A summary of ground-loads statistics
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This paper, the first of three, describes the cloud detection part of the International Satellite Cloud Climatology Project (ISCCP) analysis. Key features of the cloud detection alogrithm are (1) use of space and time radiance variation tests over several different space and time domains to account for the global variety of cloudy and clear characteristics, (2) estimation of clear radiance values for every time and place, and, (3) use of radiance thresholds that vary with the type of surface and climate regime. Design of the detection algorithm was supported by global, multiyear surveys of the statistical behavior of satellite-measured infrared and visible radiances to determine those characteristics that differentiate cloudy and clear scenes and how these characteristics vary among climate regimes. A summary of these statistical results is presented to illustrate how the cloud detection method works in a variety of circumstances. The sensitivity of the results to changing test parameter values is determined to provide a first estimate of the uncertainty of ISCCP cloud amounts. These test results (which exclude polar regions) suggest detection uncertainties of about 10% with possible negative biases of 5% (especially at night).
Statistics compiled from Nimbus-6 temperature retrievals processed during the 18 August-4 September 1975 DST-5, and the 1 February-4 March 1976 DST-6 are addressed. All statistics were compiled from samples of colocated satellite sounding and radiosonde measurements. The colocation window is 222 km in space and 6 hours in time.
Advanced structural reliability methods are utilized on the Probabilistic Structural Analysis Methods (PSAM) project to provide a tool for analysis and design of space propulsion system hardware. The role of the effort at the University of Arizona is to provide reliability technology support to this project. PSAM computer programs will provide a design tool for analyzing uncertainty associated with thermal and mechanical loading, material behavior, geometry, and the analysis methods used. Specifically, reliability methods are employed to perform sensitivity analyses, to establish the distribution of a critical response variable (e.g., stress, deflection), to perform reliability assessment, and ultimately to produce a design which will minimize cost and/or weight. Uncertainties in the design factors of space propulsion hardware are described by probability models constructed using statistical analysis of data. Statistical methods are employed to produce a probability model, i.e., a statistical synthesis or summary of each design variable in a format suitable for reliability analysis and ultimately, design decisions.
We will examine the validity of means and standard deviations as a basis for climate data products. We will explore the conditions under which these two simple statistics are inadequate summaries of the underlying empirical probability distributions by contrasting them with a nonparametric, method called Deterministic Annealing technique
An Interactive Cluster Analysis Procedure (ICAP) was developed to derive classifier training statistics from remotely sensed data. The algorithm interfaces the rapid numerical processing capacity of a computer with the human ability to integrate qualitative information. Control of the clustering process alternates between the algorithm, which creates new centroids and forms clusters and the analyst, who evaluate and elect to modify the cluster structure. Clusters can be deleted or lumped pairwise, or new centroids can be added. A summary of the cluster statistics can be requested to facilitate cluster manipulation. The ICAP was implemented in APL (A Programming Language), an interactive computer language. The flexibility of the algorithm was evaluated using data from different LANDSAT scenes to simulate two situations: one in which the analyst is assumed to have no prior knowledge about the data and wishes to have the clusters formed more or less automatically; and the other in which the analyst is assumed to have some knowledge about the data structure and wishes to use that information to closely supervise the clustering process. For comparison, an existing clustering method was also applied to the two data sets.
An Interactive Cluster Analysis Procedure (ICAP) was developed to derive classifier training statistics from remotely sensed data. ICAP differs from conventional clustering algorithms by allowing the analyst to optimize the cluster configuration by inspection, rather than by manipulating process parameters. Control of the clustering process alternates between the algorithm, which creates new centroids and forms clusters, and the analyst, who can evaluate and elect to modify the cluster structure. Clusters can be deleted, or lumped together pairwise, or new centroids can be added. A summary of the cluster statistics can be requested to facilitate cluster manipulation. The principal advantage of this approach is that it allows prior information (when available) to be used directly in the analysis, since the analyst interacts with ICAP in a straightforward manner, using basic terms with which he is more likely to be familiar. Results from testing ICAP showed that an informed use of ICAP can improve classification, as compared to an existing cluster analysis procedure.
