On the spectral dissipation of ocean waves due to white capping

Summary The effect of white capping on the spectral energy balance of surface waves is investigated by expressing the white-cap interactions in terms of an equivalent ensemble of random pressure pulses. It is shown first that the source function for any non-expansible interaction process which is weak-in-the-mean is quasi-linear. In the case of white capping, the damping coefficient is then shown to be proportional to the square of the frequency, provided the wave scales are large compared with the white-cap dimensions. The remaining free factor is determined indirectly from consideration of the spectral energy balance. The proposed white-capping dissipation function is consistent with the structure of the energy balance derived from JONSWAP, and the existence of a ^–5 spectrum governed by a non-local energy balance between the atmospheric input, the nonlinear energy transfer and dissipation. However, closure of the energy balance involves hypotheses regarding the structure of the atmospheric input function which need to be tested by further measurements. The proposed set of source functions may nevertheless be useful for numerical wave-prediction. According to the model, nearly all the momentum transferred across the air-sea interface enters the wave field. For fetchlimited and fully developed spectra in a stationary, uniform wind field, the drag coefficient remains approximately constant. However, for more general wind conditions, this will not be the case and the wave spectrum should be included in an accurate parameterisation of the air-sea momentum transfer.Contribution from the Sonderforschungsbereich Meeresforschung Hamburg of the Deutsche Forschungsgemeinschaft.     

Drag coefficient modeling for the near coastal zone

Using the JONSWAP spectrum for describing the surface wave state in the near coastal zone, models for the roughness length and the drag coefficient are used to simulate the dependence of the wind stress on fetch and depth. The results of each model are then compared with a compiled set of past investigations of the neutral drag coefficient over a variety of conditions. It is found that the models of Donelan, Hsu, and Kitaigorodskii correctly predict the trends in the drag coefficient with fetch and depth. Although it did not account for all the observed variations in the neutral drag coefficient. Kitaigorodskii's model, when incorporating the JONSWAP spectrum, more accurately simulated the slopes of the various C_DN regressions against windspeed.     

Comparison Between Eddy-Correlation and Inertial Dissipation Methods in the Marine Atmospheric Surface Layer

A comparison of momentum fluxes determined by the eddy-correlation method(ECM) and the inertial dissipation method (IDM) has been performed using longterm measurements over the sea. The measurements were made on the island ofÖstergarnsholm in the middle of the Baltic Sea. The results show that a`classical' form of the inertial dissipation method, i.e., assuming that the transportterms are negligible, and using an effective value for the Kolmogorov constant of0.55, can be used with a mean relative difference between the two methods of about15% for -1 < z/L < 0.5 (z being height and L the Obukhov length). The IDMmethod works best for high wind speeds and neutral conditions. For low windspeeds (U < 6 m s^-1) the relation between the two methods is morecomplex. IDM then gives higher values than ECM on the average (about 20%),especially for swell conditions, indicating the need for an imbalance function inthe turbulent kinetic energy budget. Calculations of the effective Kolmogorovconstant, _a, suggest a dependence upon the wave age, _a increasing with increasing wave age, where the value 0.59 fits the data well for saturated waves.     

Dynamics of lateral boundary meso-scale jet in the ocean and atmosphere

By using an ageostrophic shallow water model, it is pointed out that a kind of lateral boundary meso-scales jet can be established near the plateau or coast. The characteristic width of this kind of jet is proportional to the scale ofL _c=L₀(C₀/V_g), whereL ₀=C ₀/f is the radius of Rossby deformation,C ₀=(g ^* H)^1/2 the speed of gravity wave and g^* the reduced gravity. In general,L _c is of the order of one hundred kilometes and tens of kilometers in the atmosphere and in the ocean respectively. The large-scale geostrophic current is an important background condition for forming this kind of jet. From this view point it seems that this kind of atmospheric meso-scale jet only occurs in late spring and summer in the eastern part of Asia, because there is a large-scale south monsoon over there. For the ocean, this kind of meso-scale jet seems to be a semi-persistant system and not to show a significant seasonal variation, and it can be established on both sides of the ocean.     

