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Estimates of solar wind speed obtained by Armstrong et al. [1986] based on 1983 VLA multiple-station intensity scintillation measurements inside 12 R(sub)O have been compared with white light coronagraph measurements.
In an effort to estimate the highest flow velocity that the solar wind has exhibited at earth during the past 50 years, geomagnetic storms that occurred from 1938 to 1989 were surveyed, and the storms that were preceded by a major proton flare were selected. For each identified flare-storm pair, the average speed ('transit speed') of the associated interplanetary shock from the interval between the flare onset and the sudden commencement of the geomagnetic storm was calculated. In each case, the maximum solar wind flow speed was inferred from an empirical relationship (derived for a sample of recent events) between the shock transit speed and the peak flow velocity of the associated transient stream, obtaining a distribution of maximum solar wind speeds, which presumably corresponds to a sample of the most energetic events of this 50-yr period. Results show no evidence for bulk flow velocities greater than the about 2000 km/sec value deduced by Zastenker et al. (1978) and Grunwaldt (1975) for the August 4, 1972 event.
The values of the Normalized Radar Backscattering Cross Section (NRCS), sigma (o), obtained by a scatterometer are random variables whose variance is a known function of the expected value. The probability density function can be obtained from the normal distribution. Models for the expected value obtain it as a function of the properties of the waves on the ocean and the winds that generated the waves. Point estimates of the expected value were found from various statistics given the parameters that define the probability density function for each value. Random intervals were derived with a preassigned probability of containing that value. A statistical test to determine whether or not successive values of sigma (o) are truly independent was derived. The maximum likelihood estimates for wind speed and direction were found, given a model for backscatter as a function of the properties of the waves on the ocean. These estimates are biased as a result of the terms in the equation that involve natural logarithms, and calculations of the point estimates of the maximum likelihood values are used to show that the contributions of the logarithmic terms are negligible and that the terms can be omitted.
The second Wind Forecast Improvement Project (WFIP2) was a public-private partnership funded by the U.S. Department of Energy and NOAA, aimed at enhancing the forecast skill of numerical weather prediction models for turbine-height winds in regions with complex terrain. An 18-month Weather Research and Forecasting (WRF) model simulation was conducted over the Pacific Northwest, with model outputs validated against observational data collected during WFIP2. Simulated wind speeds were used to estimate wind power generation using reV (the Renewable Energy Potential Model developed by NREL) at ten wind project sites. Two sets of results were produced: one using wind speeds extracted from the model grid cell at the project centroid, and another using wind speeds from the actual turbine locations. For each dataset, power output was calculated using both actual turbine-specific power curves and nine generic power curves to convert wind speed into power.
WIND Toolkit Long-term Ensemble Dataset (WTK-LED), an updated version of the meteorological WIND Toolkit, is a meteorological dataset providing high-resolution time series, including interannual variability and model uncertainty of wind speed at every modeling grid point to indicate ranges of possible wind speeds. The data were produced using the Weather Research and Forecasting Model (WRF). The vertical grid used in WTK-LED includes many vertical layers in the atmospheric boundary layer to provide information of atmospheric quantities across the rotor layer of utility scale and distributed wind turbines. The WTK-LED includes: (1) Numerical simulations of wind speed and other meteorological variables covering the contiguous United States (CONUS) and Alaska, with high-resolution (5-minute [min], 2-kilometer [km]) data for 3 years (2018-2020): WTK-LED CONUS, WTK-LED Alaska. (2) Climate simulations from Argonne National Laboratory covering North America, including Alaska, Canada, and most of Mexico and the Caribbean islands. These simulations complement the new WTK-LED to offer a 4-km, hourly dataset covering 20 years (2001-2020): WTK-LED Climate. (3) Specific long-term, high-resolution offshore simulations have been conducted separately for the U.S. coasts, Hawaii, and the Great Lakes, leading to the 2023 National Offshore Wind dataset: NOW-23. The data for Hawaii include land-based data and are part of WTK-LED Hawaii. Because the accuracy of simulations from a mesoscale model, such as WRF, varies depending on the location and weather situation, and can reach up to several m/s for wind speed, we provide simulated wind speed uncertainty estimates to the community to be used in conjunction with the deterministic model simulations. This dataset was developed to satisfy a wide group of stakeholders across various wind energy disciplines, including but not limited to stakeholders in the distributed and utility scale wind industry, the new emerging airborne wind energy field, grid integration, power systems modeling, environmental modeling, and researchers in academia, and to close some of the gaps that current public datasets have. Based on our validation results to date, we suggest use cases and applications for each dataset of the WTK-LED as shown in "WTK-LED Use Cases" resource below.
