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1.
The relationship between satellite-derived low-level cloud motion, surface wind and geostrophic wind vectors is examined using GATE data. In the trades, surface wind speeds can be derived from cloud motion vectors by the linear relation: V = 0.62 V s + 1.9 m s–1 with a mean scatter of ±1.3 m s–1. The correlation coefficient between surface and satellite wind speed is 0.25. Considering baroclinicity, i.e., the influence of the thermal wind, the correlation coefficient does not increase, because of the uncertainty of the thermal wind vectors. The ratios of surface to geostrophic wind speed and surface to satellite wind speed are 0.7 and 0.8, respectively, with a statistical uncertainty of ±0.3. Calculations of the ratio of surface to geostrophic wind speed on the basis of the resistance law yield V/V g = 0.8 ± 0.2, in agreement with experimental results. The mean angle difference between the surface and the satellite wind vectors amounts to - 18 °, taking into account baroclinicity. This value is in good agreement with the mean ageostrophic angle - 25 °.  相似文献   

2.
In this paper we analyse diabatic wind profiles observed at the 213 m meteorological tower at Cabauw, the Netherlands. It is shown that the wind speed profiles agree with the well-known similarity functions of the atmospheric surface layer, when we substitute an effective roughness length. For very unstable conditions, the agreement is good up to at least 200 m or z/L–7(z is height, L is Obukhov length scale). For stable conditions, the agreement is good up to z/L1. For stronger stability, a semi-empirical extension is given of the log-linear profile, which gives acceptable estimates up to ~ 100 m. A scheme is used for the derivation of the Obukhov length scale from single wind speed, total cloud cover and air temperature. With the latter scheme and the similarity functions, wind speed profiles can be estimated from near-surface weather data only. The results for wind speed depend on height and stability. Up to 80 m, the rms difference with observations is on average 1.1 m s–1. At 200 m, 0.8 m s–1 for very unstable conditions increasing to 2.1 m s–1 for very stable conditions. The proposed methods simulate the diurnal variation of the 80 m wind speed very well. Also the simulated frequency distribution of the 80 m wind speed agrees well with the observed one. It is concluded that the proposed methods are applicable up to at least 100 m in generally level terrain.  相似文献   

3.
A two-dimensional mesoscale model has been developed to simulate the air flow over the Gulf Stream area where typically large gradients in surface temperature exist in the winter. Numerical simulations show that the magnitude and the maximum height of the mesoscale circulation that develops downwind of the Gulf Stream depends on both the initial geostrophic wind and the large-scale moisture. As expected, a highly convective Planetary Boundary Layer (PBL) develops over this area and it was found that the Gulf Stream plays an important role in generating the strong upward heat fluxes causing a farther seaward penetration as cold air advection takes place. Numerical results agree well with the observed surface fluxes of momentum and heat and the mesoscale variation of vertical velocities obtained using Doppler Radars for a typical cold air outbreak. Precipitation pattern predicted by the numerical model is also in agreement with the observations during the Genesis of Atlantic Lows Experiment (GALE).List of Symbols u east-west velocity [m s–1] - v north-south velocity [m s–1] - vertical velocity in coordinate [m s–1] - w vertical velocity inz coordinate [m s–1] - gq potential temperature [K] - q moisture [kg kg–1] - scaled pressure [J kg–1 K–1] - U g the east-south component of geostrophic wind [m s–1] - V g the north-south component of geostrophic wind [m s–1] - vertical coordinate following terrain - x east-west spatial coordinate [m] - y north-south spatial coordinate [m] - z vertical spatial coordinate [m] - t time coordinate [s] - g gravity [m2 s–1] - E terrain height [m] - H total height considered in the model [m] - q s saturated moisture [kg kg–1] - p pressure [mb] - p 00 reference pressure [mb] - P precipitation [kg m–2] - vertical lapse rate for potential temperature [K km–1] - L latent heat of condensation [J kg–1] - C p specific heat at constant pressure [J kg–1 K–1] - R gas constant for dry air [J kg–1 K–1] - R v gas constant for water vapor [J kg–1 K–1] - f Coriolis parameter (2 sin ) [s–1] - angular velocity of the earth [s–1] - latitude [o] - K H horizontal eddy exchange coefficient [m2 s–1] - t integration time interval [s] - x grid interval distance inx coordinate [m] - y grid interval distance iny coordinate [m] - adjustable coefficient inK H - subgrid momentum flux [m2 s–2] - subgrid potential temperature flux [m K s–1] - subgrid moisture flux [m kg kg–1 s–1] - u * friction velocity [m s–1] - * subgrid flux temperature [K] - q * subgrid flux moisture [kg kg–1] - w * subgrid convective velocity [m s–1] - z 0 surface roughness [m] - L Monin stability length [m] - s surface potential temperature [K] - k von Karman's constant (0.4) - v air kinematic viscosity coefficient [m2 s–1] - K M subgrid vertical eddy exchange coefficient for momentum [m2 s–1] - K subgrid vertical eddy exchange coefficient for heat [m2 s–1] - K q subgrid vertical eddy exchange coefficient for moisture [m2 s–1] - z i the height of PBL [m] - h s the height of surface layer [m]  相似文献   

