Affiliation:
1. Civil and Environmental Engineering, Syracuse University
2. Instituto Geográfico Universitario, Universidad Autónoma de Santo Domingo, Santo Domingo, Dominican Republic.
3. Department of Biological and Environmental Engineering, Cornell University
Abstract
AbstractThe literature has established dozens of potential predictive indices (PIs) of anomalous warm season precipitation in the Midwestern US that could have utility in subseasonal to seasonal (S2S) forecasts This analysis posits that these predictive indices relate to one of three “modes of action” that work in tandem to drive anomalous hydroclimatic circulation into the continental interior. These include contributions from the (1) geostrophic mass flux, (2) ageostrophic mass flux, and (3) atmospheric moisture supply, and represent semi-independent, interactive forcings on S2S precipitation variability. This study aggregates 24 PIs from the literature that are related to the three modes of action. Using an interpretable machine learning algorithm that accounts for non-linear and interactive responses in a noisy predictive space, we evaluate the relative importance of PIs in predicting S2S precipitation anomalies from March-September. Physical mechanisms driving PI skill are confirmed using composite analysis of atmospheric fields related to the three modes of action. In general, PIs associated with ageostrophic mass flux anomalies are important in early summer, while PIs associated with Atlantic-sourced atmospheric moisture supply are important in late summer. At a two month lead, PIs associated with continental-scale thermodynamic processes are more important relative to PIs associated with local convective phenomena. PIs representing geostrophic mass flux anomalies are also critical throughout the warm season, in real-time and at a 1-2 month lag, but particularly in during transitional months (spring/fall). Several new PIs describing zonal and meridional asymmetry in hemispherical thermal gradients emerge as highly important, with implications for both S2S forecasting and climate change.
Publisher
American Meteorological Society
Cited by
3 articles.
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