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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10

Gap Flows Along the Columbia River Observed During the WFIP2 Field Campaign

Data collected in the Columbia River Gorge and Basin Area during the second Wind Forecasting Improvement Project (WFIP2) was used to study gap flow events in the region. In particular, the relationship between 200 m zonal wind speed and the zonal mesoscale pressure gradient at Troutdale (West of the gorge), Wasco (east of the gorge), and Boardman (farther east of the gorge) sites was examined. An objective criterion was used to identify 169 (Troutdale), 161 (Wasco), and 113 (Boardman) gap flow days that had weak synoptic forcing. The 200 m zonal wind speed exhibited a linear relationship with the zonal pressure gradient at Wasco during both easterly and westerly gap flow days at daily timescales. Such a relationship was only observed during easterly gap flow days at Troutdale and was not observed at Boardman. The zonal wind speed exhibited a diurnal cycle at Wasco and Boardman, with greater changes in the nighttime winds than the daytime winds due to changes in pressure gradient. The root mean square differences (RMSDs) between the observed pressure gradient at Wasco and that simulated by the High Resolution Rapid Refresh (HRRR) model in 3 km (HRRR-3km) and 750 m (HRRR-750m) horizontal resolution were 3.14 hPa and 0.57 hPa, respectively. However, the RMSDs for the 200 m zonal wind speed were 1.40 m s -1 for HRRR-3km and 1.20 m s -1 for HRRR- 750m. Improvement in simulating the zonal pressure gradient accompanied by negligible changes in simulating zonal wind speed due to higher horizontal resolution points to a complex interplay between different components of the model physics when simulating the meteorology. The HRRR-750m resolution model accurately mimicked the observed covariability (phase diagram) between the zonal pressure gradient and the 200 m zonal wind speed during the nighttime, but not during the daytime, suggesting model errors might be related to the representation of boundary layer processes.

54 ENVIRONMENTAL SCIENCES↗

Use of Acoustic Wind Profilers for Uninhabited Aerial Vehicle Flight Test Activities

Sonic detection and ranging (SODAR) systems provide crucial information to meteorologists for advising uninhabited aerial vehicle (UAV) flight crews and mission directors on historical, current, and forecasted wind and turbulence conditions. The SODAR system provided advanced warning of increasing surface winds for an X-38 flight on February 6, 1999. The SODAR system has also provided important postflight data for X-38 engineers to review the performance of the parafoil in the presence of strong wind shears near the surface at landing.

Donnohue, Casey J.↗

Enabling Pinpoint Landing (PPL) on Mars

Pinpoint landing (PPL) missions will deliver about 1000 kg of useful payload to the surface of Mars. Mid-to-high latitude landing site compatibility is sought which should provide the means to land at sites up to 2.5 km above Mars mean surface altitude. A dispersion and control analysis process is presented which helps to identify the effects of PPL error drivers, quantify the effect of dispersions on landing error and quantify the landing position control capability/authority along the entry path. An entry/descent/landing (EDL) profile is provided. Guided aeroshell is the baseline for all candidate Mars atmospheric entry architectures. A two-stage architecture is considered for the aerodynamic decelerator descent phase: supersonic parachute plus guided subsonic parachute or high-Mach inflatable decelerator plus guided subsonic parachute. The powered descent phase uses propulsive descent stage for soft landing and final error reduction maneuvers. Studies have found that the aeroshell entry face dispersions can be large, but closed-loop guidance can null out resulting errors to within about 2 km. Additionally, projected parachute control is inadequate to correct worst case dispersions without wind forecast data. To mitigate the problems dispersions due to atmospheric uncertainty can be reduced by providing on-board external means to measure density and winds ahead of the vehicle, higher L/D control authority options for the subsonic parachute phase can be investigated, and decelerators with control authority options for the supersonic descent phase can be examined. A navigation error analysis and wind effects summary are included.

aerodynamic↗

A total of 19 months of daily weather logging on the US east coast: the WFIP3 event log

The Third Wind Forecast Improvement Project (WFIP3) is a multi-institutional field campaign designed to advance the understanding and prediction of the offshore atmospheric boundary layer along the US east coast. Extending from February 2024 through August 2025, WFIP3 combines long-term coastal and offshore measurements with targeted modeling and forecasting efforts. This data paper presents the WFIP3 event log, a curated record of 578 d of meteorological phenomena and field observations that complements the campaign's extensive high-frequency datasets. The event log provides both manually documented daily weather discussions and automatically derived indicators of atmospheric processes – including low-level jets, wind ramps, extreme wind veer, and weak wind conditions – based on observations from scanning lidars deployed at three coastal and offshore sites. The dataset offers structured metadata, standardized time and site identifiers, and consistent terminology to facilitate its integration with WFIP3's observational and modeling data products. The log supports diverse applications, from model evaluation and forecast verification to the selection of case studies on offshore boundary-layer dynamics. The WFIP3 event log is publicly available through the US Department of Energy's Wind Data Hub, providing the research community with a transparent and enduring contextual reference for the interpretation and use of WFIP3 measurements.

17 WIND ENERGY↗

Characterization of turbulence under different stability conditions using lidar scanning data

The spatiotemporal scales of turbulence in the boundary layer flow vary with the static stability of the atmosphere. For example, turbulence structures in unstable conditions are often found to be large and coherent, whereas the turbulent structures in stable conditions are relatively small and sporadic. To better understand the behavior of such turbulent structures under different atmospheric stability conditions in the lower atmosphere, herein, we use scanning lidar data collected over several months during the US Department of Energy's second Wind Forecast Improvement Project (WFIP 2) in 2016. The radial velocity data from scanning lidar were gathered along the horizontal plane (PPI mode) and were analyzed using proper orthogonal decomposition (POD) and spectral energy methods. The results from these analyses show that the turbulent structures in daytime unstable conditions are different from those present during nighttime stable conditions in terms of amount of energy and coherent structures. The POD energy is distributed more evenly in all the higher spatial modes in the daytime unstable case compared to the nighttime stable case. Besides characterizing the turbulence in the flow, the lidar data were also used to compare the simulated flow field generated from the WRF-LES framework (Weather Research and Forecasting - large-eddy simulation) with the scanning lidar data. The results from both simulated and lidar scanned data show similar structures orienting the streak-like structure along the mean wind. This indicates that the streak-like structures can exist in the real atmosphere during unstable atmospheric condition cases.

Rai, Raj K.↗

Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators: Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators

Forecasts of available wind power are critical in key electric power systems operations planning problems, including economic dispatch and unit commitment. Such forecasts are necessarily uncertain, limiting the reliability and cost effectiveness of operations planning models based on a single deterministic or “point” forecast. A common approach to address this limitation involves the use of a number of probabilistic scenarios, each specifying a possible trajectory of wind power production, with associated probability. We present and analyze a novel method for generating probabilistic wind power scenarios, leveraging available historical information in the form of forecasted and corresponding observed wind power time series. We estimate non-parametric forecast error densities, specifically using epi-spline basis functions, allowing us to capture the skewed and non-parametric nature of error densities observed in real-world data. We then describe a method to generate probabilistic scenarios from these basis functions that allows users to control for the degree to which extreme errors are captured.We compare the performance of our approach to the current state-of-the-art considering publicly available data associated with the Bonneville Power Administration, analyzing aggregate production of a number of wind farms over a large geographic region. Finally, we discuss the advantages of our approach in the context of specific power systems operations planning problems: stochastic unit commitment and economic dispatch. Here, our methodology is embodied in the joint Sandia – University of California Davis Prescient software package for assessing and analyzing stochastic operations strategies.

17 WIND ENERGY↗