The Primary goal of the Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) effort is to provide basic validation of satellite-derived precipitation measurements over monthly climatologies. To this end, the Joint Center for Earth Systems Technology (JCET) at the University of Maryland, Baltimore County produces monthly rainfall accumulation reference products for each of the four primary TRMM GV sites. These products, standard methodology for deriving monthly, gauge-adjusted rainfall products, are utilized for each primary site. The monthly rainfall GV reference products are developed in discrete, modular steps with distinct intermediate products. These developmental steps, which will be fully discussed, include: (1) extracting radar data over locations of rain gauges, (2) merging rain gauge and radar data in time and space with user-defined options, (3) quality control of radar and gauge merged data by tracking accumulations from each instrument, and (4) deriving Z_R relationship from quality-controlled merged data over monthly time scales. A summary of all gauge statistics and GV rainfall reference products available for TRMM science users will be presented. Basic reference product results and trends involving monthly accumulation, Z-R relationship, and gauge statistics for primary GV site will be discussed. Finally, the sample impact on monthly rainfall reference products, through varying the time interval between intermediate rainfall accumulations, will be analyzed and presented.
This study compares two statistical models to construct summary dose-response curves for low boom community noise surveys. Data from two NASA field surveys are used that consist of multiple responses per survey participant. These data require an approach that accounts for the correlation among repeated annoyance observations from the same participant. A multilevel model accounts for the correlation by allowing estimated parameters to vary with each survey participant. On the other hand, a population average model utilizes generalized estimating equations and accounts for the correlation via a userspecified within-subject correlation structure. A visual comparison of the dose-response curves for these two methods reveals similar results. When comparing specific points along the summary curves, the multilevel model yields more precise confidence bounds than the population average model. The similarity between the summary curves derived from each model lends validity to both approaches for approximating a population representative summary curve, though modeling assumptions may lend favor to the multilevel logistic modeling approach over the population average model.
Deep convection in the Asian summer monsoon (ASM) rapidly transports boundary layer pollutants including ozone-depleting substances into the upper troposphere and lower stratosphere (UTLS). The confinement of the seasonal anticyclonic circulation in the UTLS over Asia initially traps the pollutants near the tropopause level, but air masses are subsequently transported throughout the global stratosphere and impact Earth’s climate. Characterizing the transport pathways and processes of these pollutants are critical for identifying source regions and quantifying regional contributions to global stratospheric concentrations. The Asian summer monsoon Chemical and Climate Impact Project (ACCLIP) was conducted in summer 2022 using two high-altitude aircraft (NSF NCAR Gulfstream V and the NASA WB-57) to obtain UTLS chemical composition and aerosol distribution for characterizing the impact of the ASM on global chemistry and climate. Backward trajectories from ACCLIP flight tracks were traced through time-varying, satellite-derived global convective cloud top altitude fields to investigate the convective air mass origins of the sampled air parcels. Analyses reveal that air masses lofted by convection within the ASM (South Asian summer monsoon) and near the edge of the of the ASM anticyclone (East Asian summer monsoon) contributed to the airborne observations. In this study, we present a summary of the transport statistics of UTLS air masses sampled during ACCLIP and discuss the implications of these results on our understanding of the role of ASM in global constituent transport.
Part 1 gives details of models tested and methods of testing of the Eiffel 36 wing alone and the JN2 aircraft. Characteristics and performance curves for standard JN are included. Part 2 presents a statistical analysis of the following: lift and drag contributed by body and chassis tested without wings; lift and drag contributed by tail, tested without wings; the effect on lift and drift of interference between the wings of a biplane combination; lift and drag contributed by the addition of body, chassis, and tail to a biplane combination; total parasite resistance; effect of varying size of tail, keeping angle of setting constant; effect of varying length of body and size of tail at the same time, keeping constant moment of tail surface about the center of gravity; forces on the tail and the effects of downwash; effect of size and setting of tail on statical longitudinal stability effects of length of body on stability; the effects of the various elements of an airplane on longitudinal stability and the placing of the force vectors. Part 3 presents the fundamental principals of dynamical stability; computations of resistance derivatives; solution of the stability equation; dynamical stability of the Curtiss JN2; tabulation of resistance derivatives; discussion of the resistance derivatives; formation and solution of stability equations; physical conceptions of the resistance derivatives; elements contributing to damping and an investigation of low speed conditions. Part 4 includes a summary of the results of the statistical investigation and a summary of the results for dynamic stability.
The following subject areas are covered: summary of the NASA program goals and objectives; major mission performance; USSR spaceflights; summary comparisons of the USA and USSR space records; and selected technical, financial, and manpower data.
