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At least 37 records · Page 2

Overview of preparation for the American WAKE ExperimeNt (AWAKEN)

The American WAKE ExperimeNt (AWAKEN) is a multi-institutional field campaign focused on gathering critical observations of wind farm–atmosphere interactions. These interactions are responsible for a large portion of the uncertainty in wind plant modeling tools that are used to represent wind plant performance both prior to construction and during operation and can negatively impact wind energy profitability. The AWAKEN field campaign will provide data for validation, ultimately improving modeling and lowering these uncertainties. The field campaign is designed to address seven testable hypotheses through the analysis of the observations collected by numerous instruments at 13 ground-based locations and on five wind turbines. The location of the field campaign in Northern Oklahoma was chosen to leverage existing observational facilities operated by the U.S. Department of Energy Atmospheric Radiation Measurement program in close proximity to five operating wind plants. The vast majority of the observations from the experiment are publicly available to researchers and industry members worldwide, which the authors hope will advance the state of the science for wind plants and lead to lower cost and increased reliability of wind energy systems.

17 WIND ENERGY↗

Precipitation Trade Wind Cumuli within EUREC 4 A Field Campaign Report

The campaign Trades Cumuli Precipitation Initiation and Characterization (TCPIC) within the overarching Elucidating the Role of Clouds-Circulation Coupling in Climate EUREC 4 A campaign took place from 17 January 2020 to 20 February 2020, a total of 35 days. The campaign complemented the more extensive EUREC 4 A campaign focusing on cumulus clouds' role in the Earth's climate. TCPIC concentrated on understanding what triggers the onset and development of precipitation in trade wind cumulus clouds. The campaign requested the deployment of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) roll, pitch, and heave (RPH) stabilization platform to stabilize two radars on the Maria S. Merian research vessel (RV). The advanced remote-sensing techniques from stabilized radars characterized the entire precipitation life cycle, from the formation of larger cloud drops to precipitation evaporating on its way to the surface. Retrievals of evaporation rates, to track how rain affects the trade wind boundary layer, will be based on the zenith-pointing Doppler observations collected from the stabilized micro rain radar (MRR). Figure 1 shows the instrumentation's deployment on the RV: we installed the AMF RPH stabilization platform and the radars on the uppermost deck (peil deck) of the ship. For installing the devices, we coordinated a test phase of the equipment on the Maria S. Merian RV from 25 to 29 October 2019 in Emden harbor, Germany. In this testing phase, we set up all the connections, tested how to mount the W-band and the micro rain radars firmly on the table, and experimented with guided movements of the table to test the resistance of the whole system. Figure 1 shows the final tests conducted in Emden with the stable platform and the radars mounted.

54 ENVIRONMENTAL SCIENCES↗

Wind Profiling With the Airborne Doppler Aerosol Wind Lidar During the 2022 Convective Processes Experiment

The 2017 Decadal Survey for Earth Science and Applications from Space (ESAS 2017) identifies a critical need for improving our understanding of Planetary Boundary Layer (PBL) processes and air-surface fluxes as well as why clouds, convection, and heavy precipitation occur when and where they do. Lidars are uniquely capable of collecting high precision and high spatio-temporal observations that have been used for atmospheric process studies from the ground, aircraft, and space. The wind lidar team at the NASA Langley Research Center (LaRC) started the development of Doppler wind lidar more than a decade ago to demonstrate technologies required for an Earth-orbiting system to globally measure wind profiles. Since then, an airborne Doppler Aerosol WiNd (DAWN) lidar system has been developed and participated in a series of field campaigns. The Doppler Aerosol WiNd (DAWN) lidar uses atmospheric aerosol motion to derive vertical profiles of horizontal wind speed and direction beneath the aircraft. In September 2022, DAWN, along with a suite of other instruments, was flown on a NASA DC-8 as part of The Convective Processes EXperiment – Cabo Verde (CPEX-CV) field campaign. A main objective of CPEX was to obtain a comprehensive set of temperature, humidity and, particularly, wind observations over tropical waters in undisturbed conditions, Saharan dust outbreaks, and in the vicinity of scattered through organized deep convection in all phases of the convective life cycle. DAWN collected data for approximately 90 hours across 13 CPEX-CV science flights. Airborne Vertical Atmospheric Profiling System (AVAPS) dropsondes were dropped throughout the flight for profiling the atmosphere and validating the DAWN instrument. DAWN had co-located data with 347 AVAPS NRD41 dropsondes, providing 32,117 vertical levels for a comprehensive validation of DAWN wind retrievals. DAWN showed very good agreement with dropsondes of ~0.2 m/s bias and ~1.8 m/s RMS. Given this agreement, DAWN is considered to be a worthy reference dataset, and its retrievals have been compared to winds derived from GOES Atmospheric Motion Vectors (AMVs), Advanced Scatterometer winds (ASCAT), and model data from GFS, GEOS, and MERRA-2 to better understand the quality of our current models and satellite wind observations. The proposed presentation will provide a brief description of the DAWN instrument, discuss the synergistic observations collected across a wide range of atmospheric conditions sampled during the CPEX-CV flights, and a summary of comparisons between DAWN, GOES AMV, ASCAT, and model analyses/predictions, with an emphasis on the PBL.

