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1.
Surface-layer features with different prevailing wind directions for two distinct seasons (Southwest Monsoon and Northeast Monsoon) on the west coast of India are studied using data obtained from tower-based sensors at a site located about 500 m from the coast. Only daytime runs have been used for the present analysis. The surface boundary-layer fluxes have been estimated using the eddy correlation method. The surface roughnessz 0 obtained using the stability-corrected wind profiles (Paulson, 1970) has been found to be low for the Southwest monsson season. For the other season,z 0 is relatively high. The drag coefficientC D varies with height in the NE monsoon season but not in the season with lowz 0. This aspect is reflected in the wind profiles for the two seasons and is discussed in detail. The scaling behaviour of friction velocityu * and the turbulence intensity of longitudinal, lateral and vertical winds u, v and w, respectively) are further examined to study their dependence on fetch. Our study shows that for the non-dimensional case, u/u* and v/u* do not show any surface roughness dependence in either season. On the other hand, for w/u* for the season with lowz 0, the values are seen to agree well with that of Panofskyet al. (1977) for homogeneous terrain whereas for the other season with highz 0, the results seem to conform more to the values observed by Smedman and Högström (1983) for coastal terrain. The results are discussed in the light of observations by other investigators.  相似文献   

2.
The standard deviation of vertical two-point longitudinal velocity fluctuation differences is analyzed experimentally with eleven sets of turbulence measurements obtained at the NASA 150-m ground-winds tower site at Cape Kennedy, Florida. It is concluded that /u *0 is proportional to (fz/u *0)0.22, where the coefficient of proportionality is a function of fz/u *0 and u *0/fL 0. The quantities f and L0 denote the Coriolis parameter and the surface Monin-Obukhov stability length, respectively; u *0 is the surface friction velocity; z is the vertical distance between the two points over which the velocity difference is calculated; and zz is the mean height of the mid-point of the interval z above natural grade. The results of the analysis are valid for 20<-u *0/fL 0<2000.  相似文献   

3.
Refuge has patchy vegetation in sandy soil. During midday and at night, the surface sources and sinks for heat and moisture may thus be different. Although the Sevilleta is broad and level, its metre-scale heterogeneity could therefore violate an assumption on which Monin-Obukhov similarity theory (MOST) relies. To test the applicability of MOST in such a setting, we measured the standard deviations of vertical (w) and longitudinal velocity (u), temperature (t), and humidity (q), the temperature-humidity covariance (¯tq), and the temperature skewness (St). Dividing the former five quantities by the appropriate flux scales (u*, *, and q*) yielded the nondimensional statistics w/u*, u/u*, t/|t*|, q/|q*|, and ¯tq/t*q*. w/u*, t/|t*|, and St have magnitudes and variations with stability similar to those reported in the literature and, thus, seem to obey MOST. Though u/u* is often presumed not to obey MOST, our u/u* data also agree with MOST scaling arguments. While q/|q*| has the same dependence on stability as t/|t*|, its magnitude is 28% larger. When we ignore ¯tq/t*q* values measured during sunrise and sunset transitions – when MOST is not expected to apply – this statistic has essentially the same magnitude and stability dependence as (t/t*)2. In a flow that truly obeys MOST, (t/t*)2, (q/q*)2, and ¯tq/t*q* should all have the same functional form. That (q/q*)2 differs from the other two suggests that the Sevilleta has an interesting surface not compatible with MOST. The sources of humidity reflect the patchiness while, despite the patchiness, the sources of heat seem uniformly distributed.  相似文献   

