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NASA NTRS2011

Direct Solar Wind Proton Access into Permanently Shadowed Lunar Polar Craters

Recent analyses of Lunar Prospector neutron spectrometer (LPNS) data have suggested that high abundances of hydrogen exist within cold traps at the lunar poles, and it has often been assumed that hydrogen-bearing volatiles sequestered in permanent shadow are topographically shielded from sputtering by solar wind protons. However, recent simulation results are presented showing that solar wind protons clearly access the floor of an idealized, shadowed lunar crater through a combination of thermal and ambipolar processes, in effect creating a plasma "miniwake". These simulations are the first to model the mini-wake environment in two spatial dimensions with a self-consistent lunar surface-plasma interaction. Progress is reported on constraining the nonzero particle fluxes and energies incident on kilometer-scale shadowed topography, such as a small crater embedded within a larger one. The importance of direct solar wind proton bombardment is discussed within the context of understanding the stability and inventory of hydrogen-bearing volatiles in shadow at the lunar poles. The support of the National Lunar Science institute, the DREAM institute, LPROPS, and the NASA Postdoctoral Program at NASA Goddard Space Flight Center administered by ORAU are gratefully acknowledged.

Zimmerman, M. I.↗
NASA NTRS1977

Aircraft measurements of the microwave scattering signature of the ocean

Microwave scattering signatures of the ocean have been measured over a range of surface wind speeds from 3 m/s to 23.6 m/s using the AAFE RADSCAT scatterometer in an aircraft. Normalized scattering coefficients are presented for vertical and horizontal polarizations as a function of incidence angle (nadir to 55 deg) and radar azimuth angle (0 to 360 deg) relative to surface wind direction. For a given radar polarization, incidence angle, and azimuth angle relative to the wind direction, these scattering data exhibit a power law dependence on surface wind speed. The relation of the scattering coefficient to azimuth angle obtained during aircraft circles (antenna conical scans) is anisotropic and suggests that microwave scatterometers can be used to infer both wind speed and direction. These results have been used for the design of the Seasat-A Satellite Scatterometer (SASS) to be flown in 1978 on this first NASA oceanographic satellite.

Jones, W. L.↗
NASA NTRS1976

Vector wind and vector wind shear models 0 to 27 km altitude for Cape Kennedy, Florida, and Vandenberg AFB, California

The techniques are presented to derive several statistical wind models. The techniques are from the properties of the multivariate normal probability function. Assuming that the winds can be considered as bivariate normally distributed, then (1) the wind components and conditional wind components are univariate normally distributed, (2) the wind speed is Rayleigh distributed, (3) the conditional distribution of wind speed given a wind direction is Rayleigh distributed, and (4) the frequency of wind direction can be derived. All of these distributions are derived from the 5-sample parameter of wind for the bivariate normal distribution. By further assuming that the winds at two altitudes are quadravariate normally distributed, then the vector wind shear is bivariate normally distributed and the modulus of the vector wind shear is Rayleigh distributed. The conditional probability of wind component shears given a wind component is normally distributed. Examples of these and other properties of the multivariate normal probability distribution function as applied to Cape Kennedy, Florida, and Vandenberg AFB, California, wind data samples are given. A technique to develop a synthetic vector wind profile model of interest to aerospace vehicle applications is presented.

Smith, O. E.↗
NASA NTRS2003

A New Objective Technique for Verifying Mesoscale Numerical Weather Prediction Models