Eddy flux measurements over the ocean and related transfer coefficients

Eddy correlation measurements of vertical turbulent fluxes made during AMTEX 1975 are used to assess the reliability of flux prediction from established bulk transfer relations, using both surface-layer and planetary boundary-layer formulations. The surface-layer formulae predict momentum and latent heat fluxes to an accuracy comparable to the direct eddy correlation method, using transfer coefficients of C _DN (at 10m and in neutral conditions) increasing with wind speed, and a constant C _EN - 1.5 × 10 ^–3 . The data suggest C _CHN , for sensible heat, increases significantly with wind speed and is on average 30% lower than C _CEN The boundary-layer drag coefficient, C _GD , agrees within about 40% of recently published values using a vertically averaged geostrophic wind to the height of the lowest temperature inversion, corrected for trajectory curvature. Values of _* / from which C _CGH is derived, are in excellent agreement if the published values are modified to account for inappropriate surface temperatures used in their derivation. Preliminary values of C _GE are also presented.     

Measuring C T 2 , C Q 2 , and C TQ in the unstable surface layer,and relations to the vertical fluxes of heat and moisture

The structure parameters of temperature (C _T ² ), humidity (C _Q ² ) and temperature-humidity (C _TQ ) were observed at a height of 4 m in the unstable surface layer using thin platinum wires and two Ly- hygrometers. Two ways of measuring structure parameters were employed: one using spaced sensors, the other using time-delayed observations at one location. It is found that the three structure parameters follow free-convection scaling down to -z/L 0.02. The scaling functions % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4baFfea0dXde9vqpa0lb9% cq0dXdb9IqFHe9FjuP0-iq0dXdbba9pe0lb9hs0dXda91qaq-xfr-x% fj-hmeGabaqaciGacaGaaeqabaWaaeaaeaaakeaacaWGMbaaaa!3346!\[f\]₁ (of C _T ² ), % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4baFfea0dXde9vqpa0lb9% cq0dXdb9IqFHe9FjuP0-iq0dXdbba9pe0lb9hs0dXda91qaq-xfr-x% fj-hmeGabaqaciGacaGaaeqabaWaaeaaeaaakeaacaWGMbaaaa!3346!\[f\]₂ (of C _TO ) and % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4baFfea0dXde9vqpa0lb9% cq0dXdb9IqFHe9FjuP0-iq0dXdbba9pe0lb9hs0dXda91qaq-xfr-x% fj-hmeGabaqaciGacaGaaeqabaWaaeaaeaaakeaacaWGMbaaaa!3346!\[f\]₃ (of C _Q ² ) are found to be related through % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4baFfea0dXde9vqpa0lb9% cq0dXdb9IqFHe9FjuP0-iq0dXdbba9pe0lb9hs0dXda91qaq-xfr-x% fj-hmeGabaqaciGacaGaaeqabaWaaeaaeaaakeaacaWGMbaaaa!3346!\[f\]₂/% MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4baFfea0dXde9vqpa0lb9% cq0dXdb9IqFHe9FjuP0-iq0dXdbba9pe0lb9hs0dXda91qaq-xfr-x% fj-hmeGabaqaciGacaGaaeqabaWaaeaaeaaakeaacaWGMbaaaa!3346!\[f\]₁ 0.69 and % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4baFfea0dXde9vqpa0lb9% cq0dXdb9IqFHe9FjuP0-iq0dXdbba9pe0lb9hs0dXda91qaq-xfr-x% fj-hmeGabaqaciGacaGaaeqabaWaaeaaeaaakeaacaWGMbaaaa!3346!\[f\]₃/% MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4baFfea0dXde9vqpa0lb9% cq0dXdb9IqFHe9FjuP0-iq0dXdbba9pe0lb9hs0dXda91qaq-xfr-x% fj-hmeGabaqaciGacaGaaeqabaWaaeaaeaaakeaacaWGMbaaaa!3346!\[f\]₁ 0.84. The usefulness of the structure parameters for inferring the fluxes of heat and water vapor, as well as the Bowen ratio, is demonstrated. The scatter is about 30% on either side of the mean.This work was done while the author was a visiting scientist at the Wave Propagation Laboratory, NOAA, ERL, Boulder, U.S.A. He received support from the Netherlands Minister for Science Policy and the U.S. Army Research Office.     

An aircraft study of turbulence dissipation rate and temperature structure function in the unstable marine atmospheric boundary layer

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).     

