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At least 127 records · Page 7

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NASA NTRS1982

A statistical examination of Nimbus 7 SMMR data and remote sensing of sea surface temperature, liquid water content in the atmosphere and surfaces wind speed

Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperature measurements over the global oceans have been examined with the help of statistical and empirical techniques. Such analyses show that zonal averages of brightness temperature measured by SMMR, over the oceans, on a large scale are primarily influenced by the water vapor in the atmosphere. Liquid water in the clouds and rain, which has a much smaller spatial and temporal scale, contributes substantially to the variability of the SMMR measurements within the latitudinal zones. The surface wind not only increases the surface emissivity but through its interactions with the atmosphere produces correlations, in the SMMR brightness temperature data, that have significant meteorological implications. It is found that a simple meteorological model can explain the general characteristics of the SMMR data. With the help of this model methods to infer over the global oceans, the surface temperature, liquid water content in the atmosphere, and surface wind speed are developed. Monthly mean estimates of the sea surface temperature and surface winds are compared with the ship measurements. Estimates of liquid water content in the atmosphere are consistent with earlier satellite measurements.

Prabhakara, C.↗

NASA NTRS1983

A statistical examination of Nimbus-7 SMMR data and remote sensing of sea surface temperature, liquid water content in the atmosphere and surface wind speed

Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperature measurements over the global oceans have been examined with the help of statistical and empirical techniques. Such analyses show that zonal averages of brightness temperature measured by SMMR over the oceans on a large scale are primarily influenced by the water vapor in the atmosphere. Liquid water in the clouds and rain, which has a much smaller spatial and temporal scale, contributes substantially to the variability of the SMMR measurements within the latitudinal zones. The surface wind not only increases the surface emissivity, but through its interactions with the atmosphere produces correlations in the SMMR brightness temperature data that have significant meteorological implications. It is found that a simple meteorological model can explain the general characteristics of the SMMR data. With the help of this model, methods to infer over the global oceans, the surface temperature, liquid water content in the atmosphere, and surface wind speed are developed. Monthly mean estimates of the sea surface temperature and surface winds are compared with the ship measurements. Estimates of liquid water content in the atmosphere are consistent with earlier satellite measurements. Previously announced in STAR as N83-19187

Prabhakara, C.↗

NASA NTRS1993

The gust-front detection and wind-shift algorithms for the Terminal Doppler Weather Radar system

The Federal Aviation Administration's (FAA) Terminal Doppler Weather Radar (TDWR) system was primarily designed to address the operational needs of pilots in the avoidance of low-altitude wind shears upon takeoff and landing at airports. One of the primary methods of wind-shear detection for the TDWR system is the gust-front detection algorithm. The algorithm is designed to detect gust fronts that produce a wind-shear hazard and/or sustained wind shifts. It serves the hazard warning function by providing an estimate of the wind-speed gain for aircraft penetrating the gust front. The gust-front detection and wind-shift algorithms together serve a planning function by providing forecasted gust-front locations and estimates of the horizontal wind vector behind the front, respectively. This information is used by air traffic managers to determine arrival and departure runway configurations and aircraft movements to minimize the impact of wind shifts on airport capacity. This paper describes the gust-front detection and wind-shift algorithms to be fielded in the initial TDWR systems. Results of a quantitative performance evaluation using Doppler radar data collected during TDWR operational demonstrations at the Denver, Kansas City, and Orlando airports are presented. The algorithms were found to be operationally useful by the FAA airport controllers and supervisors.

Hermes, Laurie G.↗

NASA NTRS1980

Comparison of conventionally measured sea surface temperature and wind speed with data retrieved from satellite-borne microwave radiometry

The Scanning Multichannel Microwave Radiometer aboard both the Seasat and Nimbus-7 satellites was designed to estimate sea surface temperature (SST) and wind speed (WS) over an extended range of atmospheric conditions. The retrieval technique is described briefly, and it is demonstrated in a case study that the instrument design goals (SST:1.5 C; WS:2 m/s) appear to be feasible.

Hofer, R.↗

NASA NTRS1992

Estimation of sensible heat flux from remotely sensed canopy temperatures

Temperatures of tallgrass priarie vegetation were measured with infrared thermometers (IRT) at different view zenith and azimuth angles. The optimum IRT view zenith angle for estimating sensible heat fluxes (H) was determined by comparing H estimated with eddy correlation and/or Bowen ratio techniques to H calculated by a method suggested by Hatfield et al. (1984). For wind speeds of 5 m/s or greater, H estimated with surface temperatures measured at a 0 deg or 20 deg view zenith angle gave the best agreement, but for wind speeds of less than 4 m/s the best estimate of H was made with surface temperatures measured at a 40 deg or 60 deg view zenith angle.

