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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

A Multi-Sensor Water Vapor, Temperature and Cloud Climate Data Record: Status of Our MEaSUREs 2012 Project

- Our primary objectives: Incorporate all A-Train water vapor, including small-scale, horizontal and vertical water vapor structure from MODIS (Moderate Resolution Imaging Spectroradiometer) and GPS (Global Positioning System); Use MODIS cloud classification that is collocated at the pixel-scale over the full AIRS/AMSU (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit) swath; Extend summaries to PDFs (Probability Distribution Functions)/higher order moments of water vapor sorted by cloud classes; Establish robust, scale-dependent statistical relationships between cloud, temperature, and water vapor PDFs for the climate modeling community. - We will also: Update our current data record to new CloudSat/CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) cloud classification; Provide merged AIRS and MLS (Microwave Limb Sounder) water vapor profiles using averaging kernels; Include temperature and water vapor from models (ECMWF - European Centre for Medium-Range Weather Forecasts) and re-analyses (MERRA - Modern Era-Retrospective Analysis for Research and Applications); Classify METOP-A (Meteorological Operational Satellite-A) and NOAA (National Oceanic and Atmospheric Administration) satellite water vapor with AVHRR (Advanced Very High Resolution Radiometer) during SNOs (Solar Neutrino Oscillations); Compare with the NVAP-M (re-analysis and extension of the NASA Water Vapor Project (NVAP)) water vapor climatologies; Use existing data sources and mature algorithms, and document processing algorithms.

Fetzer, Eric↗
NASA NTRS1973

Remote sensing of chlorophyll and temperature in marine and fresh waters.

An airborne differential radiometer was demonstrated to be a sensitive, real-time detector of surface chlorophyll content in water bodies. The instrument continuously measures the difference in radiance between two wavelength bands, one centered near the maximum of the blue chlorophyll a absorption region and the other at a reference wavelength outside this region. Flights were made over fresh water lakes, marine waters, and an estuary, and the results were compared with 'ground truth' measurements of chlorophyll concentration. A correlation between output signal of the differential radiometer and the chlorophyll concentration was obtained. Examples of flight data are illustrated. Simultaneous airborne measurements of chlorophyll content and water temperature revealed that variations in chlorophyll are often associated with changes in temperature. Thus, simultaneous sensing of chlorophyll and temperature provides useful information for studies of marine food production, water pollution, and physical processes such as upwelling.

Arvesen, J. C.↗
NASA NTRS2014

Estimating Sampling Biases and Measurement Uncertainties of AIRS-AMSU-A Temperature and Water Vapor Observations Using MERRA Reanalysis

We use MERRA (Modern Era Retrospective-Analysis for Research Applications) temperature and water vapor data to estimate the sampling biases of climatologies derived from the AIRS/AMSU-A (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A) suite of instruments. We separate the total sampling bias into temporal and instrumental components. The temporal component is caused by the AIRS/AMSU-A orbit and swath that are not able to sample all of time and space. The instrumental component is caused by scenes that prevent successful retrievals. The temporal sampling biases are generally smaller than the instrumental sampling biases except in regions with large diurnal variations, such as the boundary layer, where the temporal sampling biases of temperature can be +/- 2 K and water vapor can be 10% wet. The instrumental sampling biases are the main contributor to the total sampling biases and are mainly caused by clouds. They are up to 2 K cold and greater than 30% dry over mid-latitude storm tracks and tropical deep convective cloudy regions and up to 20% wet over stratus regions. However, other factors such as surface emissivity and temperature can also influence the instrumental sampling bias over deserts where the biases can be up to 1 K cold and 10% wet. Some instrumental sampling biases can vary seasonally and/or diurnally. We also estimate the combined measurement uncertainties of temperature and water vapor from AIRS/AMSU-A and MERRA by comparing similarly sampled climatologies from both data sets. The measurement differences are often larger than the sampling biases and have longitudinal variations.

MERRA↗
NASA NTRS1983

Factors influencing the marine boundary layer during a cold-air outbreak

The model for the cloud-topped marine boundary layer during a cold air outbreak developed by Stage and Businger (1981a) is used in conjunction with a test profile based on a fall outbreak episode over Lake Ontario to study factors influencing marine boundary-layer evolution. Sensitivity tests are done which show changes in layer evolution resulting from variation of wind speed, radiative sky temperature, water surface temperature, humidity of the shoreline sounding and divergence. The behavior of the layer in the presence of a region of cold-water upwelling near the shore is also investigated. It is found that the main effect of the upwelling region is to delay modification of the boundary-layer air.

