The National Weather Service Hurricane Probability Program

The National Weather Service Robert C. Sheets National Hurricane Center Hurricane Probability Program 1320 South Dixie Highway Coral Gables, FL 33146 1. Introduction Recent census studies have shown a general shift of the U.S. population to the Sun Belt, with a large number of these peo- ple moving to coastal counties. This trend has continued through the decades of the 1960s and the 1970s (Fig. 1). For instance, the coastal county population of Florida was 3 853 244 in 1960,5 414 868 in 1970, and 7 702 337 in 1980, or nearly a doubling of the population in these hurricane- prone areas during the past 20 years! Fortunately, Florida has experienced a considerable decline in hurricane activity during this same period. However, these population concen- trations cause concern about the adequacy of the National Weather Service (NWS) hurricane warning programs for FIG. 1. United States population trends, 1960 to 1970 and 1970 providing sufficient warnings and guidance for the protec- to 1980. tion of lives and property in these highly populated regions. The NWS attempts to provide a minimum of 12 hours of daylight warning for coastal communities to prepare for a hurricane. Community action plans have traditionally been Simply issuing warnings earlier does not seem to be a solu- built around these warnings. A highly coordinated effort in- tion to these problems. Longer warning lead times would re- volving the NWS, state, and local officials is required in this sult in much larger over-warning. For instance, the average warning and action process. This system has worked quite Atlantic area tropical cyclone official forecast errors for the well over the past several years to minimize loss of life from period of 1970 to 1979 was 109 n mi (202 km), 244 n mi (452 hurricanes. However, recent studies based upon numerical km), and 377 n mi (699 km), respectively, for 24-, 48- and storm surge model (SLOSH) simulations (Crawford, 1979, 72-hour forecasts (Neumann and Pelissier, 1981a). Instead and Lawrence, 1984) have shown that lead times much of the approximate 50 to 60% over-warning that currently ex- longer than the present 12 hours are required in several ists, over-warning would be as much as 90% at 72 hours lead communities along the coast from Texas to Maine. time. Costs of preparations for a typical warned area for an Hurricanes are rather large weather systems that can si- average-sized hurricane are nearly $50 million; these costs multaneously or nearly simultaneously affect several com- would multiply if longer lead time warnings were issued munities along or near the coastal region of landfall. Evacua- where their extent was based upon average errors for the ex- tion efforts in one community generally affect similar actions tended forecast period. Many residents would soon ignore in adjacent communities since they often share common warnings, waiting until the storm's winds or tides were affect- roadway systems and places of refuge. Many areas have now ing the area before taking action. In some areas, such courses taken a regional approach to evacuation planning. Results of of action could result in considerable loss of life and the few comprehensive evacuation studies that have been property. completed (many remain to be done) indicate a problem of One further factor to be considered is that the majority of major proportions. Evacuation of only the vulnerable resi- coastal residents do not need to be evacuated. These residents of communities such as the Tampa Bay area, the Fort dents and most businesses generally only need time to close Myers area, the Florida Keys, and Miami and Ft. Lauder- up and "board up." The familiar National Weather Service dale, Florida, as well as Galveston, Texas, and Hilton Head, hurricane watch and warning program is generally adequate South Carolina, require lead times of 20 to 30 hours or more. for these purposes. A major disadvantage of this system, es- Similar conditions are expected for several other coastal pecially for large businesses and industry as well as local gov- communities. Furthermore, these conditions will likely worsen ernments, is that it permits only a qualitative assessment of as coastal populations continue to grow. In addition, many risk. Community officials and private industry decision- businesses and industry often require long lead times to pre- makers would like to be able to assess their risks in a quantita- pare for specified storm conditions. Clearly, the standard tive fashion so that costs of preparation versus potential loss hurricane watch and warning programs do not provide suffi- analyses can be made for determining where, what, and when cient lead times or quantitative information to meet the actions, if any, should be taken. needs of many potential users of these products. With these factors in mind, the National Weather Service decided to continue the familiar hurricane watch and warning program for use by the general public. In addition, a pro- © 1985 American Meteorological Society gram has been initiated which provides quantitative infor- Vol. 66, No. 1, January 1985 Unauthenticated | Downloaded 10/05/21 06:54 PM UTC Bulletin American Meteorological Society 5 mation for assessment of the likelihood that the center of the storm will pass within a prespecified distance of selected coastal cities or island locations. This information is primar- ily intended for government officials and other decision- makers, but is made available through public distribution to assure that as many possible users as practicable will have ac- cess to these data. 2. Hurricane probabilities—background There are several possible approaches to determine the probability or likelihood that a hurricane will strike a given point FIG. 2. Schematic of overlapping 50% probability ellipses (ap- in time and space. Several methods have been developed proximated by circles) for a hypothetical hurricane forecast to move based upon climatological records (Cry, 1961; Hope and at 10 knots (5 m/sec). Neumann, 1968 and 1971; Simpson and Lawrence, 1971; Jarvinen and Neumann, 1978). Refinements have included were composited relative to the forecast position at the dis- development of statistical prediction models for future crete forecast verification times of 12, 24, 48, and 72 hours. movement of storms in probabilistic form based upon these Crutcher et al. (1981) derived three mode bivariate normal climatological data sets (Hope and Neumann, 1970); other distributions from these data. Simplified versions (i.e., circu- refinements include the addition of current and predicted en- lar distributions assumed) of these distributions were utilized vironmental conditions (Neumann and Pelissier, 1981b). The in the U.S. Navy program (Jarrell, 1981) and have been operational forecaster uses this information for guidance, as adopted for the present time by the NWS program. The pa- well as other analyses of current and expected changes of en- rameters for these discrete time period distributions are used vironmental conditions in preparing forecasts. Error statis- to interpolate and integrate at three-hourly time steps tics indicate that the resultant official forecasts generally through the 72-hour period with overlapping probabilities show improvements over these other methods. One possible removed. Fig. 2 illustrates the 50% probability ellipses (ap- refinement that would be quantitative and still take into ac- proximated by circles) at 12-hour intervals through 72 count the uncertainty in the forecast track, would be to quan- hours, for a hypothetical hurricane forecast to move at 10 tify the official forecast in probabilistic form. knots (5 m 'S_1). The final probabilities for each site of in- S. J. Kimball (1958) developed a technique for estimating terest are arrived at by proportioning the probabilities ob- the probability of hurricane force winds affecting specific lo- tained from the three distributions based upon parameters cations in the western North Pacific Ocean area. A circular, for the specific storm, such as location and the direction and normal distribution of errors was assumed for determining speed of motion. the probability densities. The size of the wind field of interest To determine probabilities for a given site, one must define was placed over the site, with appropriate offsets for asym- what is meant by a storm affecting a location. The NWS has metric distributions, and the probability was then computed arbitrarily defined a "strike" as the center of the storm mov- for determining if the center of the storm would be within or ing through a zone within approximately 50 n mi (93 km) to have passed through the area of interest in a given time pe- the right of or 75 n mi (139 km) to the left of the site of inter- riod. Nomograms were developed for use at the various loca- est. This zone is approximated by a circle of radius 62.5 n mi tions. The pioneering work of Kimball was followed by re- (116 km) whose center is offset from the point of interest by finements by Appleman (1962). Where Kimball used a single 12.5 n mi (23 km) to account for the frequent asymmetry in forecast error field distribution, Appleman used three distri- the storm's wind field. This area would approximately define butions dependent upon storm latitude. He later applied the the region of hurricane force winds for a typical hurricane. same technique to the western North Atlantic Ocean area. (Storms vary in size and intensity, but the definition of a Nearly 20 years later, Jarrell (1978), using essentially the storm "strike" has been fixed, as described above, to simplify same approach as Kimball, but with modern computer me- the communication and interpretation of the storm proba- thods and more refined estimates of forecast error distribu- bilities.) tions, developed an operational program for estimating trop- Fig. 3 provides a conceptual illustration (not the exact ical cyclone "strike probabilities" for selected United States technique used by NWS) of how probabilities may be derived Department of Defense (DoD) sites in the western North Pa- for specific sites based upon the forecast track and histor- cific Ocean area and later for the North Atlantic area (Jarrell, ical forecast error analyses.

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