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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

GeoNEX: Land Monitoring from a New Generation of Geostationary Sensors

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

GeoNEX↗
NASA NTRS1994

Surface energy changes produced by ultraviolet-ozone irradiation of poly(methylmethacrylate), polycarbone and polytetrafluoroethylene

Contact angles of water and methylene iodide were measured as a function of UV/O3 treatment time for three polymers: poly(methylmethacrylate) (PMMA), polycarbonate, and polytetrafluoroethylene (PTFE). Surface roughnesses were also measured. Surface free energies were then calculated using relationships developed by Kaelble and Neumann. The surface energy of polycarbonate was found to increase (60 percent) during UV/O3 treatment. However, calculations on PMMA were hampered by the formation of a water soluble surface product. On PTFE surfaces, the UV/O3 treatment etched the surface causing large increases in surface roughness, rendering contact angle measurements impossible. It is concluded that care must be taken in interpreting contact angle measurements and surface energy calculations on UV/O3 treated polymer surfaces.

Ponter, A. B.↗
NASA NTRS1999

Impact of Assimilating GOES-Derived Land Surface Variables into the PSU/NCAR MM5

Land surface processes are known to have a profound impact on the overlying atmosphere over a wide range of spatial and temporal scales. Many atmospheric numerical models include special parameterizations to improve the specification and partitioning of surface fluxes which are critical to the accurate prediction of warm season boundary layer behavior, organized mesoscale circulations, and convective precipitation. However, the added degrees of freedom resulting from the inclusion of vegetation and soil schemes require the specification of additional surface parameters such as vegetative resistances, green vegetation fraction, leaf area index, soil physical and hydraulic characteristics, and the vertical distribution of soil moisture. As satellite data have become more readily available in recent years, many investigations have attempted to use these new measurements to infer missing components of the surface energy budget. Sensitivity studies have shown land-skin temperature (LST) tendencies during the mid-morning hours are strongly sensitive to the surface moisture availability (a function of soil wetness and vegetation) and less sensitive to other parameters such as surface roughness. Based upon results from these and other studies, developed a simple technique that dynamically assimilates Geostationary Operational Environmental Satellite (GOES) derived land-surface products into the surface energy budget of a mesoscale model. The purpose of this paper is to demonstrate that assimilating the GOES satellite data has the potential to improve the representation of land surface characteristics within the model without prior knowledge of the land surface characteristics. The assimilation technique is presented in Section 2 and the numerical experiments are detailed in Section 3. Preliminary results and conclusions are presented in Sections 4 and 5, respectively.

Lapenta, William M.↗
NASA NTRS2014

Validation of Land Surface Temperature Products Derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) Using Ground-based and Heritage Satellite Measurements

Thermal infrared satellite observations of the Earth's surface are widely used to retrieve Land Surface Temperature (LST) and monitor LST changes around the world. Since January 2012, the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-Orbiting Partnership (S-NPP) has provided daily observations of LST with a spatial resolution of 750 m at nadir. Comparison of the standard VIIRS LST product with the equivalent daily standard product from the Moderate Resolution Imaging Spectroradiometer (MODIS) collection-5 and with ground-based measurements over vegetated and inland water surfaces showed good agreement. Analysis indicated the accuracy and precision of the VIIRS product over these cover types was 0.2 K and 2.0 K respectively provided the analyses included appropriate compensation for any spatial heterogeneity in LST within the validation site. However, comparisons between in situ LST and the VIIRS and MODIS LST.

Land surface temperature↗
NASA NTRS2019

Assessment of Satellite Sea Surface Salinity Products Using a Coupled ENSO Prediction Model

Much work has gone into revising and updating algorithms for converting satellite-measured radiances to useful ocean variables like sea surface salinity (e.g. SMOS - Boutin et al., 2017, SMAP - Fore et al., 2016 and Aquarius - Meissner et al., 2018). As part of our Ocean Salinity Science Team work, we utilize an intermediate-complexity air/sea coupled model as a transfer function to test if more mature satellite SSS model algorithms actually improve ENSO forecast skill. For initialization of the coupled forecast, we demonstrate that the positive impact of SSS assimilation is brought about by surface freshening near the eastern edge of the western Pacific warm pool and density changes that lead to shallower mixed layer between 10S-5N. In addition, salting near the ITCZ leads to a deepening of the mixed layer and thermocline near 8N. These patterns together provide the background state to amplify equatorial Kelvin waves and improve ENSO hindcasts (Hackert et al., 2019). Here we extend this work to compare the impact of various pairs of original and improved satellite SSS algorithms. For instance we compare SMAP V4.1 with the latest, SMAP V4.2, to see what impact algorithm improvements may have on ENSO forecasts. SSS observations are tested on seasonal to interannual variability of tropical Indo-Pacific Ocean dynamics as well as on dynamical ENSO forecasts by initializing twelve-month forecasts for each month of available data. All experiments assimilate satellite sea level (SL), sea surface temperature (SST), and in situ subsurface temperature and salinity observations (Tz, Sz). Additionally various satellite, blended, and in-situ SSS products are assimilated. We find that including satellite SSS significantly improves Niño3.4 sea surface temperature anomaly validation, more mature SSS model algorithms are generally improving ENSO forecasts over time, and more satellite SSS data coverage helps to extend useful forecasts.