Vining, R. C.↗

NASA NTRS2013

Adaptive Disturbance Tracking Theory with State Estimation and State Feedback for Region II Control of Large Wind Turbines

A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.

Balas, Mark J.↗

NASA NTRS1994

Evaluation of the production and the destruction of ozone in the lower atmosphere

Observed surface ozone mixing ratio X(sub ob) is partitioned into two parts; X(sub tr), transported from the free troposphere and X(sub ch), chemically produced or destructed in the boundary layer. X(sub tr) is estimated from the ozone concentration in the free troposphere and the wind speed. The ozone in the free troposphere estimated from surface ozone observations is consistent with that of ozonesonde data. X(sub ch) is obtained from the difference between X(sub ob) and X(sub tr). X(sub tr) increases with wind speed, while X(sub ch) shows maximum at hourly wind speed of 1-2 m/s in the daytime. Contribution of X(sub tr) to X(sub ob) is larger than X(sub ch) except for a short period in summer. X(sub ch) is positive for April-October, but X(sub ch) can be negative in winter, showing the net chemical destruction in the boundary layer. X(sub ch) increases linearly with solar radiation, and is negative for daily global solar radiation below 8 MJ/sq m, which is about equal to the monthly mean in winter.

Muramatsu, H.↗

DOE OSTI2023

A Multi-Fidelity Gaussian Process Regression Method for Probabilistic Wind Farm Power Curve Estimation

Accurate estimation of the power curve for wind turbines or wind farms is crucial to ensure their efficient operation and management. However, conventional methods for power curve estimation rely either on expensive and infrequent measurements or on low-quality numerical simulations. Moreover, the majority of previous studies on power curve estimation for wind turbines or wind farms focused on deterministic estimation, which provides a point estimate of the relationship between wind speed and power generation. Nevertheless, the deterministic approach fails to consider the inherent uncertainty associated with wind energy production resulting from varying turbine characteristics. This can lead to inaccurate power generation estimation and suboptimal decisions regarding energy management. In this paper, a kernel density estimation (KDE) based Multi-Fidelity Gaussian Process Regression (MFGPR) model is proposed to fuse theoretical power curve data and the ground true measurements to create a mapping of wind speed and wind power. By conducting a case study on an actual wind farm in China, the efficacy of the proposed MFGPR model was demonstrated in characterizing the variability of wind power. The probabilistic MFGPR model was also able to generate confidence intervals that encompassed the measured power, thereby improving the accuracy and confidence in wind power estimation or wind resource assessment. Overall, the proposed MFGPR model offers a reliable approach to integrate high-fidelity ground measurements and theoretical power curve data, resulting in precise wind resource assessment and power estimation.

Gaussian process regression↗

NASA NTRS1994

Observations of cloud liquid water path over oceans: Optical and microwave remote sensing methods

Published estimates of cloud liquid water path (LWP) from satellite-measured microwave radiation show little agreement, even about the relative magnitudes of LWP in the tropics and midlatitudes. To understand these differences and to obtain more reliable estimate, optical and microwave LWP retrieval methods are compared using the International Satellite Cloud Climatology Project (ISCCP) and special sensor microwave/imager (SSM/I) data. Errors in microwave LWP retrieval associated with uncertainties in surface, atmosphere, and cloud properties are assessed. Sea surface temperature may not produce great LWP errors, if accurate contemporaneous measurements are used in the retrieval. An uncertainty of estimated near-surface wind speed as high as 2 m/s produces uncertainty in LWP of about 5 mg/sq cm. Cloud liquid water temperature has only a small effect on LWP retrievals (rms errors less than 2 mg/sq cm), if errors in the temperature are less than 5 C; however, such errors can produce spurious variations of LWP with latitude and season. Errors in atmospheric column water vapor (CWV) are strongly coupled with errors in LWP (for some retrieval methods) causing errors as large as 30 mg/sq cm. Because microwave radiation is much less sensitive to clouds with small LWP (less than 7 mg/sq cm) than visible wavelength radiation, the microwave results are very sensitive to the process used to separate clear and cloudy conditions. Different cloud detection sensitivities in different microwave retrieval methods bias estimated LWP values. Comparing ISCCP and SSM/I LWPs, we find that the two estimated values are consistent in global, zonal, and regional means for warm, nonprecipitating clouds, which have average LWP values of about 5 mg/sq cm and occur much more frequently than precipitating clouds. Ice water path (IWP) can be roughly estimated from the differences between ISCCP total water path and SSM/I LWP for cold, nonprecipitating clouds. IWP in the winter hemisphere is about 3 times the LWP but only half the LWP in the summer hemisphere. Precipitating clouds contribute significantly to monthly, zonal mean LWP values determined from microwave, especially in the intertropical convergence zone (ITCZ), because they have almost 10 times the liquid water (cloud plus precipitation) of nonprecipitating clouds on average. There are significant differences among microwave LWP estimates associated with the treatment of precipitating clouds.

