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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

EVA Planning: Using Neutral Buoyancy Laboratory (NBL) Training to Predict in-Flight Energy Expenditure

Metabolic rate (“met rate”) is the amount of energy expended over a period of time and is influenced by many factors including body composition, level of physical activity, resting metabolic rate, sex, age, and food intake. Met rate is measured during Extravehicular Activity (EVA) training at the Neutral Buoyancy Laboratory (NBL) and during in-flight EVAs through indirect calorimetry, calculating energy expenditure from respiratory measurements of O 2 consumption and/or CO 2 production. During Extravehicular Activity (EVA) planning, metabolic cost is important to consider and is used to inform EVA duration based on spacesuit consumables associated with life support systems. Currently, NBL and previous ISS EVA met rate data for specified crewmembers are utilized to predict in-flight EVA metabolic costs based on a proposed EVA timeline. Timeline data collected during training is used to relate met rates to specific EVA activities, which are in turn assigned to more generalized EVA task categories, categorizing by both task type and restraint type. EVA task categories include EVA Setup/Cleanup, Worksite Setup/Cleanup, Cable Routing, Bolts, Fluid Connectors, Electrical Connectors, R&R Work, Miscellaneous Work, Incapacitated Crew Rescue (being rescued or performing), Assisted Crew Rescue (being assisted or performing), and Translation. Restraint types consist of Free-Float, Body Restraint Tether (BRT), Articulating Portable Foot Restraint (APFR), and Space Station Remote Manipulator System (SSRMS). From a crewmember’s historical data, individualized 10th, 50th and 90th percentile met rate estimates are generated for each task category and used to estimate the proposed EVA timeline metabolic cost. In-flight metabolic data (“As-Executed”) from recent ISS US EVAs 85-88 (totaling eight EVA crewmember met rates) was compared with their predicted metabolic cost (“As-Planned”) to evaluate the accuracy of the current met rate estimation method. Across the four EVAs, As-Executed Cumulative EVA Total Metabolic Cost (M = 5893.78 BTU, SD = 816.60) was not significantly different compared to As-Planned Cumulative EVA Total Metabolic Cost (M = 6106.60 BTU, SD = 826.62; t(7) = 0.751 , p = .477). Though not a significant difference, generally, As-Planned total estimates were slightly higher than As-Executed total metabolic cost. Relative Error for Cumulative EVA Total Metabolic Cost ranged from -33% to 14.7%, depending on the crewmember and EVA. When comparing As-Planned to A-Executed EVA task categories for Bolts, Electrical Connectors, EVA Cleanup, EVA Setup, Miscellaneous Work, Translation, Worksite Cleanup, and Worksite Setup during these EVAs, no significant differences were observed, however, there was a significant difference in As-Planned (M = 783.71 BTU, SD = 408.88) compared to As-Executed (M = 608.87 BTU, SD = 425.29) metabolic cost for the task category of Repair-and-Replace (R&R) Work (t(17) = 3.21 , p = .005). Looking closer within the R&R Work task category, As-Executed R&R Work with Free-Float restraint type (M = 706.17 BTU, SD = 352.18) was significantly less than As-Planned R&R Work with Free-Float restraint type (M= 887.96 BTU, SD = 381.42; t(12) = 2.59, p < .024). As-Executed R&R Work with SSRMS Restraint type (M = 355.89 BTU, SD = 534.65) was not significantly different from As-Planned values (M = 512.69 BTU, SD = 383.34; t(4) = 1.88, p = 0.132). These findings suggest that the energy expended performing R&R Work (Free-Float) is lower in flight than predicted. Accurate predictions of the metabolic cost of EVA are essential for planning and executing successful ISS EVAs. Overall, the current met rate prediction method is similar to actual in-flight values, slightly erring on the side of overestimation. Future work includes analysis of more historical in-flight EVA data to increase the power of the analysis, evaluating the NBL-ISS met rate conversion factor between NBL and ISS tasks, as well as exploring methods of substitution when crewmembers are missing prior task category data.

