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Newsom, Rob

Publications and source records attributed to Newsom, Rob.

6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Large-eddy simulation of an atmospheric bore and associated gravity wave effects on wind farm performance in the southern Great Plains

Gravity waves are a common occurrence in the atmosphere, with a variety of generation mechanisms. Their impact on wind farms has only recently gained attention, with most studies focused on wind farm-induced gravity waves. In this study, the interaction between a wind farm and gravity waves generated by an atmospheric bore event is assessed using multiscale large-eddy simulations. The atmospheric bore is created by a thunderstorm downdraft from a nocturnal mesoscale convective system (MCS). The associated gravity waves impact the wind resource and power production at a nearby wind farm during the American Wake Experiment (AWAKEN) in the US southern Great Plains. A two-domain nested setup (Δx=300 and 20 m) is used in the Weather Research and Forecasting (WRF) model, forced with data from the High-Resolution Rapid Refresh model, to capture both the formation of the bore and its interaction with individual wind turbines. The MCS is resolved on the large outer domain, where the structure of the bore and the associated gravity waves are found to be especially sensitive to parameterized microphysics processes. On the finer inner domain, gravity wave interactions with individual wind turbines are resolved; wake dynamics are captured using a generalized actuator disk parameterization in WRF. The gravity waves are found to have a strong effect on the atmosphere above the wind farm; however, the effect of the waves is more nuanced closer to the surface where there is additional turbulence, both ambient and wake-generated. Notably, the gravity waves modulate the mesoscale environment by weakening and dissipating the preexisting low-level jet, which reduces hub-height wind speed and hence the simulated power output, which is confirmed by the observed supervisory control and data acquisition (SCADA) power data. Additionally, the gravity waves induce local wind direction variations correlated with fluctuations in pressure, which lead to fluctuations in the simulated power output as various turbines within the farm are subjected to waking from nearby turbines.

17 WIND ENERGY↗
NASA NTRS2008

CART Raman Lidar Aerosol and Water Vapor Measurements in the Vicinity of Clouds

Aerosol and water vapor profiles acquired by the Raman lidar instrument located at the Climate Research Facility (CRF) at Southern Great Plains (SGP) provide data necessary to investigate the atmospheric variability in the vicinity of clouds near the top of the planetary boundary layer (PBL). Recent CARL upgrades and modifications to the routine processing algorithms afforded the necessarily high temporal and vertical data resolutions for these investigations. CARL measurements are used to investigate the behavior of aerosol backscattering and extinction and their correlation with water vapor and relative humidity.

Clayton, Marian B.↗
NASA NTRS2008

Progress on the Use of Combined Analog and Photon Counting Detection for Raman Lidar

The Atmospheric Radiation Measurement (ARM) program Raman Lidar (CARL) was upgraded in 2004 with a new data system that provides simultaneous measurements of both the photomultiplier analog output voltage and photon counts. The so-called merge value added procedure (VAP) was developed to combine the analog and count-rate signals into a single signal with improved dynamic range. Earlier versions of this VAP tended to cause unacceptably large biases in the water vapor mixing ratio during the daytime as a result of improper matching between the analog and count-rate signals in the presence of elevated solar background levels. We recently identified several problems and tested a modified version of the merge VAP by comparing profiles of water vapor mixing ratio derived from CARL with simultaneous sonde data over a six month period. We show that the modified merge VAP significantly reduces the daytime bias, and results in mean differences that are within approximately 1% for both nighttime and daytime measurements.

Newsom, Rob↗