This report presents a new objective technique to verify predictions of the sea-breeze phenomenon over east-central Florida by the Regional Atmospheric Modeling System (RAMS) mesoscale numerical weather prediction (NWP) model. The Contour Error Map (CEM) technique identifies sea-breeze transition times in objectively-analyzed grids of observed and forecast wind, verifies the forecast sea-breeze transition times against the observed times, and computes the mean post-sea breeze wind direction and speed to compare the observed and forecast winds behind the sea-breeze front. The CEM technique is superior to traditional objective verification techniques and previously-used subjective verification methodologies because: It is automated, requiring little manual intervention, It accounts for both spatial and temporal scales and variations, It accurately identifies and verifies the sea-breeze transition times, and It provides verification contour maps and simple statistical parameters for easy interpretation. The CEM uses a parallel lowpass boxcar filter and a high-order bandpass filter to identify the sea-breeze transition times in the observed and model grid points. Once the transition times are identified, CEM fits a Gaussian histogram function to the actual histogram of transition time differences between the model and observations. The fitted parameters of the Gaussian function subsequently explain the timing bias and variance of the timing differences across the valid comparison domain. Once the transition times are all identified at each grid point, the CEM computes the mean wind direction and speed during the remainder of the day for all times and grid points after the sea-breeze transition time. The CEM technique performed quite well when compared to independent meteorological assessments of the sea-breeze transition times and results from a previously published subjective evaluation. The algorithm correctly identified a forecast or observed sea-breeze occurrence or absence 93% of the time during the two- month evaluation period from July and August 2000. Nearly all failures in CEM were the result of complex precipitation features (observed or forecast) that contaminated the wind field, resulting in a false identification of a sea-breeze transition. A qualitative comparison between the CEM timing errors and the subjectively determined observed and forecast transition times indicate that the algorithm performed very well overall. Most discrepancies between the CEM results and the subjective analysis were again caused by observed or forecast areas of precipitation that led to complex wind patterns. The CEM also failed on a day when the observed sea- breeze transition affected only a very small portion of the verification domain. Based on the results of CEM, the RAMS tended to predict the onset and movement of the sea-breeze transition too early and/or quickly. The domain-wide timing biases provided by CEM indicated an early bias on 30 out of 37 days when both an observed and forecast sea breeze occurred over the same portions of the analysis domain. These results are consistent with previous subjective verifications of the RAMS sea breeze predictions. A comparison of the mean post-sea breeze winds indicate that RAMS has a positive wind-speed bias for .all days, which is also consistent with the early bias in the sea-breeze transition time since the higher wind speeds resulted in a faster inland penetration of the sea breeze compared to reality.

Case, Jonathan L.↗
NASA NTRS1995

Deriving earth science products from SSM/I

A few of the major accomplishments during the second phase include: (1) all three Special Sensor Microwave Imagers (SSM/I's: F08, F10, and F11) have been cross-calibrated; (2) a very large, quality-controlled, collocated SSM/I and radiosonde data set has been produced; (3) the SSM/I-radiosonde and SSM/I-buoy data sets have been used to calibrate the SSM/I ocean retrieval algorithm; (4) ocean products have been produced for both F10 and F11 SSM/I for 1991-1993; (5) the SSM/I-buoy data set was used to better determine the variation of the ocean T(sub B) with wind direction; and (6) it was demonstrated that under high wind conditions, wind direction information can be obtained from individual SSM/I observations.

Wentz, Frank J.↗
NASA NTRS2015

Real-Time Kennedy Space Center and Cape Canaveral Air Force Station High-Resolution Model Implementation and Verification

Customer: NASA's Launch Services Program (LSP), Ground Systems Development and Operations (GSDO), and Space Launch System (SLS) programs. NASA's LSP, GSDO, SLS and other programs at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) use the daily and weekly weather forecasts issued by the 45th Weather Squadron (45 WS) as decision tools for their day-to-day and launch operations on the Eastern Range (ER). For example, to determine if they need to limit activities such as vehicle transport to the launch pad, protect people, structures or exposed launch vehicles given a threat of severe weather, or reschedule other critical operations. The 45 WS uses numerical weather prediction models as a guide for these weather forecasts, particularly the Air Force Weather Agency (AFWA) 1.67 kilometer Weather Research and Forecasting (WRF) model. Considering the 45 WS forecasters' and Launch Weather Officers' (LWO) extensive use of the AFWA model, the 45 WS proposed a task at the September 2013 Applied Meteorology Unit (AMU) Tasking Meeting requesting the AMU verify this model. Due to the lack of archived model data available from AFWA, verification is not yet possible. Instead, the AMU proposed to implement and verify the performance of an ER version of the AMU high-resolution WRF Environmental Modeling System (EMS) model (Watson 2013) in real-time. The tasking group agreed to this proposal; therefore the AMU implemented the WRF-EMS model on the second of two NASA AMU modeling clusters. The model was set up with a triple-nested grid configuration over KSC/CCAFS based on previous AMU work (Watson 2013). The outer domain (D01) has 12-kilometer grid spacing, the middle domain (D02) has 4-kilometer grid spacing, and the inner domain (D03) has 1.33-kilometer grid spacing. The model runs a 12-hour forecast every hour, D01 and D02 domain outputs are available once an hour and D03 is every 15 minutes during the forecast period. The AMU assessed the WRF-EMS 1.33-kilometer domain model performance for the 2014 warm season (May-September). Verification statistics were computed using the Model Evaluation Tools, which compared the model forecasts to observations. The mean error values were close to 0 and the root mean square error values were less than 1.8 for mean sea-level pressure (millibars), temperature (degrees Kelvin), dewpoint temperature (degrees Kelvin), and wind speed (per millisecond), all very small differences between the forecast and observations considering the normal magnitudes of the parameters. The precipitation forecast verification results showed consistent under-forecasting of the precipitation object size. This could be an artifact of calculating the statistics for each hour rather than for the entire 12-hour period. The AMU will continue to generate verification statistics for the 1.33-kilometer WRF-EMS domain as data become available in future cool and warm seasons. More data will produce more robust statistics and reveal a more accurate assessment of model performance. Once the formal task was complete, the AMU conducted additional work to better understand the wind direction results. The results were stratified diurnally and by wind speed to determine what effects the stratifications would have on the model wind direction verification statistics. The results are summarized in the addendum at the end of this report. In addition to verifying the model's performance, the AMU also made the output available in the Advanced Weather Interactive Processing System II (AWIPS II). This allows the 45 WS and AMU staff to customize the model output display on the AMU and Range Weather Operations AWIPS II client computers and conduct real-time subjective analyses. In the future, the AMU will implement an updated version of the WRF-EMS model that incorporates local data assimilation. This model will also run in real-time and be made available in AWIPS II.

