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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

The Multi-Dimensional Nature of Wind Shear Investigations

The impact of air carrier accidents has lead to investigations into the wind shear phenomenon. This report includes such topics as wind shear characterization, aircraft pilot performance in shear conditions, terminology and language development, wind shear forecasting, ground and flight wind shear displays, wind shear data collection and dissemination, and pilot factors associated with wind shear encounters. Some areas which show promise for short term solutions to the wind shear hazards includes: (1) improved gust front warning through ground based sensors; (2) greater pilot awareness of wind shear through improved training; and (3) airborne displays based on groundspeed/airspeed comparisons.

Cox, W. J.↗
NASA NTRS1984

Observing system simulation experiments related to space-borne Lidar wind profiling. Part 1: Forecast impacts of highly idealized observing systems

Simulation experiments comparing the relative importance of an idealized LIDAR wind profiling system with idealized temperature and pressure sounding systems on 12 h forecasts are studied for three "nature' fields representing the true evolving atmospheric states. The three fields are obtained respectively from: (1) a long integration of the GLAS 4th Order Model (4 deg lat x 5 deg lon x 9 levels), (2) a continuous sequence of NMC operational analysis and, (3) a long integration of the ECMWF high resolution (1.875 deg 1 lat x 1.875 deg lon x 15 layers) operational forecast model. These fields are interpolated to the grid of the GLAS model and used for simulating the observed global analysed fields of winds, temperature, moisture and surface pressure. The same interpolated fields are also used for verification of forecast impact. The effects of clouds, aerosol concentrations, and instrument accuracies on the simulated observation will be discussed.

Halem, M.↗
NASA NTRS2019

Forecasting the Ambient Solar Wind with Numerical Models. I. On the Implementation of an Operational Framework

The ambient solar wind conditions in interplanetary space and in the near-Earth environment are determined by activity on the Sun. Steady solar wind streams modulate the propagation behavior of interplanetary coronal mass ejections and are themselves an important driver of recurrent geomagnetic storm activity. The knowledge of the ambient solar wind flows and fields is thus an essential component of successful space weather forecasting. Here, we present an implementation of an operational framework for operating, validating, and optimizing models of the ambient solar wind flow on the example of Carrington Rotation 2077. We reconstruct the global topology of the coronal magnetic field using the potential field source surface model (PFSS) and the Schatten current sheet model (SCS) and discuss three empirical relationships for specifying the solar wind conditions near the Sun, namely the Wang–Sheeley (WS) model, the distance from the coronal hole boundary model (DCHB), and the Wang-Sheeley–Arge (WSA) model. By adding uncertainty in the latitude about the sub-Earth point, we select an ensemble of initial conditions and map the solutions to Earth by the Heliospheric Upwind eXtrapolation (HUX) model. We assess the forecasting performance from a continuous variable validation and find that the WSA model most accurately predicts the solar wind speed time series (RMSE≈83 km/s). We note that the process of ensemble forecasting slightly improves the forecasting performance of all solar wind models investigated. We conclude that the implemented framework is well suited for studying the relationship between coronal magnetic fields and the properties of the ambient solar wind flow in the near-Earth environment.

Reiss, Martin A.↗
NASA NTRS1986

Aspects of the determination of winds by means of scatterometry and of the utilization of vector wind data for meteorological forecasts

The present paper provides a description of four aspects of scatterometer winds and their uses. The theory of wave generation by the wind is considered along with an analysis of the properties of superobservations, and studies of intermittent versus continuous data assimilation methods for numerical weather predictions which use remotely sensed data. A comparison of the sum of squares versus the maximum likelihood method for recovering the vector winds is also conducted. Questions regarding wind speed, friction velocity, or normal stress are discussed and synoptic scale fields from Seasat-SASS data are examined.

Pierson, W. J., Jr.↗
DOE OSTI2018

Stochastic simulation of predictive space–time scenarios of wind speed using observations and physical model outputs

We propose a statistical space-time model for predicting atmospheric wind speed based on deterministic numerical weather predictions and historical measurements. We consider a Gaussian multivariate space-time framework that combines multiple sources of past physical model outputs and measurements in order to produce a probabilistic wind speed forecast within the prediction window. We illustrate this strategy on wind speed forecasts during several months in 2012 for a region near the Great Lakes in the United States. The results show that the prediction is improved in the mean-squared sense relative to the numerical forecasts as well as in probabilistic scores. Moreover, the samples are shown to produce realistic wind scenarios based on sample spectra and space-time correlation structure.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 3