4.
A model is developed to simulate the potential temperature and the height of the mixed layer under advection conditions. It includes analytic expressions for the effects of mixed-layer conditions upwind of the interface between two different surfaces on the development of the mixed layer downwind from the interface. Model performance is evaluated against tethersonde data obtained on two summer days during sea breeze flow in Vancouver, Canada. It is found that the mixed-layer height and temperature over the ocean has a small but noticeable effect on the development of the mixed layer observed 10 km inland from the coast. For these two clear days, the subsidence velocity at the inversion base capping the mixed layer is estimated to be about 30 mm s–1 from late morning to late afternoon. When the effects of subsidence are included in the model, the mixed-layer height is considerably underpredicted, while the prediction for the mean potential temperature in the mixed layer is considerably improved. Good predictions for both height and temperature can be obtained when values for the heat entrainment ratio,c, 0.44 and 0.68 for these two days respectively for the period from 1000 to 1300 LAT, were used. These values are estimated using an equation including the additional effects on heat entrainment due to the mechanical mixing caused by wind shear at the top of the mixed layer and surface friction. The contribution of wind shear to entrainment was equal to, or greater than, that from buoyant convection resulting from the surface heat flux. Strong wind shear occurred near the top of the mixed layer between the lower level inland flow and the return flow aloft in the sea breeze circulation.Symbols c entrainment parameter for sensible heat - c p specific heat of air at constant pressure, 1010 J kg–1 K–1 - d 1 the thickness of velocity shear at the mixed-layer top, m - Q H surface sensible heat flux, W m–2 - u m mean mixed-layer wind speed, m s–1 - u * friction velocity at the surface, m s–1 - w subsidence velocity, m s–1 - W subsidence warming,oC s–1 - w e entrainment velocity, m s–1 - w * convection velocity in the mixed layer, m s–1 - x downwind horizontal distance from the water-land interface, m - y dummy variable forx, m - Z height above the surface, m - Z i height of capping inversion, m - Z m mixed-layer depth, i.e.,Z i–Zs, m - Z s height of the surface layer, m - lapse rate of potential temperature aboveZ i, K m–1 - potential temperature step atZ i, K - u h velocity step change at the mixed-layer top - m mean mixed-layer potential temperature, K  相似文献   

5.
Surface measurements of cloud condensation nuclei (CCN) number concentration (cm−3) are presented for unmodified marine air and for polluted air at Mace Head, for the years 1994 and 1995. The CCN number concentration active at 0.5% supersaturation is found to be approximately log-normal for marine and polluted air at the site. Values of geometric mean, median and arithmetic mean of CCN number concentration (cm−3) for marine air are in the range 124–135, 140–150 and 130–157 for the two years of data. Analysis of CCN number concentration for high wind speed, U, up to 20 m s−1 show enhanced CCN production for U in excess of about 10–12 m s−1. Approximately 7% increase in CCN per 1 m s−1 increase in wind speed is found, up to 17 m s−1. A relationship of the form log10CCN=a+bU is obtained for the periods March 1994 and January, February 1995 for marine air yielding values a of 1.70; 1.90 and b of 0.035 for both periods.  相似文献   