Numerical Weather Prediction↗
NASA NTRS1950

Calibration of Instruments for Measuring Wind Velocity and Direction

Signal Corps wind equipment AN/GMQ-1 consisting of a 3-cup anemometer and wind vane was calibrated for wind velocities from 1 to 200 miles per hour. Cup-shaft failure prevented calibration at higher wind velocities. The action of the wind vane was checked and found to have very poor directional accuracy below a velocity of 8 miles per hour. After shaft failure was reported to the Signal Corps, the cup rotors were redesigned by strengthening the shafts for better operation at high velocities. The anemometer with the redesigned cup rotors was recalibrated, but cup-shaft failure occurred again at a wind velocity of approximately 220 miles per hour. In the course of this calibration two standard generators were checked for signal output variation, and a wind-speed meter was calibrated for use with each of the redesigned cup rotors. The variation of pressure coefficient with air-flow direction at four orifices on a disk-shaped pitot head was obtained for wind velocities of 37.79 53.6, and 98.9 miles per hour. A pitot-static tube mounted in the nose of a vane was calibrated up to a dynamic pressure of 155 pounds per square foot, or approximately 256 miles per hour,

Vogler, Raymond D.↗
NASA NTRS2012

An Update to the Warm-Season Convective Wind Climatology of KSC/CCAFS

Total of 1100 convective events in the 17-year warm-season climatology at KSC/CCAFS. July and August typically are the peak of convective events, May being the minimum. Warning and non-warning level convective winds are more likely to occur in the late afternoon (1900-2000Z). Southwesterly flow regimes and wind directions produce the strongest winds. Storms moving from southwesterly direction tend to produce more warning level winds than those moving from the northerly and easterly directions.

Lupo, Kevin↗
NASA NTRS1976

Seasat-A - An ocean observation satellite

Mission details, onboard equipment, and measurements to be taken are described for the Seasat-A global ocean monitoring satellite. The satellite is designed for mapping the global ocean geoid, charting ice fields and leads, precision measurement of sea surface topography, global monitoring of wave height and wave directional spectra, surface winds and wind direction, current patterns, and ocean temperature. Data handling subsystems, a compressed pulse radar altimeter, coherent synthetic aperture imaging radar, microwave wind scatterometer, scanning visible/IR radiometer, scanning multispectral (5 freq) microwave radiometer mounted on the satellite are described briefly.

Williams, F. L.↗
NASA NTRS1985

Mars atmospheric circulation - Aspects from Viking Landers

Winds measured by the two Viking Landers have been filtered and then compared with predictions from the general circulation model and to Orbiter observations of clouds and surface phenomena that indicate wind direction. This was done to determine the degree to which filtered winds may represent aspects of the general circulation. Excellent agreement was found between wind direction data from Lander 1 and the model predictions and Orbiter observations. For Lander 2, agreement was generally good, but there were periods of disagreement which indicate that the filtering did not remove other extraneous effects. It is concluded that Lander 1 gives a good representation of the general circulation at 22.5 deg N latitude but that Lander 2 is suspect. Most wind data from Lander 1 have yet to be analyzed. It appears that when analyzed these Lander 1 data (covering 3.5 Mars years) can provide information about interannual variations in the general circulation at the Lander latitude.