The impact of more timely and accurate weather data on airline flight planning with the emphasis on fuel savings is studied. This volume of the report discusses the results of Task 3 of the four major tasks included in the study. Task 3 compares flight plans developed on the Suitland forecast with actual data observed by the aircraft (and averaged over 10 degree segments). The results show that the average difference between the forecast and observed wind speed is 9 kts. without considering direction, and the average difference in the component of the forecast wind parallel to the direction of the observed wind is 13 kts. - both indicating that the Suitland forecast underestimates the wind speeds. The Root Mean Square (RMS) vector error is 30.1 kts. The average absolute difference in direction between the forecast and observed wind is 26 degrees and the temperature difference is 3 degree Centigrade. These results indicate that the forecast model as well as the verifying analysis used to develop comparison flight plans in Tasks 1 and 2 is a limiting factor and that the average potential fuel savings or penalty are up to 3.6 percent depending on the direction of flight.

Keitz, J. F.↗
NASA NTRS1984

The impact of scatterometer wind data on global weather forecasting

The impact of SEASAT-A scatterometer (SASS) winds on coarse resolution atmospheric model forecasts was assessed. The scatterometer provides high resolution winds, but each wind can have up to four possible directions. One wind direction is correct; the remainder are ambiguous or "aliases'. In general, the effect of objectively dealiased-SASS data was found to be negligible in the Northern Hemisphere. In the Southern Hemisphere, the impact was larger and primarily beneficial when vertical temperature profile radiometer (VTPR) data was excluded. However, the inclusion of VTPR data eliminates the positive impact, indicating some redundancy between the two data sets.

Atlas, D.↗
DOE OSTI2017

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. Our paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind–downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.

17 WIND ENERGY↗
DOE OSTI2019

High-Resolution Regional Wave Hindcast for Hawaii

This report summarizes modeling efforts for hindcasting of wave climate within the exclusive economic zone (EEZ) around the state of Hawaii. Specifically, the report provides detailed description of model mesh development, sensitivity analysis of the configuration of model parameters, data used for model forcing and validation, model skill assessment, and model outputs for resource characterization. The unstructured, nested-grid modeling approach incorporates a regional high-resolution SWAN (Simulating WAves Nearshore) model within the global-regional WAVEWATCH III® (WW3) wave model. The models were configured to comply with the International Electrotechnical Commission (IEC) Technical Standards for wave energy resource characterization. The SWAN model domain covers the entire EEZ with a spatial resolution of approximately 300 m in the nearshore region. Two levels of WW3 nested grids, from 0.5 arc-degree at global to 7.5 arc-minute at regional scale, were used to provide boundary conditions that drive the high-resolution nearshore SWAN model. The WW3 and SWAN models were forced by 0.5 arc-degree Climate Forecast System Reanalysis wind and 5 km regional Weather Research and Forecasting wind, respectively. Wave resource and bulk wave parameters were simulated for a 32-year period from 1979 to 2010, and were subsequently validated using wave buoy data within the model domain. Model performance was evaluated using a set of error statistics. Overall, the model shows good skills in reproducing the wave climate in the Hawaii EEZ in both spatial and temporal domains. Comparisons of time series and scatter plots for the six IEC resource parameters and the associated error statistics tables, and horizontal two-dimensional plots of annually averaged and monthly averaged IEC parameters are provided.

16 TIDAL AND WAVE POWER↗
DOE OSTI2018

Generating wind power scenarios for probabilistic ramp event prediction using multivariate statistical post-processing

Wind power forecasting is gaining international significance as more regions promote policies to increase the use of renewable energy. Wind ramps, large variations in wind power production during a period of minutes to hours, challenge utilities and electrical balancing authorities. A sudden decrease in wind-energy production must be balanced by other power generators to meet energy demands, while a sharp increase in unexpected production results in excess power that may not be used in the power grid, leading to a loss of potential profits. In this study, we compare different methods to generate probabilistic ramp forecasts from the High Resolution Rapid Refresh (HRRR) numerical weather prediction model with up to 12h of lead time at two tall-tower locations in the United States. We validate model performance using 21 months of 80m wind speed observations from towers in Boulder, Colorado, and near the Columbia River gorge in eastern Oregon. We employ four statistical post-processing methods, three of which are not currently used in the literature for wind forecasting. These procedures correct biases in the model and generate short-term wind speed scenarios which are then converted to power scenarios. This probabilistic enhancement of HRRR point forecasts provides valuable uncertainty information of ramp events and improves the skill of predicting ramp events over the raw forecasts. We compute Brier skill scores for each method with regard to predicting up- and down-ramps to determine which method provides the best prediction. We find that the Standard Schaake shuffle method yields the highest skill at predicting ramp events for these datasets, especially for up-ramp events at the Oregon site. Increased skill for ramp prediction is limited at the Boulder, CO, site using any of the multivariate methods because of the poor initial forecasts in this area of complex terrain. These statistical methods can be implemented by wind farm operators to generate a range of possible wind speed and power scenarios to aid and optimize decisions before ramp events occur.

