16 research outputs found

    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

    The Ferry Lidar Experiment and Benchmark

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    The presentation consists of two parts: in the first part, the Ferry Lidar Experiment - which is one of the NEWA Experiments, ie a set of unique flow experiments conducted as part of the New European Wind Atlas (NEWA) Project - is introduced. For the Ferry Lidar Experiment a Doppler lidar instrument was placed on a ferry connecting Kiel and Klaipeda in the Southern Baltic Sea from February to June 2017. A comprehensive set of all relevant motions was recorded together with the lidar data and processed in order to obtain and provide corrected wind time series. In the second part of the presentation, first results of a benchmark study are presented which was conducted on the basis of the NEWA Ferry Lidar dataset. In this study a number of different mesoscale model simulations, provided by different participants of the study, are compared with the measurement data

    Quantifying variability of Large Eddy Simulations of very large wind farms

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    Large Eddy Simulations are inherently dynamic as the largest scales are resolved and the smallest scales are modeled temporally. This raises challenges for simulations including very large scales such as atmospheric flows, which require very long simulation times. Simple averages fail at capturing these dynamics and potentially yield misleading interpretations concerning the capabilities of different models when tested in blind tests or in benchmarking exercises such as Wakebench, where results from different flow models are compared. This article will present results from very large wind farm simulations using Actuator Disc (AD) and Line (AL) models for two different turbine spacings with turbulent inflow. The results of each numerical flow model include a certain variability, and it will be examined if different models result in comparable probability distributions
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