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RRA dataset provides a detailed profile of atmospheric conditions, including temperature, pressure, density, humidity, wind speed, and direction, for a range of altitudes over a specific geographical location.
A method of detecting a wind event utilizing Doppler lidar includes causing a Doppler lidar unit to operate in a course scan mode in which a lidar beam is scanned along several directions. Line-of-sight wind speed measurements are generated at each direction and a derivative with respect to distance of the line-of-sight wind speed measurements is calculated at each of the directions. A predicted angular position of a wind event is determined, and the lidar unit may then operate in a fine scan mode in which only a limited sector is scanned. The potential wind event is then quantified utilizing data obtained using the fine scan mode.
The low-speed characteristics of a large-scale model of the F-14A aircraft were studied in tests conducted in the Ames Research Center 40- by 80-Foot Wind Tunnel. The primary purpose of the present tests was the determination of lateral-directional stability levels and control effectiveness of the aircraft in its high-lift configuration. Tests were conducted at wing angles of attack between minus 2 deg and 30 deg and with sideslip angles between minus 12 deg and 12 deg. Data were taken at a Reynolds number of 8.0 million based on a wing mean aerodynamic chord of 2.24 m (7.36 ft). The model configuration was changed as required to show the effects of direct lift control (spoilers) at yaw, yaw angle with speed brake deflected, and various amounts and combinations of roll control.
Intercomparison of wind data from the airborne Doppler lidar, ground-based Doppler radars, the 444 m NSSL-KTVY tower, and rawinsonde were completed. The vertical profile of wind in the PBL measured by the radars compared favorably with the profiles measured by the tower and rawinsonde while the one obtained from lidar data differed from the other three by as much as 3m/sec in wind speed and 38 degrees in direction. The time dependence of differences in wind estimates from radar and lidar suggested that these discrepencies could be attributed to a Schuler resonance in the aircraft's inertial navigation system which caused an erroneous component of the aircraft's velocity vector to be subtracted from the lidar radial velocities, thus creating errors in the synthesized wind speed and direction. The vertical profile of turbulent fluctuations of the horizontal wind detected by the different systems compared well. Also, spectra from the different sensing systems compared well in both magnitude and shape, suggesting that the lidar and radar detected similar turbulent structure.
It is well recognized that advection from the North Atlantic has a profound effect on the climatic conditions in central Europe. A new dataset of the ocean-surface winds, derived from the Special Sensor Microwave Imager, SSM/1, is now available. This satellite instrument measures the wind speed, but not the direction. However, variational analysis developed at the Data Assimilation Office, NASA Goddard Space Flight Center, by combining the SSM/I measurements with wind vectors measured from ships, etc., produced global maps of the ocean surface winds suitable for climate analysis. From this SSM/I dataset, a specific index I(sub na) of the North Atlantic surface winds has been developed, which pertinently quantifies the low-level advection into central Europe. For a selected time-period, the index I(sub na) reports the average of the amplitude of the wind, averaging only the speed when the direction is from the southwest (when the wind is from another direction, the contribution counts to the average as zero speed). Strong correlations were found between February I(sub na) and the surface air temperatures in Europe 50-60 deg N. In the present study, we present the correlations between I(sub na) and temperature I(sub s), and also the sensitivity of T(sub s), to an increase in I(sub na), in various seasons and various regions. We specifically analyze the flow of maritime-air from the North Atlantic that produced two extraordinary warm periods: February 1990, and early-winter 2000/2001. The very cold December 2001 was clearly due to a northerly flow. Our conclusion is that the SSM/I dataset is very useful for providing insight to the forcing of climatic fluctuations in Europe.
Left hand polarized Alfven waves generated in coronal holes propagate in the direction of high speed solar wind streams, accelerating and heating heavy ions. As the solar wind expands, the ratio between the frequency of the Alfven waves and the proton gyrofrequency increases, due to the decrease of the interplanetary magnetic field, and encounter first the local ion gyrofrequency of the species with the largest M(sub l) = m(sub l)/z(sub l)m(sub p) (m(sub l) is the mass of species l, m(sub p) is the proton mass and z(sub l) is the degree of ionization of species l). It is shown that the Alfven waves experience there strong absorption and cannot propagate any further until the ions are accelerated and heated. Once this occurs, the Alfven waves continue to propagate until they meet the gyrofrequency of the next species giving rise to a similar phenomenon. In order to show this contention, we use the linear dispersion relation of ion cyclotron waves in a multicomponent plasma consisting of oxygen ions, alpha particles and protons. We assume that at any distance from the sun, the Alfven waves follow the local dispersion relation of electromagnetic ion cyclotron waves. To illustrate the results, we solve the dispersion relation for oxygen ions and alpha particles drifting relative to the protons. The dispersion relation has three branches. The first branch starts at zero frequency and goes to the Doppler-shifted oxygen ion gyrofrequency. The second branch starts close to the oxygen gyrofrequency, and goes to the Doppler-shifted alpha particle gyrofrequency. The third branch starts close to the alpha particle gyrofrequency, and goes to the proton gyrofrequency. The Alfven waves propagate following the first branch of the dispersion relation. When they reach the Doppler-shifted oxygen ion gyrofrequency, the ions are accelerated and heated to some definite values. When these values are reached, the dispersion relation changes, and it is now the first branch of the dispersion relation, the one which goes to the Doppler-shifted alpha particle gyrofrequency. The Alfven waves continue to propagate along the first branch of the dispersion relation and proceed to accelerate and heat the alpha particles.
