Green, P. M. (1996).
Regional Analysis of Canadian, Alaskan, and Mexican Precipitation and Temperature for ENSO Impact. COAPS Report Series. Tallahassee, FL: FSU COAPS.
Green, P., Legler, D. M., Miranda, C., & O'Brien, J. J. (1997).
The North American Climate Patterns Associated with El Nino-Southern Oscillation. COAPS Technical Report 97-1. Tallahassee, FL: Center for Ocean-Atmospheric Prediction Studies.
Griffies, S. M., Yin, J., Bates, S., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Cassou, C., Chassignet, E., Danabasoglu, G., Danilov, S., Domingues, C., Drange, H., Durack, P., Farneti, R., Fernandez, E., Goddard, P., Greatbatch, R., Ilicak, M., Lu, J., Marsland, S., Mishra, A., Lorbacher, K., Nurser, G., Salas y Mélia, D., Palter, J., Samuels, B., Schröter, J., Schwarzkopf, F., Sidorenko, D., Treguier, A. M., Tseng, Y., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., Wang, Q., Winton, M. and Zhang, X. (2013). An assessment of global and regional sea level in a suite of interannual CORE-II simulations: a synopsis.
Exchanges : newsletter of the Climate Variability and Predictability Programme (CLIVAR), 18(2), 11–15.
Griffies, S. M., Biastoch, A., Böning, C., Bryan, F., Danabasoglu, G., Chassignet, E. P., et al. (2009). Coordinated Ocean-ice Reference Experiments (COREs).
Ocean Modelling, 26(1-2), 1–46.
Griffies, S. M., Danabasoglu, G., Durack, P. J., Adcroft, A. J., Balaji, V., Böning, C. W., et al. (2016). OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project.
Geosci. Model Dev., 9(9), 3231–3296.
Griffies, S. M., Yin, J., Durack, P. J., Goddard, P., Bates, S. C., Behrens, E., et al. (2014). An assessment of global and regional sea level for years 1993-2007 in a suite of interannual CORE-II simulations.
Ocean Modelling, 78, 35–89.
Griffin, J. (2009).
Characterization of Errors in Various Moisture Roughness Length Parameterizations. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Often the parameterization of the moisture roughness length is not seen as being important, as long as the parameterization seems reasonable; that is, it is within the rather considerable bounds of error for the data sets used to determine the parameterization. However, the choice of parameterization does influence height adjustments of humidity and calculations of turbulent heat fluxes. This paper focuses on the calculation of the turbulent heat fluxes using different parameterizations of roughness length. Five roughness length parameterizations are examined herein. These parameterizations include wall theory; the Clayson, Fairall, Curry parameterization; the Liu, Katsaros, Businger parameterization; Zilitinkevich et al. parameterization; and the COARE3.0 parameterization. Turbulent heat fluxes are calculated from each parameterization of the roughness length and are compared to observed turbulent heat flux values. The bulk latent heat flux estimates have a much better signal to noise ratio than the sensible heat fluxes, and are therefore the focus of the comparison to observations. This comparison indicates how to improve the proportionality in the above roughness length parameterizations, which are causing modeled turbulent heat flux magnitudes to be too large in four of the five parameterizations. The modeled turbulent heat fluxes are evaluated again after the modification of the parameterizations. Significant improvements in both the bias and the root mean square error (RMSE) are seen. Three parameterizations see roughly the same improvements of around 17Wm^-2 in the bias and roughly 10Wm^-2 in the RMSE. The largest improvements are in the Liu, Katsaros, Businger parameterization with bias improvements of over 45Wm^-2 and a RMSE reduction of nearly 32Wm^-2.
Griffin, M. (2008). Extreme temperatures (2007-2008).
Red-Cross/Florida Emergency Management Hazardous Weather Awareness Week Brochure.
Griffin, M. L., & Smith, S. R. (2001).
Polarstern Data Quality Control Report: May 1993 – November 1996. RVSMDC Report 01-01, Center for Ocean-Atmospheric Prediction Studies, The Florida State University, Tallahassee, FL, 32306-2840.
Groenen, D. (2018). The Effects of Climate Change on the Pests and Diseases of Coffee Crops in Mesoamerica.
Journal of Climatology & Weather Forecasting, 6(3).
Abstract: Coffee is an in-demand commodity that is being threatened by climate change. Increasing temperatures and rainfall variability are predicted in the region of Mexico and Central America (Mesoamerica). This region is plagued with pests and diseases that have already caused millions of dollars in damages and losses to the coffee industry.This paper examines three pests that negatively affect coffee plants: the coffee borer beetle, the black twig borer,and nematodes. In addition, this paper examines three diseases that can destroy coffee crops: bacterial blight,coffee berry disease, and coffee leaf rust. This paper will review the literature on how these pests and diseases are predicted to affect coffee crops under climate change models. In general, increased temperatures will increase the spread of pest and disease in coffee crops. Projected decreased rainfall in Honduras and Nicaragua may decrease the spread of pest and disease. However, these are complex issues which still require further study.