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The potential benefits of remote SEASAT-A satellite sensing of wind directional wave spectra by active microwave systems are elaborated. It is shown that a combined effort which uses supplemental satellite information in numerical forecasting and hindcasting schemes upgrades the accuracy of existing forecasting methods of an order of magnitude.
The predominant weather pattern for Venus is described. Wind directions and wind velocities are given. Possible driving forces of the winds are presented and include solar heating, planetary rotation, and the greenhouse effect.
The derivation of the proper truck preload is discussed and is shown to be dependent upon the azimuth drive preload direction, the wind direction and magnitude, and the out of roundness of the track. The resulting wheel and track contact stresses were evaluated and found to be satisfactory for either the 64-m or 70-m antenna. The wheel bearing loads were found to be quite satisfactory for the larger 70-m antenna. Methods for evaluating the effects of track out of roundness and for aligning the wheel and truck assemblies are presented. It is believed that these methods are practical and that the increased loadings on the parts should not affect the expected long life of the azimuth bearing.
Atmospheric electrodynamics is reviewed. The discovery of apparent large (V/m) electric fields within the mesosphere invites the possibility for this region to be electrically active. Observations of the V/m field were made at high latitudes even under active conditions, but always below heights where significant enhancements in electrical conductivity are found to occur. Two measurements at Andoya (Norway) show anticorrelation of horizontal field directions with wind directions, suggesting a mechanism which involves mechanical separation of charged aerosols. Reported evidence for such aerosols makes this concept more viable. Noctilucent clouds and mesospheric turbulence, and their influence on the local electrical environment are mentioned.
Canadian AES personnel collected data related to surface and atmospheric meteorological conditions over the BOREAS region. This data set contains 15-minute meteorological data from 14 automated meteorology stations located across the BOREAS region. Included in this data are parameters of date, time, mean sea level pressure, station pressure, temperature, dew point, wind speed, resultant wind speed, resultant wind direction, peak wind, precipitation, maximum temperature in the last hour, minimum temperature in the last hour, pressure tendency, liquid precipitation in the last hour, relative humidity, precipitation from a weighing gauge, and snow depth. Temporally, the data cover the period of August 1993 to December 1996. The data are provided in tabular ASCII files, and are classified as AFM-Staff data.
This section on Urban Climates provides a basic understanding of what comprises the urban climate and what factors control the overall development of the urban climate. We also discuss in this section, methods for evaluating urban climate characteristics and forcing functions as well as how the urban heat island effect comes into play as a dynamic influence on urban climatology. Additionally, we examine and discuss the major radiation and energy balance of city (i.e., shortwave and longwave radiation, albedo, net all-wave radiation, total energy balance, and sensible latent, and storage heat) and the interactions of these energy balances with the lower atmosphere. The use of remote sensing to measure urban surface temperatures as a driving force in the development of the urban heat island effect is presented. We also discuss how the overall moisture, precipitation, humidity, and air movement in cities (i,e,, wind speeds and wind direction) and wind environment of the city affects urban climatology.
This report presents data analysis results for a simulation-based approach named CASPEr (Characterization of Airplane State Prediction Error) to characterize the performance of onboard energy state and automation mode prediction functions for terminal area arrival and approach phases of flight over a wide range of conditions. In particular, the results include quantification of energy state (i.e., altitude and airspeed) prediction performance, models for prediction performance as a function of initial energy state (i.e., initial altitude, airspeed, and weight) and weather factors, and analysis of outlier prediction performance. Wind speed, wind direction, and wind gradient were found to be major factors in energy state prediction performance. Initial energy and gust intensity were also significant factors in airspeed prediction performance. Furthermore, the results suggest that errors in automation mode prediction may be a major contributor to outlier prediction performance.
The present investigation is concerned with the results of a study of wind direction indicators contained in the Viking and Mariner 9 data sets. It is found that wind direction measurements from a variety of indicators, taken over several Mars years at many longitudes, exhibit a high degree of consistency and seasonal reproducibility. It is, therefore, possible to interpret most of the observations in terms of the zonally symmetric circulation of Mars. When combined with models of the atmospheric circulation, observed wind directions can be used to set loose constraints on the polar cap mass fluxes and thermal fields which drive the flows. It is pointed out that polar cap formation seems to control the wind directions at mid and high latitudes in both hemispheres during autumn and early winter.
