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Variable length data formats

The purpose of this paper is to discuss a number of variable length floating point and integer formats and to give the various advantages and disadvantages of their use. Often it is known in advance that a given integer will not exceed a certain magnitude or that a particular floating point number is accurate to only 'n' places of accuracy. Faced with this, it is good engineering to choose variable length floating point and integer formats which require the least amount of hardware or the minimum amount of software or which have some other dominant advantage. The formats discussed have the advantage that length change algorithms are invariant with respect to data types (unsigned, signed, floating point, integers, and complex numbers). The STARAN associative array processor, which uses a completely variable fixed point and floating point formats, is described.

Brakefield, J. C.↗

The Physical Interpretation of X-Ray Phase Lags and Coherence: RXTE Observations of Cygnus X-1 as a Case Study

There have been a number of recent spectral models that have been successful in reproducing the observed X-ray spectra of galactic black hole candidates (GBHC). However, there still exists controversy over such issues as: what are the sources of hard radiation, what is the system's geometry, is the accretion efficient or inefficient, etc. A potentially powerful tool for distinguishing among these possibilities, made possible by the Rossi X-ray Timing Explorer (RXTE), is the variability data, especially the observed phase lags and variability coherence. These data, in conjunction with spectral modeling, have the potential of determining physical sizes of the system, as well as placing strong constraints on both Compton corona and advection models. As an example, we present RXTE variability data of Cygnus X-1.

Nowak, M. A.↗

Bundle Data Approach at GES DISC Targeting Natural Hazards

Severe natural phenomena such as hurricane, volcano, blizzard, flood and drought have the potential to cause immeasurable property damages, great socioeconomic impact, and tragic loss of human life. From searching to assessing the Big, i.e., massive and heterogeneous scientific data (particularly, satellite and model products) in order to investigate those natural hazards, it has, however, become a daunting task for Earth scientists and applications researchers, especially during recent decades. The NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) has served Big Earth science data, and the pertinent valuable information and services to the aforementioned users of diverse communities for years. In order to help and guide our users to online readily (i.e., with a minimum effort) acquire their requested data from our enormous resource at GES DISC for studying their targeted hazard event, we have thus initiated a Bundle Data approach in 2014, first targeting the hurricane event topic. We have recently worked on new topics such as volcano and blizzard. The bundle data of a specific hazard event is basically a sophisticated integrated data package consisting of a series of proper datasets containing a group of relevant (knowledge--based) data variables readily accessible to users via a system-prearranged table linking those data variables to the proper datasets (URLs). This online approach has been developed by utilizing a few existing data services such as Mirador as search engine; Giovanni for visualization; and OPeNDAP for data access, etc. The online Data Cookbook site at GES DISC is the current host for the bundle data. We are now also planning on developing an Automated Virtual Collection Framework that shall eventually accommodate the bundle data, as well as further improve our management in Big Data.

GES DISC↗

Dataset from ORNL Flexible Research Platform (FRP)

The data comes from a two-story light commercial building which can be used to physically simulate light commercial buildings common in the nation's existing building stock. Based on a data collection plan, these measurements were performed for five different building operations. In the data set for each period, 98 data variables were selected and collected, in which 7 variables are weather data and the rest are all building and system operation data.

Cui, Borui↗

A Quarter Century of Wind Spacecraft Discoveries

The Wind spacecraft, launched on November 1, 1994, is a critical element in NASA’s Heliophysics System Observatory (HSO)—a fleet of spacecraft created to understand the dynamics of the Sun-Earth system. The combination of its longevity (>25 years in service), its diverse complement of instrumentation, and high resolution and accurate measurements has led to it becoming the “standard candle” of solar wind measurements. Wind has over 55 selectable public data products with over ∼1,100 total data variables (including OMNI data products) on SPDF/CDAWeb alone. These data have led to paradigm shifting results in studies of statistical solar wind trends, magnetic reconnection, large-scale solar wind structures, kinetic physics, electromagnetic turbulence, the Van Allen radiation belts, coronal mass ejection topology, interplanetary and interstellar dust, the lunar wake, solar radio bursts, solar energetic particles, and extreme astrophysical phenomena such as gamma-ray bursts. This review introduces the mission and instrument suites then discusses examples of the contributions by Wind to these scientific topics that emphasize its importance to both the fields of heliophysics and astrophysics.

