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At least 793 records · Page 44
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NASA NTRS2014

Detecting Change in Urban Areas at Continental Scales with MODIS Data

Urbanization is one of the most important components of global environmental change, yet most of what we know about urban areas is at the local scale. Remote sensing of urban expansion across large areas provides information on the spatial and temporal patterns of growth that are essential for understanding differences in socioeconomic and political factors that spur different forms of development, as well the social, environmental, and climatic impacts that result. However, mapping urban expansion globally is challenging: urban areas have a small footprint compared to other land cover types, their features are small, they are heterogeneous in both material composition and configuration, and the form and rates of new development are often highly variable across locations. Here we demonstrate a methodology for monitoring urban land expansion at continental to global scales using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The new method focuses on resolving the spectral and temporal ambiguities between urban/non-urban land and stable/changed areas by: (1) spatially constraining the study extent to known locations of urban land; (2) integrating multitemporal data from multiple satellite data sources to classify c. 2010 urban extent; and (3) mapping newly built areas (2000-2010) within the 2010 urban land extent using a multi-temporal composite change detection approach based on MODIS 250 m annual maximum enhanced vegetation index (EVI). We test the method in 15 countries in East-Southeast Asia experiencing different rates and manifestations of urban expansion. A two-tiered accuracy assessment shows that the approach characterizes urban change across a variety of socioeconomic/political and ecological/climatic conditions with good accuracy (70-91% overall accuracy by country, 69-89% by biome). The 250 m EVI data not only improve the classification results, but are capable of distinguishing between change and no-change areas in urban areas. Over 80% of the error in the change detection can be related to definitional issues or error propagation, rather than algorithm error. As such, these methods hold great potential for routine monitoring of urban change, as well as for providing a consistent and up-to-date dataset on urban extent and expansion for a rapidly evolving region.

Urban areas↗
NASA NTRS2015

Land Boundary Conditions for the Goddard Earth Observing System Model Version 5 (GEOS-5) Climate Modeling System: Recent Updates and Data File Descriptions

The Earths land surface boundary conditions in the Goddard Earth Observing System version 5 (GEOS-5) modeling system were updated using recent high spatial and temporal resolution global data products. The updates include: (i) construction of a global 10-arcsec land-ocean lakes-ice mask; (ii) incorporation of a 10-arcsec Globcover 2009 land cover dataset; (iii) implementation of Level 12 Pfafstetter hydrologic catchments; (iv) use of hybridized SRTM global topography data; (v) construction of the HWSDv1.21-STATSGO2 merged global 30 arc second soil mineral and carbon data in conjunction with a highly-refined soil classification system; (vi) production of diffuse visible and near-infrared 8-day MODIS albedo climatologies at 30-arcsec from the period 2001-2011; and (vii) production of the GEOLAND2 and MODIS merged 8-day LAI climatology at 30-arcsec for GEOS-5. The global data sets were preprocessed and used to construct global raster data files for the software (mkCatchParam) that computes parameters on catchment-tiles for various atmospheric grids. The updates also include a few bug fixes in mkCatchParam, as well as changes (improvements in algorithms, etc.) to mkCatchParam that allow it to produce tile-space parameters efficiently for high resolution AGCM grids. The update process also includes the construction of data files describing the vegetation type fractions, soil background albedo, nitrogen deposition and mean annual 2m air temperature to be used with the future Catchment CN model and the global stream channel network to be used with the future global runoff routing model. This report provides detailed descriptions of the data production process and data file format of each updated data set.

GEOS-5↗
NASA NTRS2016

Avoiding Stair-Step Artifacts in Image Registration for GOES-R Navigation and Registration Assessment

In developing software for independent verification and validation (IVV) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.

stair-step artifact↗
NASA NTRS2016

Cross Correlation versus Normalized Mutual Information on Image Registration

This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.

band-to-band↗
NASA NTRS2016

Solar Powered CO.Sub.2 Conversion

Methods and devices for reducing CO.sub.2 to produce hydrocarbons are disclosed. A device comprises a photoanode capable of splitting H.sub.2O into electrons, protons, and oxygen; an electrochemical cell cathode comprising an electro-catalyst capable of reducing CO.sub.2; H.sub.2O in contact with the surface of the photoanode; CO.sub.2 in contact with the surface of the cathode; and a proton-conducting medium positioned between the photoanode and the cathode. Electrical charges associated with the protons and the electrons move from the photoanode to the cathode, driven in part by a chemical potential difference sufficient to drive the electrochemical reduction of CO.sub.2 at the cathode. A light beam is the sole source of energy used to drive chemical reactions. The photoanode can comprise TiO.sub.2 nanowires or nanotubes, and can also include WO.sub.3 nanowires or nanotubes, quantum dots of CdS or PbS, and Ag or Au nanostructures. The cathode can comprise a conductive gas diffusion layer with nanostructures of an electro-catalyst such as Cu or Co.