Ryan, J. A.↗
NASA NTRS1985

Analysis of low-altitude wind speed and direction shears

Horizontal wind profile measurements recorded at the NASA 150-Meter Ground Winds Tower Facility at the Kennedy Space Center, Fla., are analyzed to evaluate wind shears known to be hazardous to the ascent and descent of conventional aircraft and the Space Shuttle. Twenty 5-s intervals of high (between 10 and 18 m/s) and gale force (18 to 33 m/s) surface winds provided instantaneous recordings every 0.1 s per speed, direction, and tower level from 3-150 m. Mathematical (maximum, mean, standard deviation) and graphical (percentage frequency distribution) descriptions of absolute, positive, and negative speed and direction shears with altitude (six vertical layers) and along flight path (one horizontal distance) are presented as functions of the intensity categories and significant values.

Alexander, M. B.↗
NASA NTRS2020

Design of a Direct-Detection Wind and Aerosol Lidar for Mars Orbit

The present knowledge of the Mars atmosphere is greatly limited by a lack of global measurements of winds and aerosols. Hence, measurements of height-resolved wind and aerosol profiles are a priority for new Mars orbiting missions. We have designed a direct-detection lidar (MARLI) to provide global measurements of dust, winds and water ice profiles from Mars orbit. From a 400-km polar orbit, the instrument is designed to provide wind and backscatter measurements with a vertical resolution of 2 km and with resolution of 2° in latitude along track. The instrument uses a single-frequency, seeded Nd:YAG laser that emits 4 mJ pulses at 1064 nm at a 250 Hz pulse rate. The receiver utilizes a 50-cm diameter telescope and a double edge Fabry-Pérot etalon as a frequency discriminator to measure the Doppler shift of the aerosol-backscatter profiles. The receiver also includes a polarization-sensitive channel to detect the cross-polarized backscatter profiles from water ice. The receiver uses a sensitive 4 × 4 pixel HgCdTe avalanche photodiode array as a detector for all signals. Here we describe the measurement concept, instrument design, and calculate its performance for several cases of Mars atmospheric conditions. The calculations show that under a range of atmospheric conditions MARLI is capable of measuring wind speed profiles with random error of 2–4 m/s within the first three scale heights, enabling vertically resolved mapping of transport processes in this important region of the atmosphere.

Cremons, Daniel R.↗
NASA NTRS1978

Engineering handbook on the atmospheric environmental guidelines for use in wind turbine generator development

The guidelines are given in the form of design criteria relative to wind speed, wind shear, turbulence, wind direction, ice and snow loading, and other climatological parameters which include rain, hail, thermal effects, abrasive and corrosive effects, and humidity. This report is a presentation of design criteria in an engineering format which can be directly input to wind turbine generator design computations. Guidelines are also provided for developing specialized wind turbine generators or for designing wind turbine generators which are to be used in a special region of the United States.

Frost, W.↗
NASA NTRS1984

Radionuclide counting technique for measuring wind velocity and direction

An anemometer utilizing a radionuclide counting technique for measuring both the velocity and the direction of wind is described. A pendulum consisting of a wire and a ball with a source of radiation on the lower surface of the ball is positioned by the wind. Detectors and are located in a plane perpendicular to pendulum (no wind). The detectors are located on the circumferene of a circle and are equidistant from each other as well as the undisturbed (no wind) source ball position.

Singh, J. J.↗
NASA NTRS1985

Terrestrial Analog Studies for Martian Patterned Ground

A recurring problem in understanding Martian patterned ground is explaining its large size. Terrestrial patterned ground in Swedish Lapland offers an analog that may help explain this. In cold, arid regions with strong winds, polygonal features are accentuated paralled to the dominant wind direction. Preliminary results of a comparison between Martian polygonal troughs and dominant wind directions suggests a good correlation. This evolutionary model involving aeolian modification of Martian polygonal ground helps explain the large size features without requiring multiple, deep freeze-thaw cycles. A well-established geographical technique, nearest neighbor analysis, can be modified and applied to the distribution of patterned ground on Earth and Mars. The procedure determines the R-statistic, which reflects the degree to which on observation departs from an expected random pattern. The R-statistic is independent of scale, and therefore it can be applied to any size of type of pattern. Preliminary results indicate that there may be a correlation between the R-statistic and the process that create the polygons.

