A numerical modeling study of the marine boundary layer over the Gulf Stream during cold air advection

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]     

Sulfur dioxide plume dispersion and subsequent absorption by coniferous forests: Field measurements and model calculations

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     

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.     

Summer boundary-layer height at the plateau site of Dome’C,antarctica

Measurements of the mean and turbulent structure of the planetary boundary layer using a sodar and a sonic anemometer, and radiative measurements using a radiometer, were carried out in the summer of 1999–2000 at the Antarctic plateau station of Dome C during a two-month period. At Dome C strong ground-based inversions dominate for most of the year. However, in spite of the low surface temperatures (between −50 and −20 °C), and the surface always covered by snow and ice, a regular daytime boundary-layer evolution, similar to that observed at mid-latitudes, was observed during summertime. The mixed-layer height generally reaches 200–300 m at 1300–1400 LST in high summer (late December, early January); late in the summer (end of January to February), as the solar elevation decreases, it reduces to 100–200 m. A comparison between the mixed-layer height estimated from sodar measurements and that calculated using a mixed-layer growth model shows a rather satisfactory agreement if we assign a value of 0.01–0.02 m s⁻¹ to the subsidence velocity at the top of the mixed layer, and a value of 0.003–0.004 K m⁻¹ to the potential temperature gradient above the mixed layer.     

A numerical study of daily transitions in the convective boundary layer

We examine daily (morning–afternoon) transitions in the atmospheric boundary layer based on large-eddy simulations. Under consideration are the effects of the stratification at the top of the mixed layer and of the wind shear. The results describe the transitory behaviour of temperature and wind velocity, their second moments, the boundary-layer height Z _m (defined by the maximum of the potential temperature gradient) and its standard deviation σ _m , the mixed-layer height z _i (defined by the minimum of the potential temperature flux), entrainment velocity W _e, and the entrainment flux H _i . The entrainment flux and the entrainment velocity are found to lag slightly in time with respect to the surface temperature flux. The simulations imply that the atmospheric values of velocity variances, measured at various instants during the daytime, and normalized in terms of the actual convective scale w_*, are not expected to collapse to a single curve, but to produce a significant scatter of observational points. The measured values of the temperature variance, normalized in terms of the actual convective scale Θ_*, are expected to form a single curve in the mixed layer, and to exhibit a considerable scatter in the interfacial layer.     

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).     

Nocturnal Low-Level Jet Characteristics Over Kansas During Cases-99

Characteristics and evolution of the low-level jet (LLJ)over southeastern Kansas were investigated during the 1999 Cooperative Surface-AtmosphereExchange Study (CASES–99) field campaign with an instrument complement consisting of ahigh-resolution Doppler lidar (HRDL), a 60 m instrumented tower, and a triangle of Dopplermini-sodar/profiler combinations. Using this collection of instrumentation we determined thespeed U_X, height Z_X and direction D_X of the LLJ. We investigate here the frequencyof occurrence, the spatial distribution, and the evolution through the night, of these LLJcharacteristics. The jet of interest in this study was that which generates the shear and turbulencebelow the jet and near the surface. This was represented by the lowest wind maximum.We found that this wind maximum, which was most often between 7 and 10 m s¹,was often at or just below 100 m above ground level as measured by HRDL at the CASEScentral site. Over the 60 km profiler–sodararray, the topography varied by 100 m. The wind speed anddirection were relatively constant over this distance (with some tendency for strongerwinds at the highest site), but Z_X was more variable. Z_X was occasionally about equal at allthree sites, indicating that the jet was following the terrain, but more often it seemed to berelatively level, i.e., at about the same height above sea level. Z_X was also more variable thanU_X in the behaviour of the LLJ with time through the night, and on some nights $U_X wasremarkably steady. Examples of two nights with strong turbulence below jet level were furtherinvestigated using the 60 m tower at the main CASES–99 site. Evidence of TKE increasing withheight and downward turbulent transport of TKE indicates that turbulence was primarilygenerated aloft and mixed downward, supporting the upside–down boundary layer notion in thestable boundary layer.     

