Seasonal Prediction of Bottom Temperature on the Northeast U.S.
The Northeast U.S. shelf (NES) is an oceanographically dynamic marine
ecosystem and supports some of the most valuable demersal fisheries in
the world. A reliable prediction of NES environmental variables,
particularly ocean bottom temperature, could lead to a significant
improvement in demersal fisheries management. However, the current
generation of climate model-based seasonal-to-interannual predictions
exhibit limited prediction skill in this continental shelf environment.
Here we have developed a hierarchy of statistical seasonal predictions
for NES bottom temperatures using an eddy-resolving ocean reanalysis
dataset. A simple, damped local persistence prediction model produces
significant skill for lead times up to ~6 months in the
Mid-Atlantic Bight and up to ~11 months in the Gulf of
Maine, although the prediction skill varies notably by season.
Considering temperature from a nearby or upstream (i.e. more polewawrd)
region as an additional predictor generally improves prediction skill,
presumably as a result of advective processes. Large-scale atmospheric
and oceanic indices, such as Gulf Stream path indices (GSIs) and the
North Atlantic Oscillation index, are also tested as predictors for NES
bottom temperatures. Only the GSI constructed from temperature observed
at 200 m depth significantly improves the prediction skill relative to
local persistence. However, the prediction skill from this GSI is not
larger than that gained using models incorporating nearby or upstream
shelf/slope temperatures. Based on these results, a simplified
statistical model has been developed, which can be tailored to fisheries
management for the NES.