Chen, Bin↗
NASA NTRS2016

Measuring a Truncated Disk in Aquila X-1

We present NuSTAR and Swift observations of the neutron star Aquila X-1 during the peak of its 2014 July outburst. The spectrum is soft with strong evidence for a broad Fe K(alpha) line. Modeled with a relativistically broadened reflection model, we find that the inner disk is truncated with an inner radius of 15 +/- 3RG. The disk is likely truncated by either the boundary layer and/or a magnetic field. Associating the truncated inner disk with pressure from a magnetic field gives an upper limit of B < 5+/- 2x10(exp 8) G. Although the radius is truncated far from the stellar surface, material is still reaching the neutron star surface as evidenced by the X-ray burst present in the NuSTAR observation.

accretion disks aEuro" magnetic fields aEuro" star↗
NASA NTRS2016

NuSTAR Discovery of a Cyclotron Line in the Accreting X-Ray Pulsar IGR J16393-4643

The high-mass X-ray binary and accreting X-ray pulsar IGR J16393-4643 was observed by the Nuclear Spectroscope Telescope Array in the 3-79 keV energy band for a net exposure time of 50 ks. We present the results of this observation which enabled the discovery of a cyclotron resonant scattering feature with a centroid energy of -29.3(sup +1.1)(sub -1.3) keV. This allowed us to measure the magnetic field strength of the neutron star for the first time: B = (2.5 +/- 0.1) x 10(exp 12) G. The known pulsation period is now observed at 904.0+/- 0.1 s. Since 2006, the neutron star has undergone a long-term spin-up trend at a rate of P= -2 x 10(exp -8) s s(exp -1) (-0.6 s per year, or a frequency derivative of v = 3 x 10(exp -14) Hz s(exp -1)). In the power density spectrum, a break appears at the pulse frequency which separates the zero slope at low frequency from the steeper slope at high frequency. This addition of angular momentum to the neutron star could be due to the accretion of a quasi-spherical wind, or it could be caused by the transient appearance of a prograde accretion disk that is nearly in corotation with the neutron star whose magnetospheric radius is around 2 x 10(exp 8) cm.

accretion disks – gamma-ray burst: general – s↗
NASA NTRS2016

The Geometry of the Infrared and X-Ray Obscurer in a Dusty Hyperluminous Quasar

We study the geometry of the active galactic nucleus (AGN) obscurer in IRAS 09104+4109, an IR-luminous, radio-intermediate FR-I source at z = 0.442, using infrared data from Spitzer and Herschel, X-ray data from NuSTAR, Swift, Suzaku, and Chandra, and an optical spectrum from Palomar. The infrared data imply a total rest-frame 1-1000 micron luminosity of 5.5 × 10(exp 46) ergs/s and require both an AGN torus and a starburst model. The AGN torus has an anisotropy-corrected IR luminosity of 4.9 × 10(exp 46) ergs/s and a viewing angle and half-opening angle both of approximately 36deg from pole-on. The starburst has a star formation rate of (110 +/- 34) Stellar Mass/yr and an age of <50 Myr. These results are consistent with two epochs of luminous activity in IRAS 09104+4109: one approximately 150 Myr ago, and one ongoing. The X-ray data suggest a photon index of Gamma approx. =l 1.8 and a line-of-sight column density of N(sub H) approx. = 5 × 10(exp 23) sq cm. This argues against a reflection-dominated hard X-ray spectrum, which would have implied a much higher N(sub H) and luminosity. The X-ray and infrared data are consistent with a bolometric AGN luminosity of L(sub bol) approx.(0.5-2.5) ×10(exp 47) ergs/s. The X-ray and infrared data are further consistent with co-aligned AGN obscurers in which the line of sight "skims" the torus. This is also consistent with the optical spectra, which show both coronal iron lines and broad lines in polarized but not direct light. Combining constraints from the X-ray, optical, and infrared data suggest that the AGN obscurer is within a vertical height of 20 pc, and a radius of 125 pc, of the nucleus.

galaxies: evolution – galaxies: individual ( IRA↗
NASA NTRS2017

Sea Ice Outlook for September 2017: June Report - NASA Global Modeling and Assimilation Office

The GMAO seasonal forecast is produced from coupled model integrations that are initialized every five days, with seven additional ensemble members generated by coupled model breeding and initialized on the date closest to the beginning of the month. The main components of the AOGCM are the GEOS-5 atmospheric model, the MOM4 ocean model, and CICE sea ice model. Forecast fields were re-gridded to the passive microwave grid for averaging.

