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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Level 1 Sensor Data v2-1

This is the version 2-1 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds, out-of-service, and outlier flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project** This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding variable-specific CSV (comma separated value) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v2-1 TEMPEST L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. The TEMPEST flood events occurred on the following dates. They lasted for ~10 hours each day and delivered ~80,000 gallons to each plot; many data streams are available at 1 or 5 minute frequency during these periods. * Tests: Aug 25 (fresh plot) and Sep 9 (salt plot), 2021 * TEMPEST 1: June 22, 2022 * TEMPEST 2: June 6-7, 2023 * TEMPEST 3: June 11-13, 2024 This dataset was updated 2026-03-12: (i) data now go through 2025-12-31 (previous end was 2025-06-30) and (ii) dataset and file names updated to “…v2-1” (previously was “v2-0”).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Active Matrix OLED Test Report

This report focuses on the limited environmental testing of the AMOLED display performed as an engineering evaluation by The NASA Johnson Space Center (JSC)-specifically. EMI. Thermal Vac, and radiation tests. The AMOLED display is an active-matrix Organic Light Emitting Diode (OLED) technology. The testing provided an initial understanding of the technology and its suitability for space applications. Relative to light emitting diode (LED) displays or liquid crystal displays (LCDs), AMOLED displays provide a superior viewing experience even though they are much lighter and smaller, produce higher contrast ratio and richer colors, and require less power to operate than LCDs. However, AMOLED technology has not been demonstrated in a space environment. Therefore, some risks with the technology must be addressed before they can be seriously considered for human spaceflight. The environmental tests provided preliminary performance data on the ability of the display technology to handle some of the simulated induced space/spacecraft environments that an AMOLED display will see during a spacecraft certification test program. This engineering evaluation is part of a Space Act Agreement (SM) between The NASA/JSC and Honeywell International (HI) as a collaborative effort to evaluate the potential use of AMOLED technology for future human spaceflight missions- both government-led and commercial. Under this SM, HI is responsible for doing optical performance evaluation, as well as temperature and touch screen studies. The NASA/JSC is responsible for performing environmental testing comprised of EMI, Thermal Vac, and radiation tests. Additionally, as part of the testing, limited optical data was acquired to assess performance as the display was subjected to the induced environments. The NASA will benefit from this engineering evaluation by understanding AMOLED suitability for future use in space as well as becoming a smarter buyer (or developer) of the technology. HI benefits from the environmental testing results by understanding its performance limitations/shortcomings to improve subsequent generations of AMOLED technology. Note that the AMOLED used in this test was not deSigned for the space environment but rather for commercial/industrial terrestrial applications.

Salazar, George↗
NASA NTRS2013

Active Matrix Organic Light Emitting Diode (AMOLED) Environmental Test Report

This report focuses on the limited environmental testing of the AMOLED display performed as an engineering evaluation by The NASA Johnson Space Center (JSC)-specifically. EMI. Thermal Vac, and radiation tests. The AMOLED display is an active-matrix Organic Light Emitting Diode (OLED) technology. The testing provided an initial understanding of the technology and its suitability for space applications. Relative to light emitting diode (LED) displays or liquid crystal displays (LCDs), AMOLED displays provide a superior viewing experience even though they are much lighter and smaller, produce higher contrast ratio and richer colors, and require less power to operate than LCDs. However, AMOLED technology has not been demonstrated in a space environment. Therefore, some risks with the technology must be addressed before they can be seriously considered for human spaceflight. The environmental tests provided preliminary performance data on the ability of the display technology to handle some of the simulated induced space/spacecraft environments that an AMOLED display will see during a spacecraft certification test program. This engineering evaluation is part of a Space Act Agreement (SM) between The NASA/JSC and Honeywell International (HI) as a collaborative effort to evaluate the potential use of AMOLED technology for future human spaceflight missions- both government-led and commercial. Under this SM, HI is responsible for doing optical performance evaluation, as well as temperature and touch screen studies. The NASA/JSC is responsible for performing environmental testing comprised of EMI, Thermal Vac, and radiation tests. Additionally, as part of the testing, limited optical data was acquired to assess performance as the display was subjected to the induced environments. The NASA will benefit from this engineering evaluation by understanding AMOLED suitability for future use in space as well as becoming a smarter buyer (or developer) of the technology. HI benefits from the environmental testing results by understanding its performance limitations/shortcomings to improve subsequent generations of AMOLED technology. Note that the AMOLED used in this test was not deSigned for the space environment but rather for commercial/industrial terrestrial applications.

