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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Objective Operational Utilization of Satellite Microwave Scatterometer Observations of Tropical Cyclones

This study has demonstrated that high-resolution scatterometer measurements in tropical cyclones and other high-marine surface wind regimes may be retrieved accurately for wind speeds up to about 35 mls (1-hour average at 10 m) when the scatterometer data are processed through a revised geophysical model function, and a spatial adaptive algorithm is applied which utilizes the fact that wind direction is so tightly constrained in tile inner core of severe marine storms that wind direction may be prescribed from conventional data. This potential is demonstrated through case studies with NSCAT data in a severe West Pacific Typhoon (Violet, 1996) and an intense North Atlantic hurricane (Lili, 1996). However, operational scatterometer winds from NSCAT and QuickScat in hurricanes and severe winter storms are biased low in winds above 25 m/s. We have developed an inverse model to specify the entire surface wind field about a tropical cyclone from operational QuickScat scatterometer measurements within 150 nm of a storm center with the restriction that only wind speeds up to 20 m/s are used until improved model function are introduced. The inverse model is used to specify the wind field over the entire life-cycle of Hurricane Floyd (1999) for use to drive an ocean wave model. The wind field compares very favorably with wind fields developed from the copious aircraft flight level winds obtained in this storm.

Cardone, Vincent J.↗
NASA NTRS2020

Modeling Whitecaps on Global Scale

Whitecaps play an important role in the surface-atmosphere interactions across the ocean. They are directly linked to the energy dissipation rate during wave breaking and transfer of heat, momentum, and gas/aerosol exchange from the wind to the sea surface. Although the first models of W were dependent only on wind speeds, a large number of diverse models based on wind and sea state which include wave height, wave age, friction velocity, and stability effects have been proposed since then. However, it is recognized that most of the proposed W models have strong systematic (e.g., zonal bias) and random errors when compared against observations. This is partly due to the differences in environmental conditions, measurement techniques, and geographical locations among these studies. But, some of these biases are linked to the inability of the proposed models to capture the variability in W in certain wind/wave regimes. Despite the knowledge of existing biases, W residual relationships from the models with wind and wave fields remain highly uncertain, with residual trends varying between the published studies. Here, we take advantage of the availability of relatively dense observations of W from WindSat microwave satellite retrievals in combination with the University of Miami wave model which was recently incorporated within the NASA GMAO/GEOS system (GEOS-UMWM). We use Windsat W retrievals to assess and constrain the previously published W models and understand the relationships of residuals from models in different wind/wave regimes. We link these unexplained residual variations to additional factors such as swell index, drag coefficient etc and add information to the existing whitecap models. Since Windsat retrievals cover wide range of environmental conditions, it helps to reduce the uncertainties associated with differences in measurement techniques. Regression of wind-wave fields against all Windsat data points (CTL) results in larger residuals for lower wave age and W is overestimated upto ~4% for wave age < 10 and underestimated by upto ~2% as wave age increases. We attest to this bias by considering two approaches. One is to perform regression separately for different stages of wave development such as developing sea, fully developed, and wind sea regimes thereby understanding the sensitivity of regression coefficients to sea state (EXP1). Another is to derive coefficients of W models in EXP1 as a function of additional wind/wave factors such as swell index, drag coefficient, and mean squared slope, deriving more nonlinear W models (EXP2). EXP2 provides reduction in Root Mean Squared Error (RMSE) by 0.1-0.3%. Sea surface drag has a stronger relationship with regression coefficients compared to swell index.These additional factors provide improved parameterizations in different wind and wave age regimes, with smaller unexplained/residual variations in W that has been a major concern in the W community.

Raman, Aishwarya↗
DOE OSTI2021

Southwest Pacific tropical cyclone development classification utilizing machine learning and synoptic composites

This study evaluates the ability of machine learning algorithms to classify tropical depressions (TDs) and tropical storms (TSs) in the western region of the southwest Pacific Ocean (SWPO). Decision rules are generated to predict the environment required for a depression to fully develop into a mature storm, and the most influential predictors in the classification decision are ranked. TD and TS are discriminated based on a maximum sustained wind speed threshold (≥17 ms -1 ). Various aerosol, thermodynamic, and dynamic parameters are extracted closest to the initiation point of each non-developing and developing sample. The covariates associated with each labelled sample are used to train a decision tree and random forest model. Results using a testing dataset suggest the random forest approach more accurately distinguishes between non-developing and developing samples. The classification accuracy of the decision tree and random forest are 72% and 91%, respectively. Random forest outperformed the decision tree by providing higher accuracy in test data. The most important variables for binary classification are sea salt aerosol optical depth (AOD), 1,000 mb relative humidity, and sea surface temperature. AOD is a quantitative estimate of the aerosols presents in the air through the extinction of a ray of light as it passes through the atmosphere. Mean composite maps constructed in an unsupervised manner have been created for the most important variables identified by the random forest classifier during TD and TS events to highlight the difference in geophysical and aerosol variables' climatology during the two different classifications. This work will advance the risk management strategies for northeastern Australia and other SWPO basin islands to control their tropical cyclone related losses through prioritizing forecasting variables that are the strongest predictors of the strengthening of tropical depressions into tropical cyclones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Observations of Coastal Wind Momentum Flux: Dependence on Fetch and Waves with Comparisons to COARE

Here, using observations from the Martha’s Vineyard Coastal Observatory, this paper investigates how momentum flux in the marine atmospheric surface layer over the coastal ocean varies with fetch, wave age, and wave slope and assesses the performance of the COARE 3.5 bulk parameterization. Long-fetch (at least 300 km) and short-fetch (3–6 km away from land) conditions have very similar momentum flux, with the latter being just 15% higher. The COARE 3.5 wind speed–dependent formulation closely matches the observations. The sea state dependence of wave age and wave slope is analyzed by considering both peak frequency and mean frequency in a wave spectrum. The slope of regression lines between normalized roughness and wave age is sensitive to wind speed ranges and the scatter of momentum flux, potentially explaining why earlier studies did not find a universal formula to characterize the wave dependence. Although the observed momentum flux exhibits an obvious dependence on wave age, a robust quadratic fit between momentum flux and the 10-m neutral wind speed exists only for young waves. For the short-fetch conditions, the momentum flux does not increase as wave slope increases. This may be because waves generated by local wind are still weak and swell that propagates from other areas dominates the wave spectra. In other words, the wave slope computed by considering the spectra does not properly reflect the local wind–wave interaction.

Air-sea interaction↗
NASA NTRS1988

A system for remote measurements of the wind stress over the ocean

The DISSTRESS system for remote measurements of the surface wind stress over the ocean from ships and buoys is described. It is fully digital, utilizing the inertial dissipation technique. Parallel processing allows anemometer data to be filtered in natural frequency space; that is, the filter cutoffs shift linearly with the mean wind speed of the data to be filtered. The construction of the digital Butterworth bandpass filters is presented in detail. The performance of the system is evaluated by analyzing the results from 28 days of operation during the Frontal Air-Sea Interaction Experiment. The mean wind speed is checked, the anemometer response function is established, and drag coefficients are compared to previous studies. The capability of the system is demonstrated by continuous time series of the friction velocity computed every 20 min. The conclusion is that the surface wind stress can be measured more reliably and accurately (20 percent) with this system than from anemometer wind speeds and a bulk formula.