Lin, Bing↗

NASA NTRS1981

Solar wind motion within 30 R solar masses - Spacecraft radio scintillation observations

New remote-sensing observations are reported of the solar wind motion within about 30 earth radii. Use is made of the interplanetary scintillation (IPS) spaced receiver technique with the radio source being a spacecraft signal (rather than a natural radio source as in previous spaced receiver studies). The spacecraft used are Helios A and B and the Viking orbiters. The purposes of the study are (1) to augment the scarce estimates of solar wind bulk flow speed near the sun and in the ecliptic with measurements made using spacecraft signals, and (2) to estimate random velocity components and identify the region where the random velocity is a significant fraction of the mean velocity. In addition, the radial evolution of speed and random velocity is compared with that of the plasma density fluctuation spectrum. Also reported are the first accurately normalized IPS scintillation index measurements using a monochromatic point source.

Armstrong, J. W.↗

NASA NTRS1997

Earth-Based Radio Tracking of the Galileo Probe for Jupiter Wind Estimation

Although the Galileo probe was designed to communicate only to the orbiter, the probe radio signal was detected at two Earth-based radio observatories where the signal was a billion times weaker. The measured signal frequency was used to derive a vertical profile of the jovian zonal wind speed. Due to the mission geometry, the Earth-based wind estimates are less sensitive to descent trajectory errors than estimates based on probe-orbiter Doppler measurements. The two estimates of wind profiles agree qualitatively; both show high wind speeds at all depths sampled.

Folkner, W. M.↗

NASA NTRS1993

Wind field model-based estimation of Seasat scatterometer winds

A model-based approach to estimating near-surface wind fields over the ocean from Seasat scatterometer (SASS) measurements is presented. The approach is a direct assimilation technique in which wind field model parameters are estimated directly from the scatterometer measurements of the radar backscatter of the ocean's surface using maximum likelihood principles. The wind field estimate is then computed from the estimated model parameters. The wind field model used in this approach is based on geostrophic approximation and on simplistic assumptions about the wind field vorticity and divergence but includes ageostrophic winds. Nine days of SASS data were processed to obtain unique wind estimates. Comparisons in performance to the traditional two-step (point-wise wind retrieval followed by ambiguity removal) wind estimate method and the model-based method are provided using both simulated radar backscatter measurements and actual SASS measurements. In the latter case the results are compared to wind fields determined using subjective ambiguity removal. While the traditional approach results in missing measurements and reduced effective swath width due to fore/aft beam cell coregistration problems, the model-based approach uses all available measurements to increase the effective swath width and to reduce data gaps. The results reveal that the model-based wind estimates have accuracy comparable to traditionally estimated winds with less 'noise' in the directional estimates, particularly at low wind speeds.

Long, David G.↗

NASA NTRS1995

Vertical neutral wind in the equatorial F-region deduced from electric field and ion density measurements

Direct current (DC) electric field and ion density measurements near density depletion regions (that is, equatorial plasma bubbles) are used to estimate the vertical neutral wind speed. The measured zonal electric field in a series of density depletions crossed by the San Marco D satellite at 01.47-01.52 Universal Time (UT) on 25 October 1988, can be explained if a downward neutral wind of 15-30 m/s exists. Simultaneously, the F-region plasma was moving downward at a speed of 30-50 m/s. These events appear in the local time sector of 23.00-23.15 in which strong downward neutral winds may occur. Indeed, airglow measurements suggest that downward neutral velocities of 25-50 m/s are possible at time near midnight in the equatorial F-region.

Laakso, Harri↗

NASA NTRS2013

Regression Analysis of Top of Descent Location for Idle-thrust Descents

In this paper, multiple regression analysis is used to model the top of descent (TOD) location of user-preferred descent trajectories computed by the flight management system (FMS) on over 1000 commercial flights into Melbourne, Australia. The independent variables cruise altitude, final altitude, cruise Mach, descent speed, wind, and engine type were also recorded or computed post-operations. Both first-order and second-order models are considered, where cross-validation, hypothesis testing, and additional analysis are used to compare models. This identifies the models that should give the smallest errors if used to predict TOD location for new data in the future. A model that is linear in TOD altitude, final altitude, descent speed, and wind gives an estimated standard deviation of 3.9 nmi for TOD location given the trajec- tory parameters, which means about 80% of predictions would have error less than 5 nmi in absolute value. This accuracy is better than demonstrated by other ground automation predictions using kinetic models. Furthermore, this approach would enable online learning of the model. Additional data or further knowl- edge of algorithms is necessary to conclude definitively that no second-order terms are appropriate. Possible applications of the linear model are described, including enabling arriving aircraft to fly optimized descents computed by the FMS even in congested airspace. In particular, a model for TOD location that is linear in the independent variables would enable decision support tool human-machine interfaces for which a kinetic approach would be computationally too slow.

trajectory prediction↗

NASA NTRS1991

The effect of the degree of wave development on the sea state bias in radar altimetry measurement

The extent by which the wave development affects the sea state bias (SSB) in the Geosat altimeter height measurements is investigated. It is shown that the altimetric SSB is not a linear function of the wave height but that it also depends on other factors of wave development, particularly on the wave age (defined as the ratio of the phase speed of the dominant ocean waves to the ocean wind speed). The wave age can be estimated crudely, as the so-called 'pseudo-wave age', on the basis of the significant wave height H(1/3) and the wind speed measured by the altimeter. The analysis of 2.7 years' worth of Geosat data showed a general trend for the dependence of the SSB on the pseudo-wave age, which agrees well with the theoretical prediction that, for a given H(1/3), the SSB decreases as the pseudo-wave age increases.

Fu, Lee-Lueng↗

NASA NTRS2007

Neutral Solar Wind Generated by Lunar Exospheric Dust at the Terminator

We calculate the flux of neutral solar wind observed on the lunar surface at the terminator due to solar wind protons penetrating exospheric dust with: (1) grains larger that 0.1 microns and (2) grains larger than 0.01 microns. For grains larger than 0.1 microns, the ratio of the neutral solar wind to solar wind flux is estimated to be approx.10(exp -4)-10(exp -3) at solar wind speeds in excess of 800 km/s, but much lower (less than 10(exp -5) at average to low solar wind speeds. However, when the smaller grain sizes are considered, the ratio of the neutral solar wind flux to solar wind flux is estimated to be greater than or equal to 10(exp -5) at all speeds and at speeds in excess of 700 km/s reaches 10(exp -3)-10(exp -2). These neutral solar wind fluxes are easily measurable with current low energy neutral atom instrumentation. Observations of neutral solar wind from the surface of the Moon could provide a very sensitive determination of the distribution of very small dust grains in the lunar exosphere and would provide data complementary to optical measurements at ultraviolet and visible wavelengths. Furthermore, neutral solar wind, unlike its ionized counterpart, is .not held-off by magnetic anomalies, and may contribute to greater space weathering than expected in certain lunar locations.

Collier, Michael R.↗

NASA NTRS1996

(abstract) Ulysses Solar Wind Ion Temperatures: Radial, Latitudinal, and Dynamical Dependencies

Observations of the Ulysses SWOOPS plasma experiment are used to determine the dependencies of solar wind ion temperatures upon radial distance, speed, and other parameters, and to estimate solar wind heating. Comparisons with three dimensional temperature estimates determined from the ion spectra by a least squares fitting program will be provided (only small samples of data have been reduced with this program).

Ulysses solar wind ions magnetic field plasmas↗

NASA NTRS1997

Analyses of 1994 Typhoons in the Taiwan Region Using Satellite Data

Taiwan is situated in the prevalent typhoon track in the northwestern Pacific. On average, about one third of the island total annual precipitation is due to typhoons, with the other two third being contributed by the summer monsoon, or Meiyu, and wintertime large scale frontal rainfall. While the typhoons bring the needed moisture for agricultural consumption and industrial utilization, heavy rainfall associated with typhoons often result in large scale flooding and land slide. The prediction of the typhoon track and its severity is therefore a high priority topic both for operation and research. The severity of a typhoon can be defined in terms of the wind strength and the moisture content. The Special Sensor Microwave/Imager (SSM/I) on board of the Defense Meteorological Satellite Program (DMSP) satellites measures microwave radiation in 19.4, 22.2, 37, and 85.5 GHz. These measurements provide an opportunity to estimate parameters such as surface wind speed, water vapor and cloud water contents, and rainfall rate over oceans. In 1994, Taiwan experienced an above normal frequency of typhoon hits, five typhoons hit the island in two months. In this report, estimates of the moisture content of these typhoons are made based on the SSM/I measurements. An assessment of the relative strength of the typhoons are made with analyzed data.

Chang, A. T. C.↗