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- Author or Editor: M. Laan x
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Abstract
A “fast thermistor string” has been built to accommodate the scientific need to accurately monitor internal wave activity in shelf seas and above sloping bottoms in the ocean. The performance of the thermistors and their custom-designed electronics allow temperature variations to be registered at an estimated relative accuracy better than 0.5 mK with a response time faster than 0.25 s. Quantization noise is less than about 40 μK and dominates instrumental noise. Currently, the string holds 32 sensors, which are sampled within 4 s. When sampling every 30 s, the batteries and the memory capacity of the recorder allow deployments up to 3 months. In all respects, this performance is about an order of magnitude superior to thermistor strings currently available commercially. Moored in combination with an acoustic Doppler current profiler the thermistor string provides data to estimate directly quasi-turbulent (high-frequency internal wave band) vertical temperature fluxes and flux gradients. Examples of field observations are given, which show enhanced levels of temperature variance extending above the canonical internal wave spectral levels near the buoyancy frequency, and detailed variations of high-frequency internal wave variability.
Abstract
A “fast thermistor string” has been built to accommodate the scientific need to accurately monitor internal wave activity in shelf seas and above sloping bottoms in the ocean. The performance of the thermistors and their custom-designed electronics allow temperature variations to be registered at an estimated relative accuracy better than 0.5 mK with a response time faster than 0.25 s. Quantization noise is less than about 40 μK and dominates instrumental noise. Currently, the string holds 32 sensors, which are sampled within 4 s. When sampling every 30 s, the batteries and the memory capacity of the recorder allow deployments up to 3 months. In all respects, this performance is about an order of magnitude superior to thermistor strings currently available commercially. Moored in combination with an acoustic Doppler current profiler the thermistor string provides data to estimate directly quasi-turbulent (high-frequency internal wave band) vertical temperature fluxes and flux gradients. Examples of field observations are given, which show enhanced levels of temperature variance extending above the canonical internal wave spectral levels near the buoyancy frequency, and detailed variations of high-frequency internal wave variability.
Abstract
Wind-farm parameterizations in weather models can be used to predict both the power output and farm effects on the flow; however, their correctness has not been thoroughly assessed. We evaluate the wind-farm parameterization of the Weather Research and Forecasting Model with large-eddy simulations (LES) of the wake performed with the same model. We study the impact on the velocity and turbulence kinetic energy (TKE) of inflow velocity, roughness, resolution, number of turbines (one or two), and inversion height and strength. We compare the mesoscale with the LES by spatially averaging the LES within areas correspondent to the mesoscale horizontal spacing: one covering the turbine area and two downwind. We find an excellent agreement of the velocity within the turbine area between the two types of simulations. However, within the same area, we find the largest TKE discrepancies because in mesoscale simulations, the turbine-added TKE has to be highest at the turbine position to be advected downwind. Within the downwind areas, differences between velocities increase as the wake recovers faster in the LES, whereas for the TKE both types of simulations show similar levels. From the various configurations, the impact of inversion height and strength is small for these heights and inversion levels. The highest impact for the one-turbine simulations appears under the low-speed case due to the higher thrust, whereas the impact of resolution is low for the large-eddy simulations but high for the mesoscale simulations. Our findings demonstrate that higher-fidelity simulations are needed to validate wind-farm parameterizations.
Abstract
Wind-farm parameterizations in weather models can be used to predict both the power output and farm effects on the flow; however, their correctness has not been thoroughly assessed. We evaluate the wind-farm parameterization of the Weather Research and Forecasting Model with large-eddy simulations (LES) of the wake performed with the same model. We study the impact on the velocity and turbulence kinetic energy (TKE) of inflow velocity, roughness, resolution, number of turbines (one or two), and inversion height and strength. We compare the mesoscale with the LES by spatially averaging the LES within areas correspondent to the mesoscale horizontal spacing: one covering the turbine area and two downwind. We find an excellent agreement of the velocity within the turbine area between the two types of simulations. However, within the same area, we find the largest TKE discrepancies because in mesoscale simulations, the turbine-added TKE has to be highest at the turbine position to be advected downwind. Within the downwind areas, differences between velocities increase as the wake recovers faster in the LES, whereas for the TKE both types of simulations show similar levels. From the various configurations, the impact of inversion height and strength is small for these heights and inversion levels. The highest impact for the one-turbine simulations appears under the low-speed case due to the higher thrust, whereas the impact of resolution is low for the large-eddy simulations but high for the mesoscale simulations. Our findings demonstrate that higher-fidelity simulations are needed to validate wind-farm parameterizations.