4.
Many applied dispersion models require the knowledge of boundary-layer parameters such as sensible heat flux,Q H , friction velocity,u *, and turbulent energy components, w and v . Formulas are suggested for calculating these parameters over a wide variety of types of ground surfaces, based on simple observations of wind speed near the ground and fractional cloud cover, and specification of constants such as roughness length, albedo, and soil moisture availability. Observations ofu *,Q H , w , and v during field experiments in St. Louis and Indianapolis are used to test the formulas for urban sites. Relative errors of about ±20% in the predictions are seen to occur whenu *,Q H , w , and v are large. However, when these quantities are small (e.g.,u * < 0.2 m/s), the errors in the predictions are as large as the mean value of the quantity itself.In addition, it is concluded from studies of available field data and theories that the magnitude of w is not well-known at elevations above about 100m during the late afternoon and night. Some simple parameterizations for w . are suggested that are consistent with the observed steady decrease in ground-level concentration in the afternoon and the sudden increase in concentration that can occur a few hours after sunset due to wind shears associated with a low-level jet, for continuous plumes emitted from moderate to tall stacks.  相似文献   

5.
Vertical dispersion in the neutral surface layer is investigated using a Markov Chain simulation procedure. The conceptual basis of the procedure is discussed and computation procedures outlined. Wind and turbulence parameterizations appropriate to the neutral surface layer are considered with emphasis on the Lagrangian time scale. Computations for a surface release are compared with field data. Good agreement is found for the variation of surface concentration and cloud height to distances 500 m downwind of the source. The functional form of the vertical concentration profile is examined and an exponential with exponent 1.6 is found to give the best fit with simulations.For elevated releases, it is demonstrated that an initial dip of the mass mean height from the simulation can be normalized for various release heights using a non-dimensionalized downwind coordinate incorporating advective wind speed and wind shear. The vertical distribution standard deviation ( z ), as employed in Gaussian models, shows a fair degree of independence with source height but close examination reveals an optimum source height for maximum z at a given downwind distance,x. This source height increases with downwind distance. Also the simulations indicate that vertical wind shear is more important than vertical variation of Lagrangian time scale close to the source, with a reverse effect farther downwind.  相似文献   

6.
Horizontal diffusion in the surface layer is dependent on the standard deviation of wind direction fluctuations . Diurnal variation of this parameter in complex terrain was studied for the July 1979 Geysers, Cal., experiment using data from a network of 11 short meteorological towers in the 25 km2 Anderson Creek watershed Valley side slopes are roughly 20 ° and maximum terrain difference is about 1 km.Values of for wind directions sampled for one hour at a height of 10 m are about 35 ° during the daytime. They slowly decrease to about 20 ° by 8 to 10 p.m. as stability increases but wind speeds are still relatively high. After 10 p.m. the drainage flow sets in at most stations, with speeds of 1 to 2 m s-1, and average increases to about 30° during the period 11 p.m. to 6 a.m. In general, highest values of at night are associated with lowest values of wind speed and greatest static stability. This enhancement of by the terrain suggests that horizontal diffusion at night always conforms to that expected during nearly neutral stabilities. That is, Pasquill class D diffusion applies to the horizontal component all night in complex terrain.  相似文献   

7.
Source/sink distributions of heat, water vapour andCO2 within a rice canopy were inferred using aninverse Lagrangian dispersion analysis and measuredmean profiles of temperature, specific humidity andCO2 mixing ratio. Monin–Obukhov similarity theorywas used to account for the effects of atmosphericstability on w(z), the standard deviation ofvertical velocity and L(z), the Lagrangian timescale of the turbulence. Classical surface layer scaling was applied in the inertial sublayer (z > zruf)using the similarity parameter = (z - d)/L, where z is height above ground, d is the zero plane displacementheight for momentum, L is the Obukhov length,and zruf 2.3hc, where hc iscanopy height. A single length scale hc, was usedfor the stability parameter 3 = hc/L in the height range 0.25 < z/hc < 2.5. This choice is justified by mixing layer theory, which shows that within the roughness sublayer there is one dominant turbulence length scaledetermined by the degree of inflection in the windprofile at the canopy top. In the absence of theoretical or experimental evidence for guidance,standard Monin–Obukhov similarity functions, with = hc/L, were used to calculate the stabilitydependence of w(z) and L(z) in the roughness sublayer. For z/hc < 0.25 the turbulence length and time scales are influenced by the presence of the lowersurface, and stability effects are minimal. With theseassumptions there was excellent agreement between eddycovariance flux measurements and deductions from theinverse Lagrangian analysis. Stability correctionswere particularly necessary for night time fluxes whenthe atmosphere was stably stratified.The inverse Lagrangian analysis provides a useful toolfor testing and refining multilayer canopy models usedto predict radiation absorption, energy partitioningand CO2 exchanges within the canopy and at thesoil surface. Comparison of model predictions withsource strengths deduced from the inverse analysisgave good results. Observed discrepancies may be dueto incorrect specification of the turbulent timescales and vertical velocity fluctuations close to theground. Further investigation of turbulencecharacteristics within plant canopies is required toresolve these issues.  相似文献   