6.
Line-averaged measurements of the structure parameter of refractive index (C n 2 ) were made using a semiconductor laser diode scintillometer above two markedly different surfaces during hours of positive net radiation. The underlying vegetation comprised in the first instance a horizontally homogeneous, pasture sward well-supplied with water, and in the second experiment, a sparse thyme canopy in a semi-arid environment. Atmospheric stability ranged between near neutral and strongly unstable (–20). The temperature structure parameterC T 2 computed from the optical measurements over four decades from 0.001 to 2 K2 m–2/3 agreed to within 5% of those determined from temperature spectra in the inertial sub-range of frequencies. Spectra were obtained from a single fine thermocouple sensor positioned near the midway position of the 100m optical path and at the beam propagation height (1.5m).With the inclusion of cup anemometer measurements, rule-of-thumb assumptions about surface roughness, and Monin-Obukhov similarity theory, path-averaged optical scintillations allow calculation of surface fluxes of sensible heat and momentum via a simple iterative procedure. Excellent agreement was obtained between these fluxes and those measured directly by eddy correlation. For sensible heat, agreement was on average close to perfect over a measured range of 0 to 500 W m–2 with a residual standard deviation of 30 W m–2. Friction velocities agreed within 2% over the range 0–0.9 m s–1 (residual standard deviation of 0.06 m s–1). The results markedly increase the range of validation obtained in previous field experiments. The potential of this scintillation technique and its theoretical foundation are briefly discussed.  相似文献   

7.
The hydrodynamic equations governing the water-level response of a lake to wind stress are inverted to determine wind stress from water-level fluctuations. In order to obtain a unique solution, the wind-stress field is represented in terms of a finite number of spatially dependent basis functions with time-dependent coefficients. The discretized version of the inverse equation is solved by a least-squares procedure to obtain the coefficients, and thereby the stress. The method is tested for several ideal cases with Lake Erie topography. Real water-level data is then used to determine hourly values of vector wind stress over Lake Erie for the period 5 May–31 October, 1979. Results are compared with measurements of wind speed and direction from buoys deployed in the lake. Calculated stress direction agrees with observed wind direction for wind speeds > 7.5 m s−1. Under neutral conditions, calculated drag coefficients increase with the wind speed from 1.53 × 10−3 for 7.5−10 m s−1 winds to 2.04 × 10−3 for 15−17.5 m s−1 winds. Drag coefficients are lower for stable conditions and higher for unstable conditions.  相似文献   

8.
Fine-resolution regional climate simulations of tropical cyclones (TCs) are performed over the eastern Australian region. The horizontal resolution (30 km) is fine enough that a good climatological simulation of observed tropical cyclone formation is obtained using the observed tropical cyclone lower wind speed threshold (17 m s–1). This simulation is performed without the insertion of artificial vortices (bogussing). The simulated occurrence of cyclones, measured in numbers of days of cyclone activity, is slightly greater than observed. While the model-simulated distribution of central pressures resembles that observed, simulated wind speeds are generally rather lower, due to weaker than observed pressure gradients close to the centres of the simulated storms. Simulations of the effect of climate change are performed. Under enhanced greenhouse conditions, simulated numbers of TCs do not change very much compared with those simulated for the current climate, nor do regions of occurrence. There is a 56% increase in the number of simulated storms with maximum winds greater than 30 m s–1 (alternatively, a 26% increase in the number of storms with central pressures less than 970 hPa). In addition, there is an increase in the number of intense storms simulated south of 30°S. This increase in simulated maximum storm intensity is consistent with previous studies of the impact of climate change on tropical cyclone wind speeds.  相似文献   

9.
Measurements have been made with fast-response multi-channel temperature, humidity and refractive index sensors flown to 2000 m on a tethered balloon to investigate small-scale fluctuations important in radio-wave scattering, their relation to atmospheric parameters, and their spatial variation in both one and three dimensions. Data from the three types of sensors at one point were consistent for frequencies up to about 8 Hz. Power spectra of data at various heights were computed over 0.1 to 10 Hz and generally showed slopes (on a log-log plot) close to - 5/3 above 1 Hz but ranged from –1.5 to – 3.5 at lower frequencies; in this range (f < 1 Hz) slopes were close to – 5/3 for negative Richardson number (Ri), provided temperature gradients were steeper than –1.1 °C 100 m–1 and wind shears > 1.4 x 10–2 s–1 approx. Steeper slopes were generally associated with stable atmospheric conditions but no precise relation to the above parameters was found. Spectral density was a maximum for Ri –0.75.Cross-correlations of 0.5 were frequently observed between sensors 1 m apart in orthogonal directions; in the vertical, examples of negative correlation of vapour pressure were occasionally found over this spacing. Using four sensors spaced in line over 9 m, cross-spectrum phase calculations of drift speeds were found to be consistent with measured wind speeds. The ratio of identification distance (coherence=0.6) to scale size of irregularities ranged from 0.25 to 0.5 with no apparent relation to height or meteorological parameters.  相似文献   