DAWN↗

Assessing the Impact of a Forest Canopy on Near-Surface Wind Statistics

Representing the forest canopy in atmospheric numerical models should improve simulated winds within and above the canopy up to a few hundred meters above the ground. Here, in this study, we implement a forest canopy parameterization into the Weather Research and Forecasting (WRF) Model in a large-eddy simulation (LES) mode by applying drag forces across multiple layers within the canopy height. We use unique observations from the Lidar Experiments for Assessing Flow over Forests (LEAFF) field campaign at the Wind River Experimental Forest (WREF) in the U.S. Pacific Northwest to evaluate model performance. In a 2-day case study, the canopy parameterization improved wind predictions both within and above the canopy, particularly during the daytime and at finer grid resolution. Without it, winds were frequently overpredicted above the canopy. Similarly, derived quantities such as the wind shear index also yielded estimates closer to observations with the canopy parameterization implemented. These findings suggest that representing the canopy using drag forces alone can improve simulated mean winds up to 200 m above the surface. Furthermore, second-order statistical moments of wind were more sensitive to canopy density than first-order moments, especially during the daytime. This increased sensitivity and the improved daytime performance in wind speed—evidenced by the lowest bias from observations (3% compared to 20% over diurnal cycle)—imply that winds above the canopy layer are strongly influenced by how well turbulence above the canopy is modeled. The results of this study can serve as a foundation for parameterizing forest canopy effects in coarser weather forecast models.

Energy - Wind↗

Studying Wind Loading on CSP Collectors to Improve Performance and Reliability

Electricity generation through Concentrating Solar-thermal Power (CSP) adds the advantage of thermal energy storage and heat production. CSP collector costs constitute nearly one-third of total plant costs. Managing wind loading, especially dynamic wind loading caused by the turbulent wind flow, is a significant design challenge. Traditional collector designs rely on wind tunnel experiments and numerical simulations, which do not fully capture dynamic effects. Here, we provide an overview of NREL's activities on wind loading on CSP collectors, aiming to improve their reliability and cost-efficiency. We present insights from field measurements at operational parabolic trough and power-tower CSP plants. Over two years, we measured turbulent wind fields and resulting structural loads in a parabolic trough plant, revealing wind, turbulence, and collector field interactions. Similar measurements are ongoing at the Crescent Dunes heliostat field. These campaigns show how atmospheric turbulence, wind direction, and collector orientation affect dynamic wind loading. Upwind collector structures can generate turbulent structures, causing fluctuating loads at downstream collectors, impacting fatigue lifetime and optical efficiency. Preliminary results indicate that interior collectors experience higher turning moments than those at the edges, suggesting higher drive wear. At Crescent Dunes, we use instrumented heliostats at the field's edge and interior to study the translation of turbulent wind to dynamic structural loads. The campaign is still ongoing, and we will present first findings. Another focus of our work is tying the experimental wind loading findings to optical performance of the collectors, using simulation tools. For example, we derive torsional errors of the parabolic troughs - the angular offset from the sun position along a collector row. This error is impacted by wind-induced mirror deformations. Future work will focus on continuing the measurement efforts and combining them with computational fluid dynamic simulations. By providing detailed field measurements and validated models, our efforts aim to enhance understanding of wind loading on CSP collectors, improving their structural integrity and optical performance.