Atmospheric effects in the remote sensing of phytoplankton pigments

We investigate the accuracy with which relevant atmospheric parameters must be estimated to derive phytoplankton pigment concentrations (chlorophyll a plus phaeophytin a ) of a given accuracy from measurements of the ocean's apparent spectral radiance at satellite altitudes. The analysis is limited to an instrument having the characteristics of the Coastal Zone Color Scanner scheduled to orbit the Earth on NIMBUS-G. A phytoplankton pigment algorithm is developed which relates the pigment concentration (C) to the three ratios of upwelling radiance just beneath the sea surface which can be formed from the wavelengths () 440, 520 and 550 nm. The pigment algorithm explains from 94 to 98% of the variance in log₁₀ C over three orders of magnitude in pigment concentration. This is combined with solutions to the radiative transfer equation to simulate the ocean's apparent spectral radiance at satellite altitudes as a function of C and the optical properties of the aerosol, the optical depth of which is assumed to be proportioned to ^-n . A specific atmospheric correction algorithm, based on the assumption that the ocean is totally absorbing at 670 nm, is then applied to the simulated spectral radiance, from which the pigment concentration is derived. Comparison between the true and derived values of C show that: (1) n is considerably more important than the actual aerosol optical thickness; (2) for C 0299-1 0.2 g l^-1 acceptable concentrations can be determined as long as n is not overestimated; (3) as C increases, the accuracy with which n must be estimated, for a given relative accuracy in C, also increases; and (4) for C greater than about 0.5 g 1^-1, the radiance at 440 nm becomes essentially useless in determining C. The computations also suggest that if separate pigment algorithms are used for C 1gl^-1 and C 1 gl^-1, accuracies considerably better than ±± in log C can be obtained for C 1 g l^-1 with only a coarse estimate of n, while for C 10 gl^-1, this accuracy can be achieved only with very good estimates of n.Contribution No. 387 from the NOAA/ERL Pacific Environmental Laboratory.On leave from Department of Physics, University of Miami, Coral Gables, Florida.     

Justification of the Inertial Dissipation Technique in Anisotropic Mean Flow

The inertial dissipation technique has been successfully employed for many years to measure the wind stress, especially over the open ocean. This method is based on Kolmogorov's theoretical prediction of universality in the inertial wavenumber range. The theory was developed under the assumption of locally isotropic turbulence, and the dissipation technique has been criticized as lacking justification in a boundary-layer shear flow. In this paper, Kolmogorov's theory is explicitly applied to the anisotropic conditions prevailing in the atmosphere. It is shown that the inertial dissipation method relies on the homogeneity and isotropy of the spectrum _ii(k) for k in the inertial range. This is a weaker condition than Kolmogorov's assumption of isotropy of the correlation function B_ij(r). In high-Reynolds-number shear flows, isotropy of _ii(k) is realized to a good approximation, whereas isotropy of B_ij(r) is not. Some consequences for the experimental implementation are discussed; in particular, sampling times (block lengths) not exceeding the order of the eddy life time are recommended in the calculation of spectra.     

The prediction of dust erosion by wind: An interactive model

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, v_g 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/C_v - (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.     

Free convection scaling over the ocean derived from buoy measurements during gate

The structure of atmospheric turbulence in the surface layer over the open ocean is examined under conditions of local free convection. The raw data consist of profile and fluctuation measurements of wind and temperature as obtained from a meteorological buoy. For near neutral conditions and for waves running approximately along the wind direction, wave-induced wind fluctuations can be described by a simplified linear theory based on Miles (1957). In this case, the spectrum of wind velocity is given as the sum of two parts; for the turbulent part, the parameterization as obtained by Kaimal et al. (1972) applies, while the wave-induced part is parameterized using a simplification of Miles' linear theory. For cases of local free convection, the measurements of the vertical component of the wind velocity are well described by similarity theory; as expected, _w /(-uw)^1/2 is proportional to (- z/L)^1/3. In order to scale the longitudinal wind velocity component, it seems to be reasonable to extend the list of relevant parameters by the height of the mixed layer z _i. We obtain _u /(- uw)^1/2 (z/z _i)^1/3(- z/L)^1/3 with only a poor correlation coefficient of r = 0.6. Overall, the results of local free convection scaling obtained from direct measurements show good agreement with those obtained from profile measurements. A comparison between direct and indirect determination of turbulent fluxes of momentum shows an unexplained difference of about 20%. This discrepancy is mainly due to a gap in the uw-cospectrum at the swell frequency.     

