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Title: Spring Onset Predictability in the North American Multimodel Ensemble

Journal Article · · Journal of Geophysical Research: Atmospheres
DOI:https://doi.org/10.1029/2018JD028597· OSTI ID:1441242

Abstract The predictability of spring onset is assessed using an index of its interannual variability (the “extended spring index” or SI‐x) and output from the North American Multimodel Ensemble reforecast experiment. The input data to compute SI‐x were treated with a daily joint bias correction approach, and the SI‐x outputs computed from the North American Multimodel Ensemble were postprocessed using an ensemble model output statistic approach—nonhomogeneous Gaussian regression. This ensemble model output statistic approach was used to quantify the effects of training period length and ensemble size on forecast skill. The lead time for predicting the timing of spring onset is found to be from 10 to 60 days, with the higher end of this range located along a narrow band between 35°N to 45°N in the eastern United States. Using continuous rank probability scores and skill score (SS) thresholds, this study demonstrates that ranges of positive predictability of SI‐x fall into two categories: 10–40 and 40–60 days. Using higher skill thresholds (SS equal to 0.1 and 0.2), predictability is confined to a lower range with values around 10–30 days. The postprocessing work using joint bias correction improves the predictive skill for SI‐x relative to the untreated input data set. Using nonhomogeneous Gaussian regression, a positive change in the SS is noted in regions where the skill with joint bias correction shows evidence of improvement. These findings suggest that the start of spring might be predictable on intraseasonal time horizons, which in turn could be useful for farmers, growers, and stakeholders making decisions on these time scales.

Sponsoring Organization:
USDOE
OSTI ID:
1441242
Alternate ID(s):
OSTI ID: 1441243
Journal Information:
Journal of Geophysical Research: Atmospheres, Journal Name: Journal of Geophysical Research: Atmospheres Vol. 123 Journal Issue: 11; ISSN 2169-897X
Publisher:
American Geophysical Union (AGU)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 3 works
Citation information provided by
Web of Science

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