SEARCH · Engineering Papers

Results for “NpP”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30

All sources NASA NTRS DOE OSTI

NASA NTRS2016

Combining Livestock Production Information in a Process-Based Vegetation Model to Reconstruct the History of Grassland Management

Grassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the greenhouse gas balance and surface energy budget of this biome, both at field scale and at large spatial scale. However, global gridded historical information on grassland management intensity is not available. Combining modelled grass-biomass productivity with statistics of the grass-biomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of unmanaged grasslands and the fraction of mown vs. grazed area at a resolution of 0.5deg by 0.5deg. The grass-biomass demand is derived from a livestock dataset for 2000, extended to cover the period 19012012. The grass-biomass supply (i.e. forage grass from mown grassland and biomass grazed) is simulated by the process-based model ORCHIDEE-GM driven by historical climate change, risingCO2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study increases from 6.1 x 10(exp 6) km(exp 2) in 1901 to 12.3 x 10(exp 6) kmI(exp 2) in 2000, although the expansion pathway varies between different regions. ORCHIDEE-GM also simulated augmentation in global mean productivity and herbage-use efficiency over managed grassland during the 20th century, indicating a general intensification of grassland management at global scale but with regional differences. The gridded grassland management intensity maps are model dependent because they depend on modelled productivity. Thus specific attention was given to the evaluation of modelled productivity against a series of observations from site-level net primary productivity (NPP) measurements to two global satellite products of gross primary productivity (GPP) (MODIS-GPP and SIF data). Generally, ORCHIDEE-GM captures the spatial pattern, seasonal cycle, and inter-annual variability of grassland productivity at global scale well and thus is appropriate for global applications presented here.

Livestock dataset↗

NASA NTRS2017

Evaluation of VIIRS and MODIS Thermal Emissive Band Calibration Stability Using Ground Target

The S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, a polar orbiting Earth remote sensing instrument built using a strong MODIS background, employs a similarly designed on-board calibrating source - a V-grooved blackbody for the thermal emissive bands (TEB). The central wavelengths of most VIIRS TEBs are very close to those of MODIS with the exception of the 10.7 micron channel. To ensure the long term continuity of climate data records derived using VIIRS and MODIS TEB, it is necessary to assess any systematic differences between the two instruments, including scenes with temperatures significantly lower than blackbody operating temperatures at approximately 290 K. Previous work performed by the MODIS Characterization Support Team (MCST) at NASAGSFC used the frequent observations of the Dome Concordia site located in Antarctica to evaluate the calibration stability and consistency of Terra and Aqua MODIS over the mission lifetime. The near-surface temperature measurements from an automatic weather station (AWS) provide a direct reference useful for tracking the stability and determining the relative bias between the two MODIS instruments. In this study, the same technique is applied to the VIIRS TEB and the results are compared with those from the matched MODIS TEB. The results of this study show a small negative bias when comparing the matching VIIRS and Aqua MODIS TEB, implying a higher scene temperature retrieval for S-VIIRS at the cold end. Statistically no significant drift is observed for VIIRS TEB performance over the first 3.5 years of the mission.

Madhavan, Sriharsha↗

NASA NTRS2015

Improved Band-to-Band Registration Characterization for VIIRS Reflective Solar Bands Based on Lunar Observations

Spectral bands of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrumentaboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite are spatially co-registered.The accuracy of the band-to-band registration (BBR) is one of the key spatial parameters that must becharacterized. Unlike its predecessor, the Moderate Resolution Imaging Spectroradiometer (MODIS), VIIRS has no on-board calibrator specifically designed to perform on-orbit BBR characterization.To circumvent this problem, a BBR characterization method for VIIRS reflective solar bands (RSB) based on regularly-acquired lunar images has been developed. While its results can satisfactorily demonstrate that the long-term stability of the BBR is well within +/- 0.1 moderate resolution bandpixels, undesired seasonal oscillations have been observed in the trending. The oscillations are most obvious between the visiblenear-infrared bands and short-middle wave infrared bands. This paper investigates the oscillations and identifies their cause as the band spectral dependence of the centroid position and the seasonal rotation of the lunar images over calibration events. Accordingly, an improved algorithm is proposed to quantify the rotation and compensate for its impact. After the correction, the seasonal oscillation in the resulting BBR is reduced from up to 0.05 moderate resolution band pixels to around 0.01 moderate resolution band pixels. After removing this spurious seasonal oscillation, the BBR, as well as its long-term drift are well determined.

