Sunday, 6 January 2019
Hall 4 (Phoenix Convention Center - West and North Buildings)
Diablo Winds are a close relative to the more commonly known Santa Ana Winds. Both wind classifications contain strong off-shore flow at the surface, that can be enhanced by topographical effects, with the Diablo Winds occurring in the San Francisco Bay area, as opposed to southern California, the home of the Santa Ana’s. The Diablo Winds have proven to be particularly destructive, when coupled with significant wildfire events, two examples being the Wine Country Fires in October 2017 and the Oakland Firestorm occurring in October 1991. Combined, these two events alone contributed to 56 deaths, over 10,000 structures destroyed, and approximately $90 billion in damage. Historically, similar events occurred in 1923 and 1964, but little to no research has been conducted to classify these winds, and their synoptic evolution and forcing throughout history. This research presents a formal definition of Diablo Winds, based on an observational archive utilizing Automated Surface Observational Systems (ASOS), Radio Automated Weather Systems (RAWS), and the Oakland sounding. This definition was then projected back in time, to determine an inter-annual frequency, determining that these winds occur predominantly in the Fall and Winter months. Additionally, synoptic composites were generated utilizing the higher resolution North American Regional Re-analysis, to determine the synoptic evolution. The composites indicated a strong high pressure system pushing into the Pacific Northwest, interacting with a thermal trough extending northward into the San Francisco Bay area, providing east to northeasterly flow over the Sierra Nevada and Berkeley Hills, contributing to possible mountain wave generation. Finally, using the composites and the definition obtained, the definition was projected back to 1948, using the NCEP/NCAR Re-analysis dataset. This provided a complete historical record of Diablo Winds, whose frequency was correlated to other climatological variability such as the El Nino Southern Oscillation, Pacific Decadal Oscillation, and the Madden Julian Oscillation.
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