The shortwave broadband albedo at the top of a molecular atmosphere over ocean between 40deg N and 40deg S is estimated using radiance measurements from the Clouds and the Earth's Radiant Energy System (CERES) instrument and the Visible Infrared Scanner (VIRS) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The albedo monotonically increases from 0.059 at a solar zenith angle of 10deg to 0.107 at a solar zenith angle of 60deg. The estimated uncertainty in the albedo is 3.5 x 10(exp -3) caused by the uncertainty in CERES-derived irradiances, uncertainty in VIRS-derived aerosol optical thicknesses, variations in ozone and water vapor, and variations in surface wind speed. The estimated uncertainty is similar in magnitude to the standard deviation of 0.003 that is derived from 72 areas divided by 20deg latitude by 20deg longitude grid boxes. The empirically estimated albedo is compared with the modeled albedo using a radiative transfer model combined with an ocean surface bidirectional reflectivity model. The modeled albedo with standard tropical atmosphere is 0.061 and 0.111 at the solar zenith angles of 10deg and 60deg, respectively. This empirically estimated albedo can be used to estimate the direct radiative effect of aerosols at the top of the atmosphere over oceans.
The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-3 team collected several data sets related to the hydrology of forested areas. This data set includes measurements of wind speed and direction; air temperature; relative humidity; and canopy, trunk, and snow surface temperatures within three forest types. The data were collected in the southern study area/Old Jack Pine (SSA-OJP) (1994), and SSA-OBS (Old Black Spruce), and SSA-OA (Old Aspen) (1996). Measurements were taken for three days in 1994 and four days at each site in 1996. These measurements were intended to be short term to allow the relationship between subcanopy measurements and those collected above the forest canopy to be determined. The subcanopy estimates of wind speed were used in a snow melt model to help predict the timing of snow ablation. The data are available in tabular ASCII files. The subcanopy meteorological measurement data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).
The development of a microjoule-class pulsed Doppler lidar and deployment of this compact system on mobile platforms such as aircraft, ships, or trucks have opened a new opportunity to characterize the dynamics of complex mesoscale wind flows. The PickUp-based Mobile Atmospheric Sounder (PUMAS) truck-based lidar system was recently used during the American Wake Experiment (AWAKEN) to assess the general structure of boundary layer (BL) wind and turbulence around wind turbines in central Oklahoma. Wind speed profiles averaged over PUMAS transects influenced by the operating turbines (waked flow) show a 1–2 m s −1 reduction compared to mean undisturbed (free flow) wind speed profiles. Spatial variability in wind speed was observed in time–height cross-sections at different distances from turbines. The wind speeds were about 9–12 m s −1 at 6 km distance compared to 5–7 m s −1 at the transects near the turbines. The PUMAS dataset from AWAKEN demonstrated the capability of the mobile Doppler lidar system to document spatial variability in wind flows at different distances from wind turbines and obtain quantitative estimates of wind speed reduction in the waked flow. The high-frequency, simultaneous measurements of the horizontal and vertical winds provide a new approach for characterizing dynamic processes critical for wind farm wake analyses.
A program for determining the feasibility of deriving sea surface wind speeds by remotely sensing ocean surface radiances in the nonglitter regions is discussed. With a knowledge of the duration and geographical extent of the wind field, information about the conventional sea state may be derived. The use of optical techniques for determining sea state has obvious limitations. For example, such means can be used only in daylight and only when a clear path of sight is available between the sensor and the surface. However, sensors and vehicles capable of providing the data needed for such techniques are planned for the near future; therefore, a secondary or backup capability can be provided with little added effort. The information currently being sought regarding white water coverage is also of direct interest to those working with passive microwave systems, the study of energy transfer between winds and ocean currents, the aerial estimation of wind speeds, and many others.
TheWang-Sheeley-Arge (WSA) model estimates solar wind speed and interplanetary magnetic field polarity in the inner heliosphere using global photospheric magnetic field maps. WSA employs the Potential Field Source Surface (PFSS) and Schatten Current Sheet (SCS) models to determine the Sun's global coronal magnetic field. The PFSS and SCS models are connected through two radial parameters, the source surface and interface radii, which specify the overlap region between the inner SCS and outer PFSS models. Though both radii values are adjustable, they have typically been fixed to 2.5 solar radii. Our work highlights how solar wind predictions improve when the radii are allowed to vary over time. Data assimilation using particle filtering (sequential Monte Carlo) is used to infer optimal values over a fixed time window. Solar wind model predictions and satellite observations are compared with a newly developed quality-of-agreement prediction metric. The agreement metric between the model and observations is assumed to correspond to the probability of the two key WSA model parameters, the source surface and interface radii, where the highest metric value implies the optimal radii.We find that the optimal particle filter values of solar radii can perform twice as well as standard values for an exploratory period during Carrington Rotation 1901, with these values also reducing nonphysical kinking effects seen in solar magnetic field lines. Data assimilation choices of input realization and time frame have implications for variation in the solar wind over time. We present this work's theoretical context and practical applications for prediction accuracy.
The prediction of the wind profile maximum speed at Cape Kennedy, Florida, is made for any selected calendar data. The prediction is based on a normal probability distribution model with 15 years of smoothed input data and is static in the sense that no dynamic principles of persistence or synoptic features are considered. Comparison with similar predictions based on 6 years of data shows the same general pattern, but the variability decreased with the increase of sample size.
