Search NASA⌕ Search

SEARCH · Search NASA

Results for “Spatial Characterization”

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.

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

At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Possible identification of a cluster of galaxies at redshift z = 3.4

We report the possible detection of a cluster of 16 radio-quiet galaxies at z = 3.4, identified in the field around the optically thick absorption system toward Q0000-263 at z(sub abs) = 3.390. Two of them, a Lyman alpha emitter at z = 3.428 and the galaxy responsible for the absorption system, have redshifts spectroscopically confirmed. The other 14 galaxies identified using a multicolor imaging technique designed to detect sources in the redshift interval 3 approximately less than z approximately less than 3.5 which are characterized by a Lyman discontinuity in an otherwise flat spectrum, have broad-band spectral energy distributions identical to the two galaxies with known redshift. They are spatially distributed in two apparent clumps, around the damped absorber and the Lyman alpha galaxy, respectively. A clustering analysis excludes with 98.8% confidence that this association is a realization of a Poissonian distribution and confirms that the observed clumps are real. The implications are that the 16 galaxies are members of a cluster at z approximately equals 3.4, by far the most distant ever detected. An estimate of the mass bounded in stars of this cluster is 3 x 10(exp 12) solar mass (q(sub 0) = 0 and H(sub 0) = 50 km/s/Mpc throughout this Letter), while the total mass (baryonic + dark) is 6 x 10(exp 14) solar mass. We also estimate that at z = 3.4 the correlation length is 2.2 Mpc, which, compared to the present value of 11 Mpc, suggests that the clustering evolution is still close to the linear regime.

Giavalisco, Mauro↗
NASA NTRS2006

Results and Lessons from MODIS Reflective Solar Bands Calibration: Pre-launch to On-orbit

MODIS is a major instrument for the NASA EOS Terra (1aunched in December 1999) and Aqua (launched in May 2002) missions. It was designed and built to enhance and extend its heritage sensors' measurements and data records with applications covering a wide range of studies of the Earth's land, oceans, and atmosphere. MODIS has 36 spectral bands (0.41 - 14.4 micrometers) located on four focal plane assemblies (FPAs). It makes measurements at three nadir spatial resolutions: 250m (bands 1-2), 500m (bands 3-7), and lkm (bands 8-36). Because of instrument design complexity and stringent calibration requirements, extensive calibration and characterization activities were conducted pre-launch by the sensor vendor (Raytheon / Santa Barbara Remote Sensing) for both Tesa and Aqua MODIS. For the 20 reflective solar bands (RSB), these activities include measurements for the detectors noise characterization and radiometric performance, system level response versus scan-angle (RVS), polarization sensitivity, and relative spectral response (RSR). Key radiometric performance was evaluated using thermal vacuum observations. On-orbit MODIS RSB calibration is performed using a solar diffuser (SD) and solar diffuser stability monitor (SDSM) system. The SD bi-directional reflectance factor (BRF) was characterized pre-launch by the sensor vendor with reference samples traceable to NIST reflectance standards. This paper provides a summary of Terra and Aqua MODIS RSB pre-launch and on-orbit calibration and characterization activities and results with focus on the detectors' noise characterization and radiometric performance. Challenging and concerning issues and lessons learned from RSB pre-launch calibration and their impact on post launch performance are also presented. A similar summary for MODIS thermal emissive bands (TEB) is reported in a separate paper in these proceedings.

Xiong, X.↗
NASA NTRS2007

An Experimental System for a Global Flood Prediction: From Satellite Precipitation Data to a Flood Inundation Map