Sea Ice↗
NASA NTRS2015

New Insights on Subsurface Imaging of Carbon Nanotubes in Polymer Composites via Scanning Electron Microscopy

Despite many studies of subsurface imaging of carbon nanotube (CNT)-polymer composites via scanning electron microscopy (SEM), significant controversy exists concerning the imaging depth and contrast mechanisms. We studied CNT-polyimide composites and, by threedimensional reconstructions of captured stereo-pair images, determined that the maximum SEM imaging depth was typically hundreds of nanometers. The contrast mechanisms were investigated over a broad range of beam accelerating voltages from 0.3 to 30 kV, and ascribed to modulation by embedded CNTs of the effective secondary electron (SE) emission yield at the polymer surface. This modulation of the SE yield is due to non-uniform surface potential distribution resulting from current flows due to leakage and electron beam induced current. The importance of an external electric field on SEM subsurface imaging was also demonstrated. The insights gained from this study can be generally applied to SEM nondestructive subsurface imaging of conducting nanostructures embedded in dielectric matrices such as graphene-polymer composites, silicon-based single electron transistors, high resolution SEM overlay metrology or e-beam lithography, and have significant implications in nanotechnology.

Zhao, Minhua↗
NASA NTRS2017

Sea Ice Outlook for September 2017 July Report - NASA Global Modeling and Assimilation Office

The GMAO seasonal forecast is produced from coupled model integrations that are initialized every five days, with seven additional ensemble members generated by coupled model breeding and initialized on the date closest to the beginning of the month. The main components of the AOGCM are the GEOS-5 atmospheric model, the MOM4 ocean model, and CICE sea ice model. Forecast fields were re-gridded to the passive microwave grid for averaging.

Arctic↗
NASA NTRS2017

GEOS-5 Seasonal Forecast System

Ensembles of numerical forecasts based on perturbed initial conditions have long been used to improve estimates of both weather and climate forecasts. The Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model, Version 5 (GEOS-5 AOGCM) Seasonal-to-Interannual Forecast System has been used routinely by the GMAO since 2008, the current version since 2012. A coupled reanalysis starting in 1980 provides the initial conditions for the 9 month experimental forecasts. Once a month, sea surface temperature from a suite of 11 ensemble forecasts is contributed to the North American Multi-Model Ensemble (NMME) consensus project, which compares and distributes seasonal forecasts of ENSO events. Since June 2013, GEOS-5 forecasts of the Arctic sea-ice distribution were provided to the Sea-Ice Outlook project. The seasonal forecast output data includes surface fields, atmospheric and ocean fields, as well as sea ice thickness and area, and soil moisture variables. The current paper aims to document the characteristics of the GEOS-5 seasonal forecast system and to highlight forecast biases and skills of selected variables (sea surface temperature, air temperature at 2 m, precipitation and sea ice extent) to be used as a benchmark for the future GMAO seasonal forecast systems and to facilitate comparison with other global seasonal forecast systems.

GEOS-5↗
NASA NTRS2017

Observations of VOC Emissions and Photochemical Products over US Oil- and Gas-Producing Regions Using High-Resolution H3O+ CIMS (PTR-ToF-MS)

VOCs (Volatile Organic Compounds) related to oil and gas extraction operations in the United States were measured by H3O (sup plus) chemical ionization time-of-flight mass spectrometry (H3O (sup plus) ToFCIMS/PTR-ToF-MS (Time of Flight Chemical Ionization Mass Spectrometry/Proton Transfer Reaction-Time of Flight-Mass Spectroscopy) from aircraft during the Shale Oil and Natural Gas Nexus (SONGNEX) campaign in March-April 2015. This work presents an overview of major VOC species measured in nine oil- and gas-producing regions, and a more detailed analysis of H3O (sup plus) ToF-CIMS measurements in the Permian Basin within Texas and New Mexico. Mass spectra are dominated by small photochemically produced oxygenates and compounds typically found in crude oil: aromatics, cyclic alkanes, and alkanes. Mixing ratios of aromatics were frequently as high as those measured downwind of large urban areas. In the Permian, the H3O (sup plus) ToF-CIMS measured a number of underexplored or previously unreported species, including aromatic and cycloalkane oxidation products, nitrogen heterocycles including pyrrole (C4H5N) and pyrroline (C4H7N), H2S, and a diamondoid (adamantane) or unusual monoterpene. We additionally assess the specificity of a number of ion masses resulting from H3O (sup plus) ion chemistry previously reported in the literature, including several new or alternate interpretations.