Wang, Zhipeng↗

NASA NTRS2016

Assessment of SNPP VIIRS VIS NIR Radiometric Calibration Stability Using Aqua MODIS and Invariant Surface Targets

The first Visible Infrared Imaging Radiometer Suite (VIIRS) is onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. As a primary sensor, it collects imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans in the spectral regions from visible (VIS) to long-wave infrared. NASA's National Polar-orbiting Partnership (NPP) VIIRS Characterization Support Team has been actively involved in the VIIRS radiometric and geometric calibration to support its Science Team Principal Investigators for their independent quality assessment of VIIRS Environmental Data Records. This paper presents the performance assessment of the radiometric calibration stability of the VIIRS VIS and NIR spectral bands using measurements from SNPP VIIRS and Aqua MODIS simultaneous nadir overpasses and over the invariant surface targets at the Libya-4 desert and Antarctic Dome Concordia snow sites. The VIIRS sensor data records (SDRs) used in this paper are reprocessed by the NASA SNPP Land Product Evaluation and Analysis Tool Element. This paper shows that the reprocessed VIIRS SDRs have been consistently calibrated from the beginning of the mission, and the calibration stability is similar to or better than MODIS. Results from different approaches indicate that the calibrations of the VIIRS VIS and NIR spectral bands are maintained to be stable to within 1% over the first three-year mission. The absolute calibration differences between VIIRS and MODIS are within 2%, with an exception for the 0.865-m band, after correction of their spectral response differences.

Wu, Aisheng↗

NASA NTRS2016

Scheduling Observations of Celestial Objects for Earth Observing Sensor Calibration

Radiometric calibration of Earth-observing satellite sensors is critical for tracking on-orbit gain changes through- out the satellite's mission. The Moon, being a stable, well-characterized radiometric target, has been used effectively for tracking the relative gain changes of the reflective solar bands for the Moderate Resolution Imaging Spectroradiometer (MODIS) on board EOS AM-1 (Terra) and PM-1 (Aqua). The Moon is viewed through the MODIS space-view port, and the relative phase of the Moon is restricted to within 0.5 degrees of a chosen target phase to increase the accuracy of the calibration. These geometric restrictions require spacecraft maneuvers in order to bring space-view port into proper alignment with the position of the Moon when the phase requirement is met. In this paper, we describe a versatile tool for scheduling such maneuvers based on the required geometry and lunar phase restrictions for a general spacecraft bound instrument. The results of the scheduling tool have been verified using lunar images from Aqua and Terra MODIS after a scheduled roll maneuver was performed. This tool has also been tested for the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Advanced Technology Microwave Sounder on-board the Suomi-NPP spacecraft. As an extension of this work, we have also developed a tool for scheduling views of bright stars. These stars provide another well-characterized radiometric source that can be used for sensor calibration. This tool has been implemented to determine the times in which a chosen star can be viewed by the high gain stages of the day/night band for the VIIRS instrument.

Wilson, Truman↗

NASA NTRS2016

Earth Remote Sensing for Weather Forecasting and Disaster Applications

NASA's constellation of current missions provide several opportunities to apply satellite remote sensing observations to weather forecasting and disaster response applications. Examples include: Using NASA's Terra and Aqua MODIS, and the NASA/NOAA Suomi-NPP VIIRS missions to prepare weather forecasters for capabilities of GOES-R; Incorporating other NASA remote sensing assets for improving aspects of numerical weather prediction; Using NASA, NOAA, and international partner resources (e.g. ESA/Sentinel Series); and commercial platforms (high-res, or UAV) to support disaster mapping.