Stage, S. A.↗
NASA NTRS1980

Validation of the solar heating and cooling high speed performance (HISPER) computer code

Developed to give a quick and accurate predictions HISPER, a simplification of the TRNSYS program, achieves its computational speed by not simulating detailed system operations or performing detailed load computations. In order to validate the HISPER computer for air systems the simulation was compared to the actual performance of an operational test site. Solar insolation, ambient temperature, water usage rate, and water main temperatures from the data tapes for an office building in Huntsville, Alabama were used as input. The HISPER program was found to predict the heating loads and solar fraction of the loads with errors of less than ten percent. Good correlation was found on both a seasonal basis and a monthly basis. Several parameters (such as infiltration rate and the outside ambient temperature above which heating is not required) were found to require careful selection for accurate simulation.

Wallace, D. B.↗
NASA NTRS1982

Radiometer mission requirements for large space antenna systems

Requirements are defined for Earth observational microwave radiometry using large space antenna systems with apertures in the 50 to 200 meter range. General Earth observational needs, specific measurement requirements, orbital mission guidelines and constraints, and general radiometric requirements are defined. Specific measurements include soil moisture, water surface temperature, water roughness, ice boundaries, salinity, and water pollutants. Measurements with 10 to 1 km spatial resolution and 3 to 1 day temporal resolution are required.

Keafer, L. S., Jr.↗
NASA NTRS2005

A Note on the Relationship of Temperature and Water Vapor over Oceans, as well as the Sea Surface Temperature Impact

This note follows up on a recent study by Shie et al. (2005) and extends the investigation of the domain-averaged moisture-temperature (Q-T) relationship from the Tropics (i.e., the previous study) to the tropical Pacific, Atlantic and Indian Oceans. The Q and T data examined in this study are obtained from the GEOS-3 [Goddard Earth Observing System Version-3] global re-analysis monthly products. Similar to what was found earlier in the Tropics, Q is also found to increase with T over the entire oceanic region; however, Q increases faster with T over oceans than over the Tropics. The Q-T distribution for the Tropics is in a quasi-linear relationship, which is embedded in a global Q-T distribution that is, however, in a more complex curvilinear relationship. The Q-T distribution over the oceanic regions seems to fall within the lower bound (ie., the relatively colder and driver regime) of the tropical Q-T distribution. T over oceans is also found increasing with SST (sea surface temperature), which seemingly implies that an air mass might have gained heat more readily from a warmer ocean as compared to a colder ocean. Q is also found to increase with SST in a manner that quantitatively resembles an earlier finding by Stevens (1990). We also found that relative humidity exhibits similar behaviors for oceanic and tropical regions, respectively, i.e., it increases with both SST and T over oceans and increases with T in the Tropics (Shie et al. 2005). All these similar features found between oceanic and tropical regions seem to inform us that oceans occupy most of the Tropics and so play a key role in determining what have happened in the Tropics.

Shie, C.-L.↗
NASA NTRS2010

Hollow Fiber Spacesuit Water Membrane Evaporator Development and Testing for Advanced Spacesuits

The spacesuit water membrane evaporator (SWME) is being developed to perform the thermal control function for advanced spacesuits to take advantage of recent advances in micropore membrane technology in providing a robust heat-rejection device that is potentially less sensitive to contamination than is the sublimator. Principles of a sheet membrane SWME design were demonstrated using a prototypic test article that was tested in a vacuum chamber at JSC in July 1999. The Membrana Celgard X50-215 microporous hollow fiber (HoFi) membrane was selected after recent contamination tests as the most suitable candidate among commercial alternatives for HoFi SWME prototype development. A design that grouped the fiber layers into stacks, which were separated by small spaces and packaged into a cylindrical shape, was developed into a full-scale prototype consisting 14,300 tube bundled into 30 stacks, each of which are formed into a chevron shape and separated by spacers and organized into three sectors of ten nested stacks. Vacuum chamber testing has been performed characterize heat rejection as a function of inlet water temperature and water vapor backpressure and to show contamination resistance to the constituents expected to be found in potable water produced by the distillation processes. Other tests showed the tolerance to freezing and suitability to reject heat in a Mars pressure environment.

