Nowcasting the variation of wind speed with height using gust factor measurement.Abstract In the atmospheric surface boundary layer boundary layer In fluid mechanics, a thin layer of flowing gas or liquid in contact with a surface (e.g., of an airplane wing or the inside of a pipe). The fluid in the boundary layer is subjected to shear forces. from the ground level up to a few hundred feet, the wind speed normally increases with height under near-neutral conditions. Knowledge of the vertical variation of the wind speed is important to operational meteorologists Atmospheric scientists
River, central U.S. It rises at Lake Itasca in Minnesota and flows south, meeting its major tributaries, the Missouri and the Ohio rivers, about halfway along its journey to the Gulf of Mexico. ? What would be the expected wind loading on a high-rise building high-rise building Multistory building taller than the maximum height people are willing to walk up, thus requiring vertical mechanical transportation. The introduction of safe passenger elevators made practical the erection of buildings more than four or five stories tall. which might be used as a vertical evacuation shelter? This increase in wind speed is often estimated operationally using the power-law wind profile. However, its exponent exponent, in mathematics, a number, letter, or algebraic expression written above and to the right of another number, letter, or expression called the base. In the expressions x2 and xn, the number 2 and the letter n needs to be determined objectively. This note provides a solution through the utilization of gust factor measurements. It is shown that the formula G = 1 + 2.88P is verified under the conditions of one tropicai storm and ten hurricanes for a total of 148 samples as measured from various airports, where G is the gust factor (i.e., the ratio of wind gust to the mean wind speed) and P is the exponent of the power-law profile. ********** 1. Introduction From time to time an operational meteorologist may be called upon to assist in the determination of the variation of wind speed with height at an elevation other than 10 m, the typical Automated Surface Observing System The Automated Surface Observing System The Automated Surface Observing Systems (ASOS) program is a joint effort of the National Weather Service (NWS), the Federal Aviation Administration (FAA), and the Department of Defense (DOD). (ASOS ASOS Automated Surface Observing System ASOS As Seen on Screen (fashion clothing site) ASOS Air Support Operations Squadron (USAF) ASOS A Saucerful of Secrets (Pink Floyd album) ) height. Nowcasting this vertical distribution of the wind speed is often needed, particularly during storm conditions or for emergency preparedness pre·par·ed·ness n. The state of being prepared, especially military readiness for combat. Noun 1. preparedness - the state of having been made ready or prepared for use or action (especially military action); "putting them (such as the event of an industrial fire) when routine weather measurements are available from airports located in the general region of the accident. This note intends to provide a rapid estimation for this practical application using the gust factor measurement for input. 2. Method and Justification In the atmospheric surface boundary layer which extends from the ground up to a few hundred feet, the wind speed generally increases with height. Operationally, this power-law wind profile is often used (e.g., Panofsky and Dutton 1984) [v.sub.2] = [v.sub.1]([z.sub.2]/[z.sub.1])[.sup.P] (1) where [v.sub.1] is the reference (or known) wind speed (e.g., from ASOS) at the known height of [z.sub.1] (e.g., 10 m), [v.sub.2] is the wind speed needed at the height of [z.sub.2], and P is the exponent of this power-law profile. According to according to prep. 1. As stated or indicated by; on the authority of: according to historians. 2. In keeping with: according to instructions. 