Aeolian features on Triton that were imaged during the Voyager Mission have been grouped. The term 'aeolian feature' is broadly defined as features produced by or blown by the wind, including surface and airborne materials. Observations of the latitudinal distributions of the features probably associated with current activity (known plumes, crescent streaks, fixed terminator clouds, and limb haze with overshoot) all occur from latitude -37 deg to latitude -62 deg. Likely indicators of previous activity (dark surface streaks) occur from latitude -5 deg to -70 deg, but are most abundant from -15 deg to -45 deg, generally north of currently active features. Those indicators which give information on wind direction and speed have been measured. Wind direction is a function of altitude. The predominant direction of the surface wind streaks is found to be between 40 deg and 80 deg measured clockwise from north. The average orientation of streaks in the northeast quadrant is 59 deg. Winds at 1- to 3-kilometer altitude are eastward, while those at more than 8 kilometers blow west.
We use repeat high-resolution airborne geophysical data consisting of laser altimetry, snow, and Ku-band radar and optical imagery acquired in 2014, 2016, and 2017 to analyze the spatial and temporal variability in surface roughness, slope, wind deposition, and snow accumulation at 88° S, an elevation bias validation site for ICESat-2 and potential validation site for CryoSat-2. We find significant small-scale variability (<10 km) in snow accumulation based on the snow radar subsurface stratigraphy, indicating areas of strong wind redistribution are prevalent at 88° S. In general, highs in snow accumulation rate correspond with topographic lows, resulting in a negative correlation coefficient of r(exp 2)=−0.32 between accumulation rate and MSWD (mean slope in the mean wind direction). This relationship is strongest in areas where the dominant wind direction is parallel to the survey profile, which is expected as the geophysical surveys only capture a two-dimensional cross section of snow redistribution. Variability in snow accumulation appears to correlate with variability in MSWD. The correlation coefficient between the standard deviations of accumulation rate and MSWD is r(exp 2)=0.48, indicating a stronger link between the standard deviations than the actual parameters. Our analysis shows that there is no simple relationship between surface slope, wind direction, and snow accumulation rates for the overall survey area. We find high variability in surface roughness derived from laser altimetry measurements on length scales smaller than 10 km, sometimes with very distinct and sharp transitions. Some areas also show significant temporal variability over the course of the 3 survey years. Ultimately, there is no statistically significant slope-independent relationship between surface roughness and accumulation rates within our survey area. The observed correspondence between the small-scale temporal and spatial variability in surface roughness and backscatter, as evidenced by Ku-band radar signal strength retrievals, will make it difficult to develop elevation bias corrections for radar altimeter retrieval algorithms.
Viking Orbiter 2 images of the north polar region reveal an enormous sand sea (erg) covering an area of greater than 500,000 sq km around the perennial ice cap. All dunes are either transverse or barchan. The various dune morphologies and modifications of primary dune types reflect a wind regime having more than one wind direction. In the summer, two major wind directions prevail: (1) off-pole winds that become easterly due to coriolis forces and (2) on-pole winds that become westerly. During the winter and/or spring, only the on-pole winds exist. Strong winds greater than 75 m/s are required for sand accumulation to form the thick transverse dunes. The strongest winds in the north polar region are thought to exist during summer over the transverse dune field between 110 deg and 220 deg W; this area is a relatively warm belt (temperature greater than 230 K) between two ice zones (temperature less than 220 K). The lack of well-developed longitudinal dunes implies that the dune field is young. The relationship of the present dune field to the perennial ice indicates that the dunes began to form after the formation of the present ice cap.
A computerized simulation analysis for a number of scatterometer antenna configuration and polarization modes including the Seasat scatterometer (SASS) is presented. The results of the simulations were expressed in terms of performance statistics. These statistics relate to the wind direction alias removal capability and to the rms sensing errors for friction velocity and wind direction X. The statistics are analyzed, and optimum scatterometer configurations are recommended. The accuracy of the SASS in measuring U* and X, and its capability to resolve wind direction aliases are assessed.
A simplified algorithm is derived for retrieving wind vectors from microwave scatterometer observations. The azimuthal dependence of the sea-surface radar cross section is modeled by a double-cosine function, rather than the traditional second-order cosine expansion. The algorithm is tested using the aircraft scatterometer observations obtained during the AAFE-RADSCAT Experiment in 1975 and 1976. There is little difference between the performance of the simplified algorithm and the more involved least-squares searching algorithm. The AAFE-RADSCAT aircraft observations are sampled so as to simulate the three-look satellite scatterometer NSCAT that will be launched on the Japanese Advanced Earth Observing Satellite. The results of the retrievals indicate that it is probably not possible to uniquely determine the wind direction using just NSCAT observations because of a 180 degree ambiguity. However, if forecast models can predict the wind direction to an accuracy of +/- 90 deg, thereby eliminating the ambiguity, then the results indicate that NSCAT can determine the wind direction to an accuracy of about +/- 20 deg. Better performance is obtained when the three observations are the same polarization (either v-pol or h-pol), as compared to using a mix of v-pol and h-pol observations.