Lauren Cox↗
NASA NTRS1980

Remote sensing of benthic microalgal biomass with a tower-mounted multispectral scanner

A remote sensing instrument was mounted on a 50-ft tower overlooking North Inlet Estuary, South Carolina in order to conduct a remote sensing study of benthic microalgae. The instrument was programmed to take multispectral imagery data along a 90 deg horizontal frame in six spectral bands ranging from 400-1050 nm and had a ground resolution of about 3 cm. Imagery measurements were encoded in digital form on magnetic tape and were stored, decoded, and manipulated by computer. Correlation coefficients were calculated on imagery data and chlorophyll a concentrations derived from ground truth data. The most significant correlation occurred in the blue spectral band with numerical values ranging from -0.81 to -0.88 for three separate sampling periods. Mean values of chlorophyll a for a larger section of mudflat were estimated using regression equations. The scanner has provided encouraging results and promises to be a useful tool in sampling the biomass of intertidal benthic microalgae.

Jobson, D. J.↗
NASA NTRS2012

Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then applying them to a given cloud-enabled infrastructure to assesses and compare environment setup options and enabled technologies. This project reviews findings that were observed when cloud platforms were evaluated for bulk geoprocessing capabilities based on data handling and application development requirements.

Brown, Richard B.↗
NASA NTRS1972

A precompiler for the formula manipulation system TRIGMAN.

Discussion of a translator designed to simplify the programming of problems involving the TRIGMAN formula manipulation system. The translator allows for the introduction of a new data type, SERIES, into a FORTRAN program and translates a user's program into legal FORTRAN. The translator is adaptable to other formula manipulation systems presently used in celestial mechanics.

Jefferys, W. H.↗
DOE OSTI2024

Data and scripts associated with the manuscript "Estimating soil moisture and salinity response to simulated coastal flooding using time-lapse electrical resistivity and induced polarization monitoring”

This package contains geophysics datasets generated during the simulated ecosystem-flooding experiment – TEMPEST (Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatment). These geophysics data consist of Electrical Resistivity Imaging (ERI) and Induced Polarization (IP) datasets collected to estimate the soil moisture and salinity response to the simulated coastal flooding experiment. In addition to using geophysics datasets to estimate soil moisture and salinity response, petrophysical relationship between the measured resistivity and moisture content and salinity using the multisalinity. This package consists of two folders: “MultiSalinity Experiment” folder and “TEMPEST Experiment and petrophysical conversion” folders. The “MultiSalinity Experiment” folder contains the datasets generated from the multisalinity experiment used to develop the petrophysical reslationship. The “TEMPEST Experiment and petrophysical conversion” folder contains ERI, IP, Ground Penetrating Radar (GPR) and Electromagnetic Induction (EMI) datasets collected during the TEMPEST experiment. This study shows the ability to used geophysical datasets in estimating moisture content and salinity at scale will be useful in calibrating Earth System Models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

Subjective Workload Assessment and Voluntary Control of Effort in a Tracking Task

A manual control tracking task was manipulated along two dimensions: (1) control order and (2) forcing function bandwidth. In the first phase of the experiment subjective workload assessments were collected. It was found that subjective assessments of workload were closely associated with performance in the case of increasing control order, but not in the case of increasing bandwidth. This was interpreted as indicating that subjective workload assessments are most appropriate for the study of increasing difficulty centered in response selection processes as opposed to response execution processes. In the second phase of the experiment the subjects were asked to voluntarily limit the effort they applied in the performance of the tracking task. The results indicate that the subjects were quite facile in doing this. However, comparison of these data to the findings of other studies that manipulated effort via dual-task biasing indicate that effort manipulation is much more potent in a single-task configuration. This finding is discussed in terms of multiple resource theories of attentional capacity. The utility of an analysis of covariance procedure in studying the relationships between subjective ratings and performance is highlighted.

Vidulich, M. A.↗
DOE OSTI2013

DETECTING ACTIVE GALACTIC NUCLEI USING MULTI-FILTER IMAGING DATA. II. INCORPORATING ARTIFICIAL NEURAL NETWORKS

This is the second paper of the series Detecting Active Galactic Nuclei Using Multi-filter Imaging Data. In this paper we review shapelets, an image manipulation algorithm, which we employ to adjust the point-spread function (PSF) of galaxy images. This technique is used to ensure the image in each filter has the same and sharpest PSF, which is the preferred condition for detecting AGNs using multi-filter imaging data as we demonstrated in Paper I of this series. We apply shapelets on Canada-France-Hawaii Telescope Legacy Survey Wide Survey ugriz images. Photometric parameters such as effective radii, integrated fluxes within certain radii, and color gradients are measured on the shapelets-reconstructed images. These parameters are used by artificial neural networks (ANNs) which yield: photometric redshift with an rms of 0.026 and a regression R-value of 0.92; galaxy morphological types with an uncertainty less than 2 T types for z ≤ 0.1; and identification of galaxies as AGNs with 70% confidence, star-forming/starburst (SF/SB) galaxies with 90% confidence, and passive galaxies with 70% confidence for z ≤ 0.1. The incorporation of ANNs provides a more reliable technique for identifying AGN or SF/SB candidates, which could be very useful for large-scale multi-filter optical surveys that also include a modest set of spectroscopic data sufficient to train neural networks.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1989