10.
Summary A 1290MHz wind profiler (Radian Lap-3000), at present one of three operational wind profilers in Austria, is operated at Vienna airport. In spite of quality assurance procedures as consensus averaging included in the data evaluation process from profiler raw data, some spurious peaks of wind speed and unrealistic changes of the wind vector in time or height occur in the wind measurements. This is especially true for sampling intervals of only 5 minutes which are used to resolve the temporal evolution of summer thunderstorms and frontal passages. Averaging periods of only a few minutes are rather the lower limit apt for wind profiler observations and result in a low data availability of 28%, whereas about 55% of data (relative to the maximum height range according to the parameter setting) are available for 10 to 30 minutes profiles.Approaches to a posteriori quality control using checks for automatic error detection are proposed and tested on a one and a half year data-set: Flagging data when the three-dimensional wind divergence exceeds a predefined limit (0.5s–1) is in most cases successful in combination with thresholds for wind speed (2 times the median of the daily data-set) or wind shear (0.2s–1).The wind profiler data is compared to wind profiles from the next radiosonde station where soundings are launched 4 times a day at Hohe Warte, approx. 20km northwest, at the hill-side of the Viennese Woods. Deviations of about 1m s–1 in wind speed are found between the observations of the two systems. Differences between the wind profiles within the boundary layer can be explained by local differences in the wind regime observed at the airport and the radiosounding – blocking effects of the Viennese Woods during south-easterly flow. Comparing the profiler data to radiosoundings on a monthly basis gives a tool to monitor the profiler performance.  相似文献   

11.
For the first time, the exchange coefficient of heat CH has been estimated from eddy correlation of velocity and virtual temperature fluctuations using sonic anemometer measurements made at low wind speeds over the monsoon land atJodhpur (26°18' N, 73°04' E), a semi arid station. It shows strong dependence on wind speed, increasing rapidly with decreasing wind speed, and scales according to a power law CH = 0.025U10 -0.7 (where U10 is the mean wind speed at 10-m height). A similar but more rapid increase in the drag coefficient CDhas already been reported in an earlier study. Low winds (<4 m s-1) are associated with both near neutral and strong unstable situations. It is noted that CH increases with increasing instability. The present observations best describe a low wind convective regime as revealed in the scaling behaviour of drag, sensible heat flux and the non-dimensional temperature gradient. Neutral drag and heat cofficients,corrected using Monin–Obukhov (M–O) theory, show a more uniform behaviour at low wind speeds in convective conditions, when compared with the observed coefficients discussed in a coming paper.At low wind convective conditions, M-O theory is unable to capture the observed linear dependence of drag on wind speed, unlike during forced convections. The non-dimensional shear inferred from the present data shows noticeable deviations from Businger's formulation, a forced convection similarity. Heat flux is insensitive to drag associated with weak winds superposed on true free convection. With heat flux as the primary variable, definition of new velocity scales leads to a new drag parameterization scheme at low wind speeds during convective conditionsdiscussed in a coming paper.  相似文献   

12.
Mean atmospheric circulation, moisture budget and net heat exchange were studied during a pre-monsoon period (18th March to 3rd May, 1988), making use of the data collected on board Akademik Korolev in the central equatorial and southern Arabian Sea region. The net heat exchange (R n ) is found to be about 20 W m–2 for a small area (0–4° N; 55–60° E), 50% less than the dimatological value. The mean value of net radiation (140 W m–2) is less than the climatological value, which was due to higher cloud amount. The higher SST enhanced both the latent and sensible heat fluxes.The mean atmospheric circulation obtained from the upper air data is quite convincing. The mean exchange coefficient (C e ) estimated from the moisture budget is about 1.0 × 10–3 for a wind speed of 4 m s–1. This value is slightly lower than that obtained by the usual methods.National Institute of Oceanography, RC, 52-Kirlampudi layout, Visakhapatnam — 530 023.India Meteorological Department, Gauhati.  相似文献   

