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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Implementation of a state of the art automated system for the production of cloud/water vapor motion winds from geostationary satellites

The thrust of the proposed effort under this contract is aimed at improving techniques to track water vapor data in sequences of imagery from geostationary satellites. In regards to this task, significant testing, evaluation, and progress was accomplished during this period. Sets of winds derived from Meteosat data were routinely produced during Atlantic hurricane events in the 1993 season. These wind sets were delivered via Internet in real time to the Hurricane Research Division in Miami for their evaluation in a track forecast model. For eighteen cases in which 72-hour forecasts were produced, thirteen resulted in track forecast improvements (some quite significant). In addition, quality-controlled Meteosat water vapor winds produced by NESDIS were validated against rawinsondes, yielding an 8 m/s RMS. This figure is comparable to upper-level cloud drift wind accuracies. Given the complementary horizontal coverage in cloud-free areas, we believe that water vapor vectors can supplement cloud-drift wind information to provide good full-disk coverage of the upper tropospheric flow. The impact of these winds on numerical analysis and forecasts will be tested in the next reporting period.

Velden, Christopher S.↗
NASA NTRS2017

Identifying Stratospheric Air Intrusions and Associated Hurricane-Force Wind Events over the North Pacific Ocean

Motivation: Ocean data is sparse: reliance on satellite imagery for marine forecasting; Ocean Prediction Center (OPC) –“mariner’s weather lifeline”. Responsible for: Pacific, Atlantic, Pacific Alaska surface analyses –24, 48, 96 hrs.; Wind & wave analyses –24, 48, 96 hrs.; Issue warnings, make decisions, Geostationary Operational Environmental Satellite –R Series (now GOES-16), Compared to the old GOES: 3 times spectral resolution, 4 times spatial resolution, 5 times faster coverage; Comparable to Japanese Meteorological Agency’s Himawari-8, used a lot throughout this research. Research Question: How can integrating satellite data imagery and derived products help forecasters improve prognosis of rapid cyclogenesis and hurricane-force wind events? Phase I –Identifying stratospheric air intrusions: Water Vapor –6.2, 6.9, 7.3 micron channels; Airmass RGB Product; AIRS, IASI, NUCAPS total column ozone and ozone anomaly; ASCAT (A/B) and AMSR-2 wind data.

Ozone↗
NASA NTRS2001

The Impact of QuikScat on Weather Analysis and Forecasting

Scatterometer observations of the ocean surface wind speed and direction improve the depiction and prediction of storms at sea. These data are especially valuable where observations are otherwise sparse, mostly in the Southern Hemisphere and tropics, but also on occasion in the North Atlantic and North Pacific The SeaWinds scatterometer on the QuikScat satellite was launched in June 1999 and it represents a dramatic departure in design from the other scatterometer instruments launched during the past decade (ERS-1,2 and NSCAT). More details on the SeaWinds instrument can be found in Atlas et al. (2001) and Bloom et al. (1999). This presentation shows the influence of QuikScat data in data assimilation systems both from the NASA Data Assimilation Office (GEOS-3) and from NCEP (GDAS).

Atlas, Robert↗
DOE OSTI2026

AI/ML-Enhanced Wind Forecasts for Reducing Uncertainty in Prescribed Fire Planning

Prescribed fire is a vital tool for ecosystem management and wildfire risk reduction but its escalation is constrained by overly conservative burn windows because of uncertainties, for instance, in wind forecasts. This review describes the state of the art in weather product use by fire/smoke models and identifies three priority research gaps that artificial intelligence/machine learning (AI/ML) is well positioned to address: (1) spatial and temporal downscaling to meter-scale, sub-hourly wind fields; (2) bias correction for systematic model errors in complex terrain; and (3) robust uncertainty quantification to inform ensemble-based simulations. Emerging AI/ML techniques offer promising frameworks to address all three challenges. By providing high-resolution, bias-corrected, and probabilistic wind fields, AI/ML-enhanced forecasts will allow for expanded burn windows, improved ignition strategy design and a reduced reliance on expert intuition, especially when a prescribed fire is introduced into new areas.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

MISTiC Winds, a Micro-Satellite Constellation Approach to High Resolution Observations of the Atmosphere Using Infrared Sounding and 3D Winds Measurements

MISTiC(TM) Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiCs extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenasat much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

Maschhoff, K. R.↗
NASA NTRS2000

Evaluation of Bogus Vortex Techniques with Four-Dimensional Variational Data Assimilation

The effectiveness of techniques for creating "bogus" vortices in numerical simulations of hurricanes is examined by using the Penn State/NCAR nonhydrostatic mesoscale model (MM5) and its adjoint system. A series of four-dimensional variational data assimilation (4-D VAR) experiments is conducted to generate an initial vortex for Hurricane Georges (1998) in the Atlantic Ocean by assimilating bogus sea-level pressure and surface wind information into the mesoscale numerical model. Several different strategies are tested for improving the vortex representation. The initial vortices produced by the 4-D VAR technique are able to reproduce many of the structural features of mature hurricanes. The vortices also result in significant improvements to the hurricane forecasts in terms of both intensity and track. In particular, with assimilation of only bogus sea-level pressure information, the response in the wind field is contained largely within the divergent component, with strong convergence leading to strong upward motion near the center. Although the intensity of the initial vortex seems to be well represented, a dramatic spin down of the storm occurs within the first 6 h of the forecast. With assimilation of bogus surface wind data only, an expected dominance of the rotational component of the wind field is generated, but the minimum pressure is adjusted inadequately compared to the actual hurricane minimum pressure. Only when both the bogus surface pressure and wind information are assimilated together does the model produce a vortex that represents the actual intensity of the hurricane and results in significant improvements to forecasts of both hurricane intensity and track.

Pu, Zhao-Xia↗
DOE OSTI2020

Short-term wind forecasting using statistical models with a fully observable wind flow

The utility of model output data from the Weather Research and Forecasting mesoscale model is explored for very short-term forecasting (5-30 minutes horizon) of wind speed to be used in large scale simulations of an autonomous electric power grid. Using this synthetic data for the development and evaluation of short-term forecasting algorithms offer many unique advantages over observational data, such as the ability to observe the full wind flow field in the surrounding region. Several short-term forecasting algorithms are implemented and evaluated using the synthetic data at several different time horizons and for three different geographic locations. Comparison is made with observational data from one location. We find that short-term forecasts of the synthetic data considering wind flow from the surrounding region perform 26% better than persistence in terms of root mean square error at the 5-minute time horizon. This improvement is comparable to studies of observational data in the literature. These results provide motivation to use synthetic data for short term forecasting in grid simulations, and open the door to future algorithmic improvements.

17 WIND ENERGY↗
NASA NTRS1977

Applications of Seasat to the offshore oil, gas and mining industries

The NASA satellite Seasat-A (to be launched in 1978) has applications to the offshore oil, gas, and mining industries including: (1) improvements in weather and wave forecasting, (2) studies of past wind and wave statistics for planning design requirements, and (3) monitoring ice formation, breakup, and movement in arctic regions. The primary geographic areas which will be monitored by Seasat-A include: the Beaufort Sea, the Labrador Sea, the Gulf of Mexico, the U.S. east coast, West Africa, Equatorial East Pacific, the Gulf of Alaska, and the North Sea. Seasat-A instrumentation used in ocean monitoring consists of a radar altimeter, a radar scatterometer, a synthetic aperture radar, a microwave radiometer, and a visible and infrared radiometer. The future outlook of the Seasat program is planned in three phases: measurement feasibility demonstration (1978-1980), data accessibility/utility demonstration (1980-1983), and operational system demonstration (1983-1985).

Mourad, A. G.↗
NASA NTRS2008

A New Polar Magnetic Index of Geomagnetic Activity and its Application to Monitoring Ionospheric Parameters

For improving the reliability of Space Weather prediction, we developed a new, Polar Magnetic (PM) index of geomagnetic activity, which shows high correlation with both upstream solar wind data and related events in the magnetosphere and ionosphere. Similarly to the existing polar cap PC index, the new, PM index was computed from data from two near-pole geomagnetic observatories; however, the method for computing the PM index is different. The high correlation of the PM index with both solar wind data and events in Geospace environment makes possible to improve significantly forecasting geomagnetic disturbances and such important parameters as the cross-polar-cap voltage and global Joule heating in high latitude ionosphere, which play an important role in the development of geomagnetic, ionospheric and thermospheric disturbances. We tested the PM index for 10-year period (1995-2004). The correlation between PM index and upstream solar wind data for these years is very high (the average correlation coefficient R approximately equal to 0.86). The PM index also shows the high correlation with the cross-polar-cap voltage and hemispheric Joule heating (the correlation coefficient between the actual and predicted values of these parameters is approximately 0.9), which results in significant increasing the prediction reliability of these parameters. Using the PM index of geomagnetic activity provides a significant increase in the forecasting reliability of geomagnetic disturbances and related events in Geospace environment. The PM index may be also used as an important input parameter in modeling ionospheric, magnetospheric, and thermospheric processes.

Lyatsky, Wladislaw↗
DOE OSTI2022

Forecasted Dynamic Line Ratings for Regional Transmission Lines

This report was prepared for the Wind Energy Technology Office for the FY 2022, quarter 3 deliverable. This details the use of forecasted dynamic line rating as an improvement over static rating for three transmission lines in three regions of interest. A selection of wind plants across Idaho, the Columbia River Gorge and offshore wind in the NYSERDA territory were modeled for their concurrent cooling effects for dynamic line rating. Regional transmission lines for the wind plant interconnections were determined and a CFD domain was created to determine local wind flows over the lines. A dynamic line rating for each of the lines was calculated for both weather observation data and HRRR model forecast data. The comparison of peaks in the wind power production were compared to the DLR peaks. It was determined that for shorter regional transmission lines, the effect of concurrent cooling that commonly occur with gen-tie lines were still valid. Concurrent cooling effects drop as the length of the regional transmission lines increase in distance from the wind plants. In addition, the accuracy of the forecasted ampacity to the weather observation data for ampacity was assessed. In general, the accuracy was best for the INL region with the NOAA-maintained sites. The Columbia River Gorge and Long Island sites showed similar levels of accuracy for the forecasted DLR. The accuracy levels were around 11% for the INL region, 15% for Columbia River Gorge and 7% for New York Long Island. The higher error for the Columbia Gorge region is likely due to the sparse availability of weather stations available, whereas both the INL site and Long Island are well instrumented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1993

Investigation of water vapor motion winds from geostationary satellites

Motions deduced in animated water vapor imagery from geostationary satellites can be used to infer wind fields in cloudless regimes. For the past several years, CIMSS has been exploring this potentially important source of global-scale wind information. Recently, METEOSAT-3 data has become routinely available to both the U.S. operational and research community. Compared with the current GOES satellite, the METEOSAT has a superior resolution (5 km vs. 16 km) in its water vapor channel. Preliminary work: at CIMSS has demonstrated that wind sets derived from METEOSAT water vapor imagery can provide important upper-tropospheric wind information in data void areas, and can positively impact numerical model guidance in meteorological applications. Specifically, hurricane track forecasts can be improved. Currently, we are exploring methods to further improve the derivation and quality of the water vapor wind sets.

Velden, Christopher↗
NASA NTRS1986

Short-term numerical precipitation forecasts initialized using a diagnosed divergent-wind component

Use of the diagnosed-divergence initialization procedure of Tarbell et al. (1979) to predict the hourly rainfall data used in short-term precipitation forecasts is examined experimentally. Data simulations using a mesoscale model and balanced and internally consistent data were conducted; the physical and numerical characteristics of the mesoscale model are described. The real experiment used rainfall data from April 25-26, 1979 to investigate the capabilities of the initialization procedure to improve short-term precipitation forecasts. The derivation of the diagnosed-divergent wind using a mesoscale omega equation which includes the effects of latent heating is discussed. The diagnosed-divergence initialization forecasts are compared to nondivergence or observed-divergence initializations. It is observed that the diagnosed-divergence initializations provide better rainfall data than the other initializations.

Salmon, Ellen M.↗
NASA NTRSDate not supplied

Towards Physics Guided Optical Flow for Tracking Atmospheric Motion

Observations of atmospheric 3D winds are critical for improving short-range and long-range forecasting. Such advancement in forecasting directly applies to research in a number of areas including convective processes, wildfire plumes and tornado prediction. Atmospheric Motion Vectors (AMVs) provide a passively sensed approach to quantifying horizontal motion and cloud heights, which are typically sourced from geostationary sensors due to the availability of high frequency observations. Recent work has shown that estimating AMVs by tracking individual pixels with dense optical flow is a promising new direction. In this work, we compare state-of-the-art convolutional neural networks for optical flow in a physics-guided deep learning framework for predicting AMVs. The approach is semi-supervised and uses physically informed wind vectors from high-resolution numerical simulations for supervised learning followed by fine-tuning though warping and reconstruction of full-disk geostationary images (GOES-16). In the vertical direction, we use labels from the CALIPSO low-earth orbit satellite to predict cloud height from 16-band geostationary images with a neural network. We present results for both tasks on held-out time periods and secondary datasets.

Geostationary↗
NASA NTRS2000

Wind Prediction Accuracy for Air Traffic Management Decision Support Tools

The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an optimal interpolation of the latest ACARS reports since the RUC run. This paper presents an overview of the study's results including the identification and use of new large mor wind-prediction accuracy metrics that are key to ATM DST performance.

Cole, Rod↗
NASA NTRS2012

An OSSE on Mesoscale Model Assimilation of Simulated HIRAD-Observed Hurricane Surface Winds

The hazards of landfalling hurricanes are well known, but progress on improving the intensity forecasts of these deadly storms at landfall has been slow. Many cite a lack of high-resolution data sets taken inside the core of a hurricane, and the lack of reliable measurements in extreme conditions near the surface of hurricanes, as possible reasons why even the most state-of-the-art forecasting models cannot seem to forecast intensity changes better. The Hurricane Imaging Radiometer (HIRAD) is a new airborne microwave remote sensor for observing hurricanes, and is operated and researched by NASA Marshall Space Flight Center in partnership with the NOAA Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division, the University of Central Florida, the University of Michigan, and the University of Alabama in Huntsville. This instrument?s purpose is to study the wind field of a hurricane, specifically observing surface wind speeds and rain rates, in what has traditionally been the most difficult areas for other instruments to study; the high wind and heavy rain regions. Dr. T. N. Krishnamurti has studied various data assimilation techniques for hurricane and monsoon rain rates, and this study builds off of results obtained from utilizing his style of physical initializations of rainfall observations, but obtaining reliable observations in heavy rain regions has always presented trouble to our research of high-resolution rainfall forecasting. Reliable data from these regions at such a high resolution and wide swath as HIRAD provides is potentially very valuable to mesoscale forecasting of hurricane intensity. This study shows how the data assimilation technique of Ensemble Kalman Filtering (EnKF) in the Weather Research and Forecasting (WRF) model can be used to incorporate wind, and later rain rate, data into a mesoscale model forecast of hurricane intensity. The study makes use of an Observing System Simulation Experiment (OSSE) with a simulated HIRAD dataset sampled during a hurricane and uses EnKF to forecast the track and intensity prediction of the hurricane. Comparisons to truth and error metrics are used to assess the model?s forecast performance.

Albers, Cerese↗
NASA NTRSDate not supplied

Impact of GPM-retrieved surface meteorology condition on simulations of two winter storms during ICE-POP 2018

Led by the KMA as a component of the WMO's World Weather Research Program (WWRP) Research and Development and Forecast Demonstration Projects (RDP/FDP). Taken place during the Winter Olympics (February-March) of 2018. Goals of ICE-POP: To improve understanding on severe weathers (snowfalls, visibility, rapid wind changes and gusts,) over complex terrain; To improve the predictability of nowcasting and very-short range forecasting with a few kilometer horizontal resolution - Development of NWP-based nowcasting, multi-scale data assimilation and time-lagged ensemble for VSRF, and radar reflectivity and visibility data assimilation; To improve verification for high resolution model considering complex terrain.

Xuanli Li↗
NASA NTRS1998

Capacitively Stabilized Etalon Technology for Spaceborne Wind Lidar Application

Global monitoring by satellites is important for many types of environmental studies. Among these, the wind field is the single most important atmospheric state variable required for understanding atmospheric motion and predicting weather. Studies indicate that a global determination of the tropospheric wind field to an accuracy of 1-5 m/sec is critical for improved numerical weather forecasting. This measurement could be carried out with a spaceborne lidar system sensing the Doppler shift of a laser signal backscattered from the atmosphere. Over the past four years we have developed a ground-based Edge Technique lidar system and demonstrated wind measurements through the troposphere with high accuracy (1-6 m/s) and high spatial resolution. Recently, we began the design of a shuttle based wind measurement system for technology demonstration as part of the Zephyr program. In this paper, we present the characteristics of the high spectral resolution etalon filter technology for lidar wind measurement with the Edge Technique. In conclusion, a spacecraft motion compensation method has been discussed. We demonstrated experimentally that the etalon can be tuned to compensate for any satellite induced Doppler shift to an accuracy of better than 0.6 m/s over a time period of 2.5 ms.

Li, Steven X.↗
NASA NTRS1998

Assessment of the 60 Km Rapid Update Cycle (RUC) with Near Real-Time Aircraft Reports

NASA is developing the Center-TBACON Advisory System (CTAS), a set of Air Traffic Management (ATM) Decision Support Tools (DST) to enable controllers to increase airspace capacity and flight efficiency. A crucial component of the CTAS, or any ATM DST, is the computation of the time-of-flight of aircraft along flight path segments which requires accurate knowledge of the wind through which the aircraft are flying. CTAS currently uses wind information from the Rapid Update Cycle (RUC), a numerical prediction model run operationally by the National Weather Service (NWS) National Center for Environmental Prediction (NCEP). There exists near real-time wind observations from commercial aircraft that can be used to increase the accuracy of the RUC wind forecasts via the FAA Integrated Terminal Weather System (ITWS) Terminal Winds (TW) algorithm. This report presents a study based on the application of the ITWS TW algorithm as an improvement to the baseline RUC product. Terminal Winds generally does not support the full Center airspace; the domain of the prototype MIT/LLITWS TW system was increased to cover the Denver Center airspace to support this study. This study has three goals: 1) determine the errors in the baseline 60-kilometer resolution RUC forecast wind fields relative to the needs of en route DSTs such as CTAS; 2) determine the benefit of using the TW algorithm to refine the RUC forecast wind fields with near real-tlme Meteorological Data Collection and Reporting System (MDCRS) aircraft reports, and 3) identify factors that influence wind field errors in order to improve accuracy and estimate errors in real time. The data for this study were collected over a one-year period for the Denver Center airspace and over one miIlion verification observations were used. This study is part of a larger effort funded by NASA which includes the NOAA/FSL.

Cole, R. E.↗