64 research outputs found

    Stord Orographic Precipitation Experiment (STOPEX): an overview of phase I

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    STOPEX (Stord Orographic Precipitation Experiment) is a research project of the Geophysical Institute, University of Bergen, Norway, dedicated to the investigation of orographic effects on fine scale precipitation patterns by a combination of numerical modelling and tailored measurement campaigns. Between 24 September and 16 November 2005 the first field campaign STOPEX I has been performed at and around the island of Stord at the west coast of Norway, about 50 km south of Bergen. 12 rain gauges and 3 autonomous weather stations have been installed to measure the variability of precipitation and the corresponding meteorological conditions. This paper gives an overview of the projects motivation, a description of the campaign and a presentation of the precipitation measurements performed. In addition, the extreme precipitation event around 14 November with precipitation amounts up to 240 mm in less than 24 h, is described and briefly discussed. In this context preliminary results of corresponding MM5 simulations are presented, that indicate the problems as well as potential improvement strategies with respect to modelling of fine scale orographic precipitation

    Definition of "banner clouds" based on time lapse movies

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    International audienceBanner clouds appear on the leeward side of a mountain and resemble a banner or a flag. This article provides a comprehensive definition of "banner clouds". It is based primarily on an extensive collection of time lapse movies, but previous attempts at an explanation of this phenomenon are also taken into account. The following ingredients are considered essential: the cloud must be attached to the mountain but not appear on the windward side; the cloud must originate from condensation of water vapour contained in the air (rather than consist of blowing snow); the cloud must be persistent; and the cloud must not be of convective nature. The definition is illustrated and discussed with the help of still images and time lapse movies taken at Mount Zugspitze in the Bavarian Alps

    Defintion of "banner clouds" based on time lapse movies

    No full text
    International audienceBanner clouds appear on the leeward side of a mountain and resemble a banner or a flag. This article provides a comprehensive definition of "banner clouds". It is based primarily on an extensive collection of time lapse movies, but previous attempts at an explanation of this phenomenon are also taken into account. The following ingredients are considered essential: the cloud must be attached to the mountain but not appear on the windward side; the cloud must originate from condensation of water vapour contained in the air (rather than consist of blowing snow); the cloud must be persistent; and the cloud must not be of convective nature. The definition is illustrated and discussed with the help of still images and time lapse movies taken at Mount Zugspitze in the Bavarian Alps

    Evaluation of different wind fields for the investigation of the dynamic response of offshore wind turbines

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    As the size of offshore wind turbines increases, a realistic representation of the spatiotemporal distribution of the incident wind field becomes crucial for modeling the dynamic response of the turbine. The International Electrotechnical Commission (IEC) standard for wind turbine design recommends two turbulence models for simulations of the incident wind field, the Mann spectral tensor model, and the Kaimal spectral and exponential coherence model. In particular, for floating wind turbines, these standard models are challenged by more sophisticated ones. The characteristics of the wind field depend on the stability conditions of the atmosphere, which neither of the standard turbulence models account for. The spatial and temporal distribution of the turbulence, represented by coherence, is not modeled consistently by the two standard models. In this study, the Mann spectral tensor model and the Kaimal spectral and exponential coherence model are compared with wind fields constructed from offshore measurements and obtained from large‐eddy simulations. Cross sections and durations relevant for offshore wind turbine design are considered. Coherent structures from the different simulators are studied across various stability conditions and wind speeds through coherence and proper orthogonal decomposition mode plots. As expected, the standard models represent neutral stratification better than they do stable and unstable. Depending upon the method used for generating the wind field, significant differences in the spatial and temporal distribution of coherence are found. Consequently, the computed structural design loads on a wind turbine are expected to vary significantly depending upon the employed turbulence model. The knowledge gained in this study will be used in future studies to quantify the effect of various turbulence models on the dynamic response of large offshore wind turbines.publishedVersio

    Self-nested large-eddy simulations in PALM model system v21.10 for offshore wind prediction under different atmospheric stability conditions

