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Colin J. McAdie and Miles B. Lawrence

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.

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James L. Franklin, Colin J. McAdie, and Miles B. Lawrence

Previous studies have identified statistically significant long-term improvements in forecasts issued by the National Hurricane Center (NHC) for Atlantic basin tropical cyclones. Recently, however, attention has been focused on the forecast accuracy of landfall location and timing, and the long-term improvement trends for this relatively small sample of forecasts were mixed. These results may lead some to conclude that the accuracy of NHC forecasts close to the United States has not improved over time.

A statistically robust dataset can be obtained by considering “landfall-threatening” storms, defined as one for which tropical cyclone watches or warnings are in effect for some portion of the continental United States. In this study, long-term trends in accuracy are determined for NHC forecasts issued during these periods of threat and compared to trends for the Atlantic basin overall. A second set of trends are determined for forecasts verifying during the periods of threat.

The analysis shows that NHC forecasts for land-threatening tropical cyclones are improving. These improvement trends are statistically significant, although the improvement rates for the land-threatening storms are smaller than those for the basin overall. Over the period 1970–2001, forecasts issued during the watch/warning stage improved at annual average rates of 0.7%, 1.6%, and 1.9% at 24,48, and 72 h, respectively.

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John A. Knaff, Charles R. Sampson, Mark DeMaria, Timothy P. Marchok, James M. Gross, and Colin J. McAdie


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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Paul R. Harasti, Colin J. McAdie, Peter P. Dodge, Wen-Chau Lee, John Tuttle, Shirley T. Murillo, and Frank D. Marks Jr.


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), GBVTD- simplex, 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 ∼2 m s−1 or better if the wind intensity estimates from individual analyses are averaged together.

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Christopher W. Landsea, James L. Franklin, Colin J. McAdie, John L. Beven II, James M. Gross, Brian R. Jarvinen, Richard J. Pasch, Edward N. Rappaport, Jason P. Dunion, and Peter P. Dodge

Hurricane Andrew of 1992 caused unprecedented economic devastation along its path through the Bahamas, southeastern Florida, and Louisiana. Damage in the United States was estimated to be $26 billion (in 1992 dollars), making Andrew one of the most expensive natural disasters in U.S. history. This hurricane struck southeastern Florida with maximum 1-min surface winds estimated in a 1992 poststorm analysis at 125 kt (64 m s−1). This original assessment was primarily based on an adjustment of aircraft reconnaissance flight-level winds to the surface.

Based on recent advancements in the understanding of the eyewall wind structure of major hurricanes, the official intensity of Andrew was adjusted upward for five days during its track across the Atlantic Ocean and Gulf of Mexico by the National Hurricane Center Best Track Change Committee. In particular, Andrew is now assessed by the National Hurricane Center to be a Saffir–Simpson Hurricane Scale category-5 hurricane (the highest intensity category possible) at its landfall in southeastern Florida, with maximum 1-min winds of 145 kt (75 m s−1). This makes Andrew only the third category-5 hurricane to strike the United States since at least 1900. Implications for how this change impacts society's planning for such extreme events are discussed.

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Edward N. Rappaport, James L. Franklin, Lixion A. Avila, Stephen R. Baig, John L. Beven II, Eric S. Blake, Christopher A. Burr, Jiann-Gwo Jiing, Christopher A. Juckins, Richard D. Knabb, Christopher W. Landsea, Michelle Mainelli, Max Mayfield, Colin J. McAdie, Richard J. Pasch, Christopher Sisko, Stacy R. Stewart, and Ahsha N. Tribble


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.

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