Estimates of Various Types of Wind Speeds | Wind Engineering

In this article we will discuss about the estimates of various types of wind speeds.

Estimates of Extreme Wind Speeds from Short Records:

A procedure for estimating extreme wind speeds without regard for direction at locations where long-term data are not available was reported by Simiu et al. (1982) and Grigoriu (1984). The method, whose applicability was tested for 36 U.S. stations and a total of 67 three-year records, makes it possible to infer the approximate probabilistic behavior of extreme winds from data consisting of the largest monthly wind speeds recorded over a period of three years or longer. Estimators of the wind speed with an N-year mean recurrence interval and of the corresponding standard deviation of the sampling errors are given in Simiu and Scanlan.

Inferences concerning the probabilistic model of the extreme wind climate have also been attempted from data consisting of largest daily or largest hourly wind speeds by the authors just quoted and by Gusella (1991). Using such data raises two questions. First, what is the effect on the analysis of the mutual correlation among daily or hourly data?

According to an estimate by Grigoriu (1982) that effect is tolerably small. Second, what is the effect of basing the inferences on data that are overwhelmingly representative of weak winds having little in common metorologically with the extreme winds of interest? According to preliminary results by Gross et al. (1995), weak winds may be viewed as noise obscuring the process of interest, rather than providing useful information on wind extremes.

Estimates of Hurricane/Tropical Cyclone Wind Speeds:

In tropical-cyclone-prone regions the winds of interest to the structural engineer are primarily those associated with hurricanes (strong tropical cyclones). Statistical analyses of hurricane winds would therefore be necessary. However, the number of hurricane wind speed data at any one location is in most cases small. The confidence limits for predictions based on hurricane wind speed data at one location would, in general, be un-acceptably wide.

For this reason estimates of hurricane wind speeds at a site are obtained indirectly from statistical information on the climatological characteristics of hurricanes, used in conjunction with a physical model of the hurricane wind field.

Such a model, allows the estimation of maximum wind speeds induced at any given location by a hurricane for which the following climatological characteristics are specified:

i. Difference between atmospheric pressures at the center and the periphery of the storm,

ii. Radius of maximum wind speeds,

iii. Speed of storm motion, and

iv. Coordinate of crossing point along the coast or on a line normal to the coast.

The probability distribution of the hurricane wind speeds is then estimated as follows:

(1) A region is defined such that hurricanes occurring outside that region have a negligible effect at the site of concern. (In the United States such a region includes 750 km of coastline, say, and a 450 km segment over the ocean, normal to the coast.).

(2) The climatological characteristics of the hurricane, including the frequency of hurricane occurrences in this region, are modeled probabilistically from statistical data obtained in the region under consideration.

(3) The values of the climatological characteristics for a number, n, of hurricanes are obtained by Monte Carlo simulation from these probabilistic models.

(4) The maximum wind speeds, v_i, (i=1, 2, . . ,n) induced by each of these hurricanes at the location of concern are calculated on the basis of the climatological characteristics thus obtained and of the physical model of the hurricane wind field, including a model for the decay of the storm as it travels over land. Thus, a set of n hurricane wind speeds is calculated, which is consistent with the statistical data on climatological characteristics of hurricanes in the region of interest.

(5) A statistical estimation procedure is applied to the calculated hurricane wind speeds in order to estimate the probability distribution of the hurricane wind speeds at the location being considered.

The procedure just oulined was first developed by Russell (1971), and was applied with various modifications by, among others, Batts et al. (1980a) and Georgiou et al. (1983), whose respective estimates for the Gulf coast and the East coast of the United States are compared in Simiu and Scanlan (1986).

Recent work by Vickery and Twisdale (1994) was aimed at improving certain aspects of the estimates by Batts et al. (1980), and resulted in lower estimates of hurricane wind speeds inland. Models of the ratio between peak gusts and sustained winds in hurricanes used by Batts et al. (1980) were based on data for extra-tropical storms. Improved models based on hurricane wind speed data have been proposed by Krayer and Marshall (1902).

The issue of sampling errors in the estimation of hurricane wind speeds was examined by means of Monte Carlo simulations, which showed that the standard deviation of the errors was typically 5 to 10 percent of the estimated speeds. A computer program for estimating direction effects in hurricanes is described in Hendrickson and Simiu (1986).

Lessons drawn from observations of characteristics and effects of hurricanes Hugo and Andrew are the object of studies by Sill and Sparks (1991), Reinhold et al. (1993), and Marshall (1993). The latter study reviews in detail, and contains recommendations for the improvement of, wind load provisions for manufactured home construction.

Estimates of Tornado Winds:

The approach to the estimation of hurricane winds discussed in the preceding section could be described, roughly, as the monitoring of a billiard game played by nature with balls in the form of hurricanes having complex physical and probabilistic characteristics, against various targets such as towns. A similar approach is used for tornado winds.

Let A_o be some large reference area, and let n be the estimated number of tornado occurrences per year in area A_o. The estimated probability that a tornado will strike a particular location within A_o in any one year is assumed to be P(H) = n a/A_o, where a – estimated mean area of individual tornado path.

The probability that a tornado with maximum wind speeds higher than some specified value V_o will strike a location in any one year can be written as P(H,V_o) = P(V_o)P(H), where P(V_o) is the probability that the maximum wind speed is at least V_o, given that a tornado has occurred.

The estimation of P(H,V_o) relies on relatively few and uncertain data — inferred mostly from observations of damage — on tornado occurrences, path areas, and wind speeds, and on largely subjective extrapolations from these data to small probability levels. According to estimates presented by Markee et al. (1974), maximum tornado wind speeds corresponding to a probability P(H,V_o) = 10^-7 in any one year vary between 400 mph (179 m/s) in Oklahoma and Nebraska to 240 mph (107 m/s) in Northern California and Oregon.