Rossbacher, L. A.↗
NASA NTRS1992

The effect of turbulence on atmospheric gradient parameters estimated from ground-based radiometric and space geodetic measurements

A straightforward expression for the covariance of a general vector of atmospheric parameters is employed to calculate the effects of estimates of spatial gradients for a frozen Kolmogorov turbulence field moving over a site at constant velocities. Numerical calculations are performed to investigate the implications for three techniques: ground-based microwave radiometry, geodesy with the Global Positioning System, and VLBI. It is found that a prevailing wind with no true static gradients may give rise to apparent azimuthal asymmetries when gradient parameters are estimated. The standard deviation of the estimated north gradient parameter as a function of wind direction, for various wind speeds, is illustrated.

Davis, James L.↗
NASA NTRS1997

A Well-Calibrated Ocean Algorithm for Special Sensor Microwave/Imager

I describe an algorithm for retrieving geophysical parameters over the ocean from special sensor microwave/imager (SSM/I) observations. This algorithm is based on a model for the brightness temperature T(sub B) of the ocean and intervening atmosphere. The retrieved parameters are the near-surface wind speed W, the columnar water vapor V, the columnar cloud liquid water L, and the line-of-sight wind W(sub LS). I restrict my analysis to ocean scenes free of rain, and when the algorithm detects rain, the retrievals are discarded. The model and algorithm are precisely calibrated using a very large in situ database containing 37,650 SSM/I overpasses of buoys and 35,108 overpasses of radiosonde sites. A detailed error analysis indicates that the T(sub B) model rms accuracy is between 0.5 and 1 K and that the rms retrieval accuracies for wind, vapor, and cloud are 0.9 m/s, 1.2 mm, and 0.025 mm, respectively. The error in specifying the cloud temperature will introduce an additional 10% error in the cloud water retrieval. The spatial resolution for these accuracies is 50 km. The systematic errors in the retrievals are smaller than the rms errors, being about 0.3 m/s, 0.6 mm, and 0.005 mm for W, V, and L, respectively. The one exception is the systematic error in wind speed of -1.0 m/s that occurs for observations within +/-20 deg of upwind. The inclusion of the line-of-sight wind W(sub LS) in the retrieval significantly reduces the error in wind speed due to wind direction variations. The wind error for upwind observations is reduced from -3.0 to -1.0 m/s. Finally, I find a small signal in the 19-GHz, horizontal polarization (h(sub pol) T(sub B) residual DeltaT(sub BH) that is related to the effective air pressure of the water vapor profile. This information may be of some use in specifying the vertical distribution of water vapor.

Wentz, Frank J.↗
NASA NTRS2001

Biogeochemical Response to Mesoscale Physical Forcing in the California Current System

In the first part of the project, we investigated the local response of the coastal ocean ecosystems (changes in chlorophyll, concentration and chlorophyll, fluorescence quantum yield) to physical forcing by developing and deploying Autonomous Drifting Ocean Stations (ADOS) within several mesoscale features along the U.S. west coast. Also, we compared the temporal and spatial variability registered by sensors mounted in the drifters to that registered by the sensors mounted in the satellites in order to assess the scales of variability that are not resolved by the ocean color satellite. The second part of the project used the existing WOCE SVP Surface Lagrangian drifters to track individual water parcels through time. The individual drifter tracks were used to generate multivariate time series by interpolating/extracting the biological and physical data fields retrieved by remote sensors (ocean color, SST, wind speed and direction, wind stress curl, and sea level topography). The individual time series of the physical data (AVHRR, TOPEX, NCEP) were analyzed against the ocean color (SeaWiFS) time-series to determine the time scale of biological response to the physical forcing. The results from this part of the research is being used to compare the decorrelation scales of chlorophyll from a Lagrangian and Eulerian framework. The results from both parts of this research augmented the necessary time series data needed to investigate the interactions between the ocean mesoscale features, wind, and the biogeochemical processes. Using the historical Lagrangian data sets, we have completed a comparison of the decorrelation scales in both the Eulerian and Lagrangian reference frame for the SeaWiFS data set. We are continuing to investigate how these results might be used in objective mapping efforts.

Niiler, Pearn P.↗