Ocean↗
NASA NTRS2019

GEONEX Data Products: Geostationary Satellite Derived Land Surface and Atmospheric Public Data Products

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline will begin to produce provisional data products to be consumed by external collaborators and the academic community. In order to better inform and introduce the GEONEX products to the science community, the provisional products shall be distributed from the NAS data portal, located at data.nas.nasa.gov, and simple webpage at www.nasa.gov/geonex has been deployed, which describes any algorithms used in deriving the products, user manuals and data file information. We will also update the status of the data processing, on the website and provide links to the latest datasets, and use a geonex mailing list, using lists.nasa.gov.

Wang, Weile↗
NASA NTRS1983

NOAA satellite-derived operational sea surface temperature products

The National Oceanic and Atmospheric Administration (NOAA) began processing global measurements of emitted radiation in the 10.5 to 12.5 micron atmospheric window for purposes of deriving weekly composite and mean monthly sea surface temperature fields in the early 1970s. Atmospheric attenuation corrections, begun with empirical means, were accomplished chiefly with the aid of coarser resolution measurements from atmospheric sounders aboard the same polar orbiting spacecraft. Cloud filtering depended heavily upon the use of histogram techniques applied to 11 x 11 arrays of 8 km resolution Scanning Radiometer Infrared (SRIR) data. Details of the SRIR processing for SST are found in a NOAA Technical Memorandum.

Mcclain, E. P.↗
NASA NTRS2008

The Effect of Lightning NOx Production on Surface Ozone in the Continental United States

Lightning NO(x) emissions calculated using the US National Lightning Detection Network data were found to account for 30% of the total NO(x) emissions for July August 2004, a period chosen both for having higher lightning NO(x) production and high ozone levels, thus maximizing the likelihood that such emissions could impact peak ozone levels. Including such emissions led to modest, but sometimes significant increases in simulated surface ozone when using the Community Multi-scale Air Quality Model (CMAQ). Three model simulations were performed, two with the addition of lightning NO(x) emissions, and one without. Domain-wide daily maximum 8-h ozone changes due to lightning NO(x) were less than 2 ppbv in 71 % of the cases with a maximum of 10 ppbv; whereas the difference in 1-h ozone was less than 2 ppbv in 77% of the cases with a maximum of 6 ppbv. Daily maximum 1-h and 8-h ozone for grids containing O3 monitoring stations changed slightly, with more than 43% of the cases differing less than 2 ppbv. The greatest differences were 42 ppbv for both 1-h and 8-h O3 , though these tended to be on days of lower ozone. Lightning impacts on the season-wide maximum 1-h and 8-h averaged ozone decreased starting from the 1 st to 4th highest values (an average of 4th highest, 8-h values is used for attainment demonstration in the US). Background ozone values from the y-intercept of O3 versus NO(z) curve were 42.2 and 43.9 ppbv for simulations without and with lightning emissions, respectively. Results from both simulations with lightning NO(x) suggest that while North American lightning production of NO(x) can lead to significant local impacts on a few occasions, they will have a relatively small impact on typical maximum levels and determination of Policy Relevant Background levels.

Kaynak, B.↗
DOE OSTI2024

Beyond the visible: Accounting for ultraviolet and far‐red radiation in vegetation productivity and surface energy budgets

Photosynthetically active radiation (PAR) is typically defined as light with a wavelength within 400–700 nm. However, ultra-violet (UV) radiation within 280–400 nm and far-red (FR) radiation within 700–750 nm can also excite photosystems, though not as efficiently as PAR. Vegetation and land surface models (LSMs) typically do not explicitly account for UV's contribution to energy budgets or photosynthesis, nor FR's contribution to photosynthesis. However, whether neglecting UV and FR has significant impacts remains unknown. Here, we explored how canopy radiative transfer (RT) and photosynthesis are impacted when explicitly implementing UV in the canopy RT model and accounting for UV and FR in the photosynthesis models within a next-generation LSM that can simulate hyperspectral canopy RT. We validated our improvements using photosynthesis measurements from plants under different light sources and intensities and surface reflection from an eddy-covariance tower. Our model simulations suggested that at the whole plant level, after accounting for UV and FR explicitly, chlorophyll content, leaf area index (LAI), clumping index, and solar radiation all impact the modeling of gross primary productivity (GPP). At the global scale, mean annual GPP within a grid would increase by up to 7.3% and the increase is proportional to LAI; globally integrated GPP increases by 4.6 PgC year −1 (3.8% of the GPP without accounting for UV + FR). Further, using PAR to proxy UV could overestimate surface albedo by more than 0.1, particularly in the boreal forests. Our results highlight the importance of improving UV and FR in canopy RT and photosynthesis modeling and the necessity to implement hyperspectral or multispectral canopy RT schemes in future vegetation and LSMs.