Variability of Mixed-Layer Heights over the Indian Ocean and Central Arabian Sea during INDOEX, IFP-99

The upper air data collected from the balloon-borne GLASS Sondes launched from the Oceanic Research Vessel (ORV) Sagar Kanya during the Intensive Field Phase of the Indian Ocean experiment (INDOEX, IFP-99;SK-141 Cruise) are utilized forstudying the variability in the mixed-layer heights observed over the western tropical Indian Ocean and central Arabian Sea. During the entire cruise, typical daytime convective mixed-layer heights (roughly corresponding to 1400 LT) obtained from _V and q profiles, were observed to be in the range 200–900 m. Shallowmixed -layer heights are observed, in general, over the Inter-Tropical Convergence Zone (ITCZ). Over the central Arabian Sea, vertical profiles of _V and q demonstrate a double mixed-layer structure of the marine atmospheric boundary layer (MABL), which gradually disappears close to the Indian coastline.     

Etude experimentale d'une relation entre le coefficient de frottement et le facteur de rafales en regime de vent faible et au-dessus d'une surface d'eau

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 Ri_0–2. 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 Ri_0–2on the other hand, we found a poor relationship between C _d and Ri_0–2. 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.

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E.R.A. du C.N.R.S. n 259.     

An observational study of the structure of the nocturnal urban boundary layer

The formation mechanism of the nocturnal urban boundary layer (UBL), especially in the winter nighttime, was investigated based on the extensive field observations conducted during November 1984 in Sapporo, Japan. A strong, elevated inversion formed over the Sapporo urban area and the inversion base height was approximately twice the average building height. Velocity fluctuations _u, _w and Reynolds stress % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaa0aaaeaaca% WG1bWaaWbaaSqabeaacaaIXaaaaGGaaOGae8hiaaIaam4DamaaCaaa% leqabaGaaGymaaaaaaaaaa!3A9C!\[\overline {u^1 w^1 } \] had nearly uniform profiles within the nocturnal UBL and decreased with height above the UBL. On the other hand, temperature fluctuations _t , and heat fluxes % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaa0aaaeaaca% WG1bWaaWbaaSqabeaacaaIXaaaaGGaaOGae8hiaaIaeqiUde3aaWba% aSqabeaacaaIXaaaaaaaaaa!3B56!\[\overline {u^1 \theta ^1 } \] and % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaa0aaaeaaca% WG3bWaaWbaaSqabeaacaaIXaaaaGGaaOGae8hiaaIaeqiUde3aaWba% aSqabeaacaaIXaaaaaaaaaa!3B58!\[\overline {w^1 \theta ^1 } \] had peaks at the inversion base and small values within the nocturnal UBL. The turbulent kinetic energy budget showed that the turbulent transport term and shear generation from urban canopy elements are important in the nocturnal UBL development; the role of the buoyancy term is small. The turbulence data analysis and application of a simple advective model showed that the mechanism of UBL formation may be controlled by the downward transport of sensible heat from the elevated inversion caused by mechanically-generated turbulence.Nomenclature g accelaration due to gravity, m s^-2 - k turbulent kinetic energy, m² s^-1 - K _m eddy viscosity, m² s^-1 - L Monin-Obukhov lenght, m - p pressure, Kg m^-2 - U, V, W mean wind speed in the downwind, crosswind, and vertical directions, respectively, m s^-1 - u ¹, w ¹ wind speed fluctuation in the downwind and vertical direction, respectively, m s^-1 - u ₁ friction velocity, m s^-1 - % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaa0aaaeaaca% WG1bWaaWbaaSqabeaacaaIXaaaaGGaaOGae8hiaaIaam4DamaaCaaa% leqabaGaaGymaaaaaaaaaa!3A9C!\[\overline {u^1 w^1 } \] momentum flux, m²s^-2 - % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaa0aaaeaaca% WG1bWaaWbaaSqabeaacaaIXaaaaGGaaOGae8hiaaIaam4DamaaCaaa% leqabaGaaGymaaaaaaaaaa!3A9C!\[\overline {u^1 \theta^1 } \] sensible heat flux, m²s^-1°C - WD wind direction, deg - WS wind speed, m s^-1 - z altitude, m - Z _h inversion base height, m - Z _j wind maximum height, m - Z _t inversion top height, m - T _u-r heat island intensity, °C - temperature lapse rate at rural site, °C m^-1 - energy dissipation rate, m²s^-3 - ¹ Potential temperature fluctuation, °C - _* scaling temperature, (=-% MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaa0aaaeaaca% WG1bWaaWbaaSqabeaacaaIXaaaaGGaaOGae8hiaaIaeqiUde3aaWba% aSqabeaacaaIXaaaaaaaaaa!3B56!\[\overline {u^1 \theta ^1 } \]/u_*) °C - mean potential temperature fluctuation, K - density of air, Kgm^-3 - K von Kármán constant (=0.4) - _u, _v, _w standard deviation of wind speed in the downwind, crosswind, and vertical directions, respectively, m s^-1 - standard diviation of temperature, °C     

