The methodology used by the First Street Foundation Wildfire Model (FSF-WFM) to compute estimates of the 30-year, climate-adjusted aggregate wildfire hazard for the contiguous United States at 30 m horizontal resolution is presented. The FSF-WFM integrates several existing methods from the wildfire science community and implements computationally efficient and scalable modeling techniques to allow for new high-resolution, CONUS-wide hazard generation. Burn probability, flame length, and ember spread for the years 2022 and 2052 are computed from two ten-year representative Monte Carlo simulations of wildfire behavior, utilizing augmented LANDFIRE fuel estimates updated with all the available disturbance information. FSF-WFM utilizes ELMFIRE, an open-source, Rothermel-based wildfire behavior model, and multiple US Federal Government open data sources to drive the simulations. LANDFIRE non-burnable fuel classes within the wildland–urban interface (WUI) are replaced with fuel estimates from machine-learning models, trained on data from historical fires, to allow the propagation of wildfire through the WUI in the model. Historical wildfire ignition locations and NOAA’s hourly time series of surface weather at 2.5 km resolution are used to drive ELMFIRE to produce wildfire hazards representative of the 2022 and 2052 conditions at 30 m resolution, with the future weather conditions scaled to the IPCC CMIP5 RCP4.5 model ensemble predictions. Winds and vegetation were held constant between the 2022 and 2052 simulations, and climate change’s impacts on the future fuel conditions are the main contributors to the changes observed in the 2052 results. Non-zero wildfire exposure is estimated for 71.8 million out of 140 million properties across CONUS. Climate change impacts add another 11% properties to this non-zero exposure class over the next 30 years, with much of this change observed in the forested areas east of the Mississippi River. “Major” aggregate wildfire exposure of greater than 6% over the 30-year analysis period from 2022 to 2052 is estimated for 10.2 million properties. The FSF-WFM represents a notable contribution to the ability to produce property-specific, climate-adjusted wildfire risk assessments in the US.

Changing environmental conditions are driving worsening flood events, with consequences for counties, cities, towns, and local communities. To understand individual flood risk within this changing climate, local community resiliency and infrastructure impacts must also be considered. Past research has attempted to capture this but has faced several limitations. This study provides a nation-wide model of community flooding impacts within the United States currently and in 30 years through the use of high-resolution input data (parcel-level), multi-source flood hazard information (four major flood types), multi-return period hazard information (six return periods), operational threshold integration, and future-facing projections. Impacts are quantified here as the level of flooding relative to operational thresholds. This study finds that over the next 30 years, millions of additional properties will be impacted, as aspects of risk are expected to increase for residential properties by 10%, roads by 3%, commercial properties by 7%, critical infrastructure facilities by 6%, and social infrastructure facilities by 9%. Additionally, certain counties and cities persistently display impact patterns. A high-resolution model capturing aspects of flood risk as related to community infrastructure is important for an understanding of overall community risk.

Accurate representation of fire emissions and smoke transport is crucial for current and future wildfire-smoke projections. We present a flexible modeling framework for emissions sourced from the First Street Foundation Wildfire Model (FSF-WFM) to provide a national map for near-surface smoke conditions exceeding the threshold for unhealthy concentrations of particulate matter at or less than 2.5 µm, or PM_2.5. Smoke yield from simulated fires is converted to emissions transported by the National Oceanic and Atmospheric Administration’s HYSPLIT model. We present a strategy for sampling from a simulation of ~65 million individual fires, to depict the occurrence of “unhealthy smoke days” defined as 24-h average PM_2.5 concentration greater than 35.4 µg/m³ from HYSPLIT. The comparison with historical smoke simulations finds reasonable agreement using only a small subset of simulated fires. The total amount of PM_2.5 mass-released threshold of 10¹⁵ µg was found to be effective for simulating the occurrence of unhealthy days without significant computational burden.