29 research outputs found

    How Does the Choice of the Lower Boundary Conditions in Large-Eddy Simulations Affect the Development of Dispersive Fluxes Near the Surface?

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    Large-eddy simulations (LES) are an important tool for investigating the longstanding energy-balance-closure problem, as they provide continuous, spatially-distributed information about turbulent flow at a high temporal resolution. Former LES studies reproduced an energy-balance gap similar to the observations in the field typically amounting to 10–30% for heights on the order of 100 m in convective boundary layers even above homogeneous surfaces. The underestimation is caused by dispersive fluxes associated with large-scale turbulent organized structures that are not captured by single-tower measurements. However, the gap typically vanishes near the surface, i.e. at typical eddy-covariance measurement heights below 20 m, contrary to the findings from field measurements. In this study, we aim to find a LES set-up that can represent the correct magnitude of the energy-balance gap close to the surface. Therefore, we use a nested two-way coupled LES, with a fine grid that allows us to resolve fluxes and atmospheric structures at typical eddy-covariance measurement heights of 20 m. Under different stability regimes we compare three different options for lower boundary conditions featuring grassland and forest surfaces, i.e. (1) prescribed surface fluxes, (2) a land-surface model, and (3) a land-surface model in combination with a resolved canopy. We show that the use of prescribed surface fluxes and a land-surface model yields similar dispersive heat fluxes that are very small near the vegetation top for both grassland and forest surfaces. However, with the resolved forest canopy, dispersive heat fluxes are clearly larger, which we explain by a clear impact of the resolved canopy on the relationship between variance and flux–variance similarity functions

    Building indoor model in PALM-4U: indoor climate, energy demand, and the interaction between buildings and the urban microclimate

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    There is a strong interaction between the urban atmospheric canopy layer and the building energy balance. The urban atmospheric conditions affect the heat transfer through exterior walls, the long-wave heat transfer between the building surfaces and the surroundings, the short-wave solar heat gains, and the heat transport by ventilation. Considering also the internal heat gains and the heat capacity of the building structure, the energy demand for heating and cooling and the indoor thermal environment can be calculated based on the urban microclimatic conditions. According to the building energy concept, the energy demand results in an (anthropogenic) waste heat; this is directly transferred to the urban environment. Furthermore, the indoor temperature is re-coupled via the building envelope to the urban environment and affects indirectly the urban microclimate with a temporally lagged and damped temperature fluctuation. We developed a holistic building model for the combined calculation of indoor climate and energy demand based on an analytic solution of Fourier's equation and implemented this model into the PALM model.</p

    Turbulent heat exchange over polar leads revisited: A large eddy simulation study

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    Sea ice leads play an important role in energy exchange between the ocean and atmosphere in polar regions, and therefore must be considered in weather and climate models. As sea ice leads are not explicitly resolved in such models, lead-averaged surface heat flux is of considerable interest for the parameterization of energy exchange. Measurements and numerical studies have established that the lead-averaged surface heat flux depends not only on meteorological parameters, but also on lead width. Nonetheless, few studies to date have investigated the dependency of surface heat flux on lead width. Most findings on that dependency are based on observations with lead widths smaller than a few hundred meters, but leads can have widths from a few meters to several kilometers. In this parameter study, we present the results of three series of large-eddy simulations of turbulent exchange processes above leads. We varied the lead width and air temperature, as well as the roughness length. As this study focused on conditions without background wind, ice-breeze circulation occurred, and was the main driver of the adjustment of surface heat flux. A previous large-eddy simulation study with uncommonly large roughness length found that lead-averaged surface heat flux exhibited a distinct maximum at lead widths of about 3 km, while our results show the largest heat fluxes for the smallest leads simulated (lead width of 50 m). At more realistic roughness lengths, we observed monotonously increasing heat fluxes with increasing lead width. Further, new scaling laws for the ice-breeze circulation are proposed

    Novel approach to observing system simulation experiments improves information gain of surface-atmosphere field measurements

