7B.3 Using North American Regional Reanalysis Composites to Identify and Forecast Fire-Effective Synoptic Features in the Southern Great Plains

Wednesday, 15 January 2020: 8:45 AM
151A (Boston Convention and Exhibition Center)
Matthew R. Beitscher, MS, Saint Louis Univ., St. Louis, MO; and T. T. Lindley, C. M. Gravelle, and C. Graves

Previous research has shown that wildland fire outbreaks in grass-dominated fuels on the southern Great Plains are driven by anomalous atmospheric features. One key feature of these outbreaks is the presence of a low-level thermal ridge (LLTR); a tongue of warmer temperatures from the surface to 850 hPa that is bounded by the extent of 850-hPa temperature standardized anomalies and located ahead of a mid-latitude cyclone’s cold front. In this study, the meteorological conditions with 28 southern Great Plains wildland fire outbreaks occurring between 2005 and 2018 in the presence of a LLTR are analyzed using the North American Regional Reanalysis dataset to develop a "system-relative" composite. The results show the coupling between a midlevel jet streak and a dryline-cold front bounded LLTR. This suggests that dryline dynamics and turbulent mixing may be the atmospheric processes that support these outbreaks. Standardized anomaly composites of boundary-layer temperature, moisture, and PMSL are also calculated to statistically determine how the LLTR fields departed from climatology in the wildland fire outbreaks. To expand upon previous research, the reliability of the wildland fire outbreak composite and its most distinguishing fields are presented to identify differences in statistically similar environments between days when outbreaks occur versus days when they do not occur to identify "false alarm" cases. This information provides forecasters the ability to analyze the composite's statistically significant fields in model output for their similarity to historical wildland fire outbreaks.
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