13.
The effect of temperature on the solubility of PAN and on its hydrolysis rate in near-neutral and slightly acidic water were studied in a bubble column apparatus. The results obtained are a Henry's law coefficient H=10–9.04±0.6 exp[(6513±376)/T] M atm–1, and a first-order hydrolysis rate constant k=106.60±1.0 exp[(–6612±662)/T] s-1, which was independent of pH in the range 3.2pH6.7. The products formed are nitrite and nitrate in approximately equal proportions under near-neutral conditions. At a pH<4, nitrite is oxidized in a secondary reaction, and nitrate becomes the only product at low pH. Previously measured deposition velocities of PAN on stagnant water surfaces are shown to be hydrolysis rate limited.  相似文献   

14.
We have devised a partial differential equation for the prediction of dust concentration in a thin layer near the ground. In this equation, erosion (detachment), transport, deposition and source are parameterised in terms of known quantities. The interaction between a wind prediction model in the boundary layer and this equation affects the evolution of the dust concentration at the top of the surface layer. Numerical integrations are carried out for various values of source strength, ambient wind and particle size. Comparison with available data shows that the results appear very reasonable and that the model should be subjected to further development and testing.Notation (x, y, z, t) space co-ordinates and time (cm,t) - u, v components of horizontal wind speed (cm s–1) - u g, vg components of the geostrophic wind (cm s–1) - V=(u2+v2)1/2 (cm s–1) - (û v)= 1/(h – k) k h(u, v)dz(cm s–1) - V * friction velocity (cm s–1) - z 0 roughness length (cm) - k 1 von Karman constant =0.4 - V d deposition velocity (cm s–1) - V g gravitational settling velocity (cm s–1) - h height of inversion (cm) - k height of surface layer (cm) - potential temperature (°K) - gr potential temperature at ground (°K) - K potential temperature at top of surface layer (°K) - P pressure (mb) - P 0 sfc pressure (mb) - C p/Cv - (t)= /z lapse rate of potential temperature (°K cm–1) - A(z) variation of wind with height in transition layer - B(z) variation of wind with height in transition layer - Cd drag coefficient - C HO transfer coefficient for sensible heat - C dust concentration (g m–3) - C K dust concentration at top of surface layer (g m–3) - D(z) variation with height of dust concentration - u, v, w turbulent fluctuations of the three velocity components (cm s–1) - A 1 constant coefficient of proportionality for heat flux =0.2 - Ri Richardson number - g gravitational acceleration =980 cm s–2 - Re Reynolds number = - D s thickness of laminar sub-layer (cm) - v molecular kinematic viscosity of air - coefficient of proportionality in source term - dummy variable - t time step (sec) - n time index in numerical equations On sabbatical leave at University of Aberdeen, Department of Engineering, September 1989–February 1990.  相似文献   

15.
Fluctuations in the vertical wind velocity and air temperature were measured with a 1-dimensional sonic anemometer and fine thermocouple over a flat agricultural site in the Rhone Valley, France. Strong Mistral winds with speeds up to 20 m s–1 kept atmospheric conditions very close to neutral and ensured stationarity. Friction velocities estimated both by eddy correlation (sonic plus Gill Bivane) and inertialdissipation (sonic only) methods agreed within 1 and 5 % respectively of traditional profile measurements over the measured range of 0.2 to 1.2 m s–1. The coefficient of eddy transport for heat exceeded that of momentum by a factor of 1.38 (± 0.05), a result almost identical to that obtained in the Kansas experiment (Businger et al., 1971). For - 0.15 >= z/L >= 0.05, the ratio w /u * was 1.69 and 1.34 for unstable and stable conditions, respectively. For ¦z/L¦ >= 0.05, the ratio /T * was 1.40 independent of whether neutrality was approached from either stable or unstable conditions.  相似文献   

16.
Mean and fluctuating wind velocities were measured above a flexible stand (weeping-lovegrass). A waving phenomenon Honami appeared over the stand during the observation period. Some spectral parameters were derived from the vertical wind fluctuations. A dependency of frequency on mean horizontal wind velocity was found. The result, n m = 0.66u, was obtained under the range of wind speeds from 0.9 m s-1 to 3.1 m s-1 just above the canopy.  相似文献   

