acre), moderate (1-10 tons/acre), high (10-50 tons/acre), and very high (>50 tons/acre). Potential hillslope erosion was estimated using the GeoWEPP model. GeoWEPP is a geo-spatial interface for WEPP (Water Erosion Prediction Project). GeoWEPP Model Runs completed by Mary Miller, Michigan Tech Research Institute and USFS Rocky Mountain Research Station, Moscow, Idaho. Map Generated by Nikki Lane, Nez Perce Soil and Water Conservation District. June 2016. Files named ClearwaterComplexGeoWeppLand Cover: Land cover categories generated from National Land Cover Database (2011, USGS). Data processed by clipping NLCD by 2015 fire boundary. Fire boundary generated from InciWeb. Categories include; Developed, Open Space - Mix of constructed materials, but mostly lawn grasses. Impervious surfaces < 20% of total cover. Deciduous Forest - >20% deciduous trees. Evergreen Forest - >20% evergreen trees. Mixed Forest – >20% trees with mix of deciduous and evergreen trees. Shrub/Scrub >20% shrub vegetation. Grassland/Herbaceous - >80% grass /other herbaceous vegetation. Pasture/Hay - Areas of grasses, legumes, or grass-legume mixtures planted for livestock grazing or the production of seed or hay crops, typically on a perennial cycle. Cultivated Crops Areas used for the production of annual crops and/or being annually tilled. Woody Wetlands – Soils that are periodically saturated or covered with water and contain >20% forest or shrubland vegetation. Emergent Herbaceous Wetlands Soils that are periodically saturated or covered with water and vegetation is >80% herbaceous. Data generated by Nikki Lane, Nez Perce soil and Water Conservation District. Jan 2016. Files are named ClearwaterComplexLandCoverFINAL1_5_15Land Ownership: Ownership layer for 2015 fire boundary. Source data is BLM Federal Land Status layer clipped to 2015 fire boundary obtained from InciWeb. Bureau of Land Management (BLM); Surface Management Agency (Federal Land Status) layer. 2011. (http://insideidaho.org). Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. Ownership categories: BLM – Bureau of Land Management, Private – private, USFS – US Forest Service, IR – Indian Reservation, State – State of Idaho. Files are named ClearwaterComplexOwnershipFINAL1_6_2016Slope Class: Data generated from USGS Digital Elevation Model to identify slopes. Slopes were divided into 3 classes; 1-20, 21-40;>40. Data generated within 2015 fire boundary areas as identified by US Forest Service. Data generated by Nikki Lane, Nez Perce Soil and Water Conservation District. January 2016. Files are named ClearwaterSlopeClassFinal or ClearwaterComplexSlopeClassFINAL_1_7_16.Streams: Data shows streams (perennial and intermittent) within the Wash Complex 2015 fire boundary. Streams layer obtained from USGS. U.S. Rivers and Streams represent detailed rivers and streams in the United States. Data clipped and processed by Cody Dawes, Nez Perce Soil and Water Conservation District in January 2016. Files named ClearwaterComplexStreamNamesPrivateForestlandsBySlope: Data shows three slope classes (0-20, 20-40, >40) on private owned forestlands. Data generated from BLM ownership layer, USGS Digital Elevation Model, and the National Land Cover Database. Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. File name ClearwaterForestedAreaonPrivateLandBySlope or ClearwaterComplexPrivateForestLandSlopeClassesFINAL_1_7_16.Private land forested acres: Data shows privately owned forest acres burned during the 2015 event. Data generated by Cody Dawes, Nez Perce Soil and Water Conservation District. January 2016. File name ClearwaterComplexForestedAcresOnPrivateLandPost Fire Debris Flow Analysis for stream segments: USGS post fire debris flow hazard analysis for stream segments within the 2015 fire boundary. Debris flow hazard classified as low (stream segments with low probability of debris flow occurrence and smallest debris flow volume), moderate (stream segments with relatively low probability of occurrence and larger debris flow volume estimates) and high (high probability of occurrence and large debris flow volume estimate). File names contain the wording clw2015_segment_dfpredictions_25yr or ClearwaterComplexSegmentHazard25yr.Post Fire Debris Flow Analysis for basins: USGS post fire debris flow hazard analysis for basins within the 2015 fire boundary. Debris flow hazard classified as low (basins with low probability of debris flow occurrence and smallest debris flow volume), moderate (basins with relatively low probability of occurrence and larger debris flow volume estimates) and high (high probability of occurrence and large debris flow volume estimate). File names contain the wording clw2015_basin_dfpredictions_25yr or ClearwaterComplex25YRbasinVolume.