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    Large-eddy simulation (LES) resolves large-scale turbulence directly and parametrizes small-scale turbulence. Resolving micro-scale turbulence, e.g., in wind turbine wakes, requires both a sufficiently small grid spacing and a domain large enough to develop turbulent flow. Refining a grid locally via a nesting interface effectively decreases the required computational time compared to the global grid refinement. However, interpolating the flow between nested grid boundaries introduces another source of uncertainty. Previous studies reviewed nesting effects for a buoyancy-driven flow and observed a secondary circulation in the two-way nested area. Using a nesting interface with a shear-driven flow in LES, therefore, requires additional verification. We use PALM model system 21.10 to simulate a boundary layer in a cascading self-nested domain under neutral, convective, and stable conditions and verify the results based on the wind speed measurements taken at the FINO1 platform in the North Sea. We show that the feedback between parent and child domains in a two-way nested simulation of a non-neutral boundary layer alters the circulation in the nested area, despite spectral characteristics following the reference measurements. Unlike the pure buoyancy-driven flow, a non-neutral shear-driven flow slows down in a two-way nested area and accelerates after exiting the child domain. We also briefly review the nesting effect on the velocity profiles and turbulence anisotropy.</p

    A Ship-Based Characterization of Coherent Boundary-Layer Structures Over the Lifecycle of a Marine Cold-Air Outbreak

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    Convective coherent structures shape the atmospheric boundary layer over the lifecycle of marine cold-air outbreaks (CAOs). Aircraft measurements have been used to characterize such structures in past CAOs. Yet, aircraft case studies are limited to snapshots of a few hours and do not capture how coherent structures, and the associated boundary-layer characteristics, change over the CAO time scale, which can be on the order of several days. We present a novel ship-based approach to determine the evolution of the coherent-structure characteristics, based on profiling lidar observations. Over the lifecycle of a multi-day CAO we show how these structures interact with boundary-layer characteristics, simultaneously obtained by a multi-sensor set-up. Observations are taken during the Iceland Greenland Seas Project’s wintertime cruise in February and March 2018. For the evaluated CAO event, we successfully identify cellular coherent structures of varying size in the order of 4 × 102 m to 104 m and velocity amplitudes of up to 0.5 m s−1 in the vertical and 1 m s−1 in the horizontal. The structures’ characteristics are sensitive to the near-surface stability and the Richardson number. We observe the largest coherent structures most frequently for conditions when turbulence generation is weakly buoyancy dominated. Structures of increasing size contribute efficiently to the overturning of the boundary layer and are linked to the growth of the convective boundary-layer depth. The new approach provides robust statistics for organized convection, which would be easy to extend by additional observations during convective events from vessels of opportunity operating in relevant areas

    A new roughness length parameterization accounting for wind–wave (mis)alignment

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    Two-way feedback occurs between offshore wind and waves. However, the influence of the waves on the wind profile remains understudied, in particular the momentum transfer between the sea surface and the atmosphere. Previous studies showed that for swell waves it is possible to have increasing wind speeds in case of aligned wind–wave directions. However, the opposite is valid for opposed wind–wave directions, where a decrease in wind velocity is observed. Up to now, this behavior has not been included in most numerical models due to the lack of an appropriate parameterization of the resulting effective roughness length. Using an extensive data set of offshore measurements in the North Sea and the Atlantic Ocean, we show that the wave roughness length affecting the wind is indeed dependent on the alignment between the wind and wave directions. Moreover, we propose a new roughness length parameterization, taking into account the dependence on alignment, consisting of an enhanced roughness length for increasing misalignment. Using this new roughness length parameterization in numerical models might facilitate a better representation of offshore wind, which is relevant to many applications including offshore wind energy and climate modeling.</p

    Comparison of Parametric and Nonparametric Methods for Analyzing the Bias of a Numerical Model

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    Numerical models are presently applied in many fields for simulation and prediction, operation, or research. The output from these models normally has both systematic and random errors. The study compared January 2015 temperature data for Uganda as simulated using the Weather Research and Forecast model with actual observed station temperature data to analyze the bias using parametric (the root mean square error (RMSE), the mean absolute error (MAE), mean error (ME), skewness, and the bias easy estimate (BES)) and nonparametric (the sign test, STM) methods. The RMSE normally overestimates the error compared to MAE. The RMSE and MAE are not sensitive to direction of bias. The ME gives both direction and magnitude of bias but can be distorted by extreme values while the BES is insensitive to extreme values. The STM is robust for giving the direction of bias; it is not sensitive to extreme values but it does not give the magnitude of bias. The graphical tools (such as time series and cumulative curves) show the performance of the model with time. It is recommended to integrate parametric and nonparametric methods along with graphical methods for a comprehensive analysis of bias of a numerical model
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