Salazar, George A.↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-xSE NEON Smithsonian Environmental Research Center (SERC)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xSE NEON Smithsonian Environmental Research Center (SERC). This is the FLUXNET version of the carbon flux data for the site US-xSE NEON Smithsonian Environmental Research Center (SERC) produced by applying the standard ONEFlux (1F) software. Site Description - This site is operated at the Smithsonian Environmental Research Center, which is comprised of forests, wetlands, marshes and shoreline on the Chesapeake Bay

Network), NEON (National Ecological Observatory↗
DOE OSTI2026

Lessons Learned from Ecosystem-Scale Experimental Field Studies (Workshop Report)

Efforts to understand and predict ecosystem responses to environmental change require long-term, large-scale, spatially representative experiments and observations that capture natural variability, test predictive models, and generate transferable knowledge. Such studies are indispensable for unraveling the complexities of terrestrial ecosystems and their responses to disturbances and evolving environmental conditions, while generating the data necessary for developing mechanistic models and predictive tools that inform decision-making processes. Having a rich history of designing and executing large-scale ecosystem experiments, the U.S. Department of Energy’s Environmental System Science program convened a workshop in January 2025 that brought together leaders in the field to distill critical lessons from decades of experience in large-scale experiments. The workshop aimed to (1) provide an ecosystem experiment primer for best practices, thus ensuring a high scientific return on investment for funding agencies, and (2) offer a robust framework for the design and management of future research initiatives. This report synthesizes insights and experiences from workshop participants and is structured to capture the entire research life cycle, from goal setting and design to operations, adaptive management, team dynamics, collaborations, and the often overlooked aspect of decommissioning. By synthesizing decision-making and lessons learned across diverse research approaches, the report aims to provide a template of essential factors to consider when designing successful long-term, large-scale ecosystem experiments.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Critical Climate-Sensitive and Important Grain-Producing Regions: Grain Production/Yield Variations Due to Climate Fluctuations

Ideally, the Crop Country Inventory, CCI, is a methodology for the pre-harvest prediction of large variations in a country s crop production. This is accomplished by monitoring the historical climatic fluctuations, especially during the crop calendar period, in a climate sensitive large crop production region or sub-country, rather than the entire country. The argument can be made that the climatic fluctuations in the climatic sensitive region are responsible for the major annual crop country variations and that the remainder of the country, without major climatic fluctuations for a given year, can be assumed to be a steady-state crop producer. The principal data set that has been used is the Global Climate Mode (GCM) data from the National Center for Environmental Prediction (NCEP), taken over the last half century. As a test of its accuracy, GCM data can and has been correlated with the actual meteorological station data at the station site.

Welker, J. E.↗
DOE OSTI2026

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Level 2 Sensor Data v2-1

This is the version v2-1 Level 2 (L2) data release for COMPASS-FME environmental sensors located at our Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. Level 2 (L2) data consist of sensor observations from the COMPASS-FME synoptic sites, TEMPEST, and DELUGE. Compared to the L1 data, these are more consistent (always 15-minute timestamps for the entire year); better QA/QC’d (out of bounds, out of service, and extreme outlier values are removed); and more complete, with a gap-filled time series available alongside the main observations, and additional derived (calculated) variables. L2 data are intended to be rapidly and easily usable in analyses and simulations. However, algorithmic outlier identification always carries the risk of removing valid data, and Level 1 data may be more suitable for analyses that focus on variability or extreme events. This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding variable-specific Parquet (a high performance, space efficient format; see https://parquet.apache.org) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are reported every 15 minutes. Please see v2-1 TEMPEST L2 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. Data files are in Apache Parquet, a high performance, space efficient format for tabular data. These files can be read using R's `arrow` package (https://arrow.apache.org/docs/r/), with similar tools available in other languages. The TEMPEST flood events occurred on the following dates. They lasted for ~10 hours each day and delivered ~80,000 gallons to each plot; many data streams are available at 1 or 5 minute frequency during these periods. * Tests: Aug 25 (fresh plot) and Sep 9 (salt plot), 2021 * TEMPEST 1: June 22, 2022 * TEMPEST 2: June 6-7, 2023 * TEMPEST 3: June 11-13, 2024

