The National Hurricane Center issues analyses, forecasts, and warnings over large parts of the North Atlantic and Pacific Oceans, and in support of many nearby countries. Advances in observational capabilities, operational numerical weather prediction, and forecaster tools and support systems over the past 15-20 yr have enabled the center to make more accurate forecasts, extend forecast lead times, and provide new products and services. Important limitations, however, persist. This paper discusses the current workings and state of the nation's hurricane warning program, and highlights recent improvements and the enabling science and technology. It concludes with a look ahead at opportunities to address challenges.

An operational model used to predict tropical cyclone wind structure in terms of significant wind radii (i.e., 34-, 50-, and 64-kt wind radii, where 1 kt = 0.52 m s−1) at the National Oceanic and Atmospheric Administration/National Hurricane Center (NHC) and the Department of Defense/Joint Typhoon Warning Center (JTWC) is described. The statistical-parametric model employs aspects of climatology and persistence to forecast tropical cyclone wind radii through 5 days. Separate versions of the model are created for the Atlantic, east Pacific, and western North Pacific by statistically fitting a modified Rankine vortex, which is generalized to allow wavenumber-1 asymmetries, to observed values of tropical cyclone wind radii as reported by NHC and JTWC. Descriptions of the developmental data and methods used to formulate the model are given. A 2-yr verification and comparison with operational forecasts and an independently developed wind radii forecast method that also employs climatology and persistence suggests that the statistical-parametric model does a good job of forecasting wind radii. The statistical-parametric model also provides reliable operational forecasts that serve as a baseline for evaluating the skill of operational forecasts and other wind radii forecast methods in these tropical cyclone basins.

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The NOAA/NWS/NCEP/Tropical Prediction Center/National Hurricane Center has sought techniques that use single-Doppler radar data to estimate the tropical cyclone wind field. A cooperative effort with NOAA/Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division and NCAR has resulted in significant progress in developing a method whereby radar display data are used as a proxy for a full-resolution base data and in improving and implementing existing wind retrieval and center-finding techniques. These techniques include the ground-based velocity track display (GBVTD), tracking radar echoes by correlation (TREC), GBVTDsimplex, and the principal component analysis (PCA) methods. The GBVTD and TREC algorithms are successfully applied to the Weather Surveillance Radar-1988 Doppler (WSR-88D) display data of Hurricane Bret (1999) and Tropical Storm Barry (2001). GBVTD analyses utilized circulation center estimates provided by the GBVTD-simplex and PCA methods, whereas TREC analyses utilized wind center estimates provided by radar imagery and aircraft measurements. GBVTD results demonstrate that the use of the storm motion as a proxy for the mean wind is not always appropriate and that results are sensitive to the accuracy of the circulation center estimate. TREC results support a previous conjecture that the use of polar coordinates would produce improved wind retrievals for intense tropical cyclones. However, there is a notable effect in the results when different wind center estimates are used as the origin of coordinates. The overall conclusion is that GBVTD and TREC have the ability to retrieve the intensity of a tropical cyclone with an accuracy of ϳ2 m s Ϫ1 or better if the wind intensity estimates from individual analyses are averaged together.

Tropical cyclone track forecasts issued by the Tropical Prediction Center/National Hurricane Center for the Atlantic basin have improved over the period 1970-98. Improvement is shown at 24, 48, and 72 h. Although this improvement can be shown without any preconditioning of the data, the question of accounting for forecast difficulty is addressed, building upon the work of Neumann. A decrease in the initial position errors over the same period is also shown. Track forecast errors generated by the Atlantic climatology and persistence (CLIPER) model (run in "best-track" mode) are used as a measure of forecast difficulty. Using the annual average CLIPER errors in a regression against the official forecast errors yields an equation giving an expected error for each year under consideration. The expected error (representing forecast difficulty) is then subtracted from the observed official errors. The resulting set of differences can then be examined for long-term trends, difficulty having been accounted for. Fitting a straight line to these differences (1970-98) yields the result that official forecast errors have decreased by an average of 1.0% per year at 24 h, by 1.7% per year at 48 h, and by 1.9% per year at 72 h. A second-order fit, however, suggests that the rate of improvement has increased during the latter half of the period.