Aeolus is a small satellite mission to observe surface and atmospheric forcing and general circulation of Mars, by measuring surface energy balance, atmospheric temperatures, aerosols and clouds, and winds. Critically, Aeolus will make these measurements at all local times of day, providing information on both seasonal and diurnal variability. To date, direct measurements of Martian wind speeds have only been possible at the surface, only during daylight hours, and over small areas limited by rover traverse capabilities. From orbit, thermal measurements (e.g., estimates from assumed geostrophic balance) as well as images of dust storms and dune migration have provided inputs to derive current data sets on Martian winds. However, Mars General Circulation models demonstrate that wind speeds derived from these indirect measurements may be in error by 50 to 100%. For this reason, direct wind velocity measurements have been deemed "High Priority" by MEPAG (Mars Exploration Program Analysis Group); measuring wind speeds and corresponding thermal data is vital to understanding the climate of Mars. Aeolus will carry four Spatial Heterodyne Spectrometers (SHS), coupled to two orthogonal viewing telescopes. These high-resolution near-infrared spectrometers will measure CO2 (daytime absorption) and O2 (day and night emission) lines in the Martian atmosphere. Doppler shifts in these lines can be measured during Martian day and night, resolving wind speeds down to ~5 m/s. Orthogonal views allow the spectrometers to capture wind vectors over all observation locations. Aeolus will also carry the atmospheric limb-viewing Thermal Limb Sounder (TLS) to measure atmospheric temperatures, water ice clouds, and dust abundances across all altitudes where winds are measured. Finally, the Surface Radiometric Sensor Package (SuRSeP), a nadir viewing radiometer, will measure the total reflected solar and emitted thermal radiance, surface temperature, and water cloud and dust total column abundances. The combined spectral and thermal measurements will provide a new understanding of the global energy balance, dust transport processes, and climate cycles in the Martian atmosphere. Aeolus will consist of a single satellite in a near-polar orbit, allowing it to pass over all local times, with the baseline mission observing all seasons of an entire Martian year (two Earth years). Aeolus was one of two Martian smallsat concepts selected for study through the Planetary Science Deep Space SmallSat Studies program. This talk will provide an overview of the mission, including science rationale, instruments, spacecraft, and mission operations concept.
The SeaWinds on QuikSCAT scatterometer is a device developed by NASA JPL to measure the speed and direction of ocean surface winds. Simulations performed in order to determine the expected performance of the instrument prior to its launch have indicated that the accuracy of the retrieved wind vectors varies across the swath. In particular the mid-swath accuracy is worse than that of the rest of the swath. This behavior is a general characteristic of scanning pencil beam scatterometers. For SeaWinds, the accuracy of the rest of the swath, and the size of the swath are such that the instrument meets its science requirements despite mid-swath shortcomings. However, by understanding the problem at mid-swath, we can improve the performance there as well, yielding even better coverage and accuracy than was originally intended. The mid-swath performance degradation is due to suboptimal viewing geometry. In particular mid-swath measurements contains measurements from two azimuths, roughly 180 degrees apart. With the standard wind retrieval technique, mid-swath root mean square (RMS) wind direction errors are approximately 30 degrees for low wind speeds (3 - 5.5 m/s) and 20 degrees for moderate to high wind speeds (5.5 - 30 m/s). We discuss the underlying causes of this phenomenon in detail and propose a modification to the wind retrieval technique in order to improve mid-swath performance. By estimating the range of likely wind directions for each measurement cell, one can optimally apply information from neighboring cells in order to reduce random wind direction errors without significantly degrading the resolution of the resultant wind field. In this manner we are able to achieve mid-swath RMS wind direction errors as low as 15 degrees for low winds and 10 degrees for moderate to high winds, while at the same time preserving high resolution structures such as cyclones and fronts. Since our results are based on simulated data, we also outline a procedure for making use of real data to optimize the technique after launch.