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    The observing system design of multidisciplinary field measurements involves a variety of considerations on logistics, safety, and science objectives. Typically, this is done based on investigator intuition and designs of prior field measurements. However, there is potential for considerable increases in efficiency, safety, and scientific success by integrating numerical simulations in the design process. Here, we present a novel numerical simulation–environmental response function (NS–ERF) approach to observing system simulation experiments that aids surface–atmosphere synthesis at the interface of mesoscale and microscale meteorology. In a case study we demonstrate application of the NS–ERF approach to optimize the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19). During CHEESEHEAD19 pre-field simulation experiments, we considered the placement of 20 eddy covariance flux towers, operations for 72 h of low-altitude flux aircraft measurements, and integration of various remote sensing data products. A 2 h high-resolution large eddy simulation created a cloud-free virtual atmosphere for surface and meteorological conditions characteristic of the field campaign domain and period. To explore two specific design hypotheses we super-sampled this virtual atmosphere as observed by 13 different yet simultaneous observing system designs consisting of virtual ground, airborne, and satellite observations. We then analyzed these virtual observations through ERFs to yield an optimal aircraft flight strategy for augmenting a stratified random flux tower network in combination with satellite retrievals. We demonstrate how the novel NS–ERF approach doubled CHEESEHEAD19's potential to explore energy balance closure and spatial patterning science objectives while substantially simplifying logistics. Owing to its modular extensibility, NS–ERF lends itself to optimizing observing system designs also for natural climate solutions, emission inventory validation, urban air quality, industry leak detection, and multi-species applications, among other use cases.</p

    Novel approach to observing system simulation experiments improves information gain of surface-atmosphere field measurements

    Get PDF
    The observing system design of multidisciplinary field measurements involves a variety of considerations on logistics, safety, and science objectives. Typically, this is done based on investigator intuition and designs of prior field measurements. However, there is potential for considerable increases in efficiency, safety, and scientific success by integrating numerical simulations in the design process. Here, we present a novel numerical simulation-environmental response function (NS-ERF) approach to observing system simulation experiments that aids surface-atmosphere synthesis at the interface of mesoscale and microscale meteorology. In a case study we demonstrate application of the NS-ERF approach to optimize the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19). During CHEESEHEAD19 pre-field simulation experiments, we considered the placement of 20 eddy covariance flux towers, operations for 72h of low-altitude flux aircraft measurements, and integration of various remote sensing data products. A 2h high-resolution large eddy simulation created a cloud-free virtual atmosphere for surface and meteorological conditions characteristic of the field campaign domain and period. To explore two specific design hypotheses we super-sampled this virtual atmosphere as observed by 13 different yet simultaneous observing system designs consisting of virtual ground, airborne, and satellite observations. We then analyzed these virtual observations through ERFs to yield an optimal aircraft flight strategy for augmenting a stratified random flux tower network in combination with satellite retrievals. We demonstrate how the novel NS-ERF approach doubled CHEESEHEAD19's potential to explore energy balance closure and spatial patterning science objectives while substantially simplifying logistics. Owing to its modular extensibility, NS-ERF lends itself to optimizing observing system designs also for natural climate solutions, emission inventory validation, urban air quality, industry leak detection, and multi-species applications, among other use cases. © 2021 Stefan Metzger et al

    Chloroleucon chacÓ§ense (Leguminosae): A Study on Morphometry of Fruits and Seeds, Germinability and Development of Seedlings

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    Abstract The dehiscent legumes of Chloroleucon chacöense (Leguminosae, Mimosoideae) are highly predated. The seeds of an intermediate type (neither orthodox, nor recalcitrant) remain in latency until the rainy station start can germinate efficiently when are imbibed 36 h in water before the sown, reaching similar % than those treated with sand paper or sulphuric acid. The seeds lose their germinability when are treated with warm water, perhaps because it kills the embryo. The seedlings are developed in a high percentage (92%) although they do not receive scarification treatments. The scarified seeds increase their weight more than the no scarified, as the Baskin Index denotes. The ANOVA and MTG show that the mechanical and chemical treatments allow the seeds to germinate till 24 h since the sown. The &quot;t&quot; test highlights that the no scarified seeds exhibit high difference of weight only at 24 h since the sown; perhaps the seeds need that lapse of time to imbibe to start the germination. Between the unhealthy seeds, those with arrested development constitute a high percentage, and perhaps some problems in the reproductive system exist. The germination is epigeal, phanerocotyledonar, with photosynthesizing cotyledons, and the seedlings have two sub-opposite protophylls (one pinnate, the other bipinnate) and two or more alternate, bipinnate eophylls. This fact implies that the classification commonly used does not cover the variability existent in the Leguminosae. Studies are needed to elucidate the origin of the low density of individuals because the species is included in the RED BOOK

    Overview of the PALM model system 6.0

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    In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for Parallelized Largeeddy Simulation Model and now an independent name) is a Fortran-based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model with components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue

    Connecting Land–Atmosphere Interactions to Surface Heterogeneity in CHEESEHEAD19

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    The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models
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