3. Simpson and Riehl (1981, p. 202), for open country near the coastline, P = 1/7 = 0.14. Since airports are normally located in the open country, we use the wind measurements from airports for this study. Under near-neutral conditions, P varies with the roughness length Please [improve the article] or discuss this issue on the talk page. , [z.sub.0], which is a function of surface irregularities (i.e., average spacing and height of surface features (Simpson and Riehl 1981, p. 201)). According to Justus (1985, p. 922), P = 0.13 when the roughness [z.sub.0] = 0.01 m and P = 0.19 when [z.sub.0] = 0.1 m. Because these variations are not linear, we use the power-curve fit as follows: let [P.sub.1] = a[z.sub.01.sup.b] (2a) where [P.sub.1] = 0.13 and [z.sub.01] = 0.01 m and [P.sub.2] = a[z.sub.02.sup.b] (2b) where [P.sub.2] = 0.19 and [z.sub.02] = 0.1 m. Solving Eqs. (2a) and (2b) simultaneously using the known boundary conditions boundary condition n. Mathematics The set of conditions specified for behavior of the solution to a set of differential equations at the boundary of its domain. , we get P = 0.278[z.sub.0.sup.0.165] (2c) for the [z.sub.0] range between 0.01 and 0.1 m. According to Panofsky and Dutton (1984, p. 123), [z.sub.0] = 0.025 m for airports (runway area). Substituting this [z.sub.0] into Eq. (2c), we have P = 0.15 (3) This supports P = 0.14 as recommended in Simpson and Riehl (1981) as reasonable. Based on the formula for estimating wind maxima as suggested in Panofsky and Dutton (1984, p. 376), a relationship between the gust factor and P has been proposed by Hsu (2001, Eq. 2) that, under near-neutral conditions, G = 1 + 2.88P (4) Therefore, using Eq. (1) the wind speed at any height in the atmospheric surface boundary layer, which is typically between the ground and 100 m, can be estimated if P can be determined objectively. With the gust factor measurements, this is accomplished by applying Eq. (4). The purpose of this note is to further verify Eq. (4) so that Eq. (1) may be correctly applied for operational use. First, we need to define what is meant by "near-neutral stability". According to the Pasquill stability classification (see, e.g., Panofsky and Dutton 1984, p. 242), the neutral class D should be assumed for overcast conditions during day or night or whenever the wind speed is higher than 6 m [s.sup.-1] except under strong incoming solar radiation solar radiation, n the emission and diffusion of actinic rays from the sun. Overexposure may result in sunburn, keratosis, skin cancer, or lesions associated with photosensitivity. (i.e., when the solar altitude is greater than 60[degrees] with clear skies Clear Skies could refer to:
`yən–), upward force exerted by a fluid on any body immersed in it. Buoyant force can be explained in terms of Archimedes' principle. effect.In order to verify Eq. (4), a large sample representing a similar environment (such as from airports) is required. In the data sets compiled by Pasch et al. (2001), Lawrence et al. (2001), and Franklin et al. (2001) there were 10 hurricanes and one tropical storm tropical storm n. A cyclonic storm having winds ranging from approximately 48 to 121 kilometers (30 to 75 miles) per hour. tropical storm yielding a total of 148 samples for use in this analysis. These data are listed in Table 1. Analyses of these data indicate that the grand mean of the gust factor for these 148 samples is 1.42 and the standard deviation In statistics, the average amount a number varies from the average number in a series of numbers. (statistics) standard deviation - (SD) A measure of the range of values in a set of numbers. is 0.18. In order to estimate the dispersion dispersion, in chemistry dispersion, in chemistry, mixture in which fine particles of one substance are scattered throughout another substance. A dispersion is classed as a suspension, colloid, or solution. of this data set, the coefficient of variation Coefficient of Variation A measure of investment risk that defines risk as the standard deviation per unit of expected return. is employed, which is the ratio of standard deviation to mean so that 0.18/1.42 = 12.7%. If we accept this 13% value as reasonable, then G = 1.42 is a useful magnitude to proceed further. 3. Conclusion Now, substituting G = 1.42 into Eq. (4), we get P = 0.15. Since this value is the same as Eq. (3), we conclude that Eq. (4) can be used to get P objectively from G and then this P can confidently be employed in Eq. (1) for operational applications such as nowcasting. Since Eq. (4) is verified, it may be applied to other environments on land if G is available. Note, that if the mean wind speed is less than 6 m [s.sup.-1] (or 12 kt), P is a function of not only [Z.sub.0] but also stability. In this regard, the method to estimate P provided in Justus (1985) should be consulted.