A verification of two shear velocity equations for the wind-wave interaction in a lake environment

Under growing wind-wave conditions the shear velocity,u _*, over the water surface equalsg ² H _s ² B _a ² C _p ³ , whereg is the gravitational acceleration,H _s is the significant wave height,B _a is a constant, andC _p is the wave celerity. From an independent field experiment in a lake environment which provided all three parameters (u _*,H _s , andC _p ), the value ofB _a is found to be 0.89, which is slightly lower than but consistent (within 20%) with the literature value between 0.90 and 1.06 obtained from an oceanic environment. Since thisu _* equation does not include the wind speed,U ₁₀, anotheru _* formulation withU ₁₀ in addition to the wave information is also evaluated. It is shown that the latter equation which includesU ₁₀ is superior to the former withoutU ₁₀.     

Temperature structure parameter measurements using differential temperature sensors

The comparison of C _infT ^sup2 estimates in the atmospheric boundary layer, from spectral and differential temperature (T) measurements, is discussed. Measurements of C _infT ^sup2 using these two methods are compared and the differences between the two are shown to be due to low-frequency enhancement of the T spectrum. Possible explanations for this effect are considered and attention is drawn to the significance of the resulting errors in boundary-layer turbulence measurements.Now at Department of Electrical and Electronic Engineering, Portsmouth Polytechnic, Anglesea Road, Portsmouth, U.K.Now at Department of Meteorology, University of Athens, Greece.     

Microwave vegetation optical depth and inverse modelling of soil emissivity using Nimbus/SMMR satellite observations

Summary A radiative transfer model has been used to determine the large scale effective 6.6 GHz and 37 GHz optical depths of the vegetation cover. Knowledge of the vegetation optical depth is important for satellite-based large scale soil moisture monitoring using microwave radiometry. The study is based on actual observed large scale surface soil moisture data and observed dual polarization 6.6 and 37 GHz Nimbus/SMMR brightness temperatures over a 3-year period. The derived optical depths have been compared with microwave polarization differences and polarization ratios in both frequencies and with Normalized Difference Vegetation Index (NDVI) values from NOAA/AVHRR. A synergistic approach to derive surface soil emissivity from satellite observed brightness temperatures by inverse modelling is described. This approach improves the relationship between satellite derived surface emissivity and large scale top soil moisture fromR ²=0.45 (no correction for vegetation) toR ²=0.72 (after correction for vegetation). This study also confirms the relationship between the microwave-based MPDI and NDVI earlier described and explained in the literature.List of Symbols f frequency [Hz] - f _i(p) fractional absorption at polarizationp - h surface roughness - h h cos² - H horizontal polarization - n _i complex index of refraction - p polarization (H orV) - R _s microwave surface reflectivity - T _B(p) brightness temperature at polarizationp - T ^* normalized brightness temperature - T polarization difference (T _v-T _H) - T _s temperature of soil surface - T _c temperature of canopy - T _max daily maximum air temperature - T _min daily minimum air temperature - V vertical polarization - soil moisture distribution factor; also used for the constant to partition the influence of bound and free water components to the dielectric constant of the mixture - empirical complex constant related to soil texture - microwave transmissivity of vegetation (=e ^–) - ^* effective transmissivity of vegetation (assuming =0) - microwave emissivity - _s emissivity of smooth soil surface - _rs emissivity of rough soil surface - _vs emissivity of vegetated surface - soil moisture content (% vol.) - K dielectric constant [F·m^–1] - K _fw dielectric constant of free water [F·m^–1] - K _ss dielectric constant of soil solids [F·m^–1] - K _m dielectric constant of mixture [F·m^–1] - K _o permittivity of free space [8.854·10^–12 F·m^–1] - high frequency limit ofK _wf [F·m^–1] - wavelength [m] - incidence angle [degrees from nadir] - polarization ratio (T _H/T _V) - b soil bulk density [gr·cm^–3] - s soil particle density [gr·cm^–3] - R surface reflectivity in red portion of spectrum - NIR surface reflectivity in near infrared portion of spectrum - _eff effective conductivity of soil extract [mS·cm^–1] - vegetation optical depth - _6.6 vegetation optical depth at 6.6 GHz - ₃₇ vegetation optical depth at 37 GHz - ^* effective vegetation optical depth (assuming =0) - single scattering albedo of vegetation With 12 Figures     