Floods impact more people globally than any other type of natural disaster. It has been established by experience that the most effective means to reduce the property damage and life loss caused by floods is the development of flood early warning systems. However, advances for such a system have been constrained by the difficulty in estimating rainfall continuously over space (catchment-. national-, continental-. or even global-scale areas) and time (hourly to daily). Particularly, insufficient in situ data, long delay in data transmission and absence of real-time data sharing agreements in many trans-boundary basins hamper the development of a real-time system at the regional to global scale. In many countries around the world, particularly in the tropics where rainfall and flooding co-exist in abundance, satellite-based precipitation estimation may be the best source of rainfall data for those data scarce (ungauged) areas and trans-boundary basins. Satellite remote sensing data acquired and processed in real time can now provide the space-time information on rainfall fluxes needed to monitor severe flood events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models, which can be parameterized by a tailored geospatial database. An example that is a key to this progress is NASA's contribution to the Tropical Rainfall Measuring Mission (TRMM), launched in November 1997. Hence, in an effort to evolve toward a more hydrologically-relevant flood alert system, this talk articulates a module-structured framework for quasi-global flood potential naming, that is 'up to date' with the state of the art on satellite rainfall estimation and the improved geospatial datasets. The system is modular in design with the flexibility that permits changes in the model structure and in the choice of components. Four major components included in the system are: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM, topography-derived hydrologic parameters such as flood direction. flow accumulation, basin, and river network etc.; 3) spatially distributed hydrological models to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay thc input data to the models and display the flood inundation results to the users and decision-makers. Early results appear reasonable in terms of location and frequency of events. Case studies of this experimental system are evaluated with surface runoff data and other river monitoring systems. such as Dartmouth Flood Observatory's "Surface Water Watch" array of river reaches that are measured daily via other satellite remote sensing data. A major outcome of this progress will be the availability of a global overview of flood alerts that should consequently improve the performance of Decision Support System. We expect these developments in utilization of satellite remote sensing technology to offer a practical solution to the challenge of building a cost-effective early warning system for data scarce and under-developed areas.

Adler, Robert↗
NASA NTRS2012

Mars Sample Return: The Next Step Required to Revolutionize Knowledge of Martian Geological and Climatological History

The capability of scientific instrumentation flown on planetary orbiters and landers has made great advances since the signature Viking mission of the seventies. At some point, however, the science return from orbital remote sensing, and even in situ measurements, becomes incremental, rather than revolutionary. This is primarily caused by the low spatial resolution of such measurements, even for landed instrumentation, the incomplete mineralogical record derived from such measurements, the inability to do the detailed textural, mineralogical and compositional characterization needed to demonstrate equilibrium or reaction paths, and the lack of chronological characterization. For the foreseeable future, flight instruments will suffer from this limitation. In order to make the next revolutionary breakthrough in understanding the early geological and climatological history of Mars, samples must be available for interrogation using the full panoply of laboratory-housed analytical instrumentation. Laboratory studies of samples allow for determination of parageneses of rocks through microscopic identification of mineral assemblages, evaluation of equilibrium through electron microbeam analyses of mineral compositions and structures, determination of formation temperatures through secondary ion or thermal ionization mass spectrometry (SIMS or TIMS) analyses of stable isotope compositions. Such details are poorly constrained by orbital data (e.g. phyllosilicate formation at Mawrth Vallis), and incompletely described by in situ measurements (e.g. genesis of Burns formation sediments at Meridiani Planum). Laboratory studies can determine formation, metamorphism and/or alteration ages of samples through SIMS or TIMS of radiogenic isotope systems; a capability well-beyond flight instrumentation. Ideally, sample return should be from a location first scouted by landers such that fairly mature hypotheses have been formulated that can be tested. However, samples from clastic sediments derived from an extensive region of Mars can provide important, detailed understanding of early martian geological and climatological history. Interrogating clastic "sediments" from the Earth, Moon and asteroids has allowed discovery of new crustal units, identification of now-vanished crust, and determination of the geological history of extensive, remote regions. Returned sample of martian fluvial and/or aeolian sediments, for example from Gale crater, could be "read like a book" in terrestrial laboratories to provide truly revolutionary new insights into early martian geological and climatological evolution.