Large, William G.↗
NASA NTRS2015

OSOAA: A Vector Radiative Transfer Model of Coupled Atmosphere-Ocean System for a Rough Sea Surface Application to the Estimates of the Directional Variations of the Water Leaving Reflectance to Better Process Multi-angular Satellite Sensors Data Over the Ocean

In this study, we present a radiative transfer model, so-called OSOAA, that is able to predict the radiance and degree of polarization within the coupled atmosphere-ocean system in the presence of a rough sea surface. The OSOAA model solves the radiative transfer equation using the successive orders of scattering method. Comparisons with another operational radiative transfer model showed a satisfactory agreement within 0.8%. The OSOAA model has been designed with a graphical user interface to make it user friendly for the community. The radiance and degree of polarization are provided at any level, from the top of atmosphere to the ocean bottom. An application of the OSOAA model is carried out to quantify the directional variations of the water leaving reflectance and degree of polarization for phytoplankton and mineral-like dominated waters. The difference between the water leaving reflectance at a given geometry and that obtained for the nadir direction could reach 40%, thus questioning the Lambertian assumption of the sea surface that is used by inverse satellite algorithms dedicated to multi-angular sensors. It is shown as well that the directional features of the water leaving reflectance are weakly dependent on wind speed. The quantification of the directional variations of the water leaving reflectance obtained in this study should help to correctly exploit the satellite data that will be acquired by the current or forthcoming multi-angular satellite sensors.

Ocean surface↗
NASA NTRS1995

Rings of the North Brazil Current: Their structure and behavior inferred from observations and a numerical simulation

Large anticyclonic rings are shed from the retroflecting North Brazil Current (NBC) near 8 deg N in the tropical western Atlantic. New subsurface velocity and temperature measurements within three such rings are presented here and are found to be consistent with previous in situ and remotely sensed NBC ring measurements. A high-resolution numerical model of the Atlantic Ocean forced by monthly wind stress and an imposed meridional overturning cell is found to shed NBC rings that approximate those observed. The model rings are more surface-intensified than those observed and somewhat smaller in diameter. Both observed and modeled NBC rings move northwestward along the coast of South America with a speed of 8-16 cm/s, considerably slower than predicted by analytical theories describing westward ring propagation. At least 2-3 rings per year separate from the NBC retroflection. Annually, 1-3 rings translate intact from their formation region near 50 deg W to the islands of the southeastern Caribbean, where they disintegrate after a lifetime of about 100 days. This study is the first to make use of subsurface temperature and velocity data to compute the volume of the anomalous ring core. NBC rings may be responsible for 3-4 Sv of direct mass transport across the equatorial-tropical gyre boundary or 20-25% of the total upper ocean cross-gyre transport required by the Atlantic meridional overturning cell. Translating NBC rings may contribute 20% of the total meridional heat transport by the ocean at this latitude.

Fratantoni, David M.↗
DOE OSTI2024

Modeled estimates of permafrost hydrology and related fields for pan-Arctic region over the period 1980-2100

This dataset contains gridded estimates of total runoff (mm/day); subsurface runoff (mm/day); snow water equivalent (SWE, mm/day); vertical upward water flux of combined surface evaporation, evapotranspiration, and snow sublimation (mm/day); and soil temperature (C) across the pan-Arctic basin from simulations of the Permafrost Water Balance Model (PWBM v4). These data were generated to allow researchers to advance understanding of the changes unfolding in the Arctic's terrestrial water cycle under the influences of climate warming, hydrological cycle intensification, and permafrost thaw. The dataset will enable researchers to address important questions spanning multiple disciplines. For example, how will rising river flows exported to the coast impact critical zone ecosystems, near-shore ice dynamics, and ocean biogeochemical processes. Spatial resolution is 25x25 km with N=39926 grid cells spanning the domain. Three forcing datasets were used to drive simulations at an implicit daily time step over the period 1980-2100. Daily air temperature, precipitation, and wind speed data from the WATCH Forcing Data methodology applied to ERA5 reanalysis (W5E5) were used for meteorological forcings over the period 1980-2019. Simulations for the period 1980-2100 used meteorological data from two global climate models; IPSL-CM6A-LR and MPI-ESM1-2-HR. The PWBM hydrological outputs are organized by grid and month in gzipped ASCII text files within each archived tar file. Soil temperature is organized by grid cell and day of year from DOY 205 to DOY 260. No special software is required to work with these data. The package contains spatial domain and river basin information files. These data are most useful for analyses of the spatial and temporal variations in terrestrial hydrology and soil thermal dynamics. A manuscript describing the model simulations and associated analysis has been accepted for publication in The Cryosphere (Rawlins and Karmalkar, 2024).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Comparison of analytical methods for calculation of wind loads

