Selman, C., Misra, V., Stefanova, L., Dinapoli, S., & Smith III, T. J. (2013). On the twenty-first-century wet season projections over the Southeastern United States.
Reg Environ Change, 13(S1), 153–164.
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.
Stefanova, L., Misra, V., Chan, S., Griffin, M., O'Brien, J. J., & Smith III, T. J. (2012). A proxy for high-resolution regional reanalysis for the Southeast United States: assessment of precipitation variability in dynamically downscaled reanalyses.
Clim Dyn, 38(11-12), 2449–2466.
Steffen, J., & Bourassa, M. (2018). Barrier Layer Development Local to Tropical Cyclones based on Argo Float Observations.
J. Phys. Oceanogr., 48(9), 1951–1968.
Abstract: The objective of this study is to quantify barrier layer development due to tropical cyclone (TC) passage using Argo float observations of temperature and salinity. To accomplish this objective, a climatology of Argo float measurements is developed from 2001 to 2014 for the Atlantic, eastern Pacific, and central Pacific basins. Each Argo float sample consists of a prestorm and poststorm temperature and salinity profile pair. In addition, a no-TC Argo pair dataset is derived for comparison to account for natural ocean state variability and instrument sensitivity. The Atlantic basin shows a statistically significant increase in barrier layer thickness (BLT) and barrier layer potential energy (BLPE) that is largely attributable to an increase of 2.6 m in the post-TC isothermal layer depth (ITLD). The eastern Pacific basin shows no significant changes to any barrier layer characteristic, likely due to a shallow and highly stratified pycnocline. However, the near-surface layer freshens in the upper 30 m after TC passage, which increases static stability. Finally, the central Pacific has a statistically significant freshening in the upper 20-30 m that increases upper-ocean stratification by similar to 35%. The mechanisms responsible for increases in BLPE vary between the Atlantic and both Pacific basins; the Atlantic is sensitive to ITLD deepening, while the Pacific basins show near-surface freshening to be more important in barrier layer development. In addition, Argo data subsets are used to investigate the physical relationships between the barrier layer and TC intensity, TC translation speed, radial distance from TC center, and time after TC passage.
Strazzo, S. (2011).
Low-Frequency Minimum Temperature Variability Throughout the Southeastern United States during the 1970s: Regime Shift or Phase Coincidence? Master's thesis, Florida State University, Tallahassee, FL.
Subrahmanyam, S., & Robinson, S. (2000). Sea Surface Height Variability in the Indian Ocean from TOPEX/POSEIDON Altimetry and Model Simulations.
Marine Geodesy, 23(3), 167–195.
Sura, P., & Hannachi, A. (2015). Perspectives of Non-Gaussianity in Atmospheric Synoptic and Low-Frequency Variability.
J. Climate, 28(13), 5091–5114.
Wei, J., Dirmeyer, P. A., Guo, Z., Zhang, L., & Misra, V. (2010). How Much Do Different Land Models Matter for Climate Simulation? Part I: Climatology and Variability.
J. Climate, 23(11), 3120–3134.
Williams, M. (2010).
Characterizing Multi-Decadal Temperature Variability in the Southeastern United States. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Prior studies of the long-term temperature record in the Southeastern United States (SE US) mostly discuss the long-term cooling trend, and the inter-annual variability produced by the region's strong ties to El Niño Southern Oscillation (ENSO). An examination of long-term temperature records in the SE US show clear multi-decadal variations in temperature, with relative warm periods in the 1920's through the mid 1950's and a cool period in the late 1950's through the late 1990's. This substantial shift in multi-decadal variability is not well understood and has not been fully investigated. It appears to account for the long-term downward trend in temperatures. An accurate characterization of this variability could lead to improved interannual and long-term forecasts, which would be useful for agricultural planning, drought mitigation, water management, and preparation for extreme temperature events. Statistical methods are employed to determine the spatial coherence of the observed variability on seasonal time scales. The goal of this study is to characterize the nature of this variability through the analysis of National Weather Service Cooperative Observer Program (COOP) station data in Florida, Georgia, Alabama, North Carolina, and South Carolina. One finding is a shift in the temperature Probability Distribution Function (PDF) between warm regimes and cool regimes.
Wu, Z., Huang, N. E., Wallace, J. M., Smoliak, B. V., & Chen, X. (2011). On the time-varying trend in global-mean surface temperature.
Clim Dyn, 37(3-4), 759–773.