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This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.
WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars and anemometers during the AWAKEN campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include uncertainty estimates, offering reproducible methods for atmospheric research, model validation, and wind energy studies.
WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars and anemometers during the AWAKEN campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include uncertainty estimates, offering reproducible methods for atmospheric research, model validation, and wind energy studies.
WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars and anemometers during the AWAKEN campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include uncertainty estimates, offering reproducible methods for atmospheric research, model validation, and wind energy studies.
These files contain 24 hour periods of data collected from the CLAMPS1 Halo Streamline XR Doppler lidar. The Doppler lidar conducts regular conical scans at a set elevation angle. These data are then passed through a typical VAD algorithm to retrieve horizontal wind speed and direction profiles. These data were collected during the TRACER project. For the TRACER campaign, the CLAMPS1 Doppler lidar collected PPI scans at 70 deg elevation every 20 minutes.
WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars, wind profiling radars, and sonic anemometers across Northeast U.S. coastal/offshore sites during the WFIP3 campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include comprehensive uncertainty estimates. The Nantucket dataset covers February 2024–September 2025, offering reproducible methods for atmospheric research, model validation, and wind energy studies.
WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars, wind profiling radars, and sonic anemometers across Northeast U.S. coastal/offshore sites during the WFIP3 campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include comprehensive uncertainty estimates. The Block Island dataset covers February 2024–September 2025, offering reproducible methods for atmospheric research, model validation, and wind energy studies.
The purpose of this study was to collect and distribute ground-truth soil water content and meteorological data in the Houston, TX, area, supporting the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility, and the 2022 field campaign for the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). The files herein contain soil water content and meteorological data for three stations that the Bureau of Economic Geology at UT Austin installed in the Houston, TX, area during the period of performance. The data includes soil moisture, volumetric water content, electrical conductivity of soil, soil temperature, rain precipitation, air temperature and other parameters. Data files within this data set contain measurements at both sub-hourly and 1-hour resolution measurements. The sub-hourly meteorological data file names end with “TRACER_SubHourly_met.dat”, and the sub-hourly soil data files end with “TRACER_SubHourly_soil.dat”. For the 1-hour resolution data, the files ending with "_Soil_flagged.dat” contain mean hourly volumetric soil water content and temperature measured at 5, 10, 20 and 50 cm depths. The files ending with “_Meteoro_flagged.dat” contain mean hourly measured precipitation, air temperature and humidity, wind speed and direction, and solar radiation. All data have undergone QA/QC procedures that are described by Caldwell et al. (2019) and Dorigo et al. (2013) for the soil-specific data, and EPA (2008) for the meteorological data.
The Renewable Energy Wildlife Institute lead a team of scientists, wind developers, and turbine manufacturers in a study to develop and test a “smart curtailment” system intended to help reduce bat collisions with wind turbines. The Vestas Bat Protection System (VBPS) is a newly developed software module within the Supervisory Control and Data Acquisition (SCADA) system of Vestas turbines. The VBPS combines data from commercially available environmental sensors and the turbine’s built-in sensors with the Vestas SCADA system. VBPS is designed to receive environmental data from sensors on the turbine such as temperature, wind speed, wind direction, time of day, and time of year, relays that information to the SCADA system to determine whether to execute turbine curtailments at any given time. The goals of this study were to 1) develop a bat fatality risk model based on bat activity data and environmental data collected in year 1, and to 2) evaluate the VBPS, using the bat fatality risk model to implement curtailment, in comparison to “blanket curtailment” (turbines curtailed when wind speed is below 5.0 meters per second (m/s)) and “control” (normally operating, feathered below 3.0 m/s) turbines in year 2. The field study took place at a wind energy facility in Iowa during the fall bat migration seasons (July – October) in 2021 and 2022. For VBPS to succeed as a viable strategy for the minimization of bat fatalities, it should meet or exceed the performance of blanket curtailment. Specifically, the VBPS should meet the following performance targets to demonstrate whether it an effective, practical risk reduction measure: (1) Turbines operating VBPS should have equal or fewer bat fatalities compared to turbines operating with blanket curtailment, and significantly fewer bat fatalities compared to control turbines; and (2) Turbines operating VBPS should have greater power production compared to turbines operating with blanket curtailment. The study was completed in accordance with the Statement of Project Objectives and within the terms of the Budget Justification. This Final Report describes the progress, challenges, and outcomes of the study.