An improved calibration for tethered balloon wind measurements

A previously published technique for using tethered spherical balloons as anemometers for measuring light low-level winds has been further developed. Earlier data on the relationship between the aerodynamic drag coefficient and the Reynolds number of spherical rubber balloons were combined with a large number of new data and re-analysed; and the errors in the relationship were estimated. The results allowed a more accurate calculation of wind speed from the deflection of a tethered balloon from the vertical. When combined with a new technique for calculating the effects of the tether, this enabled light to moderate low-level winds at fixed heights up to 600 m or more to be measured with simple, cheap, and readily mobile equipment; and a slight modification of the technique allowed measurement of winds in and above fog. Wind speeds measured by the ballon technique showed reasonably good agreement with measurements by an anemometer carried beneath the balloon.Glossary of Symbols a, b, c Coefficients in the relationship between lnC _d and lnR - A Quantity under square root in solution for lnV whena0 - C _d Wind drag coefficient for balloon - C _dc Value ofC _d given by calibration curve of Table I - D Dynamic wind pressure force on balloon - F Buoyant free lift of balloon with load - Re Reynold's number of balloon (sphere) - R = Re/10⁵ - r Radius of sphere - T Tension in tether - V Wind speed - ₈₃() =(lnC _dc -lnC _d ) when 83° , or 0 for other - Error in lnC _d - Elevation of tether where attached to balloon - Elevation of balloon from ground tether point - Molecular viscosity of air - Ratio of circumference to diameter of circle - Density of air     

Turbulent fluxes of momentum,heat and water vapor in the atmospheric surface layer at sea during ATEX

The vertical turbulent fluxes have been determined during the Atlantic Trade Wind Experiment (ATEX) both by direct and profile methods. The drag coefficient obtained from direct measurements was c _D = 1.39 × 10^–3. A distortion of the wind profile due to wave action could be demonstrated, this produced an increased drag coefficient estimated by the profile method. The dissipation technique using the downwind spectrum gave a lower drag coefficient of 1.26 × 10^–3, probably due to non-isotropic conditions (the ratio of vertical to downwind spectrum at high frequencies scattered considerably with an average of 1 instead of 4/3).From direct measurements, the sensible heat flux showed a poor correlation with the bulk parameter product U, contrary to the heat flux obtained from profiles. It is shown that this is due to the higher frequency part of the cospectrum, say above 0.25 Hz, which contributes more than 50 % of the total flux. Determination of the heat flux from temperature fluctuations by the dissipation method would be in agreement with the direct determination only if the corresponding Kolmogoroff constant were 2.1 instead of 0.8.For the vertical flux of water vapor obtained from profiles, the bulk transfer coefficient was 1.28 × 10^–3.This work was supported by the Deutsche Forschungsgemeinschaft, Schwerpunktprogramm Meeresforschung and later the Sonderforschungsbereich Meeresforschung Hamburg.     

Characteristics of atmospheric turbulence in the surface layer over Antarctica

This paper presents meteorological measurements made during the antarctic summer period, on two 9 m and 3 m towers, on the rocky and ice shelf terrains of the Indian antarctic stations Maitri and Dakshin Gangotri, respectively. The measurements of fluctuations in temperature and wind speed made with relatively lesser precision instrumentation pertain to smaller wave numbers ~10^-2 m^-1 appropriate to outer scale L ₀ of the atmospheric turbulence spectrum. Autocorrelation analysis of the fluctuations in temperature and wind speed has been performed. A new autoregressive scheme has been developed to represent the computed autocorrelation functions by a Yule statistical model, and to estimate the correlation period T ₀ of the turbulent medium. Height profiles of outer scale L ₀ of turbulence may be given in terms of T ₀ and mean wind speed u. Further, the similarity theory of Monin-Obukhov has been used to compute height profiles of temperature structure parameter C _T ². At Maitri, values of L ₀ and C _T ² are higher between 03–22 h local time than between 22–03 h. Values of L ₀ and C _T ² are smaller over the ice shelf terrain of the Dakshin Gangotri station, compared to those over the rocky terrain of the Maitri station.     