17.
The temperature drop T between the ocean surface and the 5-cm depth was recorded during GATE, Phase III. With measured values of the total heat flux Q and an assumption about the thickness of the viscous boundary layer of the ocean, the wind-speed dependence of the factor of proportionality between T and Q is determined. This factor depends on the deviations of the thickness of the conductive layer from the thickness of the viscous layer and possibly partially on the wind stress. A further assumption about the thickness of the conductive layer leads to a wind-speed dependence of the ratio between total wind stress and its wave supporting part of it. This ratio increases from a value 1.5 at 1 m s–1 to 9 at 10 m s–1, which is in agreement with existing estimates.  相似文献   

18.
Air-sea bulk transfer coefficients in diabatic conditions   总被引：13，自引：0，他引：13  
On the basis of recent data for the roughness Reynolds number of the sea surface, and using the Owen-Thomson theory on the transfers of heat and mass between a rough surface and the flow above it, the bulk transfer coefficients of the sea surface have been estimated. For a reference height of 10 m, the neutral-lapse transfer coefficient for water vapor is larger by only a few percent than that for sensible heat. When the wind speed at the 10-m height is u 10>3 m s–1, the coefficient for sensible heat C H is larger by about 10% than that for momentum C D . For u 10<5 m s–1, however, the value of C D exceeds the value of C H , and for u 10=15 m s–1 it is shown that C H 0.8C D . It may be also proposed that 103 C D =1.11 to 1.70, 103 C E =1.18 to 1.30, and 103 C H =1.15 to 1.26 for a range of u 10=4 to 20 m s–1. A plot of diabatic transfer coefficients versus wind speed is obtained by using a parameter of the sea-air temperature difference. For practical purposes, the coefficients are approximated by empirical formulae.  相似文献   

19.
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   

20.
A Forest SO2 Absorption Model (ForSAM) was developed to simulate (1) SO2 plume dispersion from an emission source, (2) subsequent SO2 absorption by coniferous forests growing downwind from the source. There are three modules: (1) a buoyancy module, (2) a dispersion module, and (3) a foliar absorption module. These modules were used to calculate hourly abovecanopy SO2 concentrations and in-canopy deposition velocities, as well as daily amounts of SO2 absorbed by the forest canopy for downwind distances to 42 km. Model performance testing was done with meteorological data (including ambient SO2 concentrations) collected at various locations downwind from a coal-burning power generator at Grand Lake in central New Brunswick, Canada. Annual SO2 emissions from this facility amounted to about 30,000 tonnes. Calculated SO2 concentrations were similar to those obtained in the field. Calculated SO2 deposition velocities generally agreed with published values.Notation c air parcel cooling parameter (non-dimensional) - E foliar absorption quotient (non-dimensional) - f areal fraction of foliage free from water (non-dimensional) - f w SO2 content of air parcel - h height of the surface layer (m) - H height of the convective mixing layer (m) - H stack stack height (m) - k time level - k drag coefficient of drag on the air parcel (non-dimensional) - K z eddy viscosity coefficient for SO2 (m2·s–1) - L Monin-Obukhov length scale (m) - L A single-sided leaf area index (LAI) - n degree-of-sky cloudiness (non-dimensional) - N number of parcels released with every puff (non-dimensional) - PAR photosynthetically active radiation (W m–2) - Q emission rate (kg s–2) - r b diffusive boundary-layer resistance (s m–1) - r c canopy resistance (s m–1) - r cuticle cuticular resistance (s m–1) - r m mesophyllic resistance (s m–1) - r s stomatal resistance (s m–1) - r exit smokestack exit radius (m) - R normally distributed random variable with mean of zero and variance of t (s) - u * frictional velocity scale, (m s–1) - v lateral wind vector (m s–1) - v d SO2 dry deposition velocity (m s–1) - VCD water vapour deficit (mb) - z can mean tree height (m) - Z zenith position of the sun (deg) - environmental lapse rate (°C m–1) - dry adiabatic lapse rate (0.00986°C m–1) - von Kármán's constant (0.04) - B vertical velocities initiated by buoyancy (m s–1) - canopy extinction coefficient (non-dimensional) - ()a denotes ambient conditions - ()can denotes conditions at the top of the forest canopy - ()h denotes conditions at the top of the surface layer - ()H denotes conditions at the top of the mixed layer - ()s denotes conditions at the canopy surface - ()p denotes conditions of the air parcels  相似文献   

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