CSP↗

Sounding-Diagnosed Convective Environments and Preliminary Energy Budgets Diagnosed during the TRMM Field Campaigns

An overview of mean convective thermodynamic and wind profiles for the Tropical Rainfall Measuring Mission (TRMM) Large Scale Biosphere-Atmosphere Experiment (LBA) and Kwajalein Experiment (KWAJEX) field campaigns will be presented, highlighting the diverse continental and marine tropical environments in which rain clouds and mesoscale convective systems evolved. An assessment of ongoing sounding quality control procedures will be shown. Additionally, we will present preliminary budgets of sensible heat source (Q1) and apparent moisture sink (Q2), which have been diagnosed from the various sounding networks.

Halverson, Jeffrey B.↗

The Bi-Modal Pattern of the Summer Circulation Over South America

Submonthly variations in warm-season (January-February) precipitation over South America, in special over the Amazon basin, central southwest Brazil, north Argentina, and Paraguay are shown to be strongly linked to variations in the moisture entering the continent from the Atlantic ocean. Two distinct regimes of lower tropospheric winds (westerlies and easterlies) were observed in Rondonia during the Wet Season Atmospheric Mesoscale Campaign (WETAMC) component of the Large Scale Atmosphere-Biosphere Experiment in Amazonia (LBA) and the Tropical Rainfall Measuring Mission (TRMM) field campaign. The westerly (easterly) winds were associated with the strong (weak) convective activity over the South Atlantic Convergence Zone (SACZ). The whole period of this study (January-February) was divided into SACZ and NSACZ (No SACZ) events. The vertically integrated moisture fluxes over the Amazon and Prata basin from the National Aeronautics and Space Administration/Goddard Data Assimilation Office (NASA/DAO) assimilation show that during SACZ (NSACZ) event strong (weak) convergence occurred over the Amazon basin with divergence (convergence) over the Prata basin. Submonthly variations in the SACZ also can be linked to extreme climate anomalies such as droughts or flooding conditions over the Amazon and Prata basin.

Herdies, Dirceu Luis↗

Loads Response That is Due to Wake Steering on a Pair of Utility-Scale Wind Turbines

The goal of this report is to present the resulting turbine loads of a full-scale wind turbine wake steering field campaign. In this experiment, wake steering controls were applied to an upwind turbine (T2) and the downwind turbine (T3) was instrumented to measure mechanical loads. The test subjects (T2 & T3) were GE 1.5SLE CWE turbines located on a wind farm with a prevailing wind direction coming from the northwest. The data collection strategy involved toggling the wake steering controls of T2 between on and off. This resulted in two databases (baseline and wake steered) with similar turbulence intensities. Valid data was extracted and processed. The analysis involved scaling data to engineering units, applying coordinate transformations where applicable, calculating 10-minutes statistics, and calculating damage equivalent loads (DELs) to assess fatigue. Figures are shown as statistics and DELs binned by wind speed with supplemental scatter plots provided in the appendices. Results between the baseline and wake steered databases were compared. Overall, the binned statistics showed minimal differences in loading between the two cases. However, the DELs of the wake steered case were observed to be consistently smaller than the baseline for most of the turbine components. A potential for future work was recognized based on the findings of this report. Some areas of further study include an analysis for more granular loads sensitivity to different yaw offset angles and rotor wake overlap, an in-depth comparison of loads between the upwind and downwind turbines, and further fatigue analysis to quantify differences observed in this experiment.

