Based on the Cumulative Weather Severity Index (WSI) threshold for mallards, the team of researchers have been evaluating if the Cumulative WSI differed among decades and the effect of atmospheric teleconnections on annual changes in WSI from 1950– 2008. Severity of weather has been mild during the 2000s when compared to previous decades and differed substantially from the more severe 1960s and 1970s. Most winters during these decades were typified by cold and snowy conditions known to cause migration of mallards to southern wintering grounds. Further, the Arctic Oscillation Index explained substantial variation in the Cumulative WSI during El Niño and La Niña episodes but not when the Oceanic Niño Index was Neutral. Because we can forecast El Niño and La Niña episodes nearly 3 months in advance of their occurrence, we can develop season-long forecasts of annual distributions of ducks in the Mississippi and Atlantic Flyways. However, when the Oceanic Niño Index is Neutral this greatly reduces our ability to produce a long-term forecast.
El Niño and La Niña winters are typified by specific weather patterns, but frequency and intensity of these weather patterns can be modified greatly by the Arctic Oscillation Index. We determined that severity of weather (indexed by Cumulative WSI) increased with decreasing Arctic Oscillation Index during winters with El Niño and La Niña conditions. Increased weather severity likely resulted from decreases in temperature and increased snowfall at northern and mid-latitudes of North America that generally accompany a decreasing Arctic Oscillation Index.
Historically, the Arctic Oscillation Index could only be reliably predicted approximately 7 days in advance, but recent climate research indicates that likelihood of a negative Arctic Oscillation Index increases with increasing October and November snow cover in western Siberia (called the Snow Advance Index). Thus, the potential for severe weather and increasing Cumulative WSI can be predicted near the end of October. Initial analyses also suggest that the Snow Advance Index developed by Judah Cohen (Atmospheric and Environmental Research), correlates well with Cumulative WSI values for mid-latitudes during November – January.
For more information on using Siberian snow to forecast North American winter weather see: