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At least 487 records · Page 27

Measuring ocean waves from space; Proceedings of the Symposium, Johns Hopkins University, Laurel, MD, Apr. 15-17, 1986

Papers are presented on ocean-wave prediction; the quasi-universal form of the spectra of wind-generated gravity waves at different stages of their development; the limitations of the spectral measurements and observations of the group structure of surface waves; the effect of swell on the growth of wind wave; operational wave forecasting; ocean-wave models, and seakeeping using directional wave spectra. Consideration is given to microwave measurements of the ocean-wave directional spectra; SIR research; estimating wave energy spectra from SAR imagery, with the radar ocean-wave spectrometer, and SIR-B; the wave-measurement capabilities of the surface contour radar and the airborne oceanographic lidar; and SIR-B ocean-wave enhancement with fast-Fourier transform techniques. Topics discussed include wave-current interaction; the design and applicability of Spectrasat; the need for a global wave monitoring system; the age and source of ocean swell observed in Hurricane Josephine; and the use of satellite technology for insulin treatment.

Beal, Robert C.↗

Examples of, reasons for, and consequences of the poor quality of wind data from ships for the marine boundary layer - Implications for remote sensing

Wind reports by data buoys are used to demonstrate that these reports have in the past provided useful values for the synoptic scale winds and that at present these reports provide very reliable value for the synoptic scale winds. Past studies of wind reports by ships have revealed that the data are of poor quality, but the causes for this poor quality are not identified. Examples of the poor quality of wind data from ships are obtained by comparing ship reports with buoy reports and comparing reports of different kinds of ships with each other. These comparisons identify many different reasons for the poor quality of wind data from ships. Suggestions are made for improving the quality of ship data. The consequences of the poor quality of ship winds are described in terms of the effects on weather and wave forecasts. The implications for remotely sensed winds are discussed.

Pierson, Willard J., Jr.↗

NWP Impact of Cloud Top and Boundary Layer Winds from a Satellite Borne Lidar: an Observing System Simulation Experiment

Observing systems simulation experiments (OSSE's) provide a powerful tool to assess the impact of proposed satellite borne observing systems on meteorological applications models. We describe the results of an OSSE conducted to assess the impact of data from a low power lidar wind sensor on the forecast accuracy of a global spectral numerical weather prediction (NWP) model, the Air Force Geophysics Laboratory Global Data Assimilation System. The instrument would be operating at near-infrared wavelengths thereby increasing the backscatter signal relative to comparable infrared lidar.

Isaacs, R. G.↗

Applied Meteorology Unit (AMU)

This report summarizes the Applied Meteorology Unit (AMU) activities for the first quarter of Fiscal Year 2010 (October - December 2009). A detailed project schedule is included in the Appendix. Included tasks are: (1) Peak Wind Tool for User Launch Commit Criteria (LCC), (2) Objective Lightning Probability Tool, Phase III, (3) Peak Wind Tool for General Forecasting, Phase II, (4) Upgrade Summer Severe Weather Tool in Meteorological Interactive Data Display System (MIDDS), (5) Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) Update and Maintainability, (5) Verify 12-km resolution North American Model (MesoNAM) Performance, and (5) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Graphical User Interface.

Bauman, William↗

Applied Meteorology Unit (AMU) Quarterly Report - Fourth Quarter FY-09

This report summarizes the Applied Meteorology Unit (AMU) activities for the fourth quarter of Fiscal Year 2009 (July - September 2009). Tasks reports include: (1) Peak Wind Tool for User Launch Commit Criteria (LCC), (2) Objective Lightning Probability Tool. Phase III, (3) Peak Wind Tool for General Forecasting. Phase II, (4) Update and Maintain Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS), (5) Verify MesoNAM Performance (6) develop a Graphical User Interface to update selected parameters for the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLlT)

Bauman, William↗

Applied Meteorology Unit Quarterly Report. First Quarter FY-13

The AMU team worked on five tasks for their customers: (1) Ms. Crawford continued work on the objective lightning forecast task for airports in east-central Florida. (2) Ms. Shafer continued work on the task for Vandenberg Air Force Base to create an automated tool that will help forecasters relate pressure gradients to peak wind values. (3) Dr. Huddleston began work to develop a lightning timing forecast tool for the Kennedy Space Center/Cape Canaveral Air Force Station area. (3) Dr. Bauman began work on a severe weather forecast tool focused on east-central Florida. (4) Dr. Watson completed testing high-resolution model configurations for Wallops Flight Facility and the Eastern Range, and wrote the final report containing the AMU's recommendations for model configurations at both ranges.