Mittlefehldt, D. W.↗
NASA NTRS2012

Exploring the Longwave Radiative Effects of Dust Aerosols

Dust aerosols not only affect air quality and visibility where they pose a significant health and safety risk, but they can also play a role in modulating the energy balance of the Earth-atmosphere system by directly interacting with local radiative fields. Consequently, dust aerosols can impact regional climate patterns such as changes in precipitation and the evolution of the hydrological cycle. Assessing the direct effect of dust aerosols at the solar wavelengths is fairly straightforward due in part to the relatively large signal-to-noise ratio in broadband irradiance measurements. The longwave (LW) impacts, on the other hand, are rather difficult to ascertain since the measured dust signal level (10 Wm-2) is on the same order as the instrumental uncertainties. Moreover, compared to the shortwave (SW), limited experimental data on the LW optical properties of dust makes it a difficult challenge for constraining the LW impacts. Owing to the strong absorption features found in many terrestrial minerals (e.g., silicates and clays), the LW effects, although much smaller in magnitude compared to the SW, can still have a sizeable impact on the energetics of the Earth-atmosphere system, which can potentially trigger changes in the heat and moisture surface budgets, and dynamics of the atmosphere. The current endeavor is an integral part of an on-going research study to perform detailed assessments of dust direct aerosol radiative effects (DARE) using comprehensive global datasets from NASA Goddards mobile ground-based facility (cf. http://smartlabs.gsfc.nasa.gov/) during previous field experiments near key dust source regions. Here we examine and compare the results from two of these studies: the 2006 NASA African Monsoon Multidisciplinary Activities and the 2008 Asian Monsoon Years. The former study focused on transported Saharan dust at Sal Island (16.73N, 22.93W), Cape Verde along the west coast of Africa while the latter focused on Asian dust at Zhangye China (39.082N, 100.276E), a semi-arid region between the Taklimakan and Gobi deserts. NASA Goddards Giovanni system is used to help map out the spatial distribution of retrieved aerosol optical depths across the latter desert regions. 1-D radiative transfer model constrained by local measurements, including spectral photometry/interferometry and lidar for characterizing the spatiotemporal variability in dust properties and atmospheric conditions, is employed to evaluate the local instantaneous LW DARE of dust both at the surface and at the top of the atmosphere along with heating rate profiles for cloud-free atmospheres. The efficiency in LW DARE and its significance relative to the diurnally averaged SW effects are explored and compared in both studies. Found to be non-negligible, LW DARE is an important component in the study of regional climate variation with important implications for more detailed global assessments.

Hansell, Richard A., Jr.↗
NASA NTRS2014

The Meteoroid Fluence at Mars Due to Comet C/2013 A1 (Siding Spring)

Long-period comet C/2013 A1 (Siding Spring) will experience a close encounter with Mars on 2014 Oct 19. A collision between the comet and the planet has been ruled out, but the comet's coma may envelop Mars and its man-made satellites. By the time of the close encounter, five operational spacecraft will be present near Mars. Characterizing the coma is crucial for assessing the risk posed to these satellites by meteoroid impacts. We present an analytic model of cometary comae that describes the spatial and size distributions of cometary dust and meteoroids. This model correctly reproduces, to within an order of magnitude, the number of impacts recorded by Giotto near 1P/Halley [1] and by Stardust near comet 81P/Wild 2 [2]. Applied to Siding Spring, our model predicts a total particle fluence near Mars of 0.02 particles per square meter. In order to determine the degree to which Siding Spring's coma deviates from a sphere, we perform numerical simulations which take into account both gravitational effects and radiative forces. We take the entire dust component of the coma and tail continuum into account by simulating the ejection and evolution of dust particles from comet Siding Spring. The total number of particles simulated is essentially a free parameter and does not provide a check on the total fluence. Instead, these simulations illustrate the degree to which the coma of Siding Spring deviates from the perfect sphere described by our analytic model (see Figure). We conclude that our analytic model sacrifices less than an order of magnitude in accuracy by neglecting particle dynamics and radiation pressure and is thus adequate for order-of-magnitude fluence estimates. Comet properties may change unpredictably and therefore an analytic coma model that enables quick recalculation of the meteoroid fluence is highly desirable. NASA's Meteoroid Environment Office is monitoring comet Siding Spring and taking measurements of cometary brightness and dust production. We will discuss our coma model and nominal fluence taking the latest observations into account.