17 WIND ENERGY↗

Design of the American Wake Experiment (AWAKEN) field campaign

The American WAKE experimeNt (AWAKEN) is a multi-institutional collaborative field campaign, starting in March 2022, that will gather an unprecedented data set including both atmospheric observations and wind plant operational data. This comprehensive data set will be used to characterize the wind plant performance and turbine loading in different operational and atmospheric conditions and validate the use of different wind plant control strategies and simulation frameworks. An extensive field campaign like AWAKEN requires proper coordination and long-term planning to be successful. In this paper, we review the major activities planned during AWAKEN to provide information for current and future project partners. Specifically, we provide information about the project sites, their planned instruments, and how these will relate to the scientific objectives of the overall AWAKEN project.

17 WIND ENERGY↗

Mean state densities, temperatures and winds during the MAC/SINE and MAC/EPSILON campaigns

Two field campaigns were conducted, primarily in northern Norway, in the summer and late autumn of 1987; these yielded a total of 41 in situ temperature profiles and 67 in situ wind profiles. Simultaneously, ground-based measurements were conducted of OH temperatures and sodium lidar temperatures for 85 and 104 hours, respectively. The summer campaign's mean temperature profile exhibited major deviations from the CIRA (1986) reference atmosphere; the differences between this model and the observations are less pronounced in the autumn. Both the summer and autumn mean wind profiles were in general agreement with the CIRA model.

Luebken, F.-J.↗

LiDAR Measurements to Investigate Farm-to-Farm Interactions at the AWAKEN Experiment

The exponential growth of wind energy and the need to exploit wind resources over areas with higher energy potential have led to the construction of neighboring wind turbines and farms with relatively small separation distances. As a result, for specific wind and atmospheric conditions, the wakes generated by an upstream wind farm may affect wind resources available for a downstream wind farm resulting in detrimental impacts on energy harvesting and structural loads for the downwind wind turbines. Distances between neighboring wind farms are typically larger than those associated with intra-wind-farm wake interactions, generating cumulative wakes whose characteristics might differ from those predicted through classical engineering wake models. These phenomena are referred to as farm-to-farm interactions. A better understanding and characterization of farm-to-farm interactions is one of the science goals tackled by the ongoing American WAKE experimeNt (AWAKEN). The site under investigation for this field campaign comprises two large wind farms in northern Oklahoma, USA, which are spaced roughly 5km apart along the prevailing South-North wind direction. To investigate possible interactions between these two wind farms, the WindFluX mobile LiDAR station has been deployed mainly to perform volumetric scans over their gap region. In this paper, preliminary results from these LiDAR volumetric scans will be discussed, specifically for a case with multiple wind turbine wakes evolving during the occurrence of a low-level jet.

17 WIND ENERGY↗

Characterizing model uncertainties in simulated coast-to-offshore wind over the northeast U.S. using multi-platform measurements from the TCAP field campaign

Numerical weather prediction (NWP) models, such as the Weather Research and Forecasting (WRF) model, are widely used to provide estimates of the offshore wind energy resource owing to their large spatial coverage compared to available observations. Nevertheless, spatiotemporal distribution of model biases is highly dependent on factors including model configuration, location, and the interplay of multi-scale physical processes. Here, in this study, we focus on the characterization of model uncertainties in simulated coast-to-offshore winds over the northeast U.S., by varying sea surface temperature (SST) forcings, surface layer (SL) and planetary boundary layer (PBL) parameterizations, as well as identifying biases that may be directly passed from initial and boundary conditions. Multiple measurements, including aircraft data collected during the U.S. Department of Energy's Two-Column Aerosol Project (TCAP) experiment, are used to constrain the model results and facilitate quantitative comparisons. Our analysis indicates while SST forcing has notable impacts on simulated air temperature and moisture within PBL, the modeled winds are in general more sensitive to the choices of SL and PBL physics than to SST. The model’s forcing data not only controls the vertical dependence of wind speed errors, but also alters regional variability in wind speed’s spatial correlation. Bias comparisons between ERA5 reanalysis and ensemble simulations revealed significant similarity, particularly in wind speed biases during winter, underscoring their dependency on initial and boundary conditions. Coastal and offshore near-surface wind speed biases tend to exhibit much higher similarity in winter than in summer due to the presence of much stronger and more persistent synoptic wind conditions. This study highlights the importance of accurate atmospheric forcing and parameterization choices in improving wind forecasts and suggests the potential for extrapolating coastal wind biases to offshore locations, aiding wind energy forecasting and informing the Wind Forecast Improvement Project-3 (WFIP3).

