2026-09-22T10:14:26Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/115479 2023-07-11 col_2142_5131 col_2142_14839 com_2142_5130 com_2142_14838 com_2142_13459 com_2142_8903

Wang, Zhuo Rauber, Robert Sriver, Ryan Walsh, John 2022-05 application/pdf en text Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms The student, Kevin Boyd, accepted the attached license on 2022-04-18 at 11:54. The student, Kevin Boyd, submitted this Thesis for approval on 2022-04-18 at 12:02. This Thesis was approved for publication on 2022-04-26 at 17:19. DSpace SAF Submission Ingestion Package generated from Vireo submission #17747 on 2022-11-11 at 13:15:32 A genesis potential index for polar lows Boyd, Kevin Patrick 2022-04-26 Polar Lows Statistical Modelling Arctic Climate Polar lows (PL) are intense maritime mesocyclones that develop during marine cold-air outbreaks events over the high-latitudes. The impacts posed by these systems to humans and the broader environment demand a robust understanding of the environmental factors that promote PL formation, and in turn, skillful prediction of PL activity. We hypothesize that the variability of PL activity is associated with some key, large-scale climate variables skewed towards “extreme” values, which can provide predictable information on PL activity beyond the synoptic time scale. A PL genesis potential index (PGI) is developed that relates the climatological spatial distribution of PL genesis frequency and key climate variables in a Poisson regression framework. The optimal set of predictors consists of a static stability parameter and an environmental baroclinicity parameter. The optimal predictor categories are shown to be robust across different reanalyses and PL track datasets. The PGI well represents the observed spatial distribution and seasonal cycle of PL genesis frequency and also captures the interannual variability of PL activity skillfully. The effects of the Arctic Oscillation (AO), El Niño-Southern Oscillation (ENSO), and other climate modes on the interannual variability of PL activity are explored, and the application of the PGI to subseasonal to seasonal prediction of PL activity is briefly discussed. Thesis eng https://hdl.handle.net/2142/115479 Copyright 2022 Kevin Boyd M.S. Thesis Atmospheric Sciences University of Illinois at Urbana-Champaign Atmospheric Sciences