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  • Author or Editor: Leonard J. Pietrafesa x
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Lian Xie, Shaowu Bao, Leonard J. Pietrafesa, Kristen Foley, and Montserrat Fuentes


A real-time hurricane wind forecast model is developed by 1) incorporating an asymmetric effect into the Holland hurricane wind model; 2) using the National Oceanic and Atmospheric Administration (NOAA)/National Hurricane Center’s (NHC) hurricane forecast guidance for prognostic modeling; and 3) assimilating the National Data Buoy Center (NDBC) real-time buoy data into the model’s initial wind field. The method is validated using all 2003 and 2004 Atlantic and Gulf of Mexico hurricanes. The results show that 6- and 12-h forecast winds using the asymmetric hurricane wind model are statistically more accurate than using a symmetric wind model. Detailed case studies were conducted for four historical hurricanes, namely, Floyd (1999), Gordon (2000), Lily (2002), and Isabel (2003). Although the asymmetric model performed generally better than the symmetric model, the improvement in hurricane wind forecasts produced by the asymmetric model varied significantly for different storms. In some cases, optimizing the symmetric model using observations available at initial time and forecast mean radius of maximum wind can produce comparable wind accuracy measured in terms of rms error of wind speed. However, in order to describe the asymmetric structure of hurricane winds, an asymmetric model is needed.

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Lian Xie, Tingzhuang Yan, Leonard J. Pietrafesa, John M. Morrison, and Thomas Karl


The spatial and temporal variability of North Atlantic hurricane tracks and its possible association with the annual hurricane landfall frequency along the U.S. East Coast are studied using principal component analysis (PCA) of hurricane track density function (HTDF). The results show that, in addition to the well-documented effects of the El Niño–Southern Oscillation (ENSO) and vertical wind shear (VWS), North Atlantic HTDF is strongly modulated by the dipole mode (DM) of Atlantic sea surface temperature (SST) as well as the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO). Specifically, it was found that Atlantic SST DM is the only index that is associated with all top three empirical orthogonal function (EOF) modes of the Atlantic HTDF. ENSO and tropical Atlantic VWS are significantly correlated with the first and the third EOF of the HTDF over the North Atlantic Ocean. The second EOF of North Atlantic HTDF, which represents the “zonal gradient” of North Atlantic hurricane track density, showed no significant correlation with ENSO or with tropical Atlantic VWS. Instead, it is associated with the Atlantic SST DM, and extratropical processes including NAO and AO. Since for a given hurricane season, the preferred hurricane track pattern, together with the overall basinwide hurricane activity, collectively determines the hurricane landfall frequency, the results provide a foundation for the construction of a statistical model that projects the annual number of hurricanes striking the eastern seaboard of the United States.

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Richard Rotunno, Leonard J. Pietrafesa, John S. Allen, Bradley R. Colman, Clive M. Dorman, Carl W. Kreitzberg, Stephen J. Lord, Miles G. McPhee, George L. Mellor, Christopher N. K. Mooers, Pearn P. Niiler, Roger A. Pielke Sr., Mark D. Powell, David P. Rogers, James D. Smith, and Lian Xie

U.S. Weather Research Program (USWRP) prospectus development teams (PDTs) are small groups of scientists that are convened by the USWRP lead scientist on a one-time basis to discuss critical issues and to provide advice related to future directions of the program. PDTs are a principal source of information for the Science Advisory Committee, which is a standing committee charged with the duty of making recommendations to the Program Office based upon overall program objectives. PDT-1 focused on theoretical issues, and PDT-2 on observational issues; PDT-3 is the first of several to focus on more specialized topics. PDT-3 was convened to identify forecasting problems related to U.S. coastal weather and oceanic conditions, and to suggest likely solution strategies.

There were several overriding themes that emerged from the discussion. First, the lack of data in and over critical regions of the ocean, particularly in the atmospheric boundary layer, and the upper-ocean mixed layer were identified as major impediments to coastal weather prediction. Strategies for data collection and dissemination, as well as new instrument implementation, were discussed. Second, fundamental knowledge of air–sea fluxes and boundary layer structure in situations where there is significant mesoscale variability in the atmosphere and ocean is needed. Companion field studies and numerical prediction experiments were discussed. Third, research prognostic models suggest that future operational forecast models pertaining to coastal weather will be high resolution and site specific, and will properly treat effects of local coastal geography, orography, and ocean state. The view was expressed that the exploration of coupled air-sea models of the coastal zone would be a particularly fruitful area of research. PDT-3 felt that forecasts of land-impacting tropical cyclones, Great Lakes-affected weather, and coastal cyclogenesis, in particular, would benefit from such coordinated modeling and field efforts. Fourth, forecasting for Arctic coastal zones is limited by our understanding of how sea ice forms. The importance of understanding air-sea fluxes and boundary layers in the presence of ice formation was discussed. Finally, coastal flash flood forecasting via hydrologic models is limited by the present accuracy of measured and predicted precipitation and storm surge events. Strategies for better ways to improve the latter were discussed.

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