LaRow, T. E., Stefanova, L., Shin, D. - W., & Cocke, S. (2010). Seasonal Atlantic tropical cyclone hindcasting/forecasting using two sea surface temperature datasets. Geophys. Res. Lett. , 37 (2).
Misra, V., Moeller, L., Stefanova, L., Chan, S., O'Brien, J. J., Smith III, T. J., et al. (2011). The influence of the Atlantic Warm Pool on the Florida panhandle sea breeze: FLORIDA SEA BREEZE VARIATIONS. J. Geophys. Res. , 116 (D21).
Devanas, A., & Stefanova, L. (2018). Statistical Prediction Of Waterspout Probability For The Florida Keys. Wea. Forecasting , 33 , 389–410.
Abstract: A statistical model of waterspout probability was developed for wet-season (June–September) days over the Florida Keys. An analysis was performed on over 200 separate variables derived from Key West 1200 UTC daily wet-season soundings during the period 2006–14. These variables were separated into two subsets: days on which a waterspout was reported anywhere in the Florida Keys coastal waters and days on which no waterspouts were reported. Days on which waterspouts were reported were determined from the National Weather Service (NWS) Key West local storm reports. The sounding at Key West was used for this analysis since it was assumed to be representative of the atmospheric environment over the area evaluated in this study. The probability of a waterspout report day was modeled using multiple logistic regression with selected predictors obtained from the sounding variables. The final model containing eight separate variables was validated using repeated fivefold cross validation, and its performance was compared to that of an existing waterspout index used as a benchmark. The performance of the model was further validated in forecast mode using an independent verification wet-season dataset from 2015–16 that was not used to define or train the model. The eight-predictor model was found to produce a probability forecast with robust skill relative to climatology and superior to the benchmark waterspout index in both the cross validation and in the independent verification.
Stefanova, L., Sura, P., & Griffin, M. (2013). Quantifying the Non-Gaussianity of Wintertime Daily Maximum and Minimum Temperatures in the Southeast. J. Climate , 26 (3), 838–850.
Lim, Y. - K., Stefanova, L. B., Chan, S. C., Schubert, S. D., & O'Brien, J. J. (2011). High-resolution subtropical summer precipitation derived from dynamical downscaling of the NCEP/DOE reanalysis: how much small-scale information is added by a regional model? Clim Dyn , 37 (5-6), 1061–1080.
Stefanova, L., Misra, V., O'Brien, J. J., Chassignet, E. P., & Hameed, S. (2012). Hindcast skill and predictability for precipitation and two-meter air temperature anomalies in global circulation models over the Southeast United States. Clim Dyn , 38 (1-2), 161–173.
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.
Stefanova, L., & Krishnamurti, T. N. (2011). Kinetic energy exchanges between the time scales of ENSO and the Pacific decadal oscillation. Meteorol Atmos Phys , 114 (3-4), 95–105.
Mirhosseini, G., Srivastava, P., & Stefanova, L. (2013). The impact of climate change on rainfall Intensity-Duration-Frequency (IDF) curves in Alabama. Reg Environ Change , 13 (S1), 25–33.
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.