On the log-linear wind profile and the relationship between shear stress and stability characteristics over the sea

Wind and stability characteristics in the atmospheric surface boundary layer at a height,Z, less than 20 m above the sea were examined in nine oceanic investigations. The analysis lends further support to the utility of the log-linear wind-profile law in the stability region of –0.4Z/L0.9, whereL is the Monin-Obukhov length. However, it is also shown that, inasmuch as better than 90% of the measurements fall within the range of ¦Z/L¦ 0.25, and inasmuch as this correction to the drag coefficient under neutral conditions amounts to less than 10%, the familiar logarithmic wind law may be used rather than the log-linear form. A wind-stress drag coefficient,C _d (=1.2×10^–3 between 1.0 m Z 18.3 m), is thus recommended for general deepwater oceanic applications. The situation over shallow water, which is different, is discussed briefly.     

Surface-layer scintillation measurements of daytime sensible heat and momentum fluxes

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.     

Estimating the Monin-Obukhov length in the stable boundary layer for dispersion calculations

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.     

The atmospheric tide as a continuous spectrum: Lunar semidiurnal tide in surface pressure

Summary The standard equations for the theory of atmospheric tides are solved here by an integral representation on the continuous spectrum of free oscillations. The model profile of back-ground temperature is that of the U.S. Standard Atmosphere in the lower and middle atmosphere, and in the lower thermosphere, above which an isothermal top extends to arbitrarily great heights. The top is warm enough to bring both the Lamb and the Pekeris modes into the continuous spectrum.Computations are made for semidiurnal lunar tidal pressure at sea level at the equator, and the contributions are partitioned according to vertical as well as horizontal structure. Almost all the response is taken up by the Lamb and Pekeris modes of the slowest westward-propagating gravity wave. At sea level, the Lamb-mode response is direct and is relatively insensitive to details of the temperature profile. The Pekeris mode at sea level has an indirect response-in competition with the Lamb mode-and, as has been known since the time of its discovery, it is quite sensitive to the temperature profile, in particular to stratopause temperature. In the standard atmosphere the Lamb mode contributes about +0.078 mb to tidal surface pressure at the equator and the Pekeris mode about –0.048 mb.The aim of this investigation is to illustrate some consequences of representing the tide in terms of the structures of free oscillations. To simplify that task as much as possible, all modifying influences were omitted, such as background wind and ocean or earth tide. Perhaps the main defect of this paper's implementation of the free-oscillation spectrum is that, in contrast to the conventional expansion in the structures of forced oscillations, it does not include dissipation, either implicity or explicity, and thus does not satisfy causality. Dissipation could be added implicity by means of an impedance condition, for example, which would cause up-going energy flux to exceed downgoing flux at the base of the isothermal top layer. To achieve complete causality, however, the dissipation must be modeled explicity. Nevertheless, since the Lamb and Pekeris modes are strongly trapped in the lower and middle atmosphere, where dissipation is rather weak (except possibly in the surface boundary layer), more realistic modeling