17 WIND ENERGY↗

Double-Edge Molecular Measurement of Lidar Wind Profiles in the VALID Campaign

We have developed a transportable container based direct detection Doppler lidar based on the double-edge molecular technique. The pulsed solid state system was built at the University of Geneva. It was used to make range resolved measurements of the atmospheric wind field as part of the VALID campaign at the Observatoire de Haute Provence in Provence, France in July 1999. Comparison of our lidar wind measurements, which were analyzed without knowledge of the results of rawinsonde measurements made under the supervision of ESA, show good agreement with these rawinsondes. These are the first Doppler lidar field measurements made with an eyesafe direct detection molecular-based system at 355 nm and serve as a demonstrator for future spaceborne direct detection wind systems such as the Atmospheric Dynamics mission. Winds are an important contributor to sea surface temperature measurements made with the Tropical Rainfall Measuring Mission (TRMM) and also affect the TRMM rainfall estimates.

Korb, C. Laurence↗

Holistic scan optimization of nacelle-mounted lidars for inflow and wake characterization at the RAAW and AWAKEN field campaigns

In this article, we provide a methodological framework for designing the scanning strategies of nacelle-mounted scanning lidars for wind energy field experiments, and apply it at two major experimental field campaigns. For the Rotor Aerodynamics, Aeroelastics, and Wake project (RAAW), we leverage two scanning lidars on one turbine to characterize the incoming turbulence and the turbine wake. For the American WAKE experimeNt (AWAKEN), we use four scanning lidars on top of four turbines in a large wind power plant to investigate both individual wakes and wind-plant-scale flow features.

17 WIND ENERGY↗

Measurement of Wind Loading on Heliostats at the Crescent Dunes Power Plant: An Overview

The cost of solar collectors constitutes almost one third of the total cost of a CSP plant. One of the ongoing challenges in the design of these collectors is wind loading on mirrors, support structures, and drives. A particular challenge is dynamic wind loading, caused by the turbulent wind flow. To date, the design of solar collector structures has relied on wind tunnel experiments and numerical simulations that do not entirely capture the dynamic effects observed at scale. The CSP industry has shown increased interest in validating the idealized assumptions with measurements obtained in operational settings to improve wind load assumptions and increase reliability and cost-efficiency of the collector design. Further, performance models need realistic assumptions about wind loading and its impact on optical performance. In a parabolic trough field campaign, NREL successfully collected a wealth of long-term, high-resolution wind and loads data [2], that are publicly available and that can be used for the above-mentioned purposes. Heliostats are impacted differently by wind than parabolic troughs, due to their different shape, size, and field layout. To study the impact of wind and turbulence on heliostats, we initiated another field campaign in an operational power- tower plant, Crescent Dunes, in Nevada, USA. In this work, we present an overview of the measurements, first results, and potential implications of wind driven loads on Heliostats.