Finite solid representation of robot manipulation in three-dimensional geometric reasoning

Intelligence robotic system design involves sensor allocation and sensor data fusion. In the field of geometric reasoning, a fast and effective representation method is needed to determine the physical dimensions of the manipulator as well as the motion environment in sufficient detail. Due to the capability of current sensor technology, the integrity of the sensor information is location dependent and point-wise, line-wise and plane-wise in nature. In order to maneuver the robot by reasoning the environment, there is a minimum requirement of prior information for integrating the allocated sensor feedback. Some new theoretical developments of how to associate the number and the locations of the sensors with three-dimensional geometry of the robot and the motion environment is presented. The related collision avoidance problem (CAP) will be addressed as well.

Chen, Alexander Y. K.↗
NASA NTRS1977

Earth orbital teleoperator manipulator system evaluation program

The operator's ability to perform five manipulator tip movements while using monoptic and stereoptic video systems was assessed. Test data obtained were compared with previous results to determine the impact of camera placement and stereoptic viewing on manipulator system performance. The tests were performed using the NASA MSFC extendible stiff arm Manipulator and an analog joystick controller. Two basic manipulator tasks were utilized. The minimum position change test required the operator to move the manipulator arm to touch a target contract. The dexterity test required removal and replacement of pegs.

Brye, R. G.↗
DOE OSTI2021

Microbial Biomass in Soils Receiving Varying Levels of Organic Inputs - A Data Compilation

This dataset contains soil microbial biomass data compiled from published laboratory studies and field manipulations of organic inputs to soils. Each study included at least three levels of a given type of organic input applied to a given type of soil. Studies were selected from the literature that had experimentally manipulated organic input rates to soils using unburned, non-synthetic material (e.g. plant litters, manures, and composts). Fifty-five (55) studies, conducted from 1997 to October 2019, were chosen and compiled into a dataset with 358 observations from 96 combinations of a given organic material applied to a given soil in agricultural systems, laboratory incubations, forests, or grasslands. • Studies were selected when biomass measurements used the chloroform fumigation-extraction procedure followed by carbon analysis, or, in two instances, studies estimated microbial biomass using phospholipid fatty acid analysis. • Studies that used fewer than three input rates or characterized microbial biomass via substrate induced respiration were excluded. • The temporal and spatial aspects of the laboratory and field studies were not essential to the analyses (Craig et al., 2021) and were not included with the measurement data. These data were used to assess the relationship between organic input amounts and microbial biomass. Complete reference citations are provided if additional information is needed. The compiled data are provided in two .csv files: (1) soil treatments and microbial biomass data and (2) literature citations. The “Study” field is the cross reference between files. Also provided is the R code for reproducing the results in the related publication.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Short interval testing of solar cells

A drawback of conventional electrical evaluation procedures regarding solar cells is related to time consuming operations required in the determination of specific parameters, such as the maximum power point, from the plotted curves, and to the transfer of data to a large digital computer for analysis and manipulation. This is especially true when large numbers of cells must be measured. To overcome such drawbacks, a digital short interval tester was designed and constructed. The new tester provides rapid and accurate measurements at constant temperature. The utilization of a light shutter makes it possible to measure up to 200 data points along the I-V curve in less than a second, thus avoiding thermal effects. Because the system is digital, parameters such as the maximum power may be calculated directly from the data.