Sea surface wind stress measurements recorded by a sonic anemometer are correlated with airborne scatterometer measurements of ocean roughness (cross section of radar backscatter) to establish the accuracy of remotely sensed data and assist in the definition of geophysical algorithms for the scatterometer sensor aboard Seasat A. Results of this investigation are as follows: Comparison of scatterometer and sonic anemometer wind stress measurements are good for the majority of cases; however, a tendency exists for scatterometer wind stress to be somewhat high for higher wind conditions experienced in this experiment (6-9 m/s). The scatterometer wind speed algorithm tends to overcompute the higher wind speeds by approximately 0.5 m/s. This is a direct result of the scatterometer overestimate of wind stress from which wind speeds are derived. Algorithmic derivations of wind speed and direction are, in most comparisons, within accuracies defined by Seasat A scatterometer sensor specifications.
Data from infrared imaging systems and satellite infrared spectrometer (SIRS) for determining sea surface temperature and the atmospheric structure in cloudless areas over the oceans are discussed. Although some interpretations differ, it is clear that simultaneous measurements of radar sea return and passive microwave temperature will provide estimates of the wind speed, and perhaps wind direction, over the oceans, especially in cloudless areas, for a wide range of wind speeds. The problem of integrating the data that would be obtained by a spacecraft, especially one with a combination radar-radiometer, into global analysis procedures for meteorological, wave, and oceanographic predictions is described.
Current LSP, GSDO, and SLS space vehicle operations are halted when wind speeds from specific directions exceed defined thresholds and when lightning is a threat. Strong winds and lightning are difficult parameters for the 45th Weather Squadron (45 WS) to forecast, yet are important in the protection of customer vehicle operations and the personnel that conduct them. A display of the low-level horizontal wind field to reveal areas of high winds or convergence would be a valuable tool for forecasters in assessing the timing of high winds, or convection initiation and subsequent lightning occurrence. This is especially important for areas where no weather observation platforms exist. Developing a dual-Doppler radar capability would provide such a display to assist forecasters in predicting high winds and convection initiation. The wind fields can also be used to initialize a local mesoscale numerical weather prediction model to help improve the model forecast winds, convection initiation, and other phenomena. The 45 WS and NWS MLB tasked the Applied Meteorology Unit (AMU) to develop a dual- Doppler wind field display using data from the 45th Space Wing radar, known as the Weather Surveillance Radar (WSR), NWS MLB Weather Surveillance Radar 1988 Doppler (KMLB), and the Orlando International Airport Terminal Doppler Weather Radar (KMCO). They also stipulated that the software used should be freely available. The AMU evaluated two software packages and, with concurrence from NWS MLB and the 45 WS, chose the Warning Decision Support System-Integrated Information (WDSS-II). The AMU collected data from two significant weather cases: a tornadic event on 14 April 2013 and a severe wind and hail event on 12 February 2014. For the 14 April case, the data were from WSR and KMLB. For the 12 February case, the data were from KMCO and KMLB. The AMU installed WDSS-II on a Linux PC, then processed and quality controlled the radar data for display and analysis using WDSS-II tools. Because of issues with de-aliasing the WSR velocity field, the AMU did not use data from this radar in this study and only analyzed the 12 February case. Merging the data to create the dual-Doppler analysis involved several steps. The AMU used instructions from the WDSS-II website and discussion forum to determine the correct tools to use for the analysis, and was successful in creating a merged reflectivity field, which was critical to the success of creating a merged velocity field. However, the AMU was unable to create a merged velocity field. The AMU researched the WDSS-II forum for discussions on similar issues, asked questions on the forum, and tested different options and values in the merger tool with no success. Developing a dual-Doppler wind field was the main goal of this task, but that was not accomplished. It could be an issue of not using the correct options or the correct value for the options used, or there could be issues with the radar data. There is a follow-on AMU task to install the operational version of WDSS-II in the NWS MLB office. This will provide more opportunities to try different options and input values in order to create a merged wind field from KMCO and KMLB.
Data from nine spacecraft are combined to study the properties of solar wind protons and the interplanetary magnetic field under unusual conditions that proton speed, density, and temperature variations are small over periods comparable to the solar wind expansion time. From the 14 quiet intervals studied it is determined that (1) the square root of T versus velocity relation is less steep than was calculated from long-term-averaged or 3-hour quiet data; (2) the density varies approximately as the inverse square of the velocity; however, the data scatter is large, and an alternative interpretation is that mass flux is constant for velocities over about 400 km/s, in agreement with earlier studies; (3) the magnitude of the interplanetary magnetic field is independent of solar wind speed and density; and (4) the average field direction varies with the solar wind speed as predicted by Parker's spiral model. The intercalibration of solar wind measurements by different spacecraft is discussed in an appendix.