mass spectrometr↗
NASA NTRS2017

Understanding Arctic Surface Temperature Differences in Reanalyses

Reanalyses in the Arctic are widely used for model evaluation and for understanding contemporary climate change. Nevertheless, differences among reanalyses in fundamental meteorological variables including surface air temperature are large. A review of surface temperature differences is presented with a particular focus on differences in contemporary reanalyses. An important consideration is the significant differences in Arctic surfaces, including the central Arctic Ocean, the Greenland Ice Sheet, and non-glaciated land. While there is significant correlation among reanalyses in annual time series, there is substantial disagreement in mean values. For the period 1980-2013, the trend in annual temperature ranges from 0.3 to 0.7K per decade. Over the central Arctic Ocean, differences in mean values and trends are larger. Most of the uncertainty is associated with winter months. This is likely associated with the constraint imposed by melting processes (i.e. 0 deg. Celsius), rather than seasonal changes to the observing system.

Sea Ic↗
NASA NTRS2017

Understanding Arctic Surface Temperature Differences in Reanalyses

Reanalyses in the Arctic are widely used for model evaluation and for understanding contemporary climate change. Nevertheless, differences among reanalyses in fundamental meteorological variables including surface air temperature are large. For example, the 1980-2009 mean surface air temperature for the north polar cap (70ÂdegN-90ÂdegN) among global reanalyses span a range of 2.4 K, which approximates the average warming trend from these reanalyses over the 30-year period of 2.1 K. Understanding these differences requires evaluation over the three principal surface domains of the Arctic: glaciated land, the unglaciated terrestrial surface, and sea ice/ocean. An examination is conducted of contemporary global reanalyses of the ECMWF Interim project, NASA MERRA, MERRA-2, JRA-55, and NOAA CFSR using available in situ data and assessments of the surface energy budget. Overly-simplistic representations of the Greenland Ice Sheet surface are found to be associated with local warm air temperature biases in winter. A review of progress made in the development of the MERRA-2 land-ice representation is presented. Large uncertainty is also found in temperatures over the Arctic tundra and boreal forest zone. But a key focus of temperature differences for northern high latitudes is the Arctic Ocean. Near-surface air temperature differences over the Arctic Ocean are found to be related to discrepancies in sea ice and sea surface temperature boundary data, which are severely compromised in current reanalyses. Issues with the modeled representation of sea ice cover are an additional factor in reanalysis temperature trends. Differences in the representation of the surface energy budget among the various reanalyses are also reviewed.

Surface Temperatur↗
NASA NTRS2017

Raman Life Detection Instrument Development for Icy Worlds

The objective of this project is to develop a compact, high sensitivity Raman sensor for detection of life signatures in a flow cell configuration to enable bio-exploration and life detection during future mission to our Solar Systems Icy Worlds. The specific project objectives are the following: 1) Develop a Raman spectroscopy liquid analysis sensor for biosignatures; 2) Demonstrate applicability towards a future Enceladus or other Icy Worlds missions; 3) Establish key parameters for integration with the ARC Sample Processor for Life on Icy Worlds (SPLIce); 4) Position ARC for a successful response to upcoming Enceladus or other Icy World mission instrument opportunities.

astrobiolog↗
NASA NTRS2017

Sensitivity of CONUS Summer Rainfall to the Selection of Cumulus Parameterization Schemes in NU-WRF Seasonal Simulations

This study investigates the sensitivity of daily rainfall rates in regional seasonal simulations over the contiguous United States (CONUS) to different cumulus parameterization schemes. Daily rainfall fields were simulated at 24-km resolution using the NASA-Unified Weather Research and Forecasting (NU-WRF) Model for June-August 2000. Four cumulus parameterization schemes and two options for shallow cumulus components in a specific scheme were tested. The spread in the domain-mean rainfall rates across the parameterization schemes was generally consistent between the entire CONUS and most subregions. The selection of the shallow cumulus component in a specific scheme had more impact than that of the four cumulus parameterization schemes. Regional variability in the performance of each scheme was assessed by calculating optimally weighted ensembles that minimize full root-mean-square errors against reference datasets. The spatial pattern of the seasonally averaged rainfall was insensitive to the selection of cumulus parameterization over mountainous regions because of the topographical pattern constraint, so that the simulation errors were mostly attributed to the overall bias there. In contrast, the spatial patterns over the Great Plains regions as well as the temporal variation over most parts of the CONUS were relatively sensitive to cumulus parameterization selection. Overall, adopting a single simulation result was preferable to generating a better ensemble for the seasonally averaged daily rainfall simulation, as long as their overall biases had the same positive or negative sign. However, an ensemble of multiple simulation results was more effective in reducing errors in the case of also considering temporal variation.

Iguchi, Takamichi↗