17 WIND ENERGY↗
NASA NTRS2010

Tool for Forecasting Cool-Season Peak Winds Across Kennedy Space Center and Cape Canaveral Air Force Station (CCAFS)

Peak wind speed is important element in 24-Hour and Weekly Planning Forecasts issued by 45th Weather Squadron (45 WS). Forecasts issued for planning operations at KSC/CCAFS. 45 WS wind advisories issued for wind gusts greater than or equal to 25 kt. 35 kt and 50 kt from surface to 300 ft. AMU developed cool-season (Oct - Apr) tool to help 45 WS forecast: daily peak wind speed, 5-minute average speed at time of peak wind, and probability peak speed greater than or equal to 25 kt, 35 kt, 50 kt. AMU tool also forecasts daily average wind speed from 30 ft to 60 ft. Phase I and II tools delivered as a Microsoft Excel graphical user interface (GUI). Phase II tool also delivered as Meteorological Interactive Data Display System (MIDDS) GUI. Phase I and II forecast methods were compared to climatology, 45 WS wind advisories and North American Mesoscale model (MesoNAM) forecasts in a verification data set.

Barrett, Joe H., III↗
NASA NTRS2008

Forecasting Cool Season Daily Peak Winds at Kennedy Space Center and Cape Canaveral Air Force Station

The expected peak wind speed for the day is an important element in the daily 24-Hour and Weekly Planning Forecasts issued by the 45th Weather Squadron (45 WS) for planning operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The morning outlook for peak speeds also begins the warning decision process for gusts ^ 35 kt, ^ 50 kt, and ^ 60 kt from the surface to 300 ft. The 45 WS forecasters have indicated that peak wind speeds are a challenging parameter to forecast during the cool season (October-April). The 45 WS requested that the Applied Meteorology Unit (AMU) develop a tool to help them forecast the speed and timing of the daily peak and average wind, from the surface to 300 ft on KSC/CCAFS during the cool season. The tool must only use data available by 1200 UTC to support the issue time of the Planning Forecasts. Based on observations from the KSC/CCAFS wind tower network, surface observations from the Shuttle Landing Facility (SLF), and CCAFS upper-air soundings from the cool season months of October 2002 to February 2007, the AMU created multiple linear regression equations to predict the timing and speed of the daily peak wind speed, as well as the background average wind speed. Several possible predictors were evaluated, including persistence, the temperature inversion depth, strength, and wind speed at the top of the inversion, wind gust factor (ratio of peak wind speed to average wind speed), synoptic weather pattern, occurrence of precipitation at the SLF, and strongest wind in the lowest 3000 ft, 4000 ft, or 5000 ft. Six synoptic patterns were identified: 1) surface high near or over FL, 2) surface high north or east of FL, 3) surface high south or west of FL, 4) surface front approaching FL, 5) surface front across central FL, and 6) surface front across south FL. The following six predictors were selected: 1) inversion depth, 2) inversion strength, 3) wind gust factor, 4) synoptic weather pattern, 5) occurrence of precipitation at the SLF, and 6) strongest wind in the lowest 3000 ft. The forecast tool was developed as a graphical user interface with Microsoft Excel to help the forecaster enter the variables, and run the appropriate regression equations. Based on the forecaster's input and regression equations, a forecast of the day's peak and average wind is generated and displayed. The application also outputs the probability that the peak wind speed will be ^ 35 kt, 50 kt, and 60 kt.

Barrett, Joe, III↗
NASA NTRS1975

Application of monochromatic ocean wave forecasts to prediction of wave-induced currents

The use of monochromatic wind-wave forecasts in prediction of wind-wave-induced currents was assessed. Currents were computed for selected combinations of wind conditions by using a spectrum approach which was developed by using the Bretschneider wave spectrum for partially developed wind seas. These currents were compared with currents computed by using the significant and average monochromatic wave parameters related to the Bretschneider spectrum. Results indicate that forecasts of significant wave parameters can be used to predict surface wind-wave-induced currents. Conversion of these parameters to average wave parameters can furnish reasonable estimates of subsurface current values.