Molthan, Andrew↗

NASA NTRS2017

Towards A Representation of Vertically Resolved Ozone Changes in Reanalyses

The Solar Backscatter Ultraviolet Radiometer (SBUV) instruments on NASA and NOAA spacecraft provide a long-term record of total-column ozone and deep-layer partial columns since about 1980. These data have been carefully processed to extract long-term trends and offer a valuable resource for ozone monitoring. Studies assimilating limb-sounding observations in the Goddard Earth Observing System (GEOS) data assimilation system (DAS) demonstrate that vertical ozone gradients in the upper troposphere and lower stratosphere (UTLS) are much better represented than with the deep-layer SBUV observations. This is exemplified by the use of retrieved ozone from the EOS Microwave Limb Sounder (EOS-MLS) instrument in the MERRA-2 reanalysis, for the period after 2004. This study examines the potential for extending the use of limb-sounding observations at earlier times and into the future, so that future reanalyses may be more applicable to the study of long-term ozone changes.Historical data are available from NASA instruments: the Limb Infrared Monitor of the Stratosphere (LIMS: 1978-1979); the Upper Atmospheric Research Satellite (UARS: 1991-1995); Sounding of the Atmosphere using Broadband Emission Radiometry (SABER: 2000-onwards). For the post EOS-MLS period, the joint NASA-NOAA Ozone Monitoring and Profiling Suite Limb Profiler (OMPS-LP) instrument was launched on the Suomi-NPP platform in 201x and is planned for future platforms. This study will examine two aspects of these data pertaining to future reanalyses. First, the feasibility of merging the EOS-MLS and OMPS-LP instruments to provide a long-term record that extends beyond the potential lifetime of EOS-MLS. If feasible, this would allow for long-term monitoring of ozone recovery in a three-dimensional reanalysis context. Second, the skill of the GEOS DAS in ingesting historical data types will be investigated. Because these do not overlap with EOS-MLS, use will be made of system statistics and evaluation using independent datasets. Impacts of using a complete ozone chemistry module will also be considered.

ML↗

NASA NTRS2017

Assimilation of All-Weather GMI and ATMS Observations into HWRF

Moradi, Isaac↗

NASA NTRS2017

Development of Multi-Sensor Global Cloud and Radiance Composites for DSCOVR EPIC Imager with Subpixel Definition

The Deep Space Climate Observatory (DSCOVR) enables analysis of the daytime Earth radiation budget via the onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). EPIC delivers adequate spatial resolution imagery but only in shortwave bands (317-780 nm), while NISTAR measures the top-of-atmosphere (TOA) whole-disk radiance in shortwave and longwave broadband windows. Accurate calculation of albedo and outgoing longwave flux requires a high-resolution scene identification such as the radiance observations and cloud properties retrievals from low earth orbit (LEO, including NASA Terra and Aqua MODIS, Suomi-NPP VIIRS, and NOAA AVHRR) and geosynchronous (GEO, including GOES east and west, METEOSAT, INSAT-3D, MTSAT-2, and Himawari-8) satellite imagers. The cloud properties are derived using the Clouds and the Earth's Radiant Energy System (CERES) mission Cloud Subsystem group algorithms. These properties have to be co-located with EPIC pixels to provide the scene identification and to select anisotropic directional models (ADMs), which are then used to adjust the NISTAR-measured radiance and subsequently obtain the global daytime shortwave and longwave fluxes. This work presents an algorithm for optimal merging of selected radiance and cloud property parameters derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. Selection of satellite data for each 5-km pixel is based on an aggregated rating that incorporates five parameters: nominal satellite resolution, pixel time relative to the EPIC time, viewing zenith angle, distance from day/night terminator, and probability of sun glint. To provide a smoother transition in the merged output, in regions where candidate pixel data from two satellite sources have comparable aggregated rating, the selection decision is defined by the cumulative function of the normal distribution so that abrupt changes in the visual appearance of the composite data are avoided. Higher spatial accuracy in the composite product is achieved by using the inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling.