Lynn B. Wilson III↗

Timeseries Unlabeled and Labeled Photos, Modeled Stream Elevation, and (Meta)Data of Variably Inundated Streams Across The Yakima River Basin, Washington, United States (v2)

This dataset is associated with the “River Monitoring Photos” (RMP) study and subsequent manuscript (Bao et al. 2025. Monitoring river flow status using low-cost wildlife camera and image segmentation artificial intelligence doi: 10.1016/j.envsoft.2025.106715). Game camera timeseries photos were collected to evaluate stream variable inundation via changes in width. A subset of photos was labeled for training the YOLOv8 and Mask2Former models and used to segment water surface fractions from all the game camera photos.This data package was originally published in March 2024. It was updated in October 2025 (v2) to add additional photos and files associated with the manuscript (i.e., processed data, labeled photos, and trained models). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to a readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; and (5) folders containing game camera photos and manuscript-associated files. Each Yakima River Basin site has a folder that contains subfolders for each month photos were collected. There is also a folder for files associated with the manuscript which has subfolders for labeled data, trained models, Yakima River Basin site water surface fractions, and USGS site water surface fractions. All files are .csv, .json, .txt, .yaml, .pth, .pt, or .pdf. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

Rain attenuation measurements: Variability and data quality assessment

Year to year variations in the cumulative distributions of rain rate or rain attenuation are evident in any of the published measurements for a single propagation path that span a period of several years of observation. These variations must be described by models for the prediction of rain attenuation statistics. Now that a large measurement data base has been assembled by the International Radio Consultative Committee, the information needed to assess variability is available. On the basis of 252 sample cumulative distribution functions for the occurrence of attenuation by rain, the expected year to year variation in attenuation at a fixed probability level in the 0.1 to 0.001 percent of a year range is estimated to be 27 percent. The expected deviation from an attenuation model prediction for a single year of observations is estimated to exceed 33 percent when any of the available global rain climate model are employed to estimate the rain rate statistics. The probability distribution for the variation in attenuation or rain rate at a fixed fraction of a year is lognormal. The lognormal behavior of the variate was used to compile the statistics for variability.

Crane, Robert K.↗

Nickel Cadmium Cell Design Variable Program Data Analysis

A program was undertaken to evaluate eight of the more important nickel-cadmium cell designs that are currently being used or that have been used during the past 15 years. Design variables tested in this program included teflonated negative plates, silver treated negative plates, light plate loading level, no positive plate cadmium treatment, plate design of 1968, utilizing both old and new processing techniques, and electrochemically impregnated positive plates. The data acquired from these test packs in a low Earth orbit cycling regime is presented and analyzed here. This data showed conclusively that the cells manufactured with no positive plate cadmium treatment outperformed all other cell designs in all aspects of the program and that the cells with teflonated negative electrodes performed very poorly.

Morrow, G. W.↗

An Approach to Evaluate Precision and Inter-Laboratory Variability of Flammability Test Methods for Aerospace Materials

Materials selection for spacecraft is based on conventional flammability or ignition sensitivity acceptance tests. Current procedures for determining the inter-laboratory repeatability and reproducibility of aerospace materials flammability tests are not considering the dependence of data variability on test conditions and consequently attempts to characterize the precision of these methods were not successful. The inter-laboratory data variability is determined with tests conducted under arbitrary conditions, which consequently may not provide sufficient information to enable adequate determination of a method's precision. For evaluating the precision of NASA's flammability test methods, the protocol recommended includes selecting critical parameters and determining the 50% failure point by considering the specific failure criteria of each method using the critical parameter as a variable. Upon performing inter-laboratory round robin testing using this approach, the laboratories' performance could be evaluated by comparing the repeatability of the 50% failure point and/or the repeatability of critical conditions where the probabilities of passing and failing are unity, i.e., the transition zone repeatability. When a sufficient amount of data has been acquired with this method, an adequate estimation of precision of aerospace materials flammability test methods will be possible.