Bue, Grant C.↗
NASA NTRS2010

Hollow Fiber Flight Prototype Spacesuit Water Membrane Evaporator Design and Testing

The spacesuit water membrane evaporator (SWME) is being developed to perform thermal control for advanced spacesuits and to take advantage of recent advances in micropore membrane technology. This results in a robust heat-rejection device that is potentially less sensitive to contamination than is the sublimator. The Membrana Celgard X50-215 microporous hollow-fiber (HoFi) membrane was selected after recent extensive testing as the most suitable candidate among commercial alternatives for continued SWME prototype development. The current design was based on a previous design that grouped the fiber layers into stacks, which were separated by small spaces and packaged into a cylindrical shape. This was developed into a full-scale prototype consisting of 14,300 tube bundled into 30 stacks, each of which is formed into a chevron shape and separated by spacers and organized into three sectors of 10 nested stacks. The new design replaced metal components with plastic ones, and has a custom built flight like backpressure valve mounted on the side of the SWME housing to reduce backpressure when fully open. The spacers that provided separation of the chevron fiber stacks were eliminated. Vacuum chamber testing showed improved heat rejection as a function of inlet water temperature and water vapor backpressure compared with the previous design. Other tests pushed the limits of tolerance to freezing and showed suitability to reject heat in a Mars pressure environment with and without a sweep gas. Tolerance to contamination by constituents expected to be found in potable water produced by distillation processes was tested in a conventional way by allowing constituents to accumulate in the coolant as evaporation occurs. For this purpose, the SWME cartridge has endured an equivalent of 30 EVAs exposure and demonstrated minimal performance decline.

Bue, Grant↗
NASA NTRS2011

Hollow Fiber Space Water Membrane Evaporator Flight Prototype Design and Testing

The spacesuit water membrane evaporator (SWME) is being developed to perform thermal control for advanced spacesuits and to take advantage of recent advances in micropore membrane technology. This results in a robust heat-rejection device that is potentially less sensitive to contamination than is the sublimator. The current design was based on a previous design that grouped the fiber layers into stacks, which were separated by small spaces and packaged into a cylindrical shape. This was developed into a full-scale prototype consisting of 14,300 tube bundled into 30 stacks, each of which is formed into a chevron shape and separated by spacers and organized into three sectors of 10 nested stacks. The new design replaced metal components with plastic ones, eliminated the spacers, and has a custom built flight like backpressure valve mounted on the side of the SWME housing to reduce backpressure when fully open. A number of tests were performed in order to improve the strength of the polyurethane header that holds the fibers in place while the system is pressurized. Vacuum chamber testing showed similar heat rejection as a function of inlet water temperature and water vapor backpressure was similar to the previous design. Other tests pushed the limits of tolerance to freezing and showed suitability to reject heat in a Mars pressure environment with and without a sweep gas. Tolerance to contamination by constituents expected to be found in potable water produced by distillation processes was tested in a conventional way by allowing constituents to accumulate in the coolant as evaporation occurs. For this purpose, the SWME cartridge has endured an equivalent of 30 EVAs exposure and demonstrated acceptable performance decline.

Bue, Grant C.↗
NASA NTRS2013

Hollow-Fiber Spacesuit Water Membrane Evaporator

The hollow-fiber spacesuit water membrane evaporator (HoFi SWME) is being developed to perform the thermal control function for advanced spacesuits and spacecraft to take advantage of recent advances in micropore membrane technology in providing a robust, heat-rejection device that is less sensitive to contamination than is the sublimator. After recent contamination tests, a commercial-off-the-shelf (COTS) micro porous hollow-fiber membrane was selected for prototype development as the most suitable candidate among commercial hollow-fiber evaporator alternatives. An innovative design that grouped the fiber layers into stacks, which were separated by small spaces and packaged into a cylindrical shape, was developed into a full-scale prototype for the spacesuit application. Vacuum chamber testing has been performed to characterize heat rejection as a function of inlet water temperature and water vapor back-pressure, and to show contamination resistance to the constituents expected to be found in potable water produced by the wastewater reclamation distillation processes. Other tests showed tolerance to freezing and suitability to reject heat in a Mars pressure environment. In summary, HoFi SWME is a lightweight, compact evaporator for heat rejection in the spacesuit that is robust, contamination- insensitive, freeze-tolerant, and able to reject the required heat of spacewalks in microgravity, lunar, and Martian environments. The HoFi is packaged to reject 810 W of heat through 800 hours of use in a vacuum environment, and 370 W in a Mars environment. The device also eliminates free gas and dissolved gas from the coolant loop.

