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Anirban Garai and Jan Kleissl

Abstract

In a convective boundary layer, coherent structures were detected through their thermal signature on an artificial turf surface using high-frequency thermal infrared (TIR) imagery and surface layer turbulence measurements. The coherent structures cause surface temperature variations over tens of seconds and spatial scales of tens to a few hundred meters. Evidence of processes similar to those in a renewal event was observed. Spatial and temporal correlation analysis revealed the geometric and velocity information of the structures at the ground footprint of air temperature measurements. The velocity of the coherent structures was consistent with the wind speed at 6.5 m AGL. Practical implications of turbulence-driven surface temperature variability for thermal remote sensing are also discussed.

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Bengu Ozge Akyurek and Jan Kleissl

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Stratocumulus clouds play an important role in climate cooling and are hard to predict using global climate and weather forecast models. Thus, previous studies in the literature use observations and numerical simulation tools, such as large-eddy simulation (LES), to solve the governing equations for the evolution of stratocumulus clouds. In contrast to the previous works, this work provides an analytic closed-form solution to the cloud thickness evolution of stratocumulus clouds in a mixed-layer model framework. With a focus on application over coastal lands, the diurnal cycle of cloud thickness and whether or not clouds dissipate are of particular interest. An analytic solution enables the sensitivity analysis of implicitly interdependent variables and extrema analysis of cloud variables that are hard to achieve using numerical solutions. In this work, the sensitivity of inversion height, cloud-base height, and cloud thickness with respect to initial and boundary conditions, such as Bowen ratio, subsidence, surface temperature, and initial inversion height, are studied. A critical initial cloud thickness value that can be dissipated pre- and postsunrise is provided. Furthermore, an extrema analysis is provided to obtain the minima and maxima of the inversion height and cloud thickness within 24 h. The proposed solution is validated against LES results under the same initial and boundary conditions.

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Neda Yaghoobian, Jan Kleissl, and E. Scott Krayenhoff

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The effects of artificial turf (AT) on the urban canopy layer energy balance, air and surface temperatures, and building cooling loads are compared to those of other common ground surface materials (asphalt, concrete, and grass) through heat transfer modeling of radiation, convection, and conduction. The authors apply the Temperatures of Urban Facets in 3D (TUF3D) model—modified to account for latent heat fluxes—to a clear summer day at a latitude of 33° over a typical coastal suburban area in Southern California. The low albedo of artificial turf relative to the other materials under investigation results in a reduction in shortwave radiation incident on nearby building walls and an approximately equal increase in longwave radiation. Consequently, building walls remain at a relatively cool temperature that is similar to those that are adjacent to irrigated grass surfaces. Using a simple offline convection model, replacing grass ground cover with artificial turf was found to add 2.3 kW h m−2 day−1 of heat to the atmosphere, which could result in urban air temperature increases of up to 4°C. Local effects of AT on building design cooling loads were estimated. The increased canopy air temperatures with AT increase heat conduction through the building envelope and ventilation in comparison with a building near irrigated grass. However, in this temperate climate these loads are small relative to the reduction in radiative cooling load through windows. Consequently, overall building design cooling loads near AT decrease by 15%–20%. In addition, the irrigation water conservation with AT causes an embodied energy savings of 10 W h m−2 day−1. Locally, this study points to a win–win situation for AT use for urban landscaping as it results in water and energy conservation.

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Jan Kleissl, Marc B. Parlange, and Charles Meneveau
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Jan Kleissl, Marc B. Parlange, and Charles Meneveau

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An analysis of dynamic Smagorinsky models is performed based on the Horizontal Array Turbulence Study (HATS) dataset. In the experiment, two vertically separated horizontal arrays of 14 three-dimensional sonic anemometers were placed in the atmospheric surface layer. Subgrid-scale (SGS) and resolved quantities are derived from 2D filtering at a filter scale Δ and differentiation of filtered velocity fields. In a previous study the Smagorinsky coefficient c(Δ)s was computed directly from these data and found to depend on atmospheric stability and height above the ground. The present study examines the scale-invariant dynamic model of Germano et al. and the scale-dependent dynamic model of Porté-Agel et al. and tests their accuracy in predicting c(Δ)s and its dependencies on stability and height above the ground. The Germano identity uses a test filter at αΔ (in this study α = 1.75 is used). The coefficient is derived from various data test-filtered at this scale assuming that the Smagorinsky coefficient is scale invariant. The results show that the scale-invariant dynamic model severely underpredicts the coefficient and its trends whenever Δ is similar to, or larger than, the large-scale limit of the inertial range (typically the smaller of the height above the ground z or the Obukhov length L). The scale-dependent dynamic model uses a second test filter at scale α 2Δ to deduce dependence of c(Δ)s on the filtering scale. This model gives excellent predictions of c(Δ)s and its dependence upon stability and height.