Hirsch, David↗

Nickel-Cadmium Cell Design Variable Program Data Analysis

A program was undertaken in conjunction with the General Electric Company to evaluate 9 of the more important nickel cadmium aerospace cell designs that are currently being used or that have been used in the past 15 years. Design variables tested in this program included teflonated negative plates, silver treated negative plates, light plate loading level, no positive plate cadmium treatment, plate design of 1968 utilizing both old and new processing techniques, and electrochemically impregnated positive plates. The data acquired from these test packs in a low Earth orbit cycling regime is presented and analyzed here. This data showed conclusively that the cells manufactured with no positive plate cadmium treatment outperformed all other cell designs in all aspects of the program and that the cells with teflonated negative electrodes performed very poorly.

Morrow, G. W.↗

Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability: Supporting Data and Code

This repository contains R code and associated datasets for reproducing the analysis described in the manuscript titled “Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability” (DOI: 10.1029/2024JG008604). The provided scripts facilitate a comprehensive analysis of snow depth variability influenced by microtopography and vegetation distribution in a subarctic watershed. Included datasets are high-resolution spatial maps of snow depth, terrain elevation, vegetation height, and distance from shrubs taller than 1 meter, all formatted as text files (.txt). These data are fully describe in doi:10.15485/2316038. Users can adapt the provided R scripts to accommodate different data formats or larger spatial domains, noting that some output files may require modification due to their size.The code includes implementations for boosted regression tree analysis adapted from methods outlined in Elith et al. (2008). Users interested in understanding or modeling landscape-scale snow distribution patterns, particularly in Arctic or subarctic ecosystems, will find this package useful. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Federated Giovanni: A Distributed Web Service for Analysis and Visualization of Remote Sensing Data

The Geospatial Interactive Online Visualization and Analysis Interface (Giovanni) is a popular tool for users of the Goddard Earth Sciences Data and Information Services Center (GES DISC) and has been in use for over a decade. It provides a wide variety of algorithms and visualizations to explore large remote sensing datasets without having to download the data and without having to write readers and visualizers for it. Giovanni is now being extended to enable its capabilities at other data centers within the Earth Observing System Data and Information System (EOSDIS). This Federated Giovanni will allow four other data centers to add and maintain their data within Giovanni on behalf of their user community. Those data centers are the Physical Oceanography Distributed Active Archive Center (PO.DAAC), MODIS Adaptive Processing System (MODAPS), Ocean Biology Processing Group (OBPG), and Land Processes Distributed Active Archive Center (LP DAAC). Three tiers are supported: Tier 1 (GES DISC-hosted) gives the remote data center a data management interface to add and maintain data, which are provided through the Giovanni instance at the GES DISC. Tier 2 packages Giovanni up as a virtual machine for distribution to and deployment by the other data centers. Data variables are shared among data centers by sharing documents from the Solr database that underpins Giovanni's data management capabilities. However, each data center maintains their own instance of Giovanni, exposing the variables of most interest to their user community. Tier 3 is a Shared Source model, in which the data centers cooperate to extend the infrastructure by contributing source code.

Giovanni↗

Development of an Uncertainty Model for the National Transonic Facility

This paper introduces an uncertainty model being developed for the National Transonic Facility (NTF). The model uses a Monte Carlo technique to propagate standard uncertainties of measured values through the NTF data reduction equations to calculate the combined uncertainties of the key aerodynamic force and moment coefficients and freestream properties. The uncertainty propagation approach to assessing data variability is compared with ongoing data quality assessment activities at the NTF, notably check standard testing using statistical process control (SPC) techniques. It is shown that the two approaches are complementary and both are necessary tools for data quality assessment and improvement activities. The SPC approach is the final arbiter of variability in a facility. Its result encompasses variation due to people, processes, test equipment, and test article. The uncertainty propagation approach is limited mainly to the data reduction process. However, it is useful because it helps to assess the causes of variability seen in the data and consequently provides a basis for improvement. For example, it is shown that Mach number random uncertainty is dominated by static pressure variation over most of the dynamic pressure range tested. However, the random uncertainty in the drag coefficient is generally dominated by axial and normal force uncertainty with much less contribution from freestream conditions.