The drag coefficient as determined by the dissipation method and its relation to intermittent convection in the surface layer

The influence of intermittent convection on surface-layer stress estimates during the GARP Atlantic Tropical Experiment (GATE) is described. A negative correlation between the drag coefficient (C _D) and the wind speed (% MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGabmyvayaara% aaaa!36DE!\[\bar U\]) is found when short averaging periods are used. Well-defined, discrete events produce this negative correlation, and these events are shown to correspond to the passage of convective plumes. Constraints on averaging times necessary to obtain reasonable stress estimates using the bulk method are discussed.Conditional sampling is used to produce average values of dissipation (% MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGafqyTduMbae% baaaa!37AB!\[\bar \varepsilon \]), wind speed (% MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGabmyvayaara% aaaa!36DE!\[\bar U\]), and virtual temperature (% MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGabmivayaara% WaaSbaaSqaaiaaiw8aaeqaaaaa!385B!\[\bar T_\upsilon \]) for each high turbulent intensity event, and for the quiescent periods in between. Such statistics indicate that the highly turbulent states coincide with the presence of plumes and account for the negative correlation between C _D and % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGabmyvayaara% aaaa!36DE!\[\bar U\]. Some of these statistics are also stability dependent.The probability distributions of the dissipation rate are bimodally log-normal which suggests that turbulence generated at two different heights is being sampled. This, along with other results of this paper, support a picture of a boundary layer which is dominated by vertical exchange.Contribution Number 409, Department of Atmospheric Sciences, University of Washington.     

Spectral Characteristics and Correction of Long-Term Eddy-Covariance Measurements Over Two Mixed Hardwood Forests in Non-Flat Terrain

We present turbulence spectra and cospectra derived from long-term eddy-covariancemeasurements (nearly 40,000 hourly data over three to four years) and the transferfunctions of closed-path infrared gas analyzers over two mixed hardwood forests inthe mid-western U.S.A. The measurement heights ranged from 1.3 to 2.1 times themean tree height, and peak vegetation area index (VAI) was 3.5 to 4.7; the topographyat both sites deviates from ideal flat terrain. The analysis follows the approach ofKaimal et al. (Quart. J. Roy. Meteorol. Soc. 98, 563–589, 1972) whose results were based upon 15 hours of measurements atthree heights in the Kansas experiment over flatter and smoother terrain. Both thespectral and cospectral constants and stability functions for normalizing and collapsingspectra and cospectra in the inertial subrange were found to be different from those ofKaimal et al. In unstable conditions, we found that an appropriate stabilityfunction for the non-dimensional dissipation of turbulent kinetic energy is of the form ₍₎ = (1 - b^-)^-1/4 - c^-, where representsthe non-dimensional stability parameter. In stable conditions, a non-linear functionG_xy() = 1 + b_xy^c _xy (c_xy < 1) was found to benecessary to collapse cospectra in the inertial subrange. The empirical cospectralmodels of Kaimal et al. were modified to fit the somewhat more (neutraland unstable) or less (stable) sharply peaked scalar cospectra observed over forestsusing the appropriate cospectral constants and non-linear stability functions. Theempirical coefficients in the stability functions and in the cospectral models varywith measurement height and seasonal changes in VAI. The seasonal differencesare generally larger at the Morgan Monroe State Forest site (greater peak VAI) andcloser to the canopy.The characteristics of transfer functions of the closed-path infrared gas analysersthrough long-tubes for CO₂ and water vapour fluxes were studied empirically. This was done by fitting the ratio between normalized cospectra of CO₂ or watervapour fluxes and those of sensible heat to the transfer function of a first-order sensor.The characteristic time constant for CO₂ is much smaller than that for water vapour. The time constant for water vapour increases greatly with aging tubes. Three methods were used to estimate the flux attenuations and corrections; from June through August, the attenuations of CO₂ fluxes are about 3–4% during the daytime and 6–10% at night on average. For the daytime latent heat flux (Q_E), the attenuations are foundto vary from less than 10% for newer tubes to over 20% for aged tubes. Correctionsto Q_E led to increases in the ratio (Q_H + Q_E)/(Q^* - Q_G) by about 0.05 to0.19 (Q_H is sensible heat flux, Q^* is net radiation and Q_G is soil heat flux),and thus are expected to have an important impact on the assessment of energy balanceclosure.