In December 2001, a series of cyclonic centers progressed rapidly into Europe from the west and north. The cyclones moved in generally similar directions, along paths separated by few hundreds of kilometers. The advancing cyclones brought the usual sequence of changing wind directions and produced some high speed wind events. We investigate the wind patterns for this month based on analyses derived the Special Sensor Microwave/Imager observations and NCEP analyses. Whereas southwesterlies from the North Atlantic produced moderate temperatures early in the month, strong northerlies and northwesterlies (up to 15 m/s on 20-22 December) produced a drop in daily minimum and maximum temperatures of 18.8 C and 9.9 C, respectively, over a 4 day period (to -18.8 C and -6.8 C, respectively, on December 23 in Torun, Poland). Such low values in December are unprecedented in recent decades, though not for January or February.
We have used data from Dynamics Explorer 2 to investigate the rate of conversion of electromagnetic energy into both thermal and bulk flow particle kinetic energy in the high-latitude ionosphere. The flux tube integrated conversion rate E(dot)J can be determined from spacecraft measurements of the electric and magnetic field vectors by deriving the field-aligned Poynting flux, S(parallel) = S(dot)B(sub 0), where B(sub 0) is in the direction of the geomagnetic field. Determination of the Poynting flux from satellite observations is critically dependent upon the establishment of accurate values of the fields and is especially sensitive to errors in the baseline (unperturbed) geomagnetic field. We discuss our treatment of the data in some detail, particularly in regard to systematically correcting the measured magnetic field to account for attitude changes and model deficiencies. S(parallel) can be used to identify the relative strengths of the magnetosphere and thermospheric winds as energy drivers and we present observations demonstrating the dominance of each of these. Dominance of the magnetospheric driver is indicated by S(parallel) directed into the ionosphere. Electromagnetic energy is delivered to and dissipated within the region. Dominance of the neutral wind requires that the conductivity weighted neutral wind speed in the direction of the ion drift be larger than the ion drift, resulting in observations of an upward directed Poynting flux. Electromagnetic energy is generated within the ionospheric region in this case. We also present observations of a case where the neutral atmosphere motion may be reaching a state of sustained bulk flow velocity as evidenced by very small Poynting flux in the presence of large electric fields.
The non-linear least squared MHD fitting technique of Szabo 11 9941 has been recently further refined to provide realistic confidence regions for interplanetary shock normal directions and speeds. Analyzing Wind observed interplanetary shocks from 1995 to 200 1, macro characteristics such as shock strength, Theta Bn and Mach numbers can be compared to the details of shock micro or kinetic structures. The now commonly available very high time resolution (1 1 or 22 vectors/sec) Wind magnetic field data allows the precise characterization of shock kinetic structures, such as the size of the foot, ramp, overshoot and the duration of damped oscillations on either side of the shock. Detailed comparison of the shock micro and macro characteristics will be given. This enables the elucidation of shock kinetic features, relevant for particle energization processes, for observations where high time resolution data is not available. Moreover, establishing a quantitative relationship between the shock micro and macro structures will improve the confidence level of shock fitting techniques during disturbed solar wind conditions.
An investigation was conducted in the Langley full-scale tunnel to measure the performance of several helicopter tail-rotor/fin configurations with regard to directional control problems encountered at low speeds in ground effect. Tests were conducted at wind azimuths of 0 deg to 360 deg in increments of 30 deg and 60 deg and at wind speeds from 0 to 35 knots. The results indicate that at certain combinations of wind speed and wind azimuth, large increases in adverse fin force require correspondingly large increases in the tail-rotor thrust, collective pitch, and power required to maintain yaw trim. Changing the tail-rotor direction of rotation to top blade aft for either a pusher tail rotor (tail-rotor wake blowing away from fin) or a tractor tail rotor (tail-rotor wake blowing against fin) will alleviate this problem. For a pusher tail rotor at 180 deg wind azimuth, increases in the fin/tail-rotor gap were not found to have any significant influence on the overall vehicle directional control capability. Changing the tail rotor to a higher position was found to improve tail-rotor performance for a fin-off configuration at a wind azimuth of 180 deg. A V-tail configuration with a pusher tail rotor with top blade aft direction of rotation was found to be the best configuration with regard to overall directional control capability.
Seasat radar observations of the Gulf of Alaska by the Synthetic Aperture Radar (SAR) and the Wind Speed Scatterometer (SASS) indicate that L-band backscatter is modulated by wind speed and possibly by wind direction. It is noted that the L-band backscatter is approximately proportional to the square root of surface winds and that upwind/crosswind differences in backscatter can be as large as 10% in the range of these wind speeds. It is suggested that Seasat SAR images, in conjunction with Seasat Scatterometer data may provide fine-scale mapping of ocean winds and directions. The need for further Seasat SAR-SASS comparisons in order to extend the range of wind speeds is stressed.
Satellite scatterometers are microwave radars capable of measuring near-surface vector winds (both speed and direction) over the oceans under all weather conditions. The data generated from these instruments are used in scientific studies of upper ocean circulation, tropospheric dynamics, air -sea interaction, and climate change.