Chen, B., Smith, S. R., & Bromwich, D. H. (1996). Evolution of the Tropospheric Split Jet over the South Pacific Ocean during the 1986-89 ENSO Cycle. Mon. Wea. Rev., 124(8), 1711–1731.
|
Chien, C. - Y., K. Speer, and M. Bourassa. (2010). Comparison of Wind Products in the Southern Ocean. U.S. CLIVAR Variations, 8(1), 8–10.
|
Cocke, S. (1998). Case Study of Erin Using the FSU Nested Regional Spectral Model. Mon. Wea. Rev., 126(5), 1337–1346.
|
Cocke, S. D., & LaRow, T. E. (1999). ), Seasonal Predictions of ENSO Impacts using a Nested Regional Spectral Model (H. Ritchie, Ed.). CAS/JSC Working Group on Numerical Experimentation, Research Activities in Atmospheric and Oceanic Modeling.
|
Cocke, S., Christidis, Z., LaRow, T., & Shin, D. W. (2002). Performance of a Coupled Ocean-Amosphere Model on the IBM SP4. In Proceedings from the Tenth Workshop on the Use of Parallel Computers, ECMWF, in Meteorology, Reading, U.K..
|
Cocke, S., & LaRow, T. E. (2000). Seasonal Predictions Using a Regional Spectral Model Embedded within a Coupled Ocean-Atmosphere Model. Mon. Wea. Rev., 128(3), 689–708.
|
Cocke, S., LaRow, T. E., & Shin, D. W. (2007). Seasonal rainfall predictions over the southeast United States using the Florida State University nested regional spectral model. J. Geophys. Res., 112(D4).
|
Coles, V. J., Stukel, M. R., Brooks, M. T., Burd, A., Crump, B. C., Moran, M. A., et al. (2017). Ocean biogeochemistry modeled with emergent trait-based genomics. Science, 358(6367), 1149–1154.
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Coles, V. J., Stukel, M. R., Brooks, M. T., Burd, A., Crump, B. C., Moran, M. A., et al. (2017). Ocean biogeochemistry modeled with emergent trait-based genomics. Science, 358(6367), 1149–1154.
Abstract: Marine ecosystem models have advanced to incorporate metabolic pathways discovered with genomic sequencing, but direct comparisons between models and “omics” data are lacking. We developed a model that directly simulates metagenomes and metatranscriptomes for comparison with observations. Model microbes were randomly assigned genes for specialized functions, and communities of 68 species were simulated in the Atlantic Ocean. Unfit organisms were replaced, and the model self-organized to develop community genomes and transcriptomes. Emergent communities from simulations that were initialized with different cohorts of randomly generated microbes all produced realistic vertical and horizontal ocean nutrient, genome, and transcriptome gradients. Thus, the library of gene functions available to the community, rather than the distribution of functions among specific organisms, drove community assembly and biogeochemical gradients in the model ocean.
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Collier, C. (2012). Effects of Sea State on Offshore Wind Resourcing in Florida. Master's thesis, Florida State University, Tallahassee, FL.
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