Integrating Satellite Fire Detections with Coupled Fire-Weather-Smoke Forecasting System WRFx for Improved Wildland Fire Decision Making
Abstract
The United States has entered a new era of increasing wildfire frequency and intensity, which has culminated in a number of devastating wildfire seasons over the past decade. The landscape has become more fire-prone due to climate change and urban development, which has resulted in steeply rising fire-suppression costs. There is a significant need for management decisions that are based on a multifaceted analysis of risks and benefits associated with wildfires and prescribed burns. As a result, new advanced decision support tools that integrate satellite/aerial remote sensing with economic data, with a coupled fire, weather, fuel and smoke modeling framework are needed.
The primary goal of our project is to significantly reduce the hazardous risks associated with wildland fires and their management through the development and deployment of new decision support and situational awareness tools. These new tools will focus on rendering the spatial and temporal variability of weather and fuel conditions, in addition to the two-way interactions between fire behavior, local weather, and smoke, which do not currently exist in operational fire management. This project aims to improve situational awareness and support decisions, especially for wildland fire incidents that are impacted by significant weather variability. Such incidents are difficult to handle with the current system, which utilizes hourly weather station data often located miles away from the fire. Through a seamless integration of weather data, surface fuel moisture observations, satellite fire detections, operational numerical weather prediction models and a state-of-the-art high-resolution coupled fire-atmosphere smoke modeling, the project will result in the deployment of novel integrated decision support tools that are designed to reduce the risk associated with wildfire management. The new system will provide a 3-D spatial representation of essential elements that are affecting fire behavior (i.e. weather conditions and dead-fuel moisture), fire spread and smoke. This system will take advantage of advanced assimilation techniques of MODIS and VIIIRS data, and will be extended to GOES-16/17 data with 5-minute refresh. This presentation will report on the progress of the above project.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.A53S2911F
- Keywords:
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- 0305 Aerosols and particles;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 3360 Remote sensing;
- ATMOSPHERIC PROCESSES;
- 4301 Atmospheric;
- NATURAL HAZARDS;
- 4337 Remote sensing and disasters;
- NATURAL HAZARDS