The following analysis is a comparison of analytical methods for calculation of wind load pressures. The analytical methods specified in ASCE Paper No. 3269, ANSI A58.1-1982, the Standard Building Code, and the Uniform Building Code were analyzed using various hurricane speeds to determine the differences in the calculated results. The winds used for the analysis ranged from 100 mph to 125 mph and applied inland from the shoreline of a large open body of water (i.e., an enormous lake or the ocean) a distance of 1500 feet or ten times the height of the building or structure considered. For a building or structure less than or equal to 250 feet in height acted upon by a wind greater than or equal to 115 mph, it was determined that the method specified in ANSI A58.1-1982 calculates a larger wind load pressure than the other methods. For a building or structure between 250 feet and 500 feet tall acted upon by a wind rangind from 100 mph to 110 mph, there is no clear choice of which method to use; for these cases, factors that must be considered are the steady-state or peak wind velocity, the geographic location, the distance from a large open body of water, and the expected design life and its risk factor.

Minderman, Donald J.↗
NASA NTRS2015

Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python‐based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre‐existing Python modules as well as to be object‐oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25‐year history into a common data structure suitable for user‐defined analyses. It features rapid, simplified (i.e., one line of code) production of quick‐look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication‐ready figures. Deconvolution of the polarization‐varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real‐time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May‐June 2014. The second software package is the Marshall Multi‐Radar/Multi‐Sensor (MRMS) Mosaic Python Toolkit, or MMM‐Py for short. MMM‐Py was designed to read, analyze, and display three‐dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM‐Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM‐Py can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMM‐Py can also write to the native MRMS binary format, and sub‐sectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMM‐Py also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMM‐Py, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Python‐based analysis routines with the U.S. Department of Energy's Py‐ART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFC‐based implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convective‐scale analysis, situational awareness, and forensic meteorology. PyTDA exploits Py‐ART's radar data ingest routines and data model to rapidly produce aviation‐relevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the Py‐ART framework will be highlighted. Python‐based analysis within the Py‐ART framework is also being done for new research related to intercomparison of ground‐based radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.

Lang, Timothy J.↗
NASA NTRS2001

The Continuation of Cloud Statistics for NASA Climate Change Studies

The weather systems, cyclones, and anticyclones, along with air trajectories and cloud forms, are compared to past studies of the Arctic to assess compatibility of the four month study of the Arctic Cloud Experiment flights of the First ISCCP Regional Experiment (FIRE/ACE) with past climatologies. The frequency and movement of cyclones (lows) and anticyclones (highs) followed the general eastward and northeastward directions indicated by past studies. Most cyclones (lows) came from eastern Siberia and the Bering Sea to the south and moved north across the Bering Straight or Alaska into the Arctic Ocean. They generally weakened in central pressure as they moved poleward. Anticyclones (highs) were most common in the eastern Beaufort Sea near Canada in June and July as predicted from previous studies. However, many cyclones and anticyclones moved in westward directions which is rare in other latitudes. Erratic changes in shape and intensity on a daily basis also were observed. The National Center for Environmental Prediction (NCEP) analysis generally reflected the Surface Heat Budget in the Arctic (SHEBA) Ship World Meteorological Organization (WMO) observations which it used. However, NCEP temperatures were biased warm by 1.0 to 1.5 C in April and early May. In July when the surface temperature were at the freezing/thawing point, the NCEP analysis changed to a cold bias of -1.0 C. Dew points had smaller biases except for July where they were biased cold by -1.4 C. Wind speeds had a -2 m/s low bias for the six windiest days. Surface barometric pressures had consistently low biases from -1.2 to -2.8 hPa in all four months. Air parcel historical trajectories were mainly from the south or from local anticyclonic gyres in the Beaufort Sea. Most air came to the SHEBA Ship from the north Pacific Ocean or from Alaska and Canada and occasionally from eastern Siberia. Very few trajectories traced back across the pole to Europe and Central Asia. Cloud cover was high, as expected, from 69-86% of the time. Satellite data also indicate frequent stratus, altostratus, and cirrus clouds (occurring 61% of the time) above the expected boundary layer fog and Arctic stratus clouds.