Surface meteorological data (3m wind speed, wind direction, 2m air temperature, relative humidity, pressure, downwelling irradiance, total rainfall) gathered on the Sequim-PNNL campus ('upstairs'). Equipment is manufactured and calibrated by Campbell Scientific. Placement and height of sensors follows recommended guidelines of the NWS.
Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.
Much like their counterparts in utility-scale wind energy, developers of industrial, small-scale and distributed wind turbine deployments need to understand and accurately characterize the wind resource to properly assess the power generation and financial ramifications during siting and planning. National Renewable Energy Laboratory’s WIND (Wind Integration National Dataset) Toolkit (WTK) provides a best-in-class wind resource dataset generated using the Weather Research and Forecasting (WRF) model. This dataset includes parameters such as the wind speed, wind direction, and temperature at various heights, plus atmospheric stability near the surface. This data is available at 2-km spatial resolution and five-minute temporal resolution across 7 years, from 2007 to 2013 through a publicly accessible API interface. The Tools Assessing Performance (TAP) project seeks to extend this dataset to allow long term resource estimates and leverage it to better equip distributed wind equipment manufacturers, owner-operators, and installation professionals with better tools for practical siting applications. In this report, we present the results from our investigation within the TAP project focused on characterization of bias in WTK-based wind speed estimates and evaluation of vertical and horizontal interpolation techniques. We discuss the tradeoffs between different techniques and their combinations, as well as describe the lower bounds we determine for the studied validation errors. While the specific estimates we present are specific to WTK and the validation dataset we have chosen for this investigation (NREL's Wind Resource Meteorological Database), the overall analysis and the studied techniques are general enough to be applied to a broader set of wind datasets, both simulation-based and observational.
Desert Research Institute (DRI) conducted a field assessment of the potential for contaminated soil to be transported from the Smoky Site Contamination Area (CA) because of storm runoff. This activity supported U.S. Department of Energy (DOE) Environmental Management Nevada Program (EM NV) efforts to establish post-closure monitoring plans for the Smoky Site Soils Corrective Action Unit (CAU) 550. The work was intended to confirm the likely mechanism of transport and determine the meteorological conditions that might cause the movement of contaminated soils, as well as determine the particle size fraction most closely associated with transported radionuclide-contaminated soils. These data will facilitate the design of the appropriate post-closure monitoring program. In 2011, DRI installed a meteorological monitoring station on the west side of the Smoky Site CA and a hydrologic (runoff) monitoring station within the CA, near the east side. The meteorological station collected air temperature, wind speed, wind direction, relative humidity, precipitation, solar radiation, barometric pressure, soil temperature, and soil water content data. The maximum, minimum, and average or total values (as appropriate) for each of these parameters were recorded for each 10-minute interval. The maximum, minimum, and average water depth in the flume installed at the hydrologic station were also recorded for each 10-minute interval. This report presents the data collected from these stations during fiscal year (FY) 2019. During the FY2019 reporting period, the warmest months were June, July, and August and the coldest were December and February. The highest monthly solar radiation (i.e., sunshine) values were recorded in June, July, and August, whereas December through February had the lowest solar radiation values. Monthly mean wind speeds were highest in the spring (April) and early summer (June). Winds were predominantly from the north, except in February, July, August, and September when winds were mostly from the west. The monthly average relative humidity ranged from 17 percent to approximately 60 percent. Humidity was lowest in the summer and highest in the winter. Monthly total precipitation ranged from 0.0 during August and September to 2.22 inches (in) (56.39 millimeters [mm]) in February. Total precipitation for FY2019 was 7.83 in (198.88 mm). During the reporting period, a single, nonzero, flow event was recorded at the flume. This occurred over two days between March 6 and 7, 2019, in response to 1.16 in (29.46 mm) of precipitation falling within 9.3 hours on March 6, 2019. This event produced a peak water depth of 0.39 in (0.99 centimeters [cm]) in the flume, and runoff was measured for approximately 23.5 hours. However, the maximum recorded flow depth was less than the limit for flow discharge and velocity that can be calculated for the six-inch (15 cm) throat of a Parshall flume. The runoff event produced insufficient flow velocities through the natural channel to cause local erosion and transport of bedload materials. No bedload samples were collected for radiological analysis. Observing meteorological and environmental conditions that lead to storm runoff will help identify the parameters and threshold conditions that should be incorporated into post-closure monitoring plans for this and similar Soils CAU sites. Routine monitoring of meteorological and hydrologic parameters at the Smoky Site CA has been discontinued at the request of EM NV, effective at the conclusion of FY2019. Environmental data acquisition was completed and the meteorological and runoff monitoring stations were removed from the Smoky Site on October 15, 2019.