Moorhead, A.↗
NASA NTRS2016

Post Launch Calibration and Testing of the Geostationary Lightning Mapper on GOES-R Satellite

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration (NOAA). The National Aeronautics and Space Administration (NASA) is procuring the GOES-R spacecraft and instruments with the first launch of the GOES-R series planned for October 2016. Included in the GOES-R Instrument suite is the Geostationary Lightning Mapper (GLM). GLM is a single-channel, near-infrared optical detector that can sense extremely brief (800 s) transient changes in the atmosphere, indicating the presence of lightning. GLM will measure total lightning activity continuously over the Americas and adjacent ocean regions with near-uniform spatial resolution of approximately 10 km. Due to its large CCD (1372x1300 pixels), high frame rate, sensitivity and onboard event filtering, GLM will require extensive post launch characterization and calibration. Daytime and nighttime images will be used to characterize both image quality criteria inherent to GLM as a space-based optic system (focus, stray light, crosstalk, solar glint) and programmable image processing criteria (dark offsets, gain, noise, linearity, dynamic range). In addition ground data filtering will be adjusted based on lightning-specific phenomenology (coherence) to isolate real from false transients with their own characteristics. These parameters will be updated, as needed, on orbit in an iterative process guided by pre-launch testing. This paper discusses the planned tests to be performed on GLM over the six-month Post Launch Test period to optimize and demonstrate GLM performance.

validation↗
NASA NTRS2016

Post Launch Calibration and Testing of the Geostationary Lightning Mapper on the GOES-R Satellite

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration (NOAA). The National Aeronautics and Space Administration (NASA) is procuring the GOES-R spacecraft and instruments with the first launch of the GOES-R series planned for October 2016. Included in the GOES-R Instrument suite is the Geostationary Lightning Mapper (GLM). GLM is a single-channel, near-infrared optical detector that can sense extremely brief (800 microseconds) transient changes in the atmosphere, indicating the presence of lightning. GLM will measure total lightning activity continuously over the Americas and adjacent ocean regions with near-uniform spatial resolution of approximately 10 km. Due to its large CCD (1372x1300 pixels), high frame rate, sensitivity and onboard event filtering, GLM will require extensive post launch characterization and calibration. Daytime and nighttime images will be used to characterize both image quality criteria inherent to GLM as a space-based optic system (focus, stray light, crosstalk, solar glint) and programmable image processing criteria (dark offsets, gain, noise, linearity, dynamic range). In addition ground data filtering will be adjusted based on lightning-specific phenomenology (coherence) to isolate real from false transients with their own characteristics. These parameters will be updated, as needed, on orbit in an iterative process guided by pre-launch testing. This paper discusses the planned tests to be performed on GLM over the six-month Post Launch Test period to optimize and demonstrate GLM performance.

validation↗
NASA NTRS2019

GRAIL-Identified Gravity Anomalies in Oceanus Procellarum: Insight into Subsurface Impact and Magmatic Structures on the Moon

Four, quasi-circular, positive Bouguer gravity anomalies (PBGAs) that are similar in diameter (~90-190 km) and gravitational amplitude (> 140 mGal contrast) are identified within the central Oceanus Procellarum region of the Moon. These spatially associated PBGAs are located south of Aristarchus Plateau, north of Flamsteed crater, and two are within the Marius Hills volcanic complex (north and south). Each is characterized by distinct surface geologic features suggestive of ancient impact craters and/or volcanic/plutonic activity. Here, we combine geologic analyses with forward modeling of high-resolution gravity data from the Gravity Recovery and Interior Laboratory (GRAIL) mission in order to constrain the subsurface structures that contribute to these four PBGAs. The GRAIL data presented here, at spherical harmonic degrees 6–660, permit higher resolution analyses of these anomalies than previously reported, and reveal new information about subsurface structures. Specifically, we find that the amplitudes of the four PBGAs cannot be explained solely by mare-flooded craters, as suggested in previous work; an additional density contrast is required to explain the high-amplitude of the PBGAs. For Northern Flamsteed (190 km diameter), the additional density contrast may be provided by impact-related mantle uplift. If the local crust has a density ~2800 kg/cu.m, then ~7 km of uplift is required for this anomaly, although less uplift is required if the local crust has a lower mean density of ~2500 kg/cu.m. For the Northern and Southern Marius Hills anomalies, the additional density contrast is consistent with the presence of a crustal complex of vertical dikes that occupies up to ~50% of the regionally thin crust. The structure of Southern Aristarchus Plateau (90 km diameter), an anomaly with crater-related topographic structures, remains ambiguous. Based on the relatively small size of the anomaly, we do not favor mantle uplift; however, understanding mantle response in a region of especially thin crust needs to be better resolved. It is more likely that this anomaly is due to subsurface magmatic material given the abundance of volcanic material in the surrounding region. Overall, the four PBGAs analyzed here are important in understanding the impact and volcanic/plutonic history of the Moon, specifically in a region of thin crust and elevated temperatures characteristic of the Procellarum KREEP Terrane.