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗
DOE OSTI2020

Nevada National Security Site Environmental Report 2019

This report presents the National Nuclear Security Administration Nevada Field Office environmental protection and monitoring programs data and the compliance status for calendar year 2019 at the Nevada National Security Site and at its two support facilities, the North Las Vegas Facility and the Remote Sensing Laboratory-Nellis. This report also addresses environmental restoration projects conducted by the Environmental Management Nevada Program Office at the Tonopah Test Range.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

OSSE spectral analysis techniques

Analysis of the spectra from the Oriented Scintillation Spectrometer Experiment (OSSE) is complicated because of the typically low signal to noise (approx. 0.1 percent) and the large background variability. The OSSE instrument was designed to address these difficulties by periodically offset-pointing the detectors from the source to perform background measurements. These background measurements are used to estimate the background during each of the source observations. The resulting background-subtracted spectra can then be accumulated and fitted for spectral lines and/or continua. Data selection based on various environmental parameters can be performed at various stages during the analysis procedure. In order to achieve the instrument's statistical sensitivity, however, it will be necessary for investigators to develop a detailed understanding of the instrument operation, data collection, and the background spectrum and its variability. A brief description of the major steps in the OSSE spectral analysis process is described, including a discussion of the OSSE background spectrum and examples of several observational strategies.

Purcell, W. R.↗
NASA NTRS2014

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Service (KMS)

Flooding and drought are two key forecasting challenges for the Kenya Meteorological Service (KMS). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the planetary boundary layer (PBL) of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface, particularly within weakly-sheared environments such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in land surface and numerical weather prediction (NWP) models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-impact weather over eastern Africa. KMS currently runs a configuration of the Weather Research and Forecasting (WRF) NWP model in real time to support its daily forecasting operations, making use of the NOAA/National Weather Service (NWS) Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the KMS-WRF runs on a regional grid over eastern Africa. Two organizations at the NASA Marshall Space Flight Center in Huntsville, AL, SERVIR and the Shortterm Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMS for enhancing its regional modeling capabilities through new datasets and tools. To accomplish this goal, SPoRT and SERVIR is providing enhanced, experimental land surface initialization datasets and model verification capabilities to KMS as part of this collaboration. To produce a land-surface initialization more consistent with the resolution of the KMS-WRF runs, the NASA Land Information System (LIS) is run at a comparable resolution to provide real-time, daily soil initialization data in place of data interpolated from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model soil moisture and temperature fields. Additionally, realtime green vegetation fraction (GVF) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi- NPP) satellite will be incorporated into the KMS-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service (NESDIS). Finally, model verification capabilities will be transitioned to KMS using the Model Evaluation Tools (MET; Brown et al. 2009) package in conjunction with a dynamic scripting package developed by SPoRT (Zavodsky et al. 2014), to help quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. Furthermore, the transition of these MET tools will enable KMS to monitor model forecast accuracy in near real time. This paper presents preliminary efforts to improve land surface model initialization over eastern Africa in support of operations at KMS. The remainder of this extended abstract is organized as follows: The collaborating organizations involved in the project are described in Section 2; background information on LIS and the configuration for eastern Africa is presented in Section 3; the WRF configuration used in this modeling experiment is described in Section 4; sample experimental WRF output with and without LIS initialization data are given in Section 5; a summary is given in Section 6 followed by acknowledgements and references.

Case, Johnathan L.↗
NASA NTRS1977

Quo vadis, remote sensing

The use of satellite remote sensing data for resource management is discussed. The evaluation of the need for management data is reviewed, and some legislative programs which require the monitoring of environmental resources are summarized. Several characteristics of data used in the monitoring of dynamic processes are analyzed, and the implications of routine processing of extensive remote sensing data for the development of a new world view are considered.

Billingsley, F. C.↗
NASA NTRS1979

Development of LACIE CCEA-1 weather/wheat yield models

The advantages and disadvantages of the casual (phenological, dynamic, physiological), statistical regression, and analog approaches to modeling for grain yield are examined. Given LACIE's primary goal of estimating wheat production for the large areas of eight major wheat-growing regions, the statistical regression approach of correlating historical yield and climate data offered the Center for Climatic and Environmental Assessment the greatest potential return within the constraints of time and data sources. The basic equation for the first generation wheat-yield model is given. Topics discussed include truncation, trend variable, selection of weather variables, episodic events, strata selection, operational data flow, weighting, and model results.