is not likely to change the broad features of the present results.Symbols a earth's mean radius; expansion coefficient in (5.3) - b recursion variable in (7.4); proximity to resonance in (9.2) - c sound speed in (2.2); specific heatc _p in (2.2) - f Coriolis parameter 2sin in (2.2) - g standard surface gravity - h equivalent depth - i ; discretization index in (7.3) - j index for horizontal structure - k index for horizontal structure; upward unit vectork in (2.2) - m wave number in longitude - n spherical-harmonic degree; number of grid layers in a model layer - p tidal pressure perturbation; background pressurep ₀ - q heating function (energy per mass per time) - r tidal state vector in (2.1) - s tidal entropy perturbation; background entropys ₀ - t time - u tidal horizontal velocityu - w tidal vertical component of velocity - x excitation vector defined in (2.3); vertical coordinate lnp _*/p ₀ [except in (3.8), where it is lnp /p ₀] - y vertical-structure function in (7.1) - z geopotential height - A constant defined in (6.2) - C spherical-harmonic expansion coefficient in (3.6) - D vertical cross section defined in (5.6) and (5.9) - E eigenstate vector - F vertical-structure function for eigenstate pressure in (3.2) [re-defined with WKB scaling in (7.2)] - G vertical-structure function for eigenstate vertical velocity in (3.2) [re-defined with WKB scaling in (7.2)] - H pressure-scale height - I mode intensity defined in (8.1) - K quadratic form defined in (4.4) - L quadratic form defined in (4.4); horizontal-structure magnification factor defined in (5.11) - M vertical-structure magnification factor defined in (4.6) - P eigenstate pressure in (3.2); tidal pressure in (6.2) - R tidal state vector in (5.1) - S eigenstate entropy in (3.2); spherical surface area, in differential dS - T background molecular-scale (NOAA, 1976) absolute temperatureT ₀ - U eigenstate horizontal velocityU in (3.2); coefficient in (7.3) - V horizontal-structure functionV for eigenstate horizontal velocity in (3.2); recursion variable in (7.3) - W eigenstate vertical velocity in (3.2) - X excitation vector in (5.1) - Y surface spherical harmonic in (3.7) - Z Hough function defined in (3.6) - +dH/dz - (1––)/2 - Kronecker delta; Dirac delta; correction operator in (7.6) - equilibrium tide elevation - (square-root of Hough-function eigenvalue) - ratio of specific gas constant to specific heat for air=2/7 - longitude - - - background density ₀ - eigenstate frequency in (3.1) - proxy for heating functionq =c _P/t - latitude - tide frequency - operator for the limitz - horizontal-structure function for eigenstate pressure in (3.2) - Hough function defined in (6.2) - earth's rotation speed - horizontal gradient operator - ()₀ background variable - ()_* surface value of background variable - () value at base of isothermal top layer - Õ state vector with zerow-component - , energy product defined in (2.4) - | | energy norm - ()^* complex conjugate With 10 Figures     

Air-sea bulk transfer coefficients in diabatic conditions

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.     

A discharge flow mass-spectrometric study of the reaction between the NO3 radical and isoprene

The kinetics and mechanism of the reactionNO₃+CH₂=C(CH₃)–CH=CH₂productswere studied in two laboratories at 298 K in the pressure range 0.7–3 torr using the discharge-flow mass-spectrometric method. The rate constant obtained under pseudo-first-order conditions with excess of either NO₃ or isoprene was: k ₁=(7.8±0.6)×10^–13 cm³ molecule^–1 s^–1. The product analysis indicated that the primary addition of NO₃ occurred on both -bonds of the isprene molecule.     

