An Examination of Extreme Fire Behavior and its Impact on Smoke Injection Altitude using Remote Sensing and Meteorological Data

Abstract:

A variety of regional smoke forecasting applications are currently available to identify air quality, visibility, and societal impacts during large fire events. However, these systems typically assume persistent fire activity, and therefore can have large errors before, during, and after short-term periods of extreme fire behavior. This study employs a wide variety of ground, airborne, and satellite observations, including data collected during a major NASA airborne and field campaign, to examine the conditions required for both extreme spread and pyrocumulonimbus (pyroCb) development. Results highlight the importance of upper-level and nocturnal meteorology, as well as the limitations of traditional fire weather indices. Increasing values of fire radiative power (FRP) at the pixel and sub-pixel level are shown to systematically correspond to higher altitude smoke plumes, and an increased probability of injection above the boundary layer. Lidar data collected during the 2013 Rim Fire, one of the most severe fire events in California’s history, show that high FRP observed during extreme spread can facilitate long-distance smoke transport, but fails to loft smoke to the altitude of a large pyroCb. The most extreme fire spread was also observed on days without pyroCb activity or significant regional convection. By incorporating additional fire events across North America, conflicting hypotheses surrounding the primary source of moisture during pyroCb development are examined. The majority of large pyroCbs, and therefore the highest direct injection altitude of smoke particles, is shown to occur with conditions very similar to those that produce dry thunderstorms. The current suite of automated forecasting applications predict only general trends in fire behavior, and specifically do not predict (1) extreme fire spread events and (2) injection of smoke to high altitudes. While (1) and (2) are related, results show that they are not predicted by the same set of conditions and variables. The combination of meteorology from numerical forecast models and satellite observations exhibits great potential for improving regional forecasts of fire behavior and smoke production in automated systems, especially in remote areas where detailed observations are unavailable