Walter, Joel A.↗

Arctic Impact Identification with Less Data Using Variable Relationships: An Exploratory Express LDRD project.

Regional impacts from sea ice loss can be challenging to separate from internal climate variability, potentially requiring thousands of ensemble members. East Asian wintertime cooling has been linked to sea ice loss from present day conditions in the Polar Amplification Model Intercomparison Project with these large ensemble counts. This cooling is theorized to arise from a strengthened Siberian High and East Asian Jet response. The strengthened Siberian High can be detected with one fifth the ensemble members needed for the East Asian wintertime cooling in a single model. We thus hypothesize that leveraging relationships between multiple variables in a conditional pathways-based approach would reduce the number of required ensemble members to conclusively attribute East Asian wintertime cooling to future sea ice concentrations. In all analyzed cases, confidence was increased when evaluating sea ice loss’s responsibility for the joint effects of East Asian cooling, East Asian Jet strengthening, and Siberian High strengthening over just East Asian cooling. However, we were not able to confidently attribute future East Asian wintertime cooling to sea ice loss in a single model. We found that significant intra-ensemble variability within single Earth System Models (ESMs) produced highly uncertain forcing response models upon which attribution results were undermined. We were able to show that ensemble mean seasonally averaged metrics from multiple ESMs greatly improved the accuracy of the forcing response linear models and exposed the necessity of all three steps in the pathway (sea ice area, Siberian High pressure, and East Asian Jet speed) for accurate prediction of East Asian wintertime cooling. Although all three steps were necessary, East Asian wintertime cooling possesses a large dependence on the Siberian High pressure, which weakens the confidence associated with overall strong joint-attribution comparing present day and future scenarios. We believe transitioning the pathway nodes to relative changes between the Siberian High and Aleutian Low as well as between the midlatitude westerlies and subtropical jet in the East Asianj Jet region may be able to produce significant attribution more fully dependent upon all three steps. Ultimately, this research demonstrates the simple extensibility of conditional pathways-based attribution to sea ice loss forcing on the Earth system.

54 ENVIRONMENTAL SCIENCES↗

Validating of Atmospheric Signals Associated with some of the Major Earthquakes in Asia (2003-2009)

The recent catastrophic earthquake in Haiti (January 2010) has provided and renewed interest in the important question of the existence of precursory signals related to strong earthquakes. Latest studies (VESTO workshop in Japan 2009) have shown that there were precursory atmospheric signals observed on the ground and in space associated with several recent earthquakes. The major question, still widely debated in the scientific community is whether such signals systematically precede major earthquakes. To address this problem we have started to validate the anomalous atmospheric signals during the occurrence of large earthquakes. Our approach is based on integration analysis of several physical and environmental parameters (thermal infrared radiation, electron concentration in the ionosphere, Radon/ion activities, air temperature and seismicity) that were found to be associated with earthquakes. We performed hind-cast detection over three different regions with high seismicity Taiwan, Japan and Kamchatka for the period of 2003-2009. We are using existing thermal satellite data (Aqua and POES); in situ atmospheric data (NOAA/NCEP); and ionospheric variability data (GPS/TEC and DEMETER). The first part of this validation included 42 major earthquakes (M greater than 5.9): 10 events in Taiwan, 15 events in Japan, 15 events in Kamchatka and four most recent events for M8.0 Wenchuan earthquake (May 2008) in China and M7.9 Samoa earthquakes (Sep 2009). Our initial results suggest a systematic appearance of atmospheric anomalies near the epicentral area, 1 to 5 days prior to the largest earthquakes, that could be explained by a coupling process between the observed physical parameters, and the earthquake preparation processes.

Ouzounov, D. P.↗