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Generalized Einstein equations invariant under scale transformations are presented, and several astrophysical tests studied. It is assumed that the dynamics of atoms or clocks used as measuring apparatus is given a priori. Connection with gauge fields and broken symmetries is made through the cosmological constant.
Geological data are used as cosmological determinants in a study of the temperature of the early earth (2.3 to 4.5 billion years ago). It is known that the energy output of the sun during that period was on the order of 30-40% lower than at present, and deduced that the mean temperature of the earth should have fallen to as low as 245 K, i.e., below the freezing point of seawater. Strong evidence exists, however, to indicate that algae (therefore liquid water) was present. To reconcile the discrepancies, a model is proposed whereby terrestrial G and M vary. It is further noted that atmosphere H2 may be a better agent than NH3 for producing a greenhouse effect.
A program is described which is intended to derive a generalized system of gravitational equations that allow (but do not require) G to vary, to use the 3-K blackbody radiation to fix the relation between G and the gauge function, and to employ Dirac's (1937) Large Numbers Hypothesis to derive the geometry of the universe. Einstein's equations are retained in their total integrity, but the specification is made that they are valid only when gravitational units are used. A scale-invariant form of Einstein's equations is obtained, and from this are derived the energy conservation law, the baryon-number conservation law, and the appropriate cosmological equations. Dirac's proposals of 1937 and 1973 are incorporated into the formalism, and a gauge based on consolidation of the 3-K blackbody radiation is presented. A unique solution for the geometry of the universe is determined for zero curvature solely from the 3-K radiation and the Large Numbers Hypothesis; this solution predicts a deceleration parameter exactly equal to unity.
There are no author-identified significant results in this report.
There are no author-identified significant results in this report.
Statistical structure functions have been computed independently for nine satellite-derived mesoscale wind fields that were obtained on two different days. Small cumulus clouds were tracked at 5 min intervals, but since these clouds occurred primarily in the warm sectors of midlatitude cyclones the results cannot be considered representative of the circulations within cyclones in general. The field structure varied considerably with time and was especially affected if mesoscale features were observed. The wind fields on the 2 days studied were highly anisotropic with large gradients in structure occurring approximately normal to the mean flow. Structure function calculations for the combined set of satellite winds were used to estimate random error present in the fields. It is concluded for these data that the random error in vector winds derived from cumulus cloud tracking using high-frequency satellite data is less than 1.75 m/s. Spatial correlation functions were also computed for the nine data sets. Normalized correlation functions were considerably different for u and v components and decreased rapidly as data point separation increased for both components. The correlation functions for transverse and longitudinal components decreased less rapidly as data point separation increased.
The requirements and limitations of employing an airborne laser ranging system for detecting crustal shifts of the Earth within centimeters over a region of approximately 200 by 400 km are presented. The system consists of an aircraft which flies over a grid of ground deployed retroreflectors, making six passes over the grid at two different altitudes. The retroreflector baseline errors are assumed to result from measurement noise, a priori errors on the aircraft and retroreflector positions, tropospheric refraction, and sensor biases.
A model based on multiple regression was developed to estimate wheat yields for the wheat growing states of Rio Grande do Sul, Parana, and Santa Catarina in Brazil. The meteorological data of these three states were pooled and the years 1972 to 1979 were used to develop the model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature.
A model based on multiple regression was developed to estimate soybean yields for the seven soybean-growing states of Brazil. The meteorological data of these seven states were pooled and the years 1975 to 1980 were used to model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation and monthly average temperature.
Friedland's technique for estimating the unknown noise variances of a linear system using multiple observers has been extended by developing a general solution for the estimates of the variances, developing the statistics (mean and standard deviation) of these estimates, and demonstrating the solution on two examples.
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The TOPEX/Poseidon satellite oceanography mission will require very accurate orbit determination in order to fulfill its mission requirements of altimetrically mapping the ocean surface with approximately 10 centimeter accuracy. To meet such stringent orbit determination specifications will require very accurate tracking data and very accurate dynamical models of the satellite motion. The accuracy of the TOPEX/Poseidon orbit is expected to be driven by the accuracy of the earth's gravity field model. Expected orbit accuracy for several recent gravity models is presented. Both the capability of the models for modeling the motion of TOPEX/Poseidon and their global modeling characteristics are discussed. In addition, the gravity model improvement that can be expected by utilizing GPS tracking of TOPEX/Poseidon is evaluated. This evalution is based on a recent simulation of a gravity field recovery using 10 days of TOPEX/Poseidon GPS tracking.
This paper discusses the biophysical stratification of the FIFE site, implementation of the stratification utilizing geographic information system methods, and validation of the stratification with respect to field measurements of biomass, Bowen ratio, soil moisture, and the greenness vegetation index (GVI) derived from TM satellite data. Maps of burning and topographic position were significantly associated with variation in GVI, biomass, and Bowen ratio. The stratified design did not significantly alter the estimated site-wide means for surface climate parameters but accounted for between 25 and 45 percent of the sample variance depending on the variable.
Simultaneous ultraviolet and optical observations of 10 bright O stars were organized in several observing campaigns lasting 3-6 days each. The observing campaigns included 12 observatories in the Northern hemisphere obtaining high resolution spectroscopy, photometry, and polarimetry, as well as 24-hour coverage with the IUE (International Ultraviolet Explorer) observatory. Over 600 high dispersion SWP spectra were acquired with IUE at both NASA and VILSPA for the completion of this work. The massive amount of data from these observing campaigns, both from IUE and the ground-based instruments, has been reduced and analyzed. The accompanying paper describes the data acquisition, analysis, and conclusions of the study performed. The most important results of this study are the strong confirmation of the ubiquitous variability of winds of O stars, and the critical correlation between rotation of the star and the wind variability as seen in the ultraviolet and optical spectral lines.
We present a cosmological model with good physical properties which is invariant not only under changes of the space and time coordinates but also under changes of an extra (Kaluza-Klein) coordinate related to rest mass. In frames where the latter is chosen to be constant we recover standard cosmology. In frames where it is chosen to be variable we obtain new astrophysical effects and gain insight into the nature of the big bang.
The extended Kalman filter (EKF) is the basis for many applications of filtering theory to real-time problems where estimates of the state of a dynamical system are to be computed based upon some set of observations. The form of the EKF may vary somewhat from one application to another, but the fundamental principles are typically unchanged among these various applications. As is the case in many filtering applications, models of the dynamical system (differential equations describing the state variables) and models of the relationship between the observations and the state variables are created. These models typically employ a set of constants whose values are established my means of theory or experimental procedure. Since the estimates of the state are formed assuming that the models are perfect, any modeling errors will affect the accuracy of the computed estimates. Note that the modeling errors may be errors of commission (errors in terms included in the model) or omission (errors in terms excluded from the model). Consequently, it becomes imperative when evaluating the performance of real-time filters to evaluate the effect of modeling errors on the estimates of the state.
During the lifetime of the Coastal Zone Color Scanner, there were 21 instances in which both satellite-derived ocean color and sea-surface temperature are simultaneously available over large areas of the Sargasso Sea. These images reveal close correspondence between mesoscale structures observed in temperature and pigment fields. In general, higher (lower) pigment biomass occurs in mesoscale features consisting of cold (warm) temperature anomalies. This relationship is consistent with the idea that upward displacement of isopycnals at the base of the euphotic zone by mesoscale eddies is an important mechanism of nutrient supply in the region.
The contents include: 1. State space, spectral space, and observation space; 2. Variances and correlations; 3. Isotropic and anisotropic correlation modeling on the sphere; 4. Operational ozone data assimilation; and 5. Kalman filtering for trace constituents.