8.
Turbulence measurements performed in a stable boundary layer over the sloping ice surface of the Vatnajökull in Iceland are described. The boundary layer, in which katabatic forces are stronger than the large-scale forces, has a structure that closely resembles that of a stable boundary layer overlying a flat land surface, although there are some important differences. In order to compare the two situations the set-up of the instruments on an ice cap in Iceland was reproduced on a flat grass surface at Cabauw, the Netherlands. Wind speed and temperature gradients were calculated and combined with flux measurements made with a sonic anemometer in order to obtain the local stability functions m and h as a function of the local stability parameter z/L. Unlike the situation at Cabauw, where m was linear as a function of z/L, in the katabatically forced boundary layer, the dependence of m on stability was found to be non-linear and related to the height of the wind maximum. Thermal stratification and the depth of the stable boundary layer however seem to be rather similar under these two different forcing conditions.Furthermore, measurements on the ice were used to construct the energy balance. These showed good agreement between observed melt and components contributing to the energy balance: net radiation (supplying 55% of the energy), sensible heat flux (30%) and latent heat flux (15%).Local sources and sinks in the turbulent kinetic energy budget are summed and indicate a reasonable balance in near-neutral conditions but not in more stable situations. The standard deviation of the velocity fluctuations u, v, and w, can be scaled satisfactorily with the local friction velocity u* and the standard deviation of the temperature fluctuation with the local temperature scale *.  相似文献   

9.
In this paper, a model simulating the effects of topography and altitude on precipitation is presented. Topography has its maximum effect on precipitation when the angle which the wind makes with the slope direction approaches zero and the inclination of the slope is near 45°. The smaller the angle , the greater the influence of slope on precipitation. When <45°, the larger the inclination, the greater the influence of slope on precipitation and the less the difference in precipitation between the windward and the leeward slopes. When <45°, the reverse holds. But for in the range of 0°–45° and in the range 30°–60°, differences in precipitation on both the windward and leeward slopes are not so well marked and can be neglected in general. In condition of uniform slope inclination, precipitation on the windward slope increases with altitude at first and then decreases after attaining a height (H m ) of maximum precipitation; alsoH m is greater, the drier the air mass. When the terrain on the windward side is stepped in shape, it is possible that more than one height of maximum precipitation will occur.  相似文献   

10.
The system transfer function ¦H(v)¦2 at frequencyv (units of Hz) for a vertical velocity propeller anemometer in a statistically stationary and horizontally homogeneous turbulent flow is determined from: (1) experimental estimates of propeller velocity spectra; and (2) estimates of Eulerian vertical velocity spectra based on the hypothesis that degradation of the input vertical velocity Fourier components occurs in the inertial subrange. The experimental estimates of ¦H(v)¦2 were adequately summarized with the mathematical expression for the system transfer function of a first-order system with parameterT which has units of time and is analogous to the time constant of a horizontal velocity propeller anemometer. Dimensional analysis techniques and the Monin-Obukhov similarity hypothesis were used to construct a model for the system parameterT which yielded the result that w /D 1 ( w /)1/3, where w , andD 1 denote the standard deviation of the input vertical velocity fluctuations, the horizontal mean wind speed, and the diameter of the propeller, respectively. The system parameterT is interpreted in terms of the time required for the propeller velocity statistics to become asymptotically independent of time upon being released from rest in a statistically stationary turbulent flow.Currently on leave of absence from the Indian Institute of Technology, New Delhi, India.  相似文献   