Source record↗

Applied Meteorology Unit (AMU)

This report summarizes the Applied Meteorology Unit (AMU) activities for the second quarter of Fiscal Year 2007 (January - March 2007). Tasks reported on are: Obiective Lightning Probability Tool, Peak Wind Tool for General Forecasting, Situational Lightning Climatologies for Central Florida, Anvil Threat Corridor Forecast Tool in AWIPS, Volume Averaqed Heiqht lnteq rated Radar Reflectivity (VAHIRR), Tower Data Skew-t Tool, and Weather Research and Forecastini (WRF) Model Sensitivity Study

Bauman, William↗

Science Service Status 2019 World Radiocommunication Conference

Science missions such as Earth-exploration and remote sensing thatuse frequencies allocated for Earth Exploration-Satellite Service(EESS) provide valuable information about, for example: (1) Air quality monitoring (2) Soil moisture mapping (3) Sensing sea salinity (4) Weather forecasting and climate models (winds, storms, clouds).Another set of science missions use Space Research Service (SRS)allocations. These space research missions can support: (1) On orbit research that for example can help in the creation of new drugsor the impact of the space environment on satellites (2) Scientific information about the universe – stars, planetary science, solarsystem, and the future evolution of the universe.

Roura, Corali↗

Initialization of a mesoscale model for April 10, 1979, using alternative data sources

A 35 km grid limited area mesoscale model was initialized with high density SESAME radiosonde data and high density TIROS-N satellite temperature profiles for April 10, 1979. These data sources were used individually and with low level wind fields constructed from surface wind observations. The primary objective was to examine the use of satellite temperature data for initializing a mesoscale model by comparing the forecast results with similar experiments employing radiosonde data. The impact of observed low level winds on the model forecasts was also investigated with experiments varying the method of insertion. All forecasts were compared with each other and with mesoscale observations for precipitation, mass and wind structure. Several forecasts produced convective precipitation systems with characteristics satisfying criteria for a mesoscale convective complex. High density satellite temperature data and balanced winds can be used in a mesoscale model to produce forecasts which verify favorably with observations.

Kalb, M. W.↗

Integration of New Technology Considering the Trade-Offs Between Operational Benefits and Risks: A Case Study of Dynamic Line Rating

Electric grid operators are adept at handling complexity and uncertainty. However, with increasing introduction of renewable generation, distributed energy resources, and more frequent severe weather events, operators will experience new workload and challenging decision scenarios. Here, this paper quantifies risks and benefits from an operator's perspective of introducing weather based forecast Dynamic Line Ratings (DLR) using variable wind conditions in addition to ambient temperature to relieve transmission congestion and facilitating more offshore wind (OSW). A concept of operations (CONOPS) applied to a forecast DLR implementation and its integration with OSW is defined. A method for evaluating tradeoffs of derating to make the rating more conservative but decreasing the benefit was developed and applied to a case study for two existing overhead transmission lines on Long Island, New York. The CONOPS uses historical day-ahead and hour-ahead High Resolution Rapid Refresh weather forecasts and weather station data to support planning and real-time operations. The analysis determines the risk of downgrades in real-time operational rating compared to the forecast and quantifies the frequency and severity of last-minute downgrades. The risk is compared against the benefits in increased capacity to provide insights on the additional amount of uncertainty DLR and OSW will add to the operator's workload.

17 WIND ENERGY↗

Deep Learning Experiments for Tropical Cyclone Intensity Forecasts

Reducing tropical cyclone (TC) intensity forecast errors is a challenging task that has interested the operational forecasting and research community for decades. To address this, we developed a deep learning (DL)-based multilayer perceptron (MLP) TC intensity prediction model. The model was trained using the global Statistical Hurricane Intensity Prediction Scheme (SHIPS) predictors to forecast the change in TC maximum wind speed for the Atlantic basin. In the first experiment, a 24-h forecast period was considered. To overcome sample size limitations, we adopted a leave one year out (LOYO) testing scheme, where a model is trained using data from all years except one and then evaluated on the year that is left out. When tested on 2010–18 operational data using the LOYO scheme, the MLP outperformed other statistical–dynamical models by 9%–20%. Additional independent tests in 2019 and 2020 were conducted to simulate real-time operational forecasts, where the MLP model again outperformed the statistical–dynamical models by 5%–22% and achieved comparable results as HWFI. The MLP model also correctly predicted more rapid intensification events than all the four operational TC intensity models compared. In the second experiment, we developed a lightweight MLP for 6-h intensity predictions. When coupled with a synthetic TC track model, the lightweight MLP generated realistic TC intensity distribution in the Atlantic basin. Therefore, the MLP-based approach has the potential to improve operational TC intensity forecasts, and will also be a viable option for generating synthetic TCs for climate studies.