Table 1. Measured Gust Factors During ten Hurricanes and one Tropical
Storm at Various Airports (Data sources: Pasch et al. (2001), Lawrence
et al. (2001), and Franklin et al. (2001))
Hurricane Station G
Bonnie St. Thomas AP U.S. V.I. 1.43
1998 Charleston Intl. AP 1.32
Florence AP 1.29
Oceana NAS 1.42
Langley AFB 1.26
Norfolk AP 1.40
Norfolk NAS 1.33
Earl Moisant Intl. AP 1.24
1998 New Orleans Lakefront AP 1.10
Pascagoula/Trent Lott AP 1.38
Mobile Regional AP 1.22
Mobile Brookley Field 1.29
Dothan AP 1.41
Pensacola Regional AP 1.53
Pensacola NAS 1.34
Hurlburt Field AFB 1.42
Whiting Field (Milton) 1.61
Panama City AP 1.28
Marianna Municipal AP 1.31
Tallahassee Regional AP 1.38
Perry-Foley AP 1.33
Cross City AP 1.37
Tampa AP 1.22
MacDill AFB 1.42
Sarasota AP 1.28
Regional SW AP 1.26
Georges Hamilton AP, St. Croix 1.23
1998 Cyril E. King AP, St. Thomas 1.23
Luis Martin AP P.R. 1.17
Roosevelt Roads NAS 1.22
Patrick AFB 1.53
Miami Intl. AP 1.33
Tamiami AP 1.73
Tampa AP 1.50
MacDill AFB 1.85
Sarasota AP 1.24
Regional SW AP 1.54
Tallahassee AP 1.21
Panama City AP 1.54
Milton/Whiting Field 1.32
Hurlburt AFB 1.57
Eglin AFB 1.88
Pensacola AP 1.32
Pensacola NAS 1.53
Mobile Regional AP 1.25
Mobile Brookley Field 1.15
Gulfport AP 1.50
Pascagoula/Trent Lott AP 1.31
Moisant Intl. AP 1.31
New Orleans Lakefront AP 1.23
Mitch Key West AP 1.37
1998 Boca Chica NAS 1.52
Marathon AP 1.67
Homestead AFB 1.75
Tamiami AP 1.65
Miami Intl. AP 1.95
Opalocka AP 1.36
Fort Lauderdale AP 1.24
Fort Lauderdale Ex. AP 1.36
Pampano Beach AP 1.39
Naples AP 1.50
Vero Beach AP 1.68
Patrick AFB 1.37
Fort Pierce AP 1.45
Orlando Intl. AP 1.26
Tampa AP 1.64
MacDill AFB 1.83
Sarasota AP 1.67
Fort Myers Regional AP 1.22
Bret Brownsville AP 1.62
1999 Cameron City AP 1.28
Harlington AP 1.26
McAllen AP 1.32
Kingsville NAS 1.26
Dennis Cherry Pt. Marine Corps. 1.29
1999 Wilmington AP 1.26
Norfolk AP 1.24
Langley AFB 1.47
Floyd Fort Lauderdale Ex. AP 1.43
1999 Fort Lauderdale Intl. AP 1.44
Melbourne AP 1.31
Patrick AFB 1.16
Tamiami AP 1.48
Savannah AP 1.31
Charleston Intl. AP 1.32
Florence AP 1.50
Seymour Johnson AFB 1.33
Wilmington AP 1.39
Langley AFB 1.38
Norfolk AP 1.48
Norfolk NAS 1.26
Patuxent NAS 1.20
Newark Intl. AP 1.21
Teterboro AP 1.58
Farmingdale AP 1.61
Islip/MacArthur AP 1.37
JFK Intl. AP 1.37
LaGuardia AP 1.37
Montgomery AP 1.52
Montauk Point AB 1.68
Westhampton AP 1.54
White Plains AP 1.68
Bridgeport AP 1.34
Danbury AP 1.40
Meridan Markham AP 1.70
Irene Key West Intl. AP 1.24
1999 Tamiami AP 1.33
Homestead AFB 1.76
Miami Intl. AP 1.49
Pompano Beach AP 1.25
Fort Lauderdale Ex. AP 1.25
Opalocka AP 1.26
West Palm Beach AP 1.43
North Perry AP 1.35
Orlando Intl. AP 1.27
Melbourne AP 1.45
Vero Beach AP 1.59
Lenny V.C. Bird Intl. AP 1.43
1999 Hamilton AP St. Croix 1.33
Cyril King AP St. Thomas 1.33
Luis Martin AP 1.17
Opal* NEW 1.40
1995 MEI 1.50
MOB 1.53
MXF 1.90
MGM 1.33
AUB 1.92
BHM 1.57
ANB 1.38
HSV 1.32
NPA 1.26
HRT 1.68
PAM 1.36
AQQ 1.86
TLH 1.64
BKV 1.40
TPA 1.82
PIE 1.54
ATL 1.57
T.S. Frances Acadiana Regional AP 1.30
1998 Jefferson Parish AP 1.30
Lake Charles AP 1.25
Lafayette Regional AP 1.30
Galveston AP 1.27
Houston Intl. AP 1.29
Houston/Hobby AP 1.25
Palacios AP 1.59
Corpus Christi NAS 1.31
GRAND MEAN 1.42
Standard Deviation 0.18
Coefficient of Variation 13%
*from Hsu (2001)