11.
Wind speed was measured at a height of 1 cm above the ground and at several other heights in and above a canopy of tall fescue grass (Festuca arundinacea) using single hot-wire and triple hot-film anemometers. The plant area density in the canopy was concentrated close to the ground, with 75% of the plant area standing belowz=15 cm, wherez is height above the ground. The frequency distributions of horizontal wind speeds,s, were sharply skewed towards positive values at all measurement heights, but were most highly skewed near the ground where the coefficient of skewness ranged from 1.6 to 2.9. Above mid-canopy height, the frequency distribution ofs was described reasonably well by a Gumbel extreme value distribution. Average wind speed,S, decreased exponentially with depth into the canopy with an exponential scale length of abouth/2.8, whereh is the height of the canopy. Atz=1 cm, the value ofS was about 11% of the surface-layeru *. The standard deviation of the fluctuations of the vertical and horizontal components of the wind speed also decreased exponentially with depth inside the canopy with a scale length of abouth/2.5.Inside the canopy, the Eulerian integral time scales for the vertical ( w ) and horizontal ( u ) components of wind speed were about 0.1 s and 1.0 s, respectively, and were approximately constant with height. Above the canopy, these time scales increased sharply and, atz=2.25h, w and u were approximately 1.0 and 3.0s, respectively. Turbulence length scales in the vertical and downwind directions, u and w ·U, respectively, were approximately 1 cm for heights between 1 to 10 cm above the ground inside the canopy, while atz=2.25h, they were about 55 cm and 277 cm. Relatively quiescent periods (lulls) in the air close to the ground were interrupted frequently by gusts. The frequency of occurrence of gusts appears to be correlated with the value of the local shear near the top of the canopy.  相似文献   

12.
Local Similarity Relationships In The Urban Boundary Layer   总被引：5，自引：3，他引：2  
To investigate turbulent structures in an urban boundary layer (UBL) with many tallbuildings, a number of non-dimensional variable groups based on turbulent observationsfrom a 325-m meteorological tower in the urban area of Beijing, China, are analyzedin the framework of local similarity. The extension of surface-layer similarity to localsimilarity in the stable and unstable boundary layer is also discussed. According to localsimilarity, dimensionless quantities of variables: e.g., velocity and temperature standarddeviations i/u*l (i=u,v,w) andT/T*l,correlation coefficients of uw and wT covariance, gradients of wind and temperaturem and h, and dissipation rates of turbulent kinetic energy (TKE) andtemperature variance and N can be represented as a functiononly of a local stability parameter z/, where is the local Obukhovlength and z is the height above ground. The average dissipation rates of TKE andtemperature variance are computed by using the u spectrum, and the uw and wTcospectra in the inertial subrange. The functions above were found to be in a goodagreement with observational behaviour of turbulence under unstable conditions, butthere were obvious differences in the stable air.  相似文献   

13.
Analysis of data collected during the Prairie Grass, Kansas and Minnesota experiments reveals the following empirical relationship between the Monin-Obukhov length L and the friction velocity u *: L = Au * 2, A = 1.1 × 103s2m-1. This result combined with the formulation for the height of the stable boundary layer h suggested by Zilitinkevich (1972) leads to h u * 3/2 f–1/2 where f is the Coriolis parameter. Data from the Minnesota study (Caughey et al., 1979) provide ample support for this expression.These empirical equations for L and h are useful for routine dispersion estimates during stable conditions.  相似文献   

