Nye Janet A.

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Nye
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Janet A.
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  • Preprint
    Silver hake tracks changes in Northwest Atlantic circulation
    ( 2011-07) Nye, Janet A. ; Joyce, Terrence M. ; Kwon, Young-Oh ; Link, Jason S.
    Recent studies documenting shifts in spatial distribution of many organisms in response to a warming climate highlight the need to understand the mechanisms underlying species distribution at large spatial scales. Here we present one noteworthy example of remote oceanographic processes governing the spatial distribution of adult silver hake, Merluccius bilinearis, a commercially important fish in the Northeast US shelf region. Changes in spatial distribution of silver hake over the last 40 years are highly correlated with the position of the Gulf Stream (GS). These changes in distribution are in direct response to local changes in bottom temperature on the continental shelf that are responding to the same large scale circulation change affecting the GS path, namely changes in the Atlantic Meridional Overturning Circulation (AMOC). If AMOC weakens as is suggested by global climate models, silver hake distribution will remain in a poleward position, the extent to which could be forecast at both decadal and multidecadal scales.
  • Article
    Observational needs supporting marine ecosystems modeling and forecasting: from the global ocean to regional and coastal systems
    (Frontiers Media, 2019-10-15) Capotondi, Antonietta ; Jacox, Michael ; Bowler, Chris ; Kavanaugh, Maria T. ; Lehodey, Patrick ; Barrie, Daniel ; Brodie, Stephanie ; Chaffron, Samuel ; Cheng, Wei ; Dias, Daniela F. ; Eveillard, Damien ; Guidi, Lionel ; Iudicone, Daniele ; Lovenduski, Nicole S. ; Nye, Janet A. ; Ortiz, Ivonne ; Pirhalla, Douglas ; Pozo Buil, Mercedes ; Saba, Vincent S. ; Sheridan, Scott ; Siedlecki, Samantha A. ; Subramanian, Aneesh C. ; de Vargas, Colomban ; Di Lorenzo, Emanuele ; Doney, Scott C. ; Hermann, Albert J. ; Joyce, Terrence M. ; Merrifield, Mark ; Miller, Arthur J. ; Not, Fabrice ; Pesant, Stephane
    Many coastal areas host rich marine ecosystems and are also centers of economic activities, including fishing, shipping and recreation. Due to the socioeconomic and ecological importance of these areas, predicting relevant indicators of the ecosystem state on sub-seasonal to interannual timescales is gaining increasing attention. Depending on the application, forecasts may be sought for variables and indicators spanning physics (e.g., sea level, temperature, currents), chemistry (e.g., nutrients, oxygen, pH), and biology (from viruses to top predators). Many components of the marine ecosystem are known to be influenced by leading modes of climate variability, which provide a physical basis for predictability. However, prediction capabilities remain limited by the lack of a clear understanding of the physical and biological processes involved, as well as by insufficient observations for forecast initialization and verification. The situation is further complicated by the influence of climate change on ocean conditions along coastal areas, including sea level rise, increased stratification, and shoaling of oxygen minimum zones. Observations are thus vital to all aspects of marine forecasting: statistical and/or dynamical model development, forecast initialization, and forecast validation, each of which has different observational requirements, which may be also specific to the study region. Here, we use examples from United States (U.S.) coastal applications to identify and describe the key requirements for an observational network that is needed to facilitate improved process understanding, as well as for sustaining operational ecosystem forecasting. We also describe new holistic observational approaches, e.g., approaches based on acoustics, inspired by Tara Oceans or by landscape ecology, which have the potential to support and expand ecosystem modeling and forecasting activities by bridging global and local observations.
  • Article
    Seasonal prediction of bottom temperature on the Northeast U.S. Continental Shelf
    (American Geophysical Union, 2021-05-03) Chen, Zhuomin ; Kwon, Young-Oh ; Chen, Ke ; Fratantoni, Paula S. ; Gawarkiewicz, Glen G. ; Joyce, Terrence M. ; Miller, Timothy J. ; Nye, Janet A. ; Saba, Vincent S. ; Stock, Brian C.
    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 exhibits 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 data set. A simple, damped local persistence prediction model produces significant skill for lead times up to ∼5 months in the Mid-Atlantic Bight and up to ∼10 months in the Gulf of Maine, although the prediction skill varies notably by season. Considering temperature from a nearby or upstream (i.e., more poleward) 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.