Murray, C. P., Morey, S. L., & O'Brien, J. J. (2001). Interannual variability of upper ocean vorticity balances in the Gulf of Alaska.
J. Geophys. Res., 106(C3), 4479–4491.
Nedbor-Gross, R., Dukhovskoy, D. S., Bourassa, M. A., Morey, S. L., & Chassignet, E. P. (2014). Investigation of the Relationship Between the Yucatan Channel Transport and the Loop Current Area in a Multidecadal Numerical Simulation.
Mar Technol Soc J, 48(4), 15–26.
Nguyen, T. - T., Morey, S. L., Dukhovskoy, D. S., & Chassignet, E. P. (2015). Nonlocal impacts of the Loop Current on cross-slope near-bottom flow in the northeastern Gulf of Mexico.
Geophys. Res. Lett., 42(8), 2926–2933.
Rudzin, J. E., Morey, S. L., Bourassa, M. A., & Smith, S. R. (2013). The Influence of Loop Current Position on Winter Sea Surface Temperatures in the Florida Straits.
Earth Interact., 17(16), 1–9.
Shropshire, T., Morey, S. L., Chassignet, E. P., Bozec, A., Coles, V. J., Landry, M. R., et al. (2019). Quantifying spatiotemporal variability in zooplankton dynamics in the Gulf of Mexico with a physical-biogeochemical model.
Abstract: Zooplankton play an important role in global biogeochemistry and their secondary production supports valuable fisheries of the world's oceans. Currently, zooplankton abundances cannot be estimated using remote sensing techniques. Hence, coupled physical-biogeochemical models (PBMs) provide an important tool for studying zooplankton on regional and global scales. However, evaluating the accuracy of zooplankton abundance estimates from PBMs has been a major challenge as a result of sparse observations. In this study, we configure a PBM for the Gulf of Mexico (GoM) from 1993�2012 and validate the model against an extensive combination of in situ biomass and rate measurements including total mesozooplankton biomass, size-fractionated mesozooplankton biomass and grazing rates, microzooplankton specific grazing rates, surface chlorophyll, deep chlorophyll maximum depth, phytoplankton specific growth rates, and net primary production. Spatial variability in mesozooplankton biomass climatology observed in a multi-decadal database for the northern GoM is well resolved by the model with a statistically significant (p < 0.01) correlation of 0.90. Mesozooplankton secondary production for the region averaged 66 + 8 mt C yr−1 equivalent to approximately 10 % of NPP and ranged from 51 to 82 mt C yr−1. In terms of diet, model results from the shelf regions suggest that herbivory is the dominant feeding mode for small mesozooplankton (< 1-mm) whereas larger mesozooplankton are primarily carnivorous. However, in open-ocean, oligotrophic regions, both groups of mesozooplankton have proportionally greater reliance on heterotrophic protists as a food source. This highlights the important role of microbial and protistan food webs in sustaining mesozooplankton biomass in the GoM which serves as the primary food source for early life stages of many commercially-important fish species, including tuna.
Todd, A. C., Morey, S. L., & Chassignet, E. P. (2014). Circulation and cross-shelf transport in the Florida Big Bend.
J Mar Res, 72(6), 445–475.
Weissman, D. E., Morey, S., & Bourassa, M. (2017). Studies of the effects of rain on the performance of the SMAP radiometer surface salinity estimates and applications to remote sensing of river plumes. In
IEEE International Symposium on Geoscience and Remote Sensing IGARSS (pp. 1491–1494).
Yu, P., Morey, S. L., & O'Brien, J. J. (2006).
Development of new techniques for assimilating satellite altimetry data into ocean models (J. Cote, Ed.). Research Activities in Atmospheric and Ocean Modeling, Report No. 36. Geneva, Switzerland: World Meteorological Organization.
Yu, P., Morey, S. L., & O'Brien, J. J. (2004).
Development of a reduced space adjoint data assimilation technique for numerical simulation of oceanic circulation (J. Cote, Ed.). Research Activities in Atmospheric and Ocean Modeling, Report No. 34. Geneva, Switzerland: World Meteorological Organization.
Yu, P., Morey, S. L., & Zavala-Hidalgo, J. (2004). New mapping method to observe propagating features.
Sea Technology, 45(5), 20–24.