14.
Summary The atmospheric aerosol scattering coefficient s , measured for more than a year more or less continuously in Vienna, Austria, exhibits unexpected patterns of variation. Apart from the usual ones following changes in relative humidity or traffic characteristics,a distinctive pattern is found before a change in air mass. s rises by a factor of 1.5 to 2 some hours (usually two or three) before the passage of the front without a corresponding change in emission characteristics or relative humidity and then falls either below or to its previous level. This behaviour of s occurred at all frontal passages during the sampling period at all times of day and of year except when the wind speeds were very high.An explanation is attempted by examining the mixing heights before a change in airmass since a reduced vertical dispersion due to pre-frontal changes of stability could account for the increase in s (and thus the aerosol concentration). It has been found that calculated mixing heights are reduced by nearly the same factor as the value of s is increased before the front. After the front the factors are similar, but then the aerosol concentration depends also on the origin of the air mass.
Zusammenfassung Der Streukoeffizient des atmosphärischen Aerosols ( s ) wurde in Wien mehr als ein Jahr lang mehr oder weniger kontinuierlich gemessen. Dabei zeigten sich unerwartete Änderungen. Abgesehen vom üblichen Tagesgang im Zusammenhang mit Verkehr und relativer Feuchte fand sich vor einem Luftmassenwechsel ein charakteristischer zeitlicher Verlauf. s steigt einige Stunden (meist zwei oder drei) vor dem Frontdurchgang an, ohne daß sich die relative Feuchte oder die Quellencharakteristik entsprechend ändert, und fällt dann entweder auf oder unter seinen ursprünglichen Wert. Dieses Verhalten trat bei allen Frontdurchgängen zu jeder Tages- und Jahreszeit auf. Die einzigen Ausnahmen waren Fronten mit sehr hohen Windgeschwindigkeiten.In dieser Arbeit wird versucht, das Verhalten des Streukoeffizienten (und damit der Aerosolkonzentration) durch eine Betrachtung der Mischungshöhen zu erklären, da eine Reduktion der vertikalen Ausbreitung durch Stabilitätsänderungen vor der Front den Anstieg von s bewirken könnte. Eine Berechnung der Mischungshöhen ergab, daß sie vor der Front um fast denselben Faktor abnahmen um den s anstieg. Nach der Front waren die Änderungsfaktoren einander ähnlich, obwohl die Aerosolkonzentration auch vom Ursprung der Luftmasse abhing.