Poole, L. R.↗
DOE OSTI2022

Expert perspectives on the wind plant of the future

Abstract Wind power technology has changed rapidly in recent years. Technology innovation, evolving power markets, and competing land and ocean uses continue to influence the design and operation of wind turbines and plants. Anticipating these trends and their impact on future facilities can inform commercial strategies and research priorities. Drawing from a recent survey of 140 of the world's foremost wind experts, we identify expectations of future wind plant design in 2035, both for onshore and offshore wind. Experts anticipate continued growth in turbine size, to 5.5 (onshore) and 17 MW (offshore), with plants located in increasingly less favorable wind and siting regimes. They expect plant sizes of 1,100 MW for fixed‐bottom and 600 MW for floating offshore wind. Experts forecast enhanced grid‐system value from wind through significant to widespread use of larger rotors, hybrid projects with batteries and hydrogen production, and more. To explain experts' perspectives on future plant design and operation, we identify five mechanisms: economies of unit, plant, and resource scale; grid‐system value economies; and production efficiencies. We characterize learning effects as a moderating influence on the strength of these mechanisms. In combination, experts predict that these design choices support levelized cost of energy reductions of 27% (onshore) and 17%–35% (floating and fixed‐bottom offshore) by 2035 compared to today, while enhancing wind energy's grid service offerings. Our findings provide a much‐needed benchmark for representing future wind technologies in power sector models and address a critical research gap by explaining the economics behind wind energy design choices.

17 WIND ENERGY↗
NASA NTRS2009

Simulation of the Impact of New Aircraft- and Satellite-Based Ocean Surface Wind Measurements on H*Wind Analyses and Numerical Forecasts

The Hurricane Imaging Radiometer (HIRAD) is a new airborne microwave remote sensor for hurricane observations that is currently under development by NASA Marshall Space Flight Center, NOAA Hurricane Research Division, the University of Central Florida and the University of Michigan. HIRAD is being designed to enhance the realtime airborne ocean surface winds observation capabilities of NOAA and USAF Weather Squadron hurricane hunter aircraft using the operational airborne Stepped Frequency Microwave Radiometer (SFMR). Unlike SFMR, which measures wind speed and rain rate along the ground track directly beneath the aircraft, HIRAD will provide images of the surface wind and rain field over a wide swath (~ 3 x the aircraft altitude). The present paper describes a set of Observing System Simulation Experiments (OSSEs) in which measurements from the new instrument as well as those from existing instruments (air, surface, and space-based) are simulated from the output of a detailed numerical model, and those results are used to construct H*Wind analyses. The H*Wind analysis, a product of the Hurricane Research Division of NOAA s Atlantic Oceanographic and Meteorological Laboratory, brings together wind measurements from a variety of observation platforms into an objective analysis of the distribution of wind speeds in a tropical cyclone. This product is designed to improve understanding of the extent and strength of the wind field, and to improve the assessment of hurricane intensity. See http://www.aoml.noaa.gov/hrd/data_sub/wind.html. Evaluations will be presented on the impact of the HIRAD instrument on H*Wind analyses, both in terms of adding it to the full suite of current measurements, as well as using it to replace instrument(s) that may not be functioning at the future time the HIRAD instrument is implemented. Also shown will be preliminary results of numerical weather prediction OSSEs in which the impact of the addition of HIRAD observations to the initial state on numerical forecasts of the hurricane intensity and structure is assessed.

Miller, Timothy↗
NASA NTRS2010

Simulation of the Impact of New Aircraft-and Satellite-based Ocean Surface Wind Measurements on Wind Analyses and Numerical Forecasts

The Hurricane Imaging Radiometer (HIRAD) is a new airborne microwave remote sensor for hurricane observations that is currently under development by NASA Marshall Space Flight Center, NOAA Hurricane Research Division, the University of Central Florida and the University of Michigan. HIRAD is being designed to enhance the realtime airborne ocean surface winds observation capabilities of NOAA and USAF Weather Squadron hurricane hunter aircraft currently using the operational airborne Stepped Frequency Microwave Radiometer (SFMR). Unlike SFMR, which measures wind speed and rain rate along the ground track directly beneath the aircraft, HIRAD will provide images of the surface wind and rain field over a wide swath (approx. 3 x the aircraft altitude). The present paper describes a set of Observing System Simulation Experiments (OSSEs) in which measurements from the new instrument as well as those from existing instruments (air, surface, and space-based) are simulated from the output of a detailed numerical model, and those results are used to construct H*Wind analyses, a product of the Hurricane Research Division of NOAA s Atlantic Oceanographic and Meteorological Laboratory. Evaluations will be presented on the impact of the HIRAD instrument on H*Wind analyses, both in terms of adding it to the full suite of current measurements, as well as using it to replace instrument(s) that may not be functioning at the future time the HIRAD instrument is implemented. Also shown will be preliminary results of numerical weather prediction OSSEs in which the impact of the addition of HIRAD observations to the initial state on numerical forecasts of the hurricane intensity and structure is assessed.

Miller, TImothy↗