Deutsch, Ariel N.↗
NASA NTRS2021

Satellite Monitoring for Air Quality and Health

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016–2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 μm in diameter (PM(sub 2.5)) and nitrogen dioxide (NO2). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.

Satellites↗
NASA NTRS2017

Imaging a Free-Geometry Magma Reservoir Using FEM-Based Linear Inverse Modeling of InSAR Data: Application to Rabaul Caldera, Papua New Guinea

We test an innovative inversion scheme using Green’s functions from an array of pressure sources embedded in finite-element method (FEM) models to image, without assuming an a-priori geometry, the composite and complex shape of a volcano deformation source. We invert interferometric synthetic aperture radar (InSAR) data to estimate the pressurization and shape of the magma reservoir of Rabaul caldera, Papua New Guinea. The results image the extended shallow magmatic system responsible for a broad and long-term subsidence of the caldera between 2007 February and 2010 December. Elastic FEM solutions are integrated into the regularized linear inversion of InSAR data of volcano surface displacements in order to obtain a 3-D image of the source of deformation. The Green’s function matrix is constructed from a library of forward line-of-sight displacement solutions for a grid of cubic elementary deformation sources. Each source is sequentially generated by removing the corresponding cubic elements from a common meshed domain and simulating the injection of a fluid mass flux into the cavity, which results in a pressurization and volumetric change of the fluidfilled cavity. The use of a single mesh for the generation of all FEM models avoids the computationally expensive process of non-linear inversion and remeshing a variable geometry domain. Without assuming an a-priori source geometry other than the configuration of the 3-D grid that generates the library of Green’s functions, the geodetic data dictate the geometry of the magma reservoir as a 3-D distribution of pressure (or flux of magma) within the source array. The inversion of InSAR data of Rabaul caldera shows a distribution of interconnected sources forming an amorphous, shallow magmatic system elongated under two opposite sides of the caldera. The marginal areas at the sides of the imaged magmatic system are the possible feeding reservoirs of the ongoing Tavurvur volcano eruption of andesitic products on the east side and of the past Vulcan volcano eruptions of more evolved materials on the west side. The interconnection and spatial distributions of sources correspond to the petrography of the volcanic products described in the literature and to the dynamics of the single and twin eruptions that characterize the caldera. The ability to image the complex geometry of deformation sources in both space and time can improve our ability to monitor active volcanoes, widen our understanding of the dynamics of active volcanic systems and improve the predictions of eruptions.

Inverse theory↗
NASA NTRS2017

Imaging the Complex Geometry of a Magma Reservoir Using Fem-Based Linear Inverse Modeling of InSAR Data: Application to Rabaul Caldera, Papua New Guinea