With 5 Figures  相似文献   

15.
In usual aerodynamic bulk formulas, the drag coefficient C d has been best estimated in the 5 to 16 m s–1 range of mean wind velocity; a value of 1.3 × 10–3 is often considered for operational use. However, in the 0 to 5 m s–1 range of mean wind velocity, corresponding to meteorological conditions of very light wind, experimental results have not resulted in any convincing agreement between various authors (Hicks et al., 1974; Wu, 1969; Kondo and Fujinawa, 1972; Mitsuta, 1973; Brocks and Krugermeyer, 1970).In the present paper, the drag coefficient is experimentally determined in conditions of very light wind and limited fetch (about 250 m). Due to this limited fetch, we have to be cautious in the extrapolation of our results to other sites. Nevertheless, some of experimental results are worth describing, considering the paucity of data in light wind conditions.Mean value and standard deviation (respectively 1.84 × 10–3 and 1.24 × 10–3) are obtained from 70 runs of 10-min duration. Mean wind velocities observed at 2 m above water surface are found to lie between 1.2 and 3.6 m s–1. Whereas this mean value is in fair agreement with C d 10 = 1.3 × 10–3, usually given for the 5 to 16 m s–1 range (Kraus, 1972), the above value for the standard deviation seems too large to be left without further analysis.A more exhaustive analysis of the 70 values obtained for C d shows that it depends on a parameter characteristic of longitudinal fluctuations of the wind velocity. A similar idea was put forward earlier by Kraus (1972). Relations between the drag coefficient and wind fluctuations may be tentatively given by: % MathType!MTEF!2!1!+-% feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4qamaaBa% aaleaacaWGKbGaaGOmaaqabaGccqGH9aqpdaqadaqaaiabgkHiTiaa% igdacaGGUaGaaGimaiaaiEdacqGHRaWkcaaIXaGaaGinaiaac6caca% aIZaGaaGinamaalaaabaGaeq4Wdm3aaSbaaSqaaiaadwhacaGGNaaa% beaaaOqaaaaaaiaawIcacaGLPaaaruqqYLwySbacfaGaa8hEaiaa-b% cacaaIXaGaaGimamaaCaaaleqabaGaeyOeI0IaaG4maaaakiaabcca% caqGGaGaaeiiaiaabccacaqGXaGaaeOlaiaabAdacaqGGaGaaeyBai% aabccacaqGZbWaaWbaaSqabeaacaqGTaGaaeymaaaakiabgsMiJkqa% dwhagaqeamaaBaaaleaacaaIYaaabeaakiabgsMiJkaaiodacaGGUa% GaaGOnaiaab2gacaqGGaGaae4CamaaCaaaleqabaGaaeylaiaabgda% aaaaaa!634E!\[C_{d2} = \left( { - 1.07 + 14.34\frac{{\sigma _{u'} }}{{}}} \right)x 10^{ - 3} {\text{ 1}}{\text{.6 m s}}^{{\text{ - 1}}} \leqslant \bar u_2 \leqslant 3.6{\text{m s}}^{{\text{ - 1}}} \] and % MathType!MTEF!2!1!+-% feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4qamaaBa% aaleaacaWGKbGaaGOmaaqabaGccqGH9aqpdaqadaqaaiabgkHiTiaa% iodacaGGUaGaaGioaiaaiAdacqGHRaWkcaaIZaGaaiOlaiaaiodaca% aI2aGaam4raaGaayjkaiaawMcaaerbbjxAHXgaiuaacaWF4bGaa8hi% aiaaigdacaaIWaWaaWbaaSqabeaacqGHsislcaaIZaaaaOGaaeilaa% aa!4B42!\[C_{d2} = \left( { - 3.86 + 3.36G} \right)x 10^{ - 3} {\text{,}}\] where u/\-u 2 and G, respectively, represent the standard deviation of u normalized with \-u 2 and the longitudinal gust factor quoted in Smith (1974).We have established a relationship between these fluctuation parameters and the stability as given by a bulk layer Richardson number (between 0 and 2 m). These relations are given by: % MathType!MTEF!2!1!+-% feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaSaaaeaacq% aHdpWCdaWgaaWcbaGaamyDaiaacEcaaeqaaaGcbaGabmyDayaaraWa% aSbaaSqaaiaaikdaaeqaaaaakiabg2da9iaaicdacaGGUaGaaGymai% aaikdacqGHRaWkcaaIZaGaaiOlaiaaiIdacaaI1aGaaeiiaiaabkfa% caqGPbWaaSbaaSqaaiaabcdacaqGTaGaaeOmaaqabaaaaa!4802!\[\frac{{\sigma _{u'} }}{{\bar u_2 }} = 0.12 + 3.85{\text{ Ri}}_{{\text{0 - 2}}} \] and G=1.35+14.56 Ri0–2. The increase in gustiness with stability is in qualitative agreement with Goptarev (1957)'s experimental results.In spite of the high-level correlation between C d and u/\-u 2(G) on the one hand and between u/\-u 2(G) and Ri0–2on the other hand, we found a poor relationship between C d and Ri0–2. It is worth noting too that the trend observed here for C d to increase with stability is in complete disagreement with the usual theoretical expectation for C d to decrease with increasing layer stability above water.

E.R.A. du C.N.R.S. n 259.  相似文献   

16.
The standard deviation of temperature T is proposed as a temperature scale and as a velocity scale to describe the behaviour of turbulent flows in the Atmospheric Surface Layer (ASL), instead of * andu * of the Monin—Obukhov similarity theory, and ofT f andU f used for free convection stability conditions. On the basis of experimental evidence reported in the literature, it is shown that T T f andv * U f in the free convection region, and T * andv * U * in nearneutral and stable conditions. This implies that the proposed scales can be applied for all stabilities. Furthermore, a new length scale is proposed and its relation with Obukhov length is given. Also, a simple semi-empirical expression is presented with which T andv * can be evaluated in a rather simple way. Some examples of practical applications are given, e.g., a stability classification for unstable conditions.  相似文献   