concentrated solar power↗

A High-Resolution Merged Wind Dataset for DYNAMO: Progress and Future Plans

In order to support research on optimal data assimilation methods for the Cyclone Global Navigation Satellite System (CYGNSS), launching in 2016, work has been ongoing to produce a high‐resolution merged wind dataset for the Dynamics of the Madden Julian Oscillation (DYNAMO) field campaign, which took place during late 2011/early 2012. The winds are produced by assimilating DYNAMO observations into the Weather Research and Forecasting (WRF) three‐dimensional variational (3DVAR) system. Data sources from the DYNAMO campaign include the upper‐air sounding network, radial velocities from the radar network, vector winds from the Advanced Scatterometer (ASCAT) and Oceansat‐2 Scatterometer (OSCAT) satellite instruments, the NOAA High Resolution Doppler Lidar (HRDL), and several others. In order the prep them for 3DVAR, significant additional quality control work is being done for the currently available TOGA and SMART‐R radar datasets, including automatically dealiasing radial velocities and correcting for intermittent TOGA antenna azimuth angle errors. The assimilated winds are being made available as model output fields from WRF on two separate grids with different horizontal resolutions ‐ a 3‐km grid focusing on the main DYNAMO quadrilateral (i.e., Gan Island, the R/V Revelle, the R/V Mirai, and Diego Garcia), and a 1‐km grid focusing on the Revelle. The wind dataset is focused on three separate approximately 2‐week periods during the Madden Julian Oscillation (MJO) onsets that occurred in October, November, and December 2011. Work is ongoing to convert the 10‐m surface winds from these model fields to simulated CYGNSS observations using the CYGNSS End‐To‐End Simulator (E2ES), and these simulated satellite observations are being compared to radar observations of DYNAMO precipitation systems to document the anticipated ability of CYGNSS to provide information on the relationships between surface winds and oceanic precipitation at the mesoscale level. This research will improve our understanding of the future utility of CYGNSS for documenting key MJO processes.

Lang, Timothy J.↗

Sensitivity of Near-Surface Variables in the RUC Land Surface Model in the Weather Research and Forecasting Model

In this study, we investigate the parametric sensitivity of near-surface variables, such as sensible heat flux, latent heat flux, ground heat flux, hub-height wind speed and land surface temperature, to the parameters used in the Rapid Update Cycle (RUC) land surface model (LSM) during a wintertime and summertime period. The model simulations are compared with observations collected from the second Wind Forecast Improvement Project (WFIP2) field campaign. The results suggest that parameters related to snow/ice and thermal processes can have significant impact on the simulated near-surface variables. Out of the 11 examined parameters, only 6 of them have considerable influences on the model behaviors and explain about 60 ~ 80 % of the estimated total variance of the simulated variables. In addition, the magnitude of the parametric sensitivity varies with season. For instance, parameters associated with snow/ice processes are dominant during the wintertime whereas those associated with thermal processes are more important during the summertime. Furthermore, the impact of the identified parameters on the simulated variables is highly related to the topography. There is a high degree of sensitivity to the parameter values over the slope region. This points out the importance of collecting field observations over steep areas to better quantity the appropriate values of key parameters. Overall, our findings provide a better understanding of the RUC LSM behavior associated with parameter uncertainties and can be used to improve the forecasting skill of land surface processes via calibration of the most uncertain model parameters.

17 WIND ENERGY↗

A Hybrid Bulk Algorithm to Predict Turbulent Fluxes over Dry and Wet Bare Soils

Measurements made in the Columbia River basin (Oregon) in an area of irregular terrain during the second Wind Forecast Improvement Project (WFIP2) field campaign are used to develop an optimized hybrid bulk algorithm to predict the surface turbulent fluxes from readily measured or modeled quantities over dry and wet bare or lightly vegetated soil surfaces. The hybrid (synthetic) algorithm combines (i) an aerodynamic method for turbulent flow, which is based on the transfer coefficients (drag coefficient and Stanton number), roughness lengths, and Monin–Obukhov similarity; and (ii) a modified Priestley–Taylor (P-T) algorithm with physically based ecophysiological constraints, which is essentially based on the surface energy budget (SEB) equation. Soil heat flux in the latter case was estimated from measurements of soil temperature and soil moisture. In the framework of the hybrid algorithm, bulk estimates of the momentum flux and the sensible heat flux are derived from a traditional aerodynamic approach, whereas the latent heat flux (or moisture flux) is evaluated from a modified P-T model. Direct measurements of the surface fluxes (turbulent and radiative) and other ancillary atmospheric/soil parameters made during WFIP2 for different soil conditions (dry and wet) are used to optimize and tune the hybrid bulk algorithm. The bulk flux estimates are validated against the measured eddy-covariance fluxes. We also discuss the SEB closure over dry and wet surfaces at various time scales based on the modeled and measured fluxes. Although this bulk flux algorithm is optimized for the data collected during the WFIP2, a hybrid approach can be used for similar flux-tower sites and field campaigns.

54 ENVIRONMENTAL SCIENCES↗