We test an innovative inversion scheme using Green’s functions from an array of pressure sources embedded in finite-element method (FEM) models to image, without assuming an a-priori geometry, the composite and complex shape of a volcano deformation source. We invert interferometric synthetic aperture radar (InSAR) data to estimate the pressurization and shape of the magma reservoir of Rabaul caldera, Papua New Guinea. The results image the extended shallow magmatic system responsible for a broad and long-term subsidence of the caldera between 2007 February and 2010 December. Elastic FEM solutions are integrated into the regularized linear inversion of InSAR data of volcano surface displacements in order to obtain a 3-D image of the source of deformation. The Green’s function matrix is constructed from a library of forward line-of-sight displacement solutions for a grid of cubic elementary deformation sources. Each source is sequentially generated by removing the corresponding cubic elements from a common meshed domain and simulating the injection of a fluid mass flux into the cavity, which results in a pressurization and volumetric change of the fluid-filled cavity. The use of a single mesh for the generation of all FEM models avoids the computationally expensive process of non-linear inversion and remeshing a variable geometry domain. Without assuming an a-priori source geometry other than the configuration of the 3-D grid that generates the library of Green’s functions, the geodetic data dictate the geometry of the magma reservoir as a 3-D distribution of pressure (or flux of magma) within the source array. The inversion of InSAR data of Rabaul caldera shows a distribution of interconnected sources forming an amorphous, shallow magmatic system elongated under two opposite sides of the caldera. The marginal areas at the sides of the imaged magmatic system are the possible feeding reservoirs of the ongoing Tavurvur volcano eruption of andesitic products on the east side and of the past Vulcan volcano eruptions of more evolved materials on the west side. The interconnection and spatial distributions of sources correspond to the petrography of the volcanic products described in the literature and to the dynamics of the single and twin eruptions that characterize the caldera. The ability to image the complex geometry of deformation sources in both space and time can improve our ability to monitor active volcanoes, widen our understanding of the dynamics of active volcanic systems and improve the predictions of eruptions.

Inverse theory↗
NASA NTRS2018

NASA NeMO-Net

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low- resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

NASA↗
NASA NTRSDate not supplied

Characterizing Spatiotemporal Uncertainty in Interpolated Meteorological Data

Interpolated meteorological data invariably contain errors. These errors have structure in time and space, particularly autocorrelation, which can cause the effects of errors to compound when model outputs are aggregated temporally or spatially. One way to account for this uncertainty is with a probabilistic model from which samples can be drawn that are coherent with respect to underlying spatial and temporal covariance structure. This work describes a probabilistic method for spatial interpolation of point-wise meteorological time series. Observational data from weather stations are generally sparse in space and dense in time (but sometimes missing). The method works by projecting time series onto orthogonal basis vectors and spatially interpolating each resulting component independently. Under suitable assumptions, and data transformations to better satisfy those assumptions, Gaussian process regression provides a complete description of the joint predictive distribution over a Gaussian random field. Spatiotemporally coherent realizations are generated as the sum of conditional (spatial) simulations of each orthogonal (temporal) component. Data-derived and generic orthogonal bases are considered. In addition to spatial interpolation, imputation of missing observational data is examined. The method is applied using near-surface air temperature over the Western United States and validated by comparing theoretical versus actual coverage of predictive distributions and analyzing the degree to which spatial and temporal covariance structure is reproduced. Computational considerations, relating to conditional simulation of random fields, are also addressed.

Conor T Doherty↗
NASA NTRS2011

Climatology of Aerosol Optical Properties in Southern Africa

A thorough regionally dependent understanding of optical properties of aerosols and their spatial and temporal distribution is required before we can accurately evaluate aerosol effects in the climate system. Long term measurements of aerosol optical depth, Angstrom exponent and retrieved single scattering albedo and size distribution, were analyzed and compiled into an aerosol optical properties climatology for southern Africa. Monitoring of aerosol parameters have been made by the AERONET program since the middle of the last decade in southern Africa. This valuable information provided an opportunity for understanding how aerosols of different types influence the regional radiation budget. Two long term sites, Mongu in Zambia and Skukuza in South Africa formed the core sources of data in this study. Results show that seasonal variation of aerosol optical thicknesses at 500 nm in southern Africa are characterized by low seasonal multi-month mean values (0.11 to 0.17) from December to May, medium values (0.20 to 0.27) between June and August, and high to very high values (0.30 to 0.46) during September to November. The spatial distribution of aerosol loadings shows that the north has high magnitudes than the south in the biomass burning season and the opposite in none biomass burning season. From the present aerosol data, no long term discernable trends are observable in aerosol concentrations in this region. This study also reveals that biomass burning aerosols contribute the bulk of the aerosol loading in August-October. Therefore if biomass burning could be controlled, southern Africa will experience a significant reduction in total atmospheric aerosol loading. In addition to that, aerosol volume size distribution is characterized by low concentrations in the non biomass burning period and well balanced particle size contributions of both coarse and fine modes. In contrast high concentrations are characteristic of biomass burning period, combined with significant dominance of fine mode particles.

