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Miller, Douglas E.

Publications and source records attributed to Miller, Douglas E..

GEFSv12 High- and Low-Skill Day-10 Tornado Forecasts

Abstract On average, modern numerical weather prediction forecasts for daily tornado frequency exhibit no skill beyond day 10. However, in this extended-range lead window, there are particular model cycles that have exceptionally high forecast skill for tornadoes because of their ability to correctly simulate the future synoptic pattern. Here, model initial conditions that produced a more skillful forecast for tornadoes over the United States were exploited while also highlighting potential causes for low-skill cycles within the Global Ensemble Forecasting System, version 12 (GEFSv12). There were 88 high-skill and 91 low-skill forecasts in which the verifying day-10 synoptic pattern for tornado conditions revealed a western U.S. thermal trough and an eastern U.S. thermal ridge, a favorable configuration for tornadic storm occurrence. Initial conditions for high skill forecasts tended to exhibit warmer sea surface temperatures throughout the tropical Pacific Ocean and Gulf of Mexico, an active Madden–Julian oscillation, and significant modulation of Earth-relative atmospheric angular momentum. Low-skill forecasts were often initialized during La Niña and negative Pacific decadal oscillation conditions. Significant atmospheric blocking over eastern Russia—in which the GEFSv12 overforecast the duration and characteristics of the downstream flow—was a common physical process associated with low-skill forecasts. This work helps to increase our understanding of the common causes of high- or low-skill extended-range tornado forecasts and could serve as a helpful tool for operational forecasters. Significance Statement This research provides a framework for the anticipation of a more (or less) skillful 10-day tornado forecast in an operational numerical weather prediction system. High-skill forecasts were associated with substantial tropical convection and warm sea surface temperature throughout the Pacific Ocean and Gulf of Mexico, whereas the underlying cause of low-skill forecasts were typically associated with a blocking anticyclone over eastern Russia. These findings are important because they permit increased or decreased confidence in a long-range forecast of tornado occurrence based on a dynamical prediction system.

Meteorology & Atmospheric Sciences↗

Madden-Julian oscillation influences United States springtime tornado and hail frequency

The Madden–Julian Oscillation (MJO) is the dominant mode of intraseasonal variability in the tropics and has a documented influence on extratropical extreme weather through modulation of synoptic atmospheric conditions. MJO phase has been correlated with anomalous tornado and severe hail frequency in the United States (US). However, the robustness of this relationship is unsettled, and the variability of physical pathways to modulation is poorly understood, despite the socioeconomic impacts that tornadoes and hail evoke. We approached this problem using pentad MJO indices and practically perfect severe weather hindcasts. MJO lifecycles were cataloged and clustered to document variability and potential pathways to enhanced subseasonal tornado and hail predictability. Statistically significant increases in US tornado and hail probabilities were documented 3–4 weeks following the period of the strongest upper-level divergence for the 53 active MJO events that propagated past the Maritime continent, contrasting with the 47 MJO events that experienced the barrier effect, during boreal spring 1979–2019. The 53 MJO events that propagated past the Maritime continent revealed three prevailing MJO evolutions—each containing unique pathways and modulation of US tornado and hail frequency—advancing our knowledge and capability to anticipate these hazards at extended lead times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