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NASA NTRS2010

Estimating Glaciation Temperature of Deep Convective Clouds with Remote Sensing Data

Major uncertainties exist for observing and modeling ice content inside deep convective clouds (DCC). One of the difficulties has been the lack of characterization of vertical profiles of cloud hydrometeor phase. Here we propose a technique to estimate the DCC glaciation temperature using passive remote sensing data. It is based on a conceptual model of vertical hydrometeor size profiles inside DCCs. Estimates from the technique agree well with our general understanding of the problem. Furthermore, the link between vertical profiles of cloud particle size and hydrometeor thermodynamic phase is confirmed by a 3-13 cloud retrieval technique. The technique is applied to aircraft measurements of cloud side reflectance and the result was compared favorably with an independent retrieval of thermodynamic phase based on different refractive indices at 2.13 micron and 2.25 micron. Possible applications of the technique are discussed.

Yuan, Tianle↗

NASA NTRS1991

A Variational Formalism for the Radiative Transfer Equation: Prelude to Model 3

The MODEL III variational data assimilation model is the third of four general assimilation models designed to blend weather data measured from space based platforms in the meteorological data mainstream in a way that maximizes the information content of the satellite data. Because there are many different observation locations and there are many instruments with different measurement error characteristics, it is also necessary to require that the blending be done to maximize the information content of the data and simultaneously to retain a dynamically consistent and reasonably accurate description of the state of the atmosphere. This is ideally a variational problem for which the data receive relative weights that are inversely proportional to measurement error and are adjusted to satisfy a set of dynamical equations that govern atmospheric processes. The advantage of MODEL III over the previous two models is that radiance, the atmospheric variable measured by satellite, becomes a dependent variable. In the previous versions, mean layer temperatures that had been retrieved from the radiances by some method, were included in the assimilation by substituting them in place of the rawinsonde temperatures. Now both rawinsonde temperatures and satellite radiances are included independently in the assimilation.

Achtemeier, Gary L.↗

NASA NTRS2003

Overview of Mount Washington Icing Sensors Project

NASA, the FAA, the Department of Defense, the National Center for Atmospheric Research and NOAA are developing techniques for retrieving cloud microphysical properties from a variety of remote sensing technologies. The intent is to predict aircraft icing conditions ahead of aircraft. The Mount Washington Icing Sensors Project MWISP), conducted in April, 1999 at Mt. Washington, NH, was organized to evaluate technologies for the prediction of icing conditions ahead of aircraft in a natural environment, and to characterize icing cloud and drizzle environments. April was selected for operations because the Summit is typically in cloud, generally has frequent freezing precipitation in spring, and the clouds have high liquid water contents. Remote sensing equipment, consisting of radars, radiometers and a lidar, was placed at the base of the mountain, and probes measuring cloud particles, and a radiometer, were operated from the Summit. NASA s Twin Otter research aircraft also conducted six missions over the site. Operations spanned the entire month of April, which was dominated by wrap-around moisture from a low pressure center stalled off the coast of Labrador providing persistent upslope clouds with relatively high liquid water contents and mixed phase conditions. Preliminary assessments indicate excellent results from the lidar, radar polarimetry, radiosondes and summit and aircraft measurements.

Ryerson, Charles C.↗

NASA NTRS2005

Airborne Sunphotometer and Solar Spectral Flux Radiometer Measurements During INTEX/ITCT 2004

During the period 12 July - 8 August 2004, the NASA Ames 14-channel Airborne Tracking Sunphotometer (MTS-14) and Solar Spectral Flux Radiometer (SSFR) were operated aboard a Jetstream 31 (J31) aircraft and acquired measurements during nineteen science flights (approx. 53 flight hours) over the Gulf of Maine in support of the INTEX-NA (INtercontinental chemical Transport Experiment-North America) and ITCT (Intercontinental Transport and Chemical Transformation of anthropogenic pollution) field studies. In this paper, we will present results from analyses of those data sets. AATS-14 measures the direct solar beam transmission at fourteen discrete wavelengths (354-2138 nm), and provides instantaneous measurements of aerosol optical depth (AOD) spectra and water vapor column content, in addition to vertical profiles of aerosol extinction and water vapor density during suitable aircraft ascents and descents. SSFR consists of separate nadir and zenith viewing hemispheric FOV sensors that yield measurements of up- and downwelling solar irradiance at a spectral resolution of approx. 8-12 nm over the wavelength range 300-1700 nm. The objectives of the J31-based measurements during INTEX/ITCT were to provide AOD data for the evaluation of MODIS (MODerate-resolution Imaging Spectroradiometer) and MISR (Multi-angle Imaging Spectro-Radiometer) AOD retrievals, quantify sea surface spectral albedo (which can contribute the largest uncertainty to satellite aerosol retrievals for low aerosol loading), test closure (consistency) among suborbital results, test chemical-transport models using AOD profiles, and assess regional radiative forcing by combining satellite and suborbital results. Specific J31 flight patterns were designed to achieve these objectives, and they included a mixture of vertical profiles (spiral and ramped ascents and descents) and constant altitude horizontal transects at a variety of altitudes. Additional information is included in the original extended abstract.