Atmospheric Dry Deposition to Marble and Red Stone

This paper presents dry deposition flux and deposition velocity of atmospheric particles on white marble and red stone at Dayalbagh, a suburban site of semi arid region, which is 10 km away from the industrial sector of the Agra city where due to agricultural practices vegetation predominates. The wind speed at Agra is mostly in the range of 1–2 m s^–1. The atmospheric calm conditions at Agra in summer, monsoon, and winter seasons are 47%, 35%, and 76%, respectively. Industrial areas of the city are away from Dayalbagh and are located in the NE, E, SE, and SW sectors. The main industrial activities, which are in operation in Agra city and its outskirts, are foundry and forging industry. The other industrial activities in Agra are rubber processing, lime oxidation and pulverization, chemicals, engineering and brick refractory kilns. Dry deposition samples were collected on dry days on white marble and red stone (0.224 m × 0.224 m × 0.02 m) using surface washing method. Both slabs were fixed to an iron stand (1.5 m height) at an angle of about 80 from the horizontal and exposed for 24 h on the roof of the faculty building. The order of deposition flux on white marble is NH₄⁺ > Mg²⁺ > Ca²⁺ > Na⁺ > Cl^– > K⁺ > NO₃^– > SO₄^2– > F^– and that on red stone is NH₄⁺ > Mg²⁺ > Ca²⁺ > SO₄^2– > Na⁺ > NO₃^– > K⁺ > F^– > Cl^–. Average dry deposition flux of major ions varies from 3.4 to 128.5 M m^–2 d^–1. The sum of major cations on white marble and red stone are 516.4 and 450.4 eq m^–2 d^–1, respectively while sum of major anions are 425.3 and 400.4 eq m^–2 d^–1 on white marble and red stone, respectively. Higher deposition of all ions was observed when wind blows from NE as most of the Agra Iron foundries and Ferozabad glass industries lie in this direction. The mean values of dry deposition velocity of ions vary between 0.22 cm s^–1 to 1.49 cm s^–1. Deposition velocity for all ions is higher on white marble than red stone inspite of rougher surface of red stone as compared to white marble. This could be due to the chemical nature of white marble, which is made of dolomite and hence adds significant amount of ions by dissolution during washing. Seasonally the deposition velocity was highest in winter.     

A numerical investigation of wind speed effects on lake-effect storms

Observations of lake-effect storms that occur over the Great Lakes region during late autumn and winter indicate a high sensitivity to ambient wind speed and direction. In this paper, a two-dimensional version of the Penn State University/National Center for Atmospheric Research (PSU/NCAR) model is used to investigate the wind speed effects on lake-effect snowstorms that occur over the Great Lakes region.Theoretical initial conditions for stability, relative humidity, wind velocity, and lake/land temperature distribution are specified. Nine different experiments are performed using wind speeds ofU=0, 2, 4,..., 16 m s^–1. The perturbation wind, temperature, and moisture fields for each experiment after 36 h of simulation are compared.It is determined that moderate (4–6 m s^–1) wind speeds result in maximum precipitation (snowfall) on the lee shore of the model lake. Weak wind speeds (0U<4 m s^–1) yield significantly higher snowfall amounts over the lake along with a spatially concentrated and intense response. Strong wind speeds (6<U16 m s^–1), yield very little, if any, significant snowfall, although significant increases in cloudiness, temperature, and perturbation wind speed occur hundreds of kilometers downwind from the lake.     

Turbulence measurements during mistral winds with a 1-dimensional sonic anemometer

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.     

A Generalized Structure-Activity Relationship for the Decomposition of (Substituted) Alkoxy Radicals

A novel and readily applicable Structure-Activity Relationship (SAR) for predicting the barrier height E_b to decomposition by C-C scission of (substituted) alkoxy radicals is presented. Alkoxy radicals are pivotal intermediates in the atmospheric oxidation of (biogenic) volatile organic compounds, and their fate is therefore of crucial importance to the understanding of atmospheric VOC degradation mechanisms. The SAR is based on available theoretical energy barriers and validated against barriers derived from experimental data. The SAR is expressed solely in terms of the number(s) N_i of alkyl-, hydroxy- and/or oxo-substituents on the - and -carbons of the breaking bond: E_b(kcal/mol) =17.5 – 2.1 × N(alk) – 3.1 ×N(alk) – 8.0 × N_,(OH) – 8.0 × N(O=) – 12 × N(O=). For barriers below 7 kcal/mol, an additional, second-order term accounts for the curvature. The SAR reproduces the available experimental and theoretical data within 0.5 to 1 kcal/mol. The SAR generally allows conclusive predictions as to the fate of alkoxy radicals; several examples concerning oxy radicals from prominent atmospheric VOC are presented. Specific limitations of the SAR are also discussed. Using the predicted barrier height E_b, the high-pressure rate coefficient for alkoxy decomposition k _diss (298 K) can be obtained from k _diss (298 K) = L ×1.8 × 10¹³ exp(–E_b/RT) s^–1, with L the reaction path degeneracy.