Cocke, S., Boisserie, M., & Shin, D. - W. (2013). A coupled soil moisture initialization scheme for the FSU/COAPS climate model.
Inverse Problems in Science and Engineering, 21(3), 420–437.
Ahern, K. K. (2015).
Analysis of Polar Mesocyclonic Surface Turbulent Fluxes in the Arctic System Reanalysis (ASRv1) Dataset. Master's thesis, Florida State University, Tallahassee, FL.
Culin, J. C. (2006).
Wintertime ENSO Variability in Wind Direction Across the Southeast United States. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Changes in wind direction in association with the phases of the El Niño-Southern Oscillation (ENSO) are identified over the Southeast region of the United States during the winter season (December-February). Wind roses, which depict the percentage of time the wind comes from each direction and can graphically identify the prevailing wind, are computed according to a 12-point compass for 24 stations in the region. Unfolding the wind rose into a 12-bin histogram visually demonstrates the peak frequencies in wind direction during each of the three (warm, cold and neutral) phases of ENSO. Normalized values represent the number of occurrences (counts) per month per ENSO phase, and comparison using percent changes illustrates the differences between phases. Based on similarities in wind direction characteristics, regional topography and results from a formal statistical test, stations are grouped into five geographic regions, with a representative station used to describe conditions in that region. Locations in South Florida show significant differences in the frequencies in wind direction from easterly directions during the cold phase and northerly directions during the warm phase. North Florida stations display cold phase southerly directions, and westerly and northerly directions during the warm phase, both of which are significant for much of the winter. Coastal Atlantic stations reveal winds from westerly directions for both phases. The Piedmont region demonstrates large variability in wind direction due to the influence from the Appalachian Mountains, but generally identifies warm phase and cold phase winds with more zonal influences rather than just from south or north. The Mountainous region also indicates southerly cold phase winds and northerly warm phase winds, but also reveals less of an influence from ENSO or significantly different distributions. Comparisons between observed patterns and those obtained using the NCEP/NCAR Reanalysis data reveal how the model-derived observations resolve the ENSO influence on surface wind direction at selected locations. Overall, resolution of the strength of the signals is not achieved, though the depiction of the general pattern is fair at two of the three locations. Connections between the synoptic flow and surface wind direction are examined via relationships to the storm track associated with the 250 hPa jet stream and sea level pressure patterns during each extreme ENSO phase. Discussion of reasons the NCEP reanalysis illustrates surface wind direction patterns different from those derived from observations is included.
Scott, J. P. (2011).
An Intercomparison of Numerically Modeled Flux Data and Satellite-Derived Flux Data for Warm Seclusions. Master's thesis, Florida State University, Tallahassee, FL.
Cammarano, D., Stefanova, L., Ortiz, B. V., Ramirez-Rodrigues, M., Asseng, S., Misra, V., et al. (2013). Evaluating the fidelity of downscaled climate data on simulated wheat and maize production in the southeastern US.
Reg Environ Change, 13(S1), 101–110.
LaRow, T. (2013). An analysis of tropical cyclones impacting the Southeast United States from a regional reanalysis.
Reg Environ Change, 13(S1), 35–43.
Li, H., & Misra, V. (2014). Thirty-two-year ocean-atmosphere coupled downscaling of global reanalysis over the Intra-American Seas.
Clim Dyn, 43(9-10), 2471–2489.
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.
De Souza-Machado, S., Tangborn, A., Sura, P., Hepplewhite, C., & Strow, L. L. (2017). Non-Gaussian Analysis of Observations from the Atmospheric Infrared Sounder Compared with ERA and MERRA Reanalyses.
J. Appl. Meteor. Climatol., 56(5), 1463–1481.
Li, H., Kanamitsu, M., & Hong, S. - Y. (2012). California reanalysis downscaling at 10 km using an ocean-atmosphere coupled regional model system.
J. Geophys. Res., 117(D12).