58 GEOSCIENCES↗

Simulating Marine Stratocumulus Clouds using Lagrangian Superdroplet Method in ERF

This study investigates the simulation of marine stratocumulus (stratoCu) clouds – common in many offshore and coastal wind energy regions - using Lagrangian Superdroplet Method (SDM) implemented in Energy Research and Forecasting (ERF) model. Developed by the Wind Energy Technologies Office (WETO), ERF is a high-resolution atmospheric modeling tool that relies on traditional bulk microphysics schemes. Under an LLNL-led Laboratory Directed Research and Development (LDRD) project, SDM was integrated into ERF to improve cloud process fidelity by explicitly tracking individual “superdroplets”. This enables a realistic representation of the droplet size spectrum, cloud-atmosphere interactions, and potential feedbacks from wind plants on atmospheric flow and cloud structure.

54 ENVIRONMENTAL SCIENCES↗

Short-term forecasting of thunderstorms at Kennedy Space Center, based on the surface wind field

Techniques incorporating wind convergence that can be used for the short-term prediction of thunderstorm development are described. With these techniques, the convergence signal is sensed by the wind network array 15 to 90 min before actual storm development. Particular attention is given to the convergence cell technique (which has been applied at the Kennedy Space Center) where each convective region is analyzed independently. It is noted that, while the monitoring of areal and cellular convergence can be used to help locate the seeds of developing thunderstorms and pinpoint the lightning threat areas, this forecasting aid cannot be used in isolation.

Watson, Andrew I.↗

Investigation of boundary-layer wind predictions during nocturnal low-level jet events using the Weather Research and Forecasting model

Simulations of two periods featuring three consecutive low level jet (LLJ) events in the US Upper Great Plains during the autumn of 2011 were conducted to explore the impacts of various setup configurations and physical process models on simulated flow parameters within the lowest 200 m above the surface, using the Weather Research and Forecasting (WRF) model. Sensitivities of simulated flow parameters to the horizontal and vertical grid spacing, planetary boundary layer (PBL) and land surface model (LSM) physics options, were assessed. Data from a Light Detection and Ranging (lidar) system, deployed to the Weather Forecast Improvement Project (WFIP; Finley et al. 2013) were used to evaluate the accuracy of simulated wind speed and direction at 80 m above the surface, as well as their vertical distributions between 120 and 40 m, covering the typical span of contemporary tall wind turbines. All of the simulations qualitatively captured the overall diurnal cycle of wind speed and stratification, producing LLJs during each overnight period, however large discrepancies occurred at certain times for each simulation in relation to the observations. 54-member ensembles encompassing changes of the above discussed configuration parameters displayed a wide range of simulated vertical distributions of wind speed and direction, and potential temperature, reflecting highly variable representations of stratification during the weakly stable overnight conditions. Root mean square error (RMSE) statistics show that different ensemble members performed better and worse in various simulated parameters at different times, with no clearly superior configuration . Simulations using a PBL parameterization designed specifically for the stable conditions investigated herein provided superior overall simulations of wind speed at 80 m, demonstrating the efficacy of targeting improvements of physical process models in areas of known deficiencies. However, the considerable magnitudes of the RMSE values of even the best performing simulations indicate ample opportunities for further improvements.

Mirocha, Jeff D.↗

Wind power costs driven by innovation and experience with further reductions on the horizon

The costs of wind power have declined to levels on par with or below those of conventional sources in many parts of the world. Wind power has become one of the fastest-growing sources of new electricity generation. We take stock of wind power cost evolution over the past 20 years, review methodologies commonly used for cost assessment, discuss the potential for continued cost reduction, and identify anticipated cost and value drivers. Our scope includes both onshore and offshore wind technologies. We draw from a vast body of literature on these topics to highlight key trends, approaches, and limitations. Furthermore, we discuss strategies for wind power assets to enhance their marginal economic value to the broader power system and consumers. We identify a myriad of factors that are expected to influence the future cost and value of wind power, including siting, project scale, turbine size, operational synergies, commodity prices, advancements in turbine technologies, enhanced management of the wind resource, and novel control technologies that provide value for the electricity grid. Because the common methods for forecasting future costs each have their own strengths and weaknesses, we find the best insights are elicited from a combination of methods. Overall, researchers and analysts anticipate further sizable cost reductions for onshore and offshore wind. Midrange forecasts for levelized cost of energy in 2050 are generally between $20 and $30/MWh for onshore wind and $40 and $60/MWh for offshore wind, a reduction to approximately half of today's levels. Optimistic forecasts anticipate these levels as early as 2030.