Saylor, C. R.↗
DOE OSTI2025

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1998

Grid Generation Techniques Utilizing the Volume Grid Manipulator

This paper presents grid generation techniques available in the Volume Grid Manipulation (VGM) code. The VGM code is designed to manipulate existing line, surface and volume grids to improve the quality of the data. It embodies an easy to read rich language of commands that enables such alterations as topology changes, grid adaption and smoothing. Additionally, the VGM code can be used to construct simplified straight lines, splines, and conic sections which are common curves used in the generation and manipulation of points, lines, surfaces and volumes (i.e., grid data). These simple geometric curves are essential in the construction of domain discretizations for computational fluid dynamic simulations. By comparison to previously established methods of generating these curves interactively, the VGM code provides control of slope continuity and grid point-to-point stretchings as well as quick changes in the controlling parameters. The VGM code offers the capability to couple the generation of these geometries with an extensive manipulation methodology in a scripting language. The scripting language allows parametric studies of a vehicle geometry to be efficiently performed to evaluate favorable trends in the design process. As examples of the powerful capabilities of the VGM code, a wake flow field domain will be appended to an existing X33 Venturestar volume grid; negative volumes resulting from grid expansions to enable flow field capture on a simple geometry, will be corrected; and geometrical changes to a vehicle component of the X33 Venturestar will be shown.

Alter, Stephen J.↗
NASA NTRS2016

Earth Science Data Analytics: Preparing for Extracting Knowledge from Information

Data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Data analytics is a broad term that includes data analysis, as well as an understanding of the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extraction, transformation, and reduction, utilizing specific tools, techniques, and methods. Turning to data science, definitions of data science sound very similar to those of data analytics (which leads to a lot of the confusion between the two). But the skills needed for both, co-analyzing large amounts of heterogeneous data, understanding and utilizing relevant tools and techniques, and subject matter expertise, although similar, serve different purposes. Data Analytics takes on a practitioners approach to applying expertise and skills to solve issues and gain subject knowledge. Data Science, is more theoretical (research in itself) in nature, providing strategic actionable insights and new innovative methodologies. Earth Science Data Analytics (ESDA) is the process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth. The large variety of datasets (temporal spatial differences, data types, formats, etc.) invite the need for data analytics skills that understand the science domain, and data preparation, reduction, and analysis techniques, from a practitioners point of view. The application of these skills to ESDA is the focus of this presentation. The Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster was created in recognition of the practical need to facilitate the co-analysis of large amounts of data and information for Earth science. Thus, from a to advance science point of view: On the continuum of ever evolving data management systems, we need to understand and develop ways that allow for the variety of data relationships to be examined, and information to be manipulated, such that knowledge can be enhanced, to facilitate science. Recognizing the importance and potential impacts of the unlimited ways to co-analyze heterogeneous datasets, now and especially in the future, one of the objectives of the ESDA cluster is to facilitate the preparation of individuals to understand and apply needed skills to Earth science data analytics. Pinpointing and communicating the needed skills and expertise is new, and not easy. Information technology is just beginning to provide the tools for advancing the analysis of heterogeneous datasets in a big way, thus, providing opportunity to discover unobvious scientific relationships, previously invisible to the science eye. And it is not easy It takes individuals, or teams of individuals, with just the right combination of skills to understand the data and develop the methods to glean knowledge out of data and information. In addition, whereas definitions of data science and big data are (more or less) available (summarized in Reference 5), Earth science data analytics is virtually ignored in the literature, (barring a few excellent sources).

data analytics↗
NASA NTRS1990

Data analysis and archival

The purpose of this task is the acquisition, distribution, archival, and analysis of data collected during and in support of the Upper Atmospheric Research Program (UARP) field experiments. Meteorological and U2 data from the 1984 Stratosphere-Troposphere Exchange Project (STEP) was analyzed to determine characteristics of internal atmospheric waves. CDROM's containing data from the 1987 STEP, 1987 Airborne Antarctic Ozone Expedition (AAOE), and the 1989 Airborne Arctic Stratospheric Expedition (AASE) were produced for archival and distribution of those data sets. The AASE CDROM contains preliminary data and a final release is planned for February 1990. Comparisons of data from the NASA ER-2 Meteorological Measurement System (MMS) with radar tracking and radiosonde data show good agreement. Planning for a Meteorological Support Facility continues. We are investigating existing and proposed hardware and software to receive, manipulate, and display satellite imagery and standard meteorological analyses, forecasts, and radiosonde data.

