Aretxabaleta, A., Blanton, B. O., Seim, H. E., Werner, F. E., Nelson, J. R., & Chassignet, E. P. (2007). Cold event in the South Atlantic Bight during summer of 2003: Model simulations and implications.
J. Geophys. Res., 112(C5).
Baigorria, G., Jones, J., Shin, D., Mishra, A., & Ingram, K. T., Jones, J. W., O'Brien, J. J., Roncoli, M. C., Fraisse, C., Breuer, N. E., Bartels, W.-L., Zierden, D. F., Letson, D. (2007). Assessing uncertainties in crop model simulations using daily bias-corrected Regional Circulation Model outputs.
Clim. Res., 34, 211–222.
Baigorria, G. A., Jones, J. W., & O'Brien, J. J. (2007). Understanding rainfall spatial variability in southeast USA at different timescales.
Int. J. Climatol., 27(6), 749–760.
Bourassa, M. A., D. Dukhovskoy, S. L. Morey, and J, J. O'Brien. (2007). Innovations in Modeling Gulf of Mexico Surface Turbulent Fluxes.
Flux News, (3), 9.
Bourassa, M. A., R. N. Maue, S. R. Smith, P. J. Hughes, and J. Rolph. (2007). Global Winds: State of the Climate in 2006.
Bulletin of the American Meteorological Society, 88(6), 135.
Brolley, J. M. (2007).
Effects of ENSO, NAO (PVO), and PDO on Monthly Extreme Temperatures and Precipitation. Ph.D. thesis, Florida State University, Tallahassee, FL.
Abstract: The El Nino-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation (PDO), and the Polar Vortex Oscillation (PVO) produce conditions favorable for monthly extreme temperatures and precipitation. These climate modes produce upper-level teleconnection patterns that favor regional droughts, floods, heat waves, and cold spells, and these extremes impact agriculture, energy, forestry, and transportation. The above sectors prefer the knowledge of the worst (and sometimes the best) case scenarios. This study examines the extreme scenarios for each phase and the combination of phases that produce the greatest monthly extremes. Data from Canada, Mexico, and the United States are gathered from the Historical Climatology Network (HCN). Monthly data are simulated by the utilization of a Monte Carlo model. This Monte Carlo method simulates monthly data by the stochastic selection of daily data with identical ENSO, PDO, and PVO (NAO) characteristics. In order to test the quality of the Monte Carlo simulation, the simulations are compared with the observations using only PDO and PVO. It has been found that temperatures and precipitation in the simulation are similar to the model. Statistics tests have favored similarities between simulations and observations in most cases. Daily data are selected in blocks of four to eight days in order to conserve temporal correlation. Because the polar vortex occurs only during the cold season, the PVO is used during January, and the NAO is used during other months. The simulated data are arranged, and the tenth and ninetieth percentiles are analyzed. The magnitudes of temperature and precipitation anomalies are the greatest in the western Canada and the southeastern United States during winter, and these anomalies are located near the Pacific North American (PNA) extrema. Western Canada has its coldest (warmest) Januaries when the PDO and PVO are low (high). The southeastern United States has its coldest Januaries with high PDO and low PVO and warmest Januaries with low PDO and high PVO. Although extremes occur during El Nino or La Nina, many stations have the highest or lowest temperatures during neutral ENSO. In California and the Gulf Coast, the driest (wettest) Januaries tend to occur during low (high) PDO, and the reverse occurs in Tennessee, Kentucky, Ohio, and Indiana. Summertime anomalies, on the other hand, are weak because temperature variance is low. Phase combinations that form the wettest (driest) Julies form spatially incoherent patterns. The magnitudes of the temperature and precipitation anomalies and the corresponding phase combinations vary regionally and seasonally. Composite maps of geopotential heights across North America are plot for low, median, and high temperatures at six selected sites and for low, median, and high precipitation at the same sites. The greatest fluctuations occur near the six sites and over some of the loci of the PNA pattern. Geopotential heights tend to decrease (increase) over the target stations during the cold (warm) cases, and the results for precipitation are variable.
Brolley, J. M., O'Brien, J. J., Schoof, J., & Zierden, D. (2007). Experimental drought threat forecast for Florida.
Agricultural and Forest Meteorology, 145(1-2), 84–96.
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).
Gierach, M. M., Bourassa, M. A., Cunningham, P., O'Brien, J. J., & Reasor, P. D. (2007). Vorticity-Based Detection of Tropical Cyclogenesis.
J. Appl. Meteor. Climatol., 46(8), 1214–1229.
Guimond, S. R. (2007).
A diagnostic study of the effects of trough interactions on tropical cyclone QPF. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: A composite study is presented analyzing the influence of upper-tropospheric troughs on the evolution of precipitation in twelve Atlantic tropical cyclones (TCs) between the years 2000 � 2005. The TRMM Multi-Satellite Precipitation Analysis (TMPA) is used to examine the enhancement of precipitation within a 24 h window centered on trough interaction (TI) time in a shear-vector relative coordinate system. Eddy angular momentum flux convergence (EFC) computed from European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses is employed to objectively determine the initiation of a TI while adding insight, along with vertical wind shear, into the intensification of TC vortices. The relative roles of the dynamics (EFC and vertical wind shear) and thermodynamics (moist static energy potential) in TIs are outlined in the context of precipitation enhancement that provides quantitative insight into the “good trough”/“bad trough” paradigm. The largest precipitation rates and enhancements are found in the down-shear left quadrant of the storm, consistent with previous studies of convective asymmetries. Maximum mean enhancement values of 1.4 mm/h are found at the 200 km radius in the down-shear left quadrant. Results indicate that the largest precipitation enhancements occur with “medium” TIs; comprised of EFC values between 17 � 22 (m/s)/day and vertical wind shear Sensitivity tests on the upper vertical wind shear boundary reveal the importance of using the tropopause for wind shear computations when a TC enters mid-latitude regions. Changes in radial mean precipitation ranging from 29 � 40 % across all storm quadrants are found when using the tropopause as the upper boundary on the shear vector. Tests on the lower boundary using QuikSCAT ocean surface wind vectors expose large sensitivities on the precipitation ranging from 42 � 60 % indicating that the standard level of 850 hPa, outside of the boundary layer in most storms, is more physically reliable for computing vertical wind shear. These results should help to improve TC quantitative precipitation forecasting (QPF) as operational forecasters routinely rely on crude statistical methods and rules of thumb for forecasting TC precipitation.