17 WIND ENERGY↗

The Effect of the Ambient Solar Wind Medium on a CME-driven Shock and the Associated Gradual Solar Energetic Particle Event

We present simulation results of a gradual solar energetic particle (SEP) event detected on 2021 October 9 by multiple spacecraft, including BepiColombo (Bepi) and near-Earth spacecraft such as the Advanced Composition Explorer (ACE). A peculiarity of this event is that the presence of a high-speed stream (HSS) affected the low-energy ion component (≲5 MeV) of the gradual SEP event at both Bepi and ACE, despite the HSS having only a modest solar wind speed increase. Using the EUHFORIA (European Heliospheric FORecasting Information Asset) magnetohydrodynamic model, we replicate the solar wind during the event and the coronal mass ejection (CME) that generated it. We then combine these results with the energetic particle transport model PARADISE (PArticle Radiation Asset Directed at Interplanetary Space Exploration). We find that the structure of the CME-driven shock was affected by the nonuniform solar wind, especially near the HSS, resulting in a shock wave front with strong variations in its properties such as its compression ratio and obliquity. By scaling the emission of energetic particles from the shock to the solar wind compression at the shock, an excellent match between the PARADISE simulation and in situ measurements of ≲5 MeV ions is obtained. Our modeling shows that the intricate intensity variations observed at both ACE and Bepi were influenced by the nonuniform emission of energetic particles from the deformed shock wave and demonstrates the influence of even modest background solar wind structures on the development of SEP events.

Solar energetic particles↗

Gaussian and Lognormal Models of Hurricane Gust Factors

A document describes a tool that predicts the likelihood of land-falling tropical storms and hurricanes exceeding specified peak speeds, given the mean wind speed at various heights of up to 500 feet (150 meters) above ground level. Empirical models to calculate mean and standard deviation of the gust factor as a function of height and mean wind speed were developed in Excel based on data from previous hurricanes. Separate models were developed for Gaussian and offset lognormal distributions for the gust factor. Rather than forecasting a single, specific peak wind speed, this tool provides a probability of exceeding a specified value. This probability is provided as a function of height, allowing it to be applied at a height appropriate for tall structures. The user inputs the mean wind speed, height, and operational threshold. The tool produces the probability from each model that the given threshold will be exceeded. This application does have its limits. They were tested only in tropical storm conditions associated with the periphery of hurricanes. Winds of similar speed produced by non-tropical system may have different turbulence dynamics and stability, which may change those winds statistical characteristics. These models were developed along the Central Florida seacoast, and their results may not accurately extrapolate to inland areas, or even to coastal sites that are different from those used to build the models. Although this tool cannot be generalized for use in different environments, its methodology could be applied to those locations to develop a similar tool tuned to local conditions.

Merceret, Frank↗

MPAS Atmospheric Boundary Layer Simulation under Selected Stability Conditions: Evaluation Using the SWIFT Datasen

Modeling the transition from mesoscale to microscale is necessary in order to model different processes that affect a wind farm and to develop forecasting tools that operate at the farm scale. The mesoscale-to-microscale coupling (MMC) project is an A2e (Atmosphere-toelectrons) coordinated activity for developing modeling capabilities at the wind farm scale. By moving the focus of the research from a single wind turbine to the collection of turbines that comprise a wind farm, A2e extends the range of spatial and timescales that need representation in a model from tens of meters to hundreds of kilometers and timescales from a few seconds to days (Bokharaie et al. 2016). In the atmosphere, these scales are represented by mesoscale-tomicroscale models. The modeling available at these scales has differed in its representation of various physical processes. The MMC group is responsible for evaluating existing models at these scales and recommending a set of options for coupling the mesoscale and microscale with the best-performing models. The group was organized in 2015 and will explore options for coupling strategies with real-world test problems in fiscal year (FY) 2017. The model of choice for this exercise is WRF (Weather Research Forecasting) for mesoscale and WRF-LES (Large Eddy Simulation) for microscale simulations. The MPAS (Model Prediction Across Scales) variable mesh model that can be continuously refined; it has dynamic core and physics options adopted from WRF, which offer an alternative platform for modeling the mesoscale.

54 ENVIRONMENTAL SCIENCES↗