A spiral approach concept is proposed as a standard procedure for independent, commercial VTOL operations conducted in close proximity to CTOL operations. A guidance logic is developed for this VTOL application, although the results may be applicable to curved approaches by STOL or CTOL aircraft as well. The guidance concept attempts to maintain constant airspeed along a fixed radius nominal spiral. The presence of wind requires a continuous variation in bank angle and heading rate to remain on the desired path. Linear perturbation analysis is used to select satisfactory feedback gains for commanded bank angle, longitudinal acceleration and vertical speed. A wind estimator detects differences between the predicted and observed wind and uses the result to modify the nominal control. For 4-D guidance the nominal time must be computed as a function of turn angle, which requires the solution of an elliptic integral. Time-varying longitudinal accelerations are necessary for 4-D guidance when the observed wind differs from the predicted wind, or when wind shear is present. The logic and the linear feedback gains have been tested in a nonlinear simulation. Results have generally verified the performance predicted by linear analysis.
A method is described for estimating low speed wind tunnel blockage, including model volume, bubble separation and viscous wake effects. A tunnel-centerline, source/sink distribution is derived from measured wall pressure signatures using fast algorithms to solve the inverse problem in three dimensions. Blockage may then be computed throughout the test volume. Correlations using scaled models or tests in two tunnels were made in all cases. In many cases model reference area exceeded 10% of the tunnel cross-sectional area. Good correlations were obtained regarding model surface pressures, lift drag and pitching moment. It is shown that blockage-induced velocity variations across the test section are relatively unimportant but axial gradients should be considered when model size is determined.
A relatively simple, objective, nocturnal temperature forecasting model suitable for freezing and near-freezing conditions has been designed so that a user, presumably a weather forecaster, can put in standard meteorological data at a particular location and receive an hour-by-hour prediction of surface and air temperatures for that location for an entire night. The user has the option of putting in his own estimates of wind speeds and background sky radiation which are treated as independent variables. An analysis of 141 test runs show that 57.4% of the time the model predicts to within 1 C for the best cases and to within 3 C for 98.0% of all cases.
The Seasat-A Satellite Scatterometer (SASS) measured the radar backscatter intensity from the sea surface using a four-beam microwave antenna. Estimates of wind speed and direction derived from these data agree well with surface measurements made during the Joint Air-Sea Interaction experiment, but there are occasions (3 out of 23 satellite passes) when the results are anomalous. One such occasion when the satellite measurements differed substantially from those at the surface of the sea has been studied, and it has been concluded that the interpretation of the SASS measurements may have been vitiated by a mid-level convective system deep enough to produce thunderstorms and lightning.
A number of important developments in satellite remote sensing techniques have occurred recently which offer the possibility of studying over vast areas of the ocean the temporally evolving energy exchange between the ocean and the atmosphere. Commencing in spring of 1985, passive and active microwave sensors that can provide valuable data for scientific utilization will start to become operational on Department of Defense (DOD) missions. The passive microwave radiometer can be used to estimate surface wind speed, total air column humidity, and rain rate. The active radar, or altimeter, senses surface gravity wave height and surface wind speed.
Zonal winds between altitudes of 25 and 120 km have been obtained from measurements of the Doppler shifts of lines of atmospheric gases in solar occultation spectra collected with the ATMOS spectrometer flown on Spacelab 3. Wind speeds of about 100 m/s near 100 km and 25 to 50 m/s between 25 and 70 km were observed at latitudes near 30 deg N and 50 deg S. The wind speeds were estimated to + or - 5 m/s and positions of the absorption lines relative to the rest frame of the instrument were simultaneously recovered to 5 x 10 to the -5th/cm.
This TM consists of two chapters. Chapter I describes the development of a coupled, one-dimensional biogeochemical model using turbulence closure mixed layer (TCMLM) dynamics. The model is applied to the Sargasso Sea at the BATS (Bermuda Atlantic Time Series) site and the results are compared with a previous model study in the same region described in NASNTP-2001-209991. The use of the TCMLM contributed to some improvements in the model simulation of chlorophyll, PAR, nitrate, phosphate, and oxygen, but most importantly, the current model achieved good agreement with the data with much more realistic background eddy diffusivity. However, off-line calculations of horizontal transport of biogeochemical properties revealed that one-dimensional dynamics can only provide a limited assessment of the nutrient and carbon balances at BATS. Future studies in the BATS region will require comprehensive three-dimensional field studies, combined with three-dimensional eddy resolving numerical experiments, to adequately quantify the impact of the local and remote forcing on ecosystem dynamics and carbon cycling. Chapter II addresses the sensitivity of global sea-air CO, flux estimates to wind speed, temperature, and salinity. Sensitivity analyses of sea-air CO, flux to wind speed climatologies, gas transfer algorithms, SSS and SST were conducted for the global oceans and regional domains. Large uncertainties in the global sea-air flux are identified, primarily due to the different gas transfer algorithms used. The sensitivity of the sea-air flux to SST and SSS is similar in magnitude to the effect of using different wind climatologies. Globally, the mean ocean uptake of CO, changes by 5 to 16%, depending upon the combination of SST and SSS used.