Russell, P. B.↗

NASA NTRS2012

Lunar Prospecting Using Thermal Wadis and Compact Rovers: Infrastructure for Surviving the Lunar Night - Part A

Recent missions have confirmed the existence of water and other volatiles on the Moon, both in permanently-shadowed craters and elsewhere. Non-volatile lunar resources may represent significant additional value as infrastructure or manufacturing feedstock. Characterization of lunar resources in terms of abundance concentrations, distribution, and recoverability is limited to in-situ Apollo samples and the expanding remote-sensing database. This paper introduces an approach to lunar resource prospecting supported by a simple lunar surface infrastructure based on the Thermal Wadi concept of thermal energy storage and using compact rovers equipped with appropriate prospecting sensors and demonstration resource extraction capabilities. Thermal Wadis are engineered sources of heat and power based on the storage and retrieval of solar-thermal energy in modified lunar regolith. Because Thermal Wadis keep compact prospecting rovers warm during periods of lunar darkness, the rovers are able to survive months to years on the lunar surface rather than just weeks without being required to carry the burdensome capability to do so. The resulting lower-cost, long-lived rovers represent a potential paradigm breakthrough in extra-terrestrial prospecting productivity and will enable the production of detailed resource maps. Integrating resource processing and other technology demonstrations that are based on the content of the resource maps will inform engineering economic studies that can define the true resource potential of the Moon. Once this resource potential is understood quantitatively, humans might return to the Moon with an economically sound objective including where to go, what to do upon arrival, and what to bring along.

Sacksteder, Kurt R.↗

NASA NTRS1979

Spectropolarimetry of Venus and Jupiter clouds - Information content of equivalent widths

The theory of the curve-of-growth for absorption lines formed in an anisotropically scattering medium, particularly the clouds of Venus and Jupiter, is generalized to the case of polarization. When the photon path-length distributions associated with each of Stokes' parameters (Il, Ir, and Q) are evaluated using Pade's approximations, analytical expressions can be derived for the corresponding equivalent widths. It is found that spectra of Q, derivable from the rotational temperature of the Q-lines, are formed at a level closer to the cloud top than the photopolarimetric level, rendering a more accurate location of the cloud top than possible by photopolarization. It is also demonstrated that simultaneous measurements of the equivalent widths of strong I- and Q-lines can provide analytical relations for retrieving the scale-height ratios of ambient gas-to-cloud particles and minor constituent-to-ambient gas molecules without resorting to any other independent measurement.

Buriez, J. C.↗

NASA NTRS1993

LDEF materials data bases

The Long Duration Exposure Facility (LDEF) and the accompanying experiments were composed of and contained a wide variety of materials representing the largest collection of materials flown in low Earth orbit (LEO) and retrieved for ground based analysis to date. The results and implications of the mechanical, thermal, optical, and electrical data from these materials are the foundation on which future LEO space missions will be built. The LDEF Materials Special Investigation Group (MSIG) has been charged with establishing and developing data bases to document these materials and their performance to assure not only that the data are archived for future generations but also that the data are available to the spacecraft user community in an easily accessed, user-friendly form. This paper discusses the format and content of the three data bases developed or being developed to accomplish this task. The hardware and software requirements for each of these three data bases are discussed along with current availability of the data bases. This paper also serves as a user's guide to the MAPTIS LDEF Materials Data Base.

Funk, Joan G.↗

NASA NTRS2000

Remote Sensing of In-Flight Icing Conditions: Operational, Meteorological, and Technological Considerations

Remote-sensing systems that map aircraft icing conditions in the flight path from airports or aircraft would allow icing to be avoided and exited. Icing remote-sensing system development requires consideration of the operational environment, the meteorological environment, and the technology available. Operationally, pilots need unambiguous cockpit icing displays for risk management decision-making. Human factors, aircraft integration, integration of remotely sensed icing information into the weather system infrastructures, and avoid-and-exit issues need resolution. Cost, maintenance, power, weight, and space concern manufacturers, operators, and regulators. An icing remote-sensing system detects cloud and precipitation liquid water, drop size, and temperature. An algorithm is needed to convert these conditions into icing potential estimates for cockpit display. Specification development requires that magnitudes of cloud microphysical conditions and their spatial and temporal variability be understood at multiple scales. The core of an icing remote-sensing system is the technology that senses icing microphysical conditions. Radar and microwave radiometers penetrate clouds and can estimate liquid water and drop size. Retrieval development is needed; differential attenuation and neural network assessment of multiple-band radar returns are most promising to date. Airport-based radar or radiometers are the most viable near-term technologies. A radiometer that profiles cloud liquid water, and experimental techniques to use radiometers horizontally, are promising. The most critical operational research needs are to assess cockpit and aircraft system integration, develop avoid-and-exit protocols, assess human factors, and integrate remote-sensing information into weather and air traffic control infrastructures. Improved spatial characterization of cloud and precipitation liquid-water content, drop-size spectra, and temperature are needed, as well as an algorithm to convert sensed conditions into a measure of icing potential. Technology development also requires refinement of inversion techniques. These goals can be accomplished with collaboration among federal agencies including NASA, the FAA, the National Center for Atmospheric Research, NOAA, and the Department of Defense. This report reviews operational, meteorological, and technological considerations in developing the capability to remotely map in-flight icing conditions from the ground and from the air.

Ryerson, Charles C.↗

NASA NTRS2023

Retrieval of Normalized Gamma Size Distribution Parameters Using Precipitation Imaging Package (Pip) Snowfall Observations During Ice-Pop 2018

Parameters of the normalized gamma particle size distribution (PSD) have been retrieved from the Precipitation Image Package (PIP) snowfall observations collected during the International Collaborative Experiment - PyeongChang Olympics and Paralympic (ICE-POP 2018). Two of the gamma