Danielsen, Edwin F.↗
NASA NTRS1999

Parallel Grid Manipulations in Earth Science Calculations

The National Aeronautics and Space Administration (NASA) Data Assimilation Office (DAO) at the Goddard Space Flight Center is moving its data assimilation system to massively parallel computing platforms. This parallel implementation of GEOS DAS will be used in the DAO's normal activities, which include reanalysis of data, and operational support for flight missions. Key components of GEOS DAS, including the gridpoint-based general circulation model and a data analysis system, are currently being parallelized. The parallelization of GEOS DAS is also one of the HPCC Grand Challenge Projects. The GEOS-DAS software employs several distinct grids. Some examples are: an observation grid- an unstructured grid of points at which observed or measured physical quantities from instruments or satellites are associated- a highly-structured latitude-longitude grid of points spanning the earth at given latitude-longitude coordinates at which prognostic quantities are determined, and a computational lat-lon grid in which the pole has been moved to a different location to avoid computational instabilities. Each of these grids has a different structure and number of constituent points. In spite of that, there are numerous interactions between the grids, e.g., values on one grid must be interpolated to another, or, in other cases, grids need to be redistributed on the underlying parallel platform. The DAO has designed a parallel integrated library for grid manipulations (PILGRIM) to support the needed grid interactions with maximum efficiency. It offers a flexible interface to generate new grids, define transformations between grids and apply them. Basic communication is currently MPI, however the interfaces defined here could conceivably be implemented with other message-passing libraries, e.g., Cray SHMEM, or with shared-memory constructs. The library is written in Fortran 90. First performance results indicate that even difficult problems, such as above-mentioned pole rotation- a sparse interpolation with little data locality between the physical lat-lon grid and a pole rotated computational grid- can be solved efficiently and at the GFlop/s rates needed to solve tomorrow's high resolution earth science models. In the subsequent presentation we will discuss the design and implementation of PILGRIM as well as a number of the problems it is required to solve. Some conclusions will be drawn about the potential performance of the overall earth science models on the supercomputer platforms foreseen for these problems.

Sawyer, W.↗
NASA NTRS1988

Plasma diagnostics package. Volume 2: Spacelab 2 section, part A

This volume (2), which consists of two parts (A and B), of the Plasma Diagnostics Package (PDP) Final Science Report contains a summary of all of the data reduction and scientific analyses which were performed using PDP data obtained on STS-51F as a part of the Spacelab 2 (SL-2) payload. This work was performed during the period of launch, July 29, l985, through June 30, l988. During this period the primary data reduction effort consisted of processing summary plots of the data received by 12 of the 14 instruments located on the PDP and submitting these data to the National Space Science Data Center (NSSDC). The scientific analyses during the performance period consisted of follow-up studies of shuttle orbiter environment and orbiter/ionosphere interactions and various plasma particle and wave studies which dealt with data taken when the PDP was on the Remote Manipulator System (RMS) arm and when the PDP was in free flight. Of particular interest during the RMS operations and free flight were the orbiter wake studies and joint studies of beam/plasma interactions with the SL-2 Fast Pulse Electron Generator (FPEG) of the Vehicle Charging and Potential Investigation (VCAP). Internal reports, published papers and presentations which involve PDP/SL-2 data are listed in Sections 3 and 4. A PDP/SL-2 scientific results meeting was held at the University of Iowa on June 10, l986. This meeting was attended by most of the PDP and VCAP investigators and provided a forum for discussing and comparing the various results, particularly with regard to the PDP free flight.

Pickett, Jolene S.↗
DOE OSTI2020

SPRUCE Plot-Level Water Table Data Assessments for Absolute Elevations and Height with Respect to Mean Hollows Beginning in 2015

This data set provides a record of the half-hourly automated water table depth data collected for 12 SPRUCE plots (4, 6, 7, 8, 10, 11, 13, 14, 16, 17, 19, 20, and 21) beginning during deep peat heating (DPH) in 2015 and continuing throughout the whole ecosystem warming (WEW) manipulations for the SPRUCE Project (Hanson et al. 2017). The data currently cover 2015-05-12 through 2024-12-31 and will be updated periodically throughout the duration of the SPRUCE project. Also provided are daily plot normalized data for water table depths with respect to mean hollow locations within each plot. The hollow referenced data provide the basis for the intercomparison of peat saturation or aeration across treatment plots. A limited data set for manual water table observations made periodically from 2015-2022 are also provided as a reference to the plot center automated observations. In August 2015, WEW was initiated at 5 warming levels (+0, +2. +4.5, +6.75 and +9 °C) with 2 plots per warming level. DPH measurements were underway before the initiation of WEW heating treatments and both are expected to operate through 2025. Elevated CO2 treatments were added in June 2016 (Enclosures 4, 10, 11, 16 and 19). All measurements were made at the 8.1-ha S1 bog forest site in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). This dataset contains three data files in comma separated (*.csv) format.

54 ENVIRONMENTAL SCIENCES↗