Queface, Antonio J.↗
NASA NTRS2018

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

satellite data↗
NASA NTRS2004

Pickup Ion Velocity Distributions at Titan: Effects of Spatial Gradients

The principle source of pickup ions at Titan is its neutral exosphere, extending well above the ionopause into the magnetosphere of Saturn or the solar wind, depending on the moon's orbital position. Thermal and nonthermal processes in the thermosphere generate the distribution of neutral atoms and molecules in the exosphere. The combination of these processes and the range of mass numbers, 1 to over 28, contribute to an exospheric source structure that produces pickup ions with gyroradii that are much larger or smaller than the corresponding scale heights of their neutral sources. The resulting phase space distributions are dependent on the spatial structure of the exosphere as well as that of the magnetic field and background plasma. When the pickup ion gyroradius is less than the source gas scale height, the pickup ion velocity distribution is characterized by a sharp cutoff near the maximum speed, which is twice that of the ambient plasma times the sine of the angle between the magnetic field and the flow velocity. This was the case for pickup H(sup +) ions identified during the Voyager 1 flyby. In contrast, as the gyroradius becomes much larger than the scale height, the peak of the velocity distribution in the source region recedes from the maximum speed. Iri addition, the amplitude of the distribution near the maximum speed decreases. These more beam like distributions of heavy ions were not observed from Voyager 1 , but should be observable by more sensitive instruments on future spacecraft, including Cassini. The finite gyroradius effects in the pickup ion velocity distributions are studied by including in the analysis the possible range of spatial structures in the neutral exosphere and background plasma.

Hartle, R. E.↗
NASA NTRS2012

Using Apollo Sites and Soils to Compositionally Ground Truth Diviner Lunar Radiometer Observations

Apollo landing sites and returned soils afford us a unique opportunity to "ground truth" Diviner Lunar Radiometer compositional observations, which are the first global, high resolution , thermal infrared measurements of an airless body. The Moon is the most accessible member of the most abundant class of solar system objects, which includes Mercury, asteroids, and icy satellites. And the Apollo samples returned from the Moon are the only extraterrestrial samples with known spatial context. Here we compare Diviner observations of Apollo landing sites and compositional and spectral laboratory measurements of returned Apollo soils. Diviner, onboard NASA's Lunar Reconnaissance Orbiter, has three spectral channels near 8 micron that were designed to characterize the mid-infrared emissivity maximum known as the Christiansen feature (CF), a well-studied indicator of silicate mineralogy. It has been observed that thermal infrared spectra measured in simulated lunar environment (SLE) are significantly altered from spectra measured under terrestrial or martian conditions, with enhanced CF contrast and shifted CF position relative to other spectral features. Therefore only thermal emission experiments conducted in SLE are directly comparable to Diviner data. With known compositions, Apollo landing sites and soils are important calibration points for the Diviner dataset, which includes all six Apollo sites at approximately 200 m spatial resolution. Differences in measured CFs caused by composition and space weathering are apparent in Diviner data. Analyses of Diviner observations and SLE measurements for a range of Apollo soils show good agreement, while comparisons to thermal reflectance measurements under ambient conditions do not agree well, which underscores the need for SLE measurements and validates our measurement technique. Diviner observations of Apollo landing sites are also correlated with geochemical measurements of Apollo soils from the Lunar Sample Compendium. In particular, the correlations between CF and FeO and AI203 are very strong, owing to the dependence on the feldspar-mafic ratio. Our analyses suggest that Diviner data may offer an independent measure of soil iron content from the existing optical and gamma-ray spectrometer datasets.

Greenhagen, Benjamin T.↗