COAPS Virtual Library (Publications)

Shin, D. W., & Krishnamurti, T. N. (1999). Improving Precipitation Forecasts over the Global Tropical Belt. Meteorology and Atmospheric Physics, 70(1-2), 1–14. Keywords: Precipitation Forecast; Global Spectral Model; Vertical Diffusion Coefficient; Horizontal Diffusion Coefficient; Normal Mode Initialization https://www.coaps.fsu.edu/bibliography/show.php?record=768
Shin, D. W., LaRow, T. E., & Cocke, S. (2003). Convective scheme and resolution impacts on seasonal precipitation forecasts. Geophys. Res. Lett., 30(20). Keywords: seasonal precipitation; cumulus parameterization; horizontal resolution https://www.coaps.fsu.edu/bibliography/show.php?record=469
Shinoda, T., Han, W., Zamudio, L., Lien, R. - C., & Katsumata, M. (2017). Remote Ocean Response to the Madden-Julian Oscillation during the DYNAMO Field Campaign: Impact on Somali Current System and the Seychelles-Chagos Thermocline Ridge. Atmosphere, 8(9), 171. Keywords: Madden-Julian oscillation; CINDY/DYNAMO; Somali current; Indian Ocean https://www.coaps.fsu.edu/bibliography/show.php?record=282
Shinoda, T., Kiladis, G. N., & Roundy, P. E. (2009). Statistical representation of equatorial waves and tropical instability waves in the Pacific Ocean. In Atmospheric Research (Vol. 94, pp. 37–44). Keywords: Equatorial waves; Tropical instability waves; Tropical air-sea interaction https://www.coaps.fsu.edu/bibliography/show.php?record=381
Shropshire, T., Li, Y., & He, R. (2016). Storm impact on sea surface temperature and chlorophyll a in the Gulf of Mexico and Sargasso Sea based on daily cloud-free satellite data reconstructions. Geophys. Res. Lett., 43(23), 12,199–12,207. Keywords: storm; sea surface temperature; surface chl a; northwest Atlantic ocean https://www.coaps.fsu.edu/bibliography/show.php?record=51
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. https://www.coaps.fsu.edu/bibliography/show.php?record=1095
Siefridt, L., Barnier, B., Legler, D. M., & O'Brien, J. J. (1998). 5-day average wind over North-West Atlantic from ERS1 using a variational analysis. Global Atmosphere and Ocean System, 5, 317–344. https://www.coaps.fsu.edu/bibliography/show.php?record=740
Singh, K., Jardak, M., Sandu, A., Bowman, K., Lee, M., & Jones, D. (2011). Construction of non-diagonal background error covariance matrices for global chemical data assimilation. Geosci. Model Dev., 4(2), 299–316. https://www.coaps.fsu.edu/bibliography/show.php?record=377
Skiba, A. W., Zeng, L., Arbic, B. K., Müller, M., & Godwin, W. J. (2013). On the Resonance and Shelf/Open-Ocean Coupling of the Global Diurnal Tides. J. Phys. Oceanogr., 43(7), 1301–1324. Keywords: Tides https://www.coaps.fsu.edu/bibliography/show.php?record=196
Smedstad, O. M., Hurlburt, H. E., Metzger, E. J., Rhodes, R. C., Shriver, J. F., Wallcraft, A. J., et al. (2003). An operational Eddy resolving 1/16° global ocean nowcast/forecast system. Journal of Marine Systems, 40-41, 341–361. Keywords: global ocean prediction; prediction of mesoscale variability; data assimilation; ocean forecast verification https://www.coaps.fsu.edu/bibliography/show.php?record=481

Shin, D. W., & Krishnamurti, T. N. (1999). Improving Precipitation Forecasts over the Global Tropical Belt. Meteorology and Atmospheric Physics, 70(1-2), 1–14.

Shin, D. W., LaRow, T. E., & Cocke, S. (2003). Convective scheme and resolution impacts on seasonal precipitation forecasts. Geophys. Res. Lett., 30(20).

Shinoda, T., Han, W., Zamudio, L., Lien, R. - C., & Katsumata, M. (2017). Remote Ocean Response to the Madden-Julian Oscillation during the DYNAMO Field Campaign: Impact on Somali Current System and the Seychelles-Chagos Thermocline Ridge. Atmosphere, 8(9), 171.

Shinoda, T., Kiladis, G. N., & Roundy, P. E. (2009). Statistical representation of equatorial waves and tropical instability waves in the Pacific Ocean. In Atmospheric Research (Vol. 94, pp. 37–44).

Shropshire, T., Li, Y., & He, R. (2016). Storm impact on sea surface temperature and chlorophyll a in the Gulf of Mexico and Sargasso Sea based on daily cloud-free satellite data reconstructions. Geophys. Res. Lett., 43(23), 12,199–12,207.

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.

https://www.coaps.fsu.edu/bibliography/show.php?record=1095

Siefridt, L., Barnier, B., Legler, D. M., & O'Brien, J. J. (1998). 5-day average wind over North-West Atlantic from ERS1 using a variational analysis. Global Atmosphere and Ocean System, 5, 317–344.

Singh, K., Jardak, M., Sandu, A., Bowman, K., Lee, M., & Jones, D. (2011). Construction of non-diagonal background error covariance matrices for global chemical data assimilation. Geosci. Model Dev., 4(2), 299–316.

Skiba, A. W., Zeng, L., Arbic, B. K., Müller, M., & Godwin, W. J. (2013). On the Resonance and Shelf/Open-Ocean Coupling of the Global Diurnal Tides. J. Phys. Oceanogr., 43(7), 1301–1324.

Smedstad, O. M., Hurlburt, H. E., Metzger, E. J., Rhodes, R. C., Shriver, J. F., Wallcraft, A. J., et al. (2003). An operational Eddy resolving 1/16° global ocean nowcast/forecast system. Journal of Marine Systems, 40-41, 341–361.

© 2024 Center for Ocean-Atmospheric Prediction Studies (COAPS), Florida State University