The present method used by the NACA for the measurement of sideslip angles in flight involves the use of a device called the yawmeter. The operation of this instrument depends on the motion of a free-swinging vane which, mounted ahead of the wing tip, alines itself with the local wind direction. Because of the flow pattern about the airplane, the local wind direction at the yaw vane may be slightly different from the direction of the relative wind and the yaw-vane readings may be in error. This error is corrected by using half the difference between the readings of two vanes, one on each wing, for unyawed flight as a calibration constant. It is possible, however, that, because of the change in location of the vane with respect to the flow pattern at large angles of yaw, the constant obtained for unyawed flight may not apply. The present report covers power-off tests made in the free-flight tunnel to check the validity of this method.
A description is given of the methods used to establish the statistical parameters and models for wind and various thermodynamic quantities at an altitude of 0-70 km for nine geographical locations. It is noted that wind is modeled as a vector quantity using the bivariate normal probability function. With the five parameters of the bivariate normal distribution, the distribution for wind speed is derived as a generalized Rayleigh distribution. In addition, the frequency of wind direction is derived, and the conditional distribution of wind speed given the wind direction is derived. It is pointed out that these and other wind models are consistent with the rigorous mathematical properties of the bivariate normal probability theory. The thermodynamic quantities are consistent with the hydrostatic equation and the equation of state for the mean values. With these methods, many statistical relationships can be derived.
Orientation, by beetles and scorpions, according to wind direction and force are analyzed. Major efforts were made to determine: (1) which physical qualities of the air current influence anemomenotaxis, (2) which physiological mechanism is responsible for such orientation, (3) which sense organs do beetles and scorpions use to perceive wind directions, and (4) what the biological significance of anemomenotaxis in the beetle and scorpion is. Experimental results show that the trichobothria in scorpions perceives wind direction; in the beetle it is perceived by sense organs excited by pendicellus-flagellum joint movements. A compensation mechanism is suggested as the basis for anemomenotactic orientation. It was also suggested that the biological significance of anemomenotaxis in scorpions is space orientation; while in beetles it was found to be part of the appetitive behavior used to search for olfactory sign stimuli.
In the past, wind measurements from space using fan-beam antennas, such as Seasat Scatterometer (SASS-1), ERS-1 &2, and NASA scatterometer (NSCAT), required up to six large stick-like antennas and suffered a nadir gap of up to 400 km. In the near future, a spinning pencil-beam scatterometer system is to be used for the SeaWinds scatterometer on QuikSCAT (QSCAT) and on ADEOS-2 (SeaWinds). This scatterometer, though offering wind measurements in the nadir region, still suffers from degraded performance in the nadir and outer swath. The purpose of this paper is to present an advanced polarimetric spinning pencil-beam scatterometer system, which can significantly improve the wind performance across the entire swath. The polarimetric scatterometer simultaneously measures co-polarized backscatter and the polarimetric correlation of co- and cross-polarized radar returns from the ocean surface. The advantage over the conventional scatterometer system is that, while the co-polarization radar returns are even function of the wind direction, the polarimetric correlation is an odd function of wind direction due to the reflection symmetry of the wind roughened surface. Therefore, this polarimetric scatterometer system can provide additional, equivalent measurements at azimuth angle 45degree away from the corresponding co-polarization measurements. The combined co-polarization and correlation measurements enable good wind performance across the whole swath to be obtained. In this paper, we will first present the theoretical formulation of all of the key components required for designing a polarimetric scatterometer. Then, we show that good wind performance can be achieved by a slight improvement in the signal-to-noise ratio of the current QSCAT/SeaWinds design. We then present the predicated wind performance using computer simulation based on a model function for the co-polarized backscatter obtained from actual spaceborne scatterometer data and an estimated model function for the polarimetric correlation based on the asymmetry observed in backscatter data. Finally, we will show that, aside from ocean applications, this polarimetric scatterometer can also be used for ice and land applications.
Several regression models were tested to explain the wind direction dependence of the 1975 JONSWAP (Joint North Sea Wave Project) scatterometer data. The models consider the radar backscatter as a harmonic function of wind direction. The constant term accounts for the major effect of wind speed and the sinusoidal terms for the effects of direction. The fundamental accounts for the difference in upwind and downwind returns, while the second harmonic explains the upwind-crosswind difference. It is shown that a second harmonic model appears to adequately explain the angular variation. A simple inversion technique, which uses two orthogonal scattering measurements, is also described which eliminates the effect of wind speed and direction. Vertical polarization was shown to be more effective in determining both wind speed and direction than horizontal polarization.