17.
The dissipation rate of turbulent kinetic energy, , and the temperature structure function parameter, C T 2, have been measured over water from the near surface (Z = 3 m) to the top of the boundary layer. The near surface values of and C T 2 were used to calculate the velocity and temperature Monin-Obukhov scaling parameters u * and T *. The data collected during unstable lapse rates were used to evaluate the feasibility of extrapolating the values of and C T 2 as a function of height with empirical scaling formulae. The dissipation rate scaling formula of Wyngaard et al. (l971 a) gave a good fit to an average of the data for Z < 0.8 Z i. In the surface layer the scaling formula of Wyngaard et al. (1971b) disagreed with the C T 2 values by as much as 50%. This disagreement is due to an unexpected reduction in the measured values of C T 2 forZ < 30 m. At this point it is not clear if the discrepancy is a unique property of the marine boundary layer or if it is simply some unknown instrumental or analytical problem. The mixed layer scaling results were similar to the overland results of Kaimal et al. (1976).  相似文献   

18.
The aerodynamic classification of the resistance laws above solid surfaces is based on the use of a so-called Reynolds roughness number Re s =h s u */, whereh s is the effective roughness height, -viscosity,u *-friction velocity. The recent experimental studies reported by Toba and Ebuchi (1991), demonstrated that the observed variability of the sea roughness cannot be explained only on the basis of the classification of aerodynamic conditions of the sea surface proposed by Kitaigorodskii and Volkov (1965) and Kitaigorodskii (1968) even though the latter approach gains some support from recent experimental studies (see for example Geernaertet al. 1986). In this paper, an attempt is made to explain some of the recently observed features of the variability of surface roughness (Toba and Ebuchi, 1991; Donelanet al., 1993). The fluctuating regime of the sea surface roughness is also described. It is shown that the contribution from the dissipation subrange to the variability of the sea surface can be very important and by itself can explain Charnock's (1955) regime.  相似文献   

19.
The derivation of the Panofsky–Dutton internal boundary-layer(IBL) height formula has been revisited. We propose that the upwindroughness length (rather than downwind) should be used in theformula and that a turbulent vertical velocity (w) ratherthan the surface friction velocity (u*) should be considered asthe appropriate scaling for the rate of propagation ofdisturbances into the turbulent flow. A published set ofwind-tunnel and atmospheric data for neutral stratification hasbeen used to investigate the influence of the magnitude ofroughness change on the IBL height.  相似文献   

20.
Standard deviations of concentration in horizontal andvertical directions i.e. y andz have been estimated by using fivedifferent schemes based on empirical(due to Pasquill and Briggs)schemes and sophisticated methods(due to Irwin, Draxler, Taylor, Hanna et al.). The fiveschemes are discussed atlength. The purpose of this study is to make use ofmeteorological observations whichare routinely available, to test all the above methods andintercompare the resultswith one another and observations so that the sensitivityof each schemeunder various atmospheric stability conditions could beassessed. It has beenfound that the existing schemes are good enough to providereasonable estimates ofdispersion coefficient (y) during highly unstableconditions (Pasquill stability classes A and B). However, thesame is not true for the case when the stability increasesfrom C to F and turbulencedecreases, specifically during stable atmospheric conditions,when the observedvalues were found to be much higher than all the existingschemes. This suggests thatwhile we continue to use the current methods of estimatingthe dispersion parameters,a rigorous search is required for methods which give predictionswhich are close-to-realityduring such conditions which are represented by lowlevels (in terms of magnitude)of atmospheric turbulence leading to higher levelsof pollution.As one of the sophisticated methods requiresthe use of v and w (standard deviationsof wind velocity fluctuation in y and z directions),these have been estimated andvalidated with observed data (field experiments conductedby EPRI at Kincaid).Statistical evaluation of v and wbased on performance measures indicate a goodperformance of the parameterisations adopted in thisstudy. In the case of w duringunstable conditions a comparison of three differentschemes with observations is made.  相似文献   

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