Wylie, Donald P.↗
DOE OSTI2021

Characterization of oceanic post-cold frontal clouds and their model representation. Final report

Low-level clouds are ubiquitous over the oceans, and their impact on the Earth’ radiative budget is important. However, general circulation models (GCMs) that are used to represent our climate and its evolution still experience problems to represent their correct amount and radiative impact. In the extratropical latitudes (~30-60 N/S), cloud properties are strongly modulated by the occurrence of anti-cyclones (high pressure systems) and cyclones (low pressure systems). While deep clouds dominate in cyclones near the center and along the cold and warm fronts, low-level clouds populate the colder regions of the cyclones, and more specifically the region in the wake of the cold fronts, the post-cold frontal region (PCF). The GCMs mentioned above were found to underestimate the amount of these PCF clouds, and this caused errors in their representation of the amount of solar radiation at the surface of the southern hemisphere oceans, causing an excess in absorption and errors in long-term predictions. To better understand which processes are ill-represented in the GCMs to cause such issues, we used ground-based observations from the Eastern North Atlantic (ENA) ARM site and a high resolution regional model (called WRF) to examine the properties of PCF clouds. With the WRF model, we simulated the passage of a cold front at the ENA site using theoretically distinct representations of convection and the physics of the boundary layer. While these physical representations had little impact on the timing, structure and circulation of the cold front, we found a high sensitivity to how the large scale information was fed into the model. Errors rapidly developed if the incoming flow information was injected too far from the site, but 1000 km was found to be an optimal distance between the outer boundary and the ENA site for a realistic cold front passage. With this model, we then conducted a series of experiment where convection and boundary layer schemes were changed, and revealed that 1) the clouds were more sensitive to the convection than boundary layer schemes and 2) the interaction between the two has a large impact. Furthermore, changing the representation of the physics in the model had greater impacts on PCF clouds than changing the initial conditions. As large-scale models increase their spatial resolution, convection will eventually be resolved but it remains that their representation of the physics of the boundary layer will matter for the correct representation of shallow (low-level) clouds. Observations were used to find which large-scale information had a clear relationship with PCF cloud and precipitation properties, in view of helping with GCM parameterizations and evaluation. Both lower troposphere stability and surface forcing were found to be important for PCF clouds that experience more vigorous dynamics than their tropical or subtropical counterparts. For cloud base and top heights, a simple measure of the change in potential temperature between the surface and the 800 hPa was found to be a good predictor. This relationship was found to hold as well when using data from campaigns recently conducted in the southern ocean south of Tasmania. A recent GCM was found to succeed in representing similar relations. For cloud depth, water content, and different characteristics of precipitation both the temperature contrast between the surface and near-air and the near-surface wind speed had a strong relationship. To summarize, through observational constraints and regional model experiments, the project has provided guidance to evaluate GCMs and tools to improve their representation of low-level clouds in the extratropics. It has also highlighted differences in behavior between these clouds and those typically found in the subtropics, thus opening new avenues of research for shallow clouds in general.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Sea level variability in the eastern tropical Pacific as observed by TOPEX and Tropical Ocean-Global Atmosphere Tropical Atmosphere-Ocean Experiment