Strommen, N. D.↗
NASA NTRS1982

Environmental exposure effects on composite materials for commercial aircraft

The data base for composite materials' properties as they are affected by the environments encountered in operating conditions, both in flight and at ground terminals is expanded. Absorbed moisture degrades the mechanical properties of graphite/epoxy laminates at elevated temperatures. Since airplane components are frequently exposed to atmospheric moisture, rain, and accumulated water, quantitative data are required to evaluate the amount of fluids absorbed under various environmental conditions and the subsequent effects on material properties. In addition, accelerated laboratory test techniques are developed are reliably capable of predicting long term behavior. An accelerated environmental exposure testing procedure is developed, and experimental results are correlated and compared with analytical results to establish the level of confidence for predicting composite material properties.

Gibbons, M. N.↗
NASA NTRS1983

Shuttle imaging radar-A (SIR-A) data analysis

The utility of shuttle imaging radar (SIR-A) data was evaluated in several geological and environmental contexts. For the Ozark Plateau of southern Missouri, SIR-A data were of little use in mapping structural features, because of generally uniform returns. For western Illinois, little was to be gained in terms of identifying land use categories by examining differences between overlapping passes. For southern Australia (Koonamore Station), information ion vegetation types that was not obtainable from LANDSAT MSS data alone was obtained. Specifically, high SIR-A returns in the Australian site were found to correlate with locations where shrubs increase surface roughness appreciably. The Australian study site results demonstrate the synergy of acquiring spectral reflectance and radar data over the same location and time. Such data are especially important in that region, since grazing animals have substantially altered and are continuing to alter the distribution of shrublands, grasslands, and soil exposures. Periodic, synoptic acquisition of MSS and SAR data would be of use in monitoring the dynamics of land-cover change in this environment.

Arvidson, R. E.↗
NASA NTRS2007

Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for constraining the use of the passive retrieval data in models and for improving the accuracy of the retrievals.

Nguyen, L.↗
NASA NTRS2007

Accessing, Utilizing and Visualizing NASA Remote Sensing Data for Malaria Modeling and Surveillance

This poster presentation reviews the use of NASA remote sensing data that can be used to extract environmental information for modeling malaria transmission. The authors discuss the remote sensing data from Landsat, Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), Tropical Rainfall Measuring Mission (TRMM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Earth Observing One (EO-1), Advanced Land Imager (ALI) and Seasonal to Interannual Earth Science Information Partner (SIESIP) dataset.

Kiang, Richard K.↗
NASA NTRSDate not supplied

Comparison of Exploration Portable Life Support Subsystem (xPLSS) Thermal Modeling to Thermal Vacuum Testing

To support NASA’s goal to return to the Moon through the Artemis mission, the development of an exploration portable life support system (xPLSS) has been conducted at Johnson Space Center (JSC). As part of this development process, a large system level thermal/fluid model of the xPLSS was developed using Thermal Desktop and an in-house human model (METMAN). The xPLSS model was used throughout the design process to predict the performance and temperature of nearly all components within the xPLSS. In the fall of 2023, the design, verification, and testing (DVT) unit of the xPLSS was tested in a thermal vacuum (TVAC) chamber at JSC. This testing consisted of combining the xPLSS with an upper torso of the exploration pressure garment system (xPGS) and simulating five extravehicular activities (EVAs) in extreme thermal conditions (two cold EVAs and three hot EVAs). The data generated in this test series provided system level data of the xPLSS operating in vacuum and at flight-like environmental temperatures for the first time. This data was compared to results output by the xPLSS system model to assess the accuracy of previous analyses and improve the fidelity and accuracy of the xPLSS system model. The comparison between model and test hardware provides valuable insight that will help improve the design and fidelity of next generation space suits. In general, comparison between test data and model data generally showed slightly un-conservative values (model predicting colder temperatures than test in hot environments, and hotter temperatures than test in cold environments). Model assumptions and test assumptions were assessed to understand potential causes of some of these sources in error. Recommendations to improve the fidelity of the xPLSS model were also made based on the results presented in this paper.

xPLSS↗