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Jan Kleissl, Charles Meneveau, and Marc B. Parlange

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Eddy-viscosity closures for large eddy simulations (LES) of atmospheric boundary layer dynamics include a parameter (Smagorinsky constant c s), which depends upon physical parameters, such as distance to the ground, atmospheric stability, and strain. A field study [Horizontal Arrays Turbulence Study (HATS)] specifically designed to measure turbulence quantities of interest in LES, such as the parameter c s, is conducted. The instrumentation consists of two vertically separated horizontal arrays of 3D sonic anemometers, placed in the atmospheric surface layer. From 2D filtering and differentiating the velocity fields, subgrid-scale (SGS) and resolved quantities are computed. The parameter c s is obtained from the data by matching measured and modeled SGS dissipations under various flow conditions. Results indicate that c s is reduced near the ground, and also decreases rapidly with increasing stability in stable atmospheric conditions. A simple fit that parameterizes the data is proposed. The variability from one sample to another is studied by means of the probability density function (pdf) of c s. The pdfs show a most preferred value, which is essentially independent of the timescale used for statistical averaging. The width of the pdfs decreases with increasing averaging time, for unstable and neutral stability conditions. For stable conditions, the relative variability of the coefficient remains strong even for long averaging times, indicative of strong intermittency. In unstable conditions, c s is fairly independent of local strain-rate magnitude, supporting the basic scaling of the Smagorinsky eddy viscosity. For stable conditions, a transition occurs between small local strain-rate magnitudes, where c s is nearly constant, and high local strain-rate magnitudes, where c s decreases appreciably. The results suggest that when the filter scale approaches the local integral scale of turbulence (height above the ground or Obukhov length), one needs to include the friction velocity as relevant velocity to scale the eddy viscosity, in addition to the standard velocity scale of the Smagorinsky model based on filtered strain-rate magnitude. The analysis is repeated for the SGS heat flux, and for the associated eddy-diffusion coefficient (PrT–1 cs2) and Prandtl number (PrT). The latter is found to depend only very weakly on stability, but it increases with decreasing distance from the ground.

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Jan Kleissl, Sung-Ho Hong, and Jan M. H. Hendrickx

In New Mexico, a first-of-its-kind network of seven large aperture scintillometer (LAS) sites was established in 2006 to measure sensible heat fluxes over irrigated fields, riparian areas, deserts, lava flows, and mountain highlands. Wireless networking infrastructure and auxiliary meteorological measurements facilitate real-time data assimilation. LAS measurements are advantageous in that they vastly exceed the footprint size of commonly used ground measurements of sensible and latent heat fluxes (~100 m2), matching the pixel size of satellite images or grid cells of hydrologic and meteorological models (~0.1–5 km2). Consequently, the LAS measurements can be used to validate, calibrate, and force hydrologic, remote sensing, and weather forecast models. Initial results are presented for 1) variability and error of sensible heat flux measurements by scintillometers over heterogeneous terrain and 2) the validation of the Surface Energy Balance Algorithm for Land (SEBAL) applied to Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery. Findings from this study are discussed in the context of researchers' and practitioners' data assimilation needs.

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Mohamed S. Ghonima, Joel R. Norris, Thijs Heus, and Jan Kleissl

Abstract

A detailed derivation of stratocumulus cloud thickness and liquid water path tendencies as a function of the well-mixed boundary layer mass, heat, and moisture budget equations is presented. The derivation corrects an error in the cloud thickness tendency equation derived by R. Wood to make it consistent with the liquid water path tendency equation derived by J. J. van der Dussen et al. The validity of the tendency equations is then tested against the output of large-eddy simulations of a typical stratocumulus-topped boundary layer case and is found to be in good agreement.

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Mohamed S. Ghonima, Thijs Heus, Joel R. Norris, and Jan Kleissl

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The breakup of stratocumulus clouds over coastal land areas is studied using a combination of large-eddy simulations (LESs) and mixed-layer models (MLMs) with a focus on mechanisms regulating the timing of the breakup. In contrast with stratocumulus over ocean, strong sensible heat flux over land prevents the cloud layer from decoupling during day. As the cloud thins during day, turbulence generated by surface flux becomes larger than turbulence generated by longwave cooling across the cloud layer. To capture this shift in turbulence generation in the MLM, an existing entrainment parameterization is extended. The MLM is able to mimic cloud evolution for a variety of Bowen ratios, but only after this modification of the entrainment parameterization. Cloud lifetime depends on a combination of the cloud-top entrainment flux, the Bowen ratio of the surface, and the strength of advection of cool ocean air by the sea breeze. For dry land surface conditions, the authors’ MLM suggests a breakup time a few hours after sunrise. For relatively wet land surface conditions, the cloud layer briefly breaks into partly cloudy conditions during midday, and the stratocumulus cloud reforms in the evening.

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Mónica Zamora Zapata, Joel R. Norris, and Jan Kleissl

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The impact of initial states and meteorological variables on stratocumulus cloud dissipation time over coastal land is investigated using a mixed-layer model. A large set of realistic initial conditions and forcing parameters are derived from radiosonde observations and numerical weather prediction model outputs, including total water mixing ratio and liquid water potential temperature profiles (within the boundary layer, across the capping inversion, and at 3 km), inversion-base height and cloud thickness, large-scale divergence, wind speed, Bowen ratio, sea surface fluxes, sky effective radiative temperature, shortwave irradiance above the cloud, and sea level pressure. We study the sensitivity of predicted dissipation time using two analyses. In the first, we simulate 195 cloudy days (all variables covary as observed in nature). We caution that simulated predictions correlate only weakly to observations of dissipation time, but the simulation approach is robust and facilitates covariability testing. In the second, a single variable is varied around an idealized reference case. While both analyses agree in that initial conditions influence dissipation time more than forcing parameters, some results with covariability differ greatly from the more traditional sensitivity analysis and with previous studies: opposing trends are observed for boundary layer total water mixing ratio and Bowen ratio, and covariability diminishes the sensitivity to cloud thickness and inversion height by a factor of 5. With covariability, the most important features extending predicted cloud lifetime are (i) initially thicker clouds, higher inversion height, and stronger temperature inversion jumps, and (ii) boundary forcings of lower sky effective radiative temperature.

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