2.1.2 CG lightning and fire weather simulation with WRF
CG lightning strikes and fire weather conditions are important factors affecting fire behaviors and are highly dynamic across space and time. Due to the lack of weather stations and very coarse resolution of climatology data in the remote tundra region, we adopted the Weather Research and Forecast (WRF) model as a downscaling tool to simulate CG lightning probability and near-surface weather conditions at 5km resolution. We used the National Centers for Environmental Prediction Final Operational Global Analysis data (NCEP FNL; National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce, 2000) at 1-degree resolution and 6-hour interval for model initialization. We ran two-way nested simulation for Alaska following the parameterization settings from He and Loboda (2020).
Considering the computing complexity of WRF, we sampled years with different fire season severities between 2001 and 2019 and ran WRF simulations for all the detected fire events from these years for further modeling efforts. We adopted the empirical-dynamical modeling framework developed by He and Loboda (2020) to model the probability of CG lightning strikes using WRF simulated variables and random forest (RF) algorithm. CG lightning probability was then used as input data for representing ignition sources of wildfires. To describe fire weather conditions that affect burnings in the tundra, we extracted near-surface weather conditions, including air temperature, relative humidity (RH), wind speed, and 24-hr precipitation. We then calculated the Canadian Forest Fire Weather Index System (CFFWIS; Van Wagner, 1987) using WRF-simulated variables. The CFFWIS tracks the moisture content of distinct fuel layers with three fuel moisture codes – Fine Fuel Moisture Code (FFMC), Drought Moisture Code (DMC), and Drought Code (DC). The three fire behavior indices – Initial Spread Index (ISI), Buildup Index (BUI), and Fire Weather Index (FWI) – provide numeric ratings of the fire spread process. Though not explicitly designed for the tundra, this system is suitable for describing fire weather conditions and quantifying fire danger in the ecosystems of the HNL (French et al., 2015; Mölders, 2010).