Khlopenkov, Konstantin V.↗

NASA NTRS2017

Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS-national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91 percent was achieved, which is a 6 percent improvement in unmixing based classification relative to per-pixel-based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

Subpixel↗

NASA NTRS2017

Evaluation of the VIIRS BRDF, Albedo and NBAR Products Suite and an Assessment of Continuity with the Long Term MODIS Record

Bidirectional Reflectance Distribution Function (BRDF) model parameters, Albedo quantities, and Nadir BRDF Adjusted Reflectance (NBAR) products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS), on the Suomi-NPP (National Polar-orbiting Partnership) satellite are evaluated with spatially representative in situ tower albedometer measurements and through comparison with the MODerate Resolution Imaging Spectroradiometer (MODIS) long term record. White Sky Albedo (WSA), Black Sky Albedo (BSA), NBAR, and Quality Assurance (QA) results show that the VIIRS algorithm is performing well at the global scale and is able to provide global data products comparable with the heritage MODIS (with an absolute bias of 0.0069 for shortwave broadband WSA) despite the spectral, angular, and effective spatial resolution differences between the two sensors. Both VIIRS and MODIS albedo are shown to agree well with in situ albedo measurements at a number of spatially representative sites. This evaluation provides confidence that the high quality, daily VIIRS BRDF model parameters, Albedo, and NBAR products will be able to provide the long term continuity required by the modeling and monitoring communities.

VIIRS↗

NASA NTRS2018

Assimilation of All-Weather GMI and ATMS Observations into HWRF

Moradi, Isaac↗

NASA NTRS2018

Improving the Performance of the OMPS Limb Profiling Instrument in Monitoring Aerosols in the Post-Pinatubo Stratosphere

The OMPS Limb Profiling (LP) instrument was launched on NOAA's Suomi NPP (SNPP) weather satellite in October 2011. The instrument measures limb-scattered radiation in the ultraviolet, visible and NIR wavelengths with high vertical resolution (~2 km) and relatively dense spatial and temporal sampling (several thousand measurements/day covering the entire sunlit globe). These measurements have very high sensitivity to stratospheric aerosols due to long path of the incoming solar photons through the aerosol layer. However, unlike the recently launched ISS/SAGE III that directly measures extinction of solar/lunar radiation by gases and particles along the line of sight (LOS) of the instrument, information content of OMPS LP measurements is complex. It consists of solar radiation singly scattered and attenuated by aerosols, air, and trace gases along the LOS of the instrument, as well as diffuse upwelling radiation from the lower atmosphere that also gets scattered and attenuated into the LOS. To unscramble this complex signal one needs to have good knowledge of aerosol size distribution (ASD) and their complex refractive index. We will describe our recent efforts in constraining the ASD parameters by analyzing in-situ balloon data from Laramie, Wyoming; aerosol microphysical model data from CARMA; and spectral information provided by OMPS LP. We will also discuss our proposed methodology to reï¬ne this information by adjusting the microphysical properties of the aerosols to make data from various occultation and scattering instruments internally consistent. This is a generalized version of the technique employed by AERONET in which solar extinction data are combined with scattered radiation measured by the almucantar technique to determine aerosol particle shape, complex refractive index and size distribution. We suggest that such closure studies are essential to develop confidence in space-based data to validate aerosol microphysical models, such as CARMA, and aerosol chemistry- transport models, such as GOCART, and for estimating radiative forcing due to stratospheric aerosols in both volcanic and quiescent time periods.