Bue, Grant↗
DOE OSTI2025

Temperature and Water Levels Collectively Regulate Methane Emissions From Subtropical Freshwater Wetlands

Abstract Wetlands are the largest and most climate‐sensitive natural sources of methane. Accurately estimating wetland methane emissions involves reconciling inversion (“top‐down”) and process‐based (“bottom‐up”) models within the global methane budget. However, estimates from these two model types are inherently interdependent and often reveal substantial discrepancies. To enhance the reliability of both approaches, we need a comprehensive understanding of wetland methane emissions and an independent high‐resolution long‐term flux data set. Here, we employed a data‐driven random forest approach to identify key variables influencing methane emissions from subtropical freshwater wetlands in the Southeastern United States. The model‐estimated monthly mean methane fluxes fit well with measured methane fluxes ( R 2 = 0.67) at four representative FLUXNET‐CH4 wetland sites across the region. Variable importance analysis highlighted the sensitivity of subtropical freshwater wetland methane emissions to variations in both temperature and water levels. High temperatures facilitate methanogenesis by enhancing microbial activities, while elevated water levels maintain anaerobic conditions necessary for methane production. Notably, the response of methane emissions to water level fluctuations is contingent on temperature conditions, and vice versa. Moreover, we constructed the first high‐spatial‐resolution (∼1 km × 1 km) and long‐term (1982–2010) gridded regional wetland methane flux product for the Southeastern United States, estimating annual methane emissions from subtropical freshwater wetlands in the region at 4.93 ± 0.11 Tg CH 4 yr −1 for 1982–2010. This new benchmark product holds promise for validating and parameterizing uncertain wetland methane emission processes in bottom‐up models and provides improved prior information for top‐down models.

He, Keqi [Earth and Climate Sciences Nicholas Scho↗
NASA NTRS1992

Determination of water surface temperature based on the use of Thermal Infrared Multispectral Scanner data

A straightforward method for compensating Thermal Infrared Multispectral Scanner (TIMS) digital data for the influence of atmospheric path radiance and the attenuation of target energy by the atmosphere is presented. A band ratioing model useful for estimating water surface temperatures, which requires no ground truth measurements, is included. A study conducted to test the potential of the model and the magnitudes of the corrections for atmosphere encountered is presented. Results of the study, which was based on data collected during an engineering evaluation flight of TIMS, indicate errors in the estimate of the surface temperature of the water fall from +/- 1.0 C for uncorrected data to +/- 0.4 C when data have been corrected according to the model presented. This value approaches the noise-limited thermal resolution of the sensor at the time of the flight.

Anderson, James E.↗
NASA NTRS2015

Stratospheric Temperatures and Water Loss From Moist Greenhouse Atmospheres of Earth-Like Planets

A radiative-convective climate model is used to calculate stratospheric temperatures and water vapor concentrations for ozone-free atmospheres warmer than that of modern Earth. Cold, dry stratospheres are predicted at low surface temperatures, in agreement with recent 3D calculations. However, at surface temperatures above 350 K, the stratosphere warms and water vapor becomes a major upper atmospheric constituent, allowing water to be lost by photodissociation and hydrogen escape. Hence, a moist greenhouse explanation for loss of water from Venus, or some exoplanet receiving a comparable amount of stellar radiation, remains a viable hypothesis. Temperatures in the upper parts of such atmospheres are well below those estimated for a gray atmosphere, and this factor should be taken into account when performing inverse climate calculations to determine habitable zone boundaries using 1D models.

Astrobiology↗
DOE OSTI2025

Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"