Sea surface height measurements from the TOPEX altimeter and dynamic height from Tropical Ocean-Global Atmosphere Tropical Atmosphere-Ocean (TOGA TAO) moorings are used to explore sea level variability in the northeastern tropical Pacific Ocean. Afetr the annual harmonic is removed, there are two distinct bands of variability: one band is centered at 5 deg N to 7 deg N and extends from 165 deg W to 110 deg W, and the other band is centered at 10 deg N to 12 deg N and extends from 120 deg W to the coast of Central America. The correspondence between the two independent observation data sets at 5 deg N is excellent with correlations of about 90%. The variability at 5 deg-7 deg N is identified as instability waves formed just south of the North Equatorial Countercurrent during the months of July and March. Wave amplitudes are largest in the range of longitudes 160 deg-140 deg W, where they can exceed 10 cm. The waves disappear when the equatorial current system weakens, during the months of March and May. The variability at 11 deg N in 1993 has the form of anticyclone eddies. These eddies propagate westward at a speed of about 17 cm/s, consistent with the dispersion characteristics of free Rossby waves. The eddies are shown to have their origin near the coast of central America during northern fall and winter. Their formation seems to result from intense wind bursts across the Gulfs of Tehuantepec and Papagayo which generate strong anticyclonic ocean eddies. The disappearance of the eddies in the summer of 1993 coincidences with the seasonal intensification of equatorial currents. Thus the variability at 11 deg N has very little overlap in time with the variability at 5 deg N.

Giese, Benjamin S.↗
NASA NTRS1995

Passive microwave algorithm development and evaluation

The scientific objectives of this grant are: (1) thoroughly evaluate, both theoretically and empirically, all available Special Sensor Microwave Imager (SSM/I) retrieval algorithms for column water vapor, column liquid water, and surface wind speed; (2) where both appropriate and feasible, develop, validate, and document satellite passive microwave retrieval algorithms that offer significantly improved performance compared with currently available algorithms; and (3) refine and validate a novel physical inversion scheme for retrieving rain rate over the ocean. This report summarizes work accomplished or in progress during the first year of a three year grant. The emphasis during the first year has been on the validation and refinement of the rain rate algorithm published by Petty and on the analysis of independent data sets that can be used to help evaluate the performance of rain rate algorithms over remote areas of the ocean. Two articles in the area of global oceanic precipitation are attached.

Petty, Grant W.↗
DOE OSTI2026

Efficient Probabilistic Visualization of Local Divergence of 2D Vector Fields with Independent Gaussian Uncertainty

This work focuses on visualizing uncertainty of local divergence of two-dimensional vector fields. Divergence is one of the fundamental attributes of fluid flows, as it can help domain scientists analyze potential positions of sources (positive divergence) and sinks (negative divergence) in the flow. However, uncertainty inherent in vector field data can lead to erroneous divergence computations, adversely impacting downstream analysis. While Monte Carlo (MC) sampling is a classical approach for estimating divergence uncertainty, it suffers from slow convergence and poor scalability with increasing data size and sample counts. Thus, we present a two-fold contribution that tackles the challenges of slow convergence and limited scalability of the MC approach. (1) We derive a closed-form approach for highly efficient and accurate uncertainty visualization of local divergence, assuming independently Gaussian-distributed vector uncertainties. (2) We further integrate our approach into Viskores, a platform-portable parallel library, to accelerate uncertainty visualization. In our results, we demonstrate significantly enhanced efficiency and accuracy of our serial analytical (speed-up up to 1946×) and parallel Viskores (speed-up up to 19698×) algorithms over the classical serial MC approach. We also demonstrate qualitative improvements of our probabilistic divergence visualizations over traditional mean-field visualization, which disregards uncertainty. We validate the accuracy and efficiency of our methods on wind forecast and ocean simulation datasets.