Bhartia, P. K.↗

NASA NTRS2018

Correcting for Trace Gas Absorption When Retrieving Aerosol Optical Depth from Satellite Observations of Reflected Shortwave Radiation

Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon Moderate Resolution Imaging Spectroradiometer (MODIS, onboard Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, onboard Suomi-NPP) sensors, use wavelength bands in "window" regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper we use High-resolution TRANsmission (HITRAN) database and Line-by-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are "similar", they are different enough that applying MODIS specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases up to 0.07. As recent studies are attempting to create a long-term data record by joining multiple satellite datasets, including MODIS and VIIRS, the consistency of gas correction becomes even more crucial.

Satellite Remote Sensing↗

NASA NTRS2018

New, Multi-Spectral (RGB) Imagery Products from GOES-16 Usher in a New Era of Satellite Meteorology

Otherwise known as "R-G-B" imagery, these new products provide a paradigm shift in short-term nowcasting and situational awareness via remote sensing. SPoRT used NASA instruments like MODIS and S-NPP VIIRS to demonstrate RGB capabilities prior to GOES-16. Now, with geostationary RGBs in operations, SPoRT has collaborated with select forecasters to assess the impact of this new GOES-16 capability.

Fuell, Kevin K.↗

NASA NTRS2018

The Evolution of Gridded NUCAPS: An Overview of Research to Operations Activities

The next-generation S-NPP and NOAA-20 Cross-track Infrared Sounder (CrIS) temperature and moisture profiles can provide valuable observations; (1) Where conventional radiosonde observations are sparse, (2) Between radiosonde launches. CrIS observations are combined with the Advanced Technology Microwave Sounder (ATMS) to produce high quality vertical soundings in clear and partly cloudy conditions. NUCAPS (NOAA Unique Combined Atmospheric Processing System) is the operational algorithm for processing combined hyperspectral infrared and microwave measurements. NUCAPS Soundings are operationally available in AWIPS as Skew-T plots. The capability to visualize the data in plan view or cross section would be valuable to maximize the benefits of NUCAPS data in AWIPS. A multi-organizational collaboration through the JPPS Soundings Applications Initiative developed the capability for plan view and cross section displays of NUCAPS in AWIPS (i.e., Gridded NUCAPS).

Berndt, Emily↗

NASA NTRS2018

Assimilation of GMI and ATMS Observations in the Rainbands of Hurricanes

We propose a novel Bayesian Monte Carlo Integration (BMCI) technique to retrieve the profiles of temperature, water vapor, and cloud liquid/ice water content from microwave cloudy measurements in the presence of tropical cyclones (TC). These retrievals then can either be directly used by meteorologists to analyze the structure of TCs or be assimilated into numerical models to provide accurate initial conditions for the NWP models. The BMCI technique is applied to the data from the Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership (NPP) and Global Precipitation Measurement (GPM) Microwave Imager (GMI). The retrieved profiles are then assimilated into Hurricane WRF using GSI data assimilation system. This talk presents the development of the BMCI retrieval system as well as the preliminary results of assimilating the retrievals into NASA GEOS-5 model.

Moradi, Isaac↗

NASA NTRS2018

Overcoming Pitfalls When Using HDF5 Compression

Compression of large datasets in S-NPP, JPSS and other HDF5 data files may substantially reduce their size, in turn reducing disk space requirements and file download time. However, mismatches between the layout of the files' datasets, the HDF5 instance's cache settings, choice of compression algorithm, and the access pattern of applications using the data can sometimes result in poor performance or exhausting machine resources when running the application. Whether designed in advance or modified in response to encountered problems, applications can be tuned to optimize efficiency of data access, avoid unnecessary repeated decompression, and reduce the amount of memory used. Examples will be given of problems that may be encountered, how to use available tools to diagnose or work around them, changing cache settings to conserve memory, and designing access strategies to avoid both performance and memory issues when creating or modifying applications.

performance↗