This data package contains the associated data and scripts for Nagamoto, E., Ombadi, M., Ciulla, F. et al. Widespread drought-driven declines in streamflows and water quality in the Upper Colorado River Basin during 1998-2022. Commun Earth Environ 7, 734 (2026). https://doi.org/10.1038/s43247-026-03890-5. This purpose of this study was to investigate the impact of the 21st century drought on water quantity and quality at catchments throughout the Upper Colorado River Basin (UCRB). We used stream flow, water temperature, specific conductance, air temperature, precipitation, and catchment attribute data for over 200 sites in the UCRB, collected from the National Water Information System using Basin3D (Varadharajan, 2023), GAGESII (Falcone, 2010), and the Google Earth Engine. We identified years of severe drought between 1998 and 2022 using the Standardized Precipitation Evaporation Index (SPEI), then calculated the relative change percentage of the stream flow, water temperature, and specific conductance from drought versus non-drought years. We used the attribute information from GAGESII to investigate what physical traits of catchments are associated streamflow vulnerability (greater relative change) or resilience to drought. We used land cover data from the National Land Cover Database (USGS, 2024) to assess any changes to physical attributes that may not be represented in the static attributes information in GAGESII. To increase data availability, we modeled stream temperature using methods from Willard, 2023. While the study period is water years 1998 to 2022, the raw water quantity and quality data extends to 1950 and the meteorological data extends to 1980. The data and code can be downloaded via the UCRB_drought.zip. Within the zip, the files are organized as follows: - INPUTS: Contains all input data used in UCRB_Drought_Workflow.ipynb - OUTPUTS: Contains all intermediate data created from UCRB_Drought_Workflow.ipynb as well as final products including the calculated Standardized Evapotranspiration Index (SPEI) - climatic_variables: The code used to collect meteorologic data from Google Earth Engine - feature_importance: The code used for the catchment attributes analysis - preprocessing: Code used in UCRB_Drought_Workflow_Preprocessing.ipynb - pyeto: Code used in UCRB_Drought_Workflow_Preprocessing.ipynb - calculations: Code used in UCRB_Drought_Workflow_Impacts.ipynb - plotting: Code used in UCRB_Drought_Workflow_Impacts.ipynb - README.md - UCRB_Drought_Workflow_Preprocessing.ipynb: The code used to prep raw data for the analysis - UCRB_Drought_Workflow_Impact.ipynb: The code which uses the prepped raw data for analysis, and plots all figures - requirements_ucrb-drought_v2.yml: The requirements file to create a virtual environment and Jupyter Lab kernel to run the code The INPUTS folder is organized into the following major directories and sub-directories. The "RDC_WT_SC_RAW" folder contains raw data for streamflow, water temperature, and specific conductance in a ".h5" file. The "NLCD_RAW" folder contains ".csv" files with annual land cover percentages for counties within the UCRB. The "MET_RAW" folder contains a ".csv" file with monthly meteorological data (air temperature and precipitation) for the sites in the UCRB which was obtained from code in the climatic_variables folder. The "GAGESII" folder contains ".csv" files with physical catchment attribute variables for catchments across the country. The "WT_LSTM_data" folder contains ".csv" files with calculated WT (Willard, 2023) and the associated RMSEs. The "Upper_Colorado_River_Basin_Boundary" folder contains geographic data including a shapefile for plotting in the UCRB_Drought_Workflow.ipynb. The "RESERVOIRS_RAW" folder contains ".csv" files for each reservoir in the UCRB with daily reservoir storage. There are also two files in the INPUTS folder that have combined reservoir storage data and reservoir metadata. The OUTPUTS folder is organized into the following major directories and sub-directories. The "RDC_WT_SC_data" folder contains a folder "Water_year" with the associated cleaned data, metadata, and data availability information in ".csv" files, a folder "Median_Relchange" with the relative change comparing drought to non-drought years in ".csv" files, and a folder "Peak95_Min5_Relchange" that has ".csv" files for the relative change in peak (95th %) and minimum (5th %) variables. The "NLCD_data" folder contains the difference in land cover from the beginning to end of the study period and the percentage of the county that is within UCRB bounds can be found in Nagamoto et al (2025)). The "MET_data" folder contains separated monthly air temperature and precipitation data and the calculated PET in ".csv" files. The "SPEI_data" folder contains ".csv" files with calculated SPEI values (one restricted to the study period and the other with information from the entire MET data period). The "Paper_Tables" folder contains two ".csv" files containing site information and data availability and information about the GAGESII trait aggregated categories. The base directory includes the file “flmd.csv” for a list and description of all files and the file “dd.csv” for data dictionaries. Scripts for preprocessing, analysis, and figure generation are located in the associated GitHub repository found at [https://github.com/iNAIADS/drought-impacts/tree/develop/UCRB-drought]. UPDATE 1: Title and code file updated to match submitted manuscript 10-15-2025. UPDATE 2: Code and data files updated to match revised manuscript 3-4-2026. UPDATE 3: Code and data files updated to match revised manuscript 6-7-2026. ** NOTE: DD and FLMD have not been updated yet. UPDATE 4: Added associated Manuscript information and DD and FLMD have been updated. To cite this code, please use the following BibTeX: @misc{nagamoto2025drought, author = {Emily Nagamoto and Fabio Ciulla and Mohammad Ombadi and Jared Willard and Rosemary Carroll and Charuleka Varadharajan}, title = {Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"}, year = {2025}, doi = {10.15485/2551894}, publisher = {ESS-DIVE Repository}, url = {https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2551894} }

54 ENVIRONMENTAL SCIENCES↗