Ouermi, Timbwaoga [University of Utah]↗
DOE OSTI2020

A Study on Modeled Wind Speed Errors Using the U.S. Department of Energy Buoys

Pacific Northwest National Laboratory (PNNL) operates two AXYS WindSentinel lidar buoys for the U.S. Department of Energy’s Wind Energy Technologies Office. The purpose of these buoys is to collect hub-height winds and supporting meteorological and oceanographic information to facilitate the development of wind energy in the U.S. waters. The first deployment for one buoy was off the coast of Virginia from December 2014 to May 2016, and the first deployment for the other buoy was off the coast of New Jersey from November 2015 until February 2017. This report describes recent analysis of data collected during these first two deployments. Specifically, we compare hub-height wind speed estimates using Monin-Obukhov Similarity Theory (MOST) to the lidar measurements, and examine how those errors are affected by wind direction, atmospheric stability, wind-wave direction differences, and various measures of the wave-state. The comparisons are done using standard similarity functions based on MOST; including the Businger - Dyer, the Beljaars & Holtslag and the Vickers & Mahrt similarity functions. All models produce large errors over the range of atmospheric stabilities that were observed, with the largest errors occurring for stable flows. The Vickers & Mahrt function resulted in the largest overall bias and standard deviation, while Beljaars & Holtslag function gave the smallest bias and standard deviation due to its better performance under stable conditions. The models perform best under unstable conditions, but even in this regime there is a consistent overestimation of the wind speed of between roughly 0 to 1 ms -1 compared to the lidar measurements. We identify specific metocean conditions (i.e. stability and wind and wave directions) at each of the deployment locations that lead to large errors in MOST predictions. Finally, a coupled ocean-atmosphere model framework was investigated to simulate large errors in weather research forecasting (WRF).

17 WIND ENERGY↗
DOE OSTI2024

Autonomous thermal tracking reveals spatiotemporal patterns of seabird activity relevant to interactions with floating offshore wind facilities

Planning is underway for placement of infrastructure needed to begin offshore wind (OSW) energy generation along the West Coast of the United States and elsewhere in the Pacific Ocean. In contrast to the primarily nearshore windfarms currently in the North Atlantic, the seabird communities inhabiting Pacific Wind Energy Areas (WEAs) include significant populations of species that fly by dynamic soaring, a behavior dependent on wind and in which flight height increases steeply with wind speed. Therefore, a more precise and detailed assessment of their 3D airspace use is needed to better understand the potential collision risks that OSW turbines may present to these seabirds. Toward this end, a novel technology called the ThermalTracker-3D (TT3D), which uses thermal imaging and stereo vision, was developed to render high-resolution (on average within ±5 m) flight tracks and related behavior of seabirds. The technology was developed and deployed on a wind-profiling LiDAR buoy in the Humboldt WEA, located 34 to 57 km off California’s coast. During the at-sea deployment between 24 May and 13 August 2021, the TT3D successfully tracked birds moving between 10 and 500 m from the device, around the clock, and in all weather conditions; a total of 1407 detections and their corresponding 3D flight trajectories were recorded. Mean altitudes of detections ranged 6-295 m above sea level (asl). Considering the degree of overlap with anticipated rotor swept zones (RSZ), which extend 25-260 m asl, 79% of detected birds (per m 3 of airspace) moved below the RSZ, 21% moved at heights overlapping the RSZ, and another 0.04% occurred at heights exceeding the RSZ. The high-resolution tracks provided valuable insight into seabird space use, especially at heights that make them vulnerable to collision during various environmental conditions (e.g., darkness, strong winds). Observations made by the TT3D will be useful in filling critical knowledge gaps related to estimating collision and avoidance between seabirds and OSW facilities in the Pacific and elsewhere. Future research will focus on enhancing the TT3D’s identification capabilities to the lowest taxon through validation studies and artificial intelligence, further contributing to seabird conservation efforts associated with OSW.

17 WIND ENERGY↗
NASA NTRS1985

Air-sea interaction with SSM/I and altimeter

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.

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