energy budget↗
NASA NTRS1988

Global land-surface primary productivity based upon Nimbus-7 37 GHz data

Accumulation and renewal of organic matter as quantified through net primary productivity (NPP) is considered a very major function of the biosphere, and its estimation is crucial in understanding the carbon cycle. A physically-based model relating NPP to the difference of vertically and horizontally polarized brightness temperatures (Delta T) observed at 37 GHz frequency of the scanning multichannel microwave radiometer on board the Nimbus-7 satellite is used for fitting areally averaged values of NPP and Delta T for five biomes. The land-surface NPP within 80 deg N to 55 deg S is then calculated using the Delta T data and compared with other estimates.

Choudhury, B. J.↗
NASA NTRS2013

Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment

The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

remote sensing↗
NASA NTRSDate not supplied

A Daily Surface Melt Product From Passive Microwave Swath Observations for Arctic Sea Ice Studies

Most passive microwave sea ice data products are produced with daily gridded brightness temperatures. However, a single polar-orbiting passive microwave instrument makes many measurements per day where swaths overlap in the polar regions. These level 1 swath brightness temperature observations can be used to derive information on sub-daily sea ice processes. One such process is the rapid transition of snow and ice between freezing and melting due to diurnal freeze-thaw cycling or brief warming events in the pre-melt season. Here, a new method utilizing the sub-daily variability in swath-to-swath observations is used to produce daily, binary maps of the melting status on Arctic Sea ice using Level 1C brightness temperatures from the Special Sensor Microwave Imager and Sounder (SSM/I-SSMIS) data record. The resulting data set will enable investigations of the frequency, inter-annual variability, and spatial extent of brief surface melting events occurring in the winter and shoulder seasons outside of the traditional summer melt season.

Angela C. Bliss↗
DOE OSTI2024

Enhancing Low-Temperature Syngas Production via Surface Tailoring of Supported Intermetallic Nanocatalysts

An active and coke-resistant silica-encapsulated intermetallic Ni 3 Zn nanoparticle catalyst was developed for low-temperature (450 °C) dry reforming of methane (DRM). The catalyst exhibited a remarkable 4-fold increase in activity (4.5 s –1 ) with over 99% CO selectivity and 3 orders of magnitude less carbonaceous species and demonstrated remarkable stability (70 h) compared to that of a monometallic Ni catalyst. Here, the key is the combined effect of surface ensemble structure and electronic interaction modulation through the surface composition tailoring achieved by off-stoichiometric Ni and Zn loading in controlling surface chemistry for achieving different activities and H 2 /CO ratios. Characterized by ion spectroscopy, X-ray photoelectron spectroscopy, and the neutron pair distribution function, it was revealed that paired Ni δ – –Zn δ+ active sites are crucial for DRM. Transient infrared spectroscopy and isotopic analysis uncovered the synergistic effect of Ni δ – –Zn δ+ sites in activating C–H bonds and dissociating CO 2 to prevent coke formation under low-temperature conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1988

Multi-property modeling of ocean basin carbon fluxes

The objectives of this project were to elucidate the causal mechanisms in some of the most important features of the global ocean/atomsphere carbon system. These included the interaction of physical and biological processes in the seasonal cycle of surface water pCo2, and links between productivity, surface chlorophyll, and the carbon cycle that would aid global modeling efforts. In addition, several other areas of critical scientific interest involving links between the marine biosphere and the global carbon cycle were successfully pursued; specifically, a possible relation between phytoplankton emitted DMS and climate, and a relation between the location of calcium carbonate burial in the ocean and metamorphic source fluxes of CO2 to the atmosphere. Six published papers covering the following topics are summarized: (1) Mass extinctions, atmospheric sulphur and climatic warming at the K/T boundary; (2) Sensitivity of climate and atmospheric CO2 to deep-ocean and shallow-ocean carbonate burial; (3) Controls on CO2 sources and sinks in the earthscale surface ocean; (4) pre-anthropogenic, earthscale patterns of delta pCO2 between ocean and atmosphere; (5) Effect on atmospheric CO2 from seasonal variations in the high latitude ocean; and (6) Limitations or relating ocean surface chlorophyll to productivity.

Volk, Tyler↗