Acknowledgments Comments to improve this paper from Mary M. Cairns Cairns, city (1991 pop. 64,463), Queensland, NE Australia, on Trinity Bay. It is a principal sugar port of Australia; lumber and other agricultural products are also exported. The city's proximity to the Great Barrier Reef has made it a tourist center. from the Office of the Federal Coordinator for Meteorological me·te·or·ol·o·gy n. The science that deals with the phenomena of the atmosphere, especially weather and weather conditions. [French météorologie, from Greek Services and Supporting Research are appreciated. References Franklin, J. L., C. A. Avila, J. L. Beven, M. B. Lawrence, R. J. Pasch, and S. R. Stewart, 2001: Atlantic hurricane Atlantic hurricane refers to a tropical cyclone that forms in the Atlantic Ocean usually in the Northern Hemisphere summer or autumn, with one-minute maximum sustained winds of 74 mph (64 knots, 33 m/s, 119 km/h). season of 2000. Mon. Wea. Rev., 129, 3037-3056. Hsu, S. A., 1988: Coastal Meteorology meteorology, branch of science that deals with the atmosphere of a planet, particularly that of the earth, the most important application of which is the analysis and prediction of weather. , Academic Press, 260 pp. ________, 2001: Spatial variations in gust factor across the coastal zone during Hurricane Opal Hurricane Opal was a major hurricane that formed in the Gulf of Mexico in September 1995. [1] Opal was the 9th hurricane of the abnormally active 1995 Atlantic hurricane season. in 1995. Natl. Wea. Dig., 25:1-2, 21-23. Justus, C. C., 1985: Wind Energy, in Handbook of AppliedMeteorology, D. Houghton (Editor), Wiley, pp. 915-944. Lawrence, M. B., L. A. Avila, J. L. Beven, J. L. Franklin, J. L. Guiney, and R. J. Pasch, 2001: Atlantic hurricane season of 1999. Mon. Wea. Rev., 129, 3057-3084. Panofsky, H. A., and J. A. Dutton, 1984: Atmospheric Turbulence. John Wiley John Wiley may refer to:
Pasch, R. J., L. A. Avila, and J. L. Guiney, 2001: Atlantic hurricane season of 1998. Mon. Wea. Rev., 129, 3085-3123. Simpson, R. H., and H. Riehl, 1981: The Hurricane and Its Impact. Louisiana State University Press This article needs sources or references that appear in reliable, third-party publications. Alone, primary sources and sources affiliated with the subject of this article are not sufficient for an accurate encyclopedia article. , Baton Rouge, Louisiana For the Canadian restaurant, see . Baton Rouge (from the French bâton rouge), pronounced /ˈbætn ˈɹuːʒ/ in English, and , 398 pp. S. A. Hsu Coastal Studies Institute Louisiana State University Louisiana State University and Agricultural and Mechanical College, generally known as Louisiana State University or LSU, is a public, coeducational university located in Baton Rouge, Louisiana and the main campus of the Louisiana State University System. Baton Rouge, Louisiana Author Dr. S Dr. Doctor. dr. dram. . A. Hsu has been a Professor of Meteorology at Louisiana State University since 1969, after he earned his Ph.D. in Meteorology from the University of Texas at Austin “University of Texas” redirects here. For other system schools, see University of Texas System. The University of Texas at Austin (often referred to as The University of Texas, UT Austin, UT, or Texas . He is the author of Coastal Meteorology (Academic Press, 1988) and numerous papers on coastal and marine meteorology and air-sea interaction. Dr. Hsu is also an AMS AMS - Andrew Message System Certified Consulting Meteorologist Certified Consulting Meteorologist is the title of a person designated by the American Meteorological Society and CCM Board to possess the attributes of Knowledge, Experience, and Character as they pertain to the field of meteorology. . Dr. Hsu can be contacted at the LSU LSU Louisiana State University LSU Large Subunit LSU La Salle University (Philadelphia, PA) LSU La Sierra University LSU Link State Update (OSPF) LSU Learning Support Unit Coastal Studies Institute, 308 Howe-Russell Geoscience ge·o·sci·ence n. Any one of the sciences, such as geology or geochemistry, that deals with the earth. ge Building, Baton Rouge, Louisiana 70803-7527; e-mail: sahsu@antares.esl.lsu.edu. |
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