Chen, Z., Y.-O. Kwon, K. Chen, P. Fratantoni, G. Gawarkiewicz, T.J. Joyce, T.J. Miller, J.A. Nye, V.S. Saba, and B.C. Stock, 2021: Seasonal Prediction of Bottom Temperature on the Northeast U.S. Continental Shelf. J. Geophys. Res., 126, e2021JC017187. https://doi.org/10.1029/2021JC017187.

Reliable prediction of bottom temperature could improve fisheries stock assessments on the Northeast U.S. shelf (NES), where some of the most commercially valuable fisheries are located. In this study, we have developed a collection of statistical models that produce seasonal predictions of NES bottom temperature with 1–12 months lead time. Predictors considered in these prediction models include local persistence of bottom temperature from prior months, bottom temperature from an upstream or nearby region, and large-scale atmospheric and oceanic indices representing the North Atlantic Oscillation or position of the Gulf Stream. The figure above shows the spatial patterns of the maximum prediction skill for the bottom temperature in the Northeast Channel region (highlighted by cyan lines) at different lead times for 1, 4, 7, and 10 months. The evolution of the pattern indicates the propagation of temperature anomalies along the continental shelf and slope is the main source of predictability.  Figure provided by Young-Oh Kwon.