The program developed to analyze magnetic field data from the magnetic field experiment flown in IMP F is reported. The analysis converts the raw X, Y, Z sensor data as received on the magnetic field experiment tape into vector measurements of the ambient magnetic field observed by the experiment. These data are computed for four frames of reference -- apparent, payload, solar ecliptic and solar magnetospheric. In addition 20.45 second statistics are computed for the last three coordinate systems. Finally, a summary tape is produced containing detailed data and sequence statistics as well as the output from the autocorrelation computer, trajectory data and identification information.
The use of light curves to characterize the dynamics of asteroids is discussed in a review of recent statistical and theoretical investigations. The summary, detailed, and bibliographic lists comprising the IAU light-curve data set are briefly characterized, and studies of rotation rates, shapes and pole positions, and phase relations are surveyed. Rotation-rate differences among the taxonomic classes and with asteroid size are noted, along with a wide dispersion of rotation rates in objects smaller than about 100 km.
Work was completed on the height tendency diagnoses of two extratropical cyclones that occurred upstream from the blocking event studied previously. One developed explosively over water 60 to 36 hours before the block first appeared, while the second developed explosively over the southeastern United States during the time of block formation. In both cases, both vorticity and temperature advection were consistently important forcing mechanisms. This is in contrast to the block itself, in which vorticity advection was easily the dominant forcing mechanism. Latent heat release was also significant, accounting for about 50 percent of the total height falls in the cyclone below 850 mb. Estimates of latent heat release were greatly enhanced by coupling parameterized estimates with values derived from GOES IR data using an algorithm developed by Marshall's F. R. Robertson. Among the difficulties encountered in this work was the identification of an appropriate lower boundary condition for the solution of the height tendency equation. The zero value currently used tends to yield underestimates of the lower troposphere height tendencies. To address this problem a new diagnostic technique was developed in cooperation with Dr. Peter Zwack of the University of Quebec at Montreal. Based on an equation Dr. Zwack had previously developed (the Zwack-Okossi development equation), researchers now have a relationship that is completely consistent with the height tendency equation and provides estimates of lower boundary geostrophic vorticity or height tendencies. Finally, comparison of the SAT (satellite data) and NOSAT (no satellite data) analyses is progressing well. The present focus is on both the new diagnostic technique and the SAT/NOSAT comparisons. The former is being tested on the southeastern United States cyclone case previously mentioned and compared with the height tendency diagnoses already completed. The latter are being examined for the blocking case described in the publications cited in this summary. In addition to obtaining statistics that will allow general comparison of the two analyses, it will be possible to determine whether conclusions about the dynamics of the block development are influenced by the analysis set used.
NASA's Integrated Resilient Aircraft Control (IRAC) Project is one of four projects within the agency s Aviation Safety Program (AvSafe) in the Aeronautics Research Mission Directorate (ARMD). The IRAC Project, which was redesigned in the first half of 2007, conducts research to advance the state of the art in aircraft control design tools and techniques. A "Key Decision Point" was established for fiscal year 2007 with the following expected outcomes: document the most currently available statistical/prognostic data associated with icing for subsonic transport, summarize reports by subject matter experts in icing research on current knowledge of icing effects on control parameters and establish future requirements for icing research for subsonic transports including the appropriate alignment. This study contains: (1) statistical analyses of accident and incident data conducted by NASA researchers for this "Key Decision Point", (2) an examination of icing in other recent statistically based studies, (3) a summary of aviation safety priority lists that have been developed by various subject-matter experts, including the significance of aircraft icing research in these lists and (4) suggested future requirements for NASA icing research. The review of several studies by subject-matter experts was summarized into four high-priority icing research areas. Based on the Integrated Resilient Aircraft Control (IRAC) Project goals and objectives, the IRAC project was encouraged to conduct work in all of the high-priority icing research areas that were identified, with the exception of the developing of methods to sense and document actual icing conditions.
This study compares two statistical modeling approaches to construct summary dose-response curves for low boom community noise surveys. NASA field survey data were used that consist of multiple responses from a survey participant. These data require an approach that accounts for the correlation among repeated annoyance observations from the same participant. A multilevel model accounts for the correlation by allowing estimated parameters to vary with each survey participant. On the other hand, a population average model utilizes generalized estimating equations and accounts for the correlation via a user-specified within-subject correlation structure. A visual comparison of the dose-response curves for these two methods reveals similar results. When comparing specific points along the summary curves, the multilevel model yields more precise confidence bounds than the population average model. The similarity between the summary curves derived from each model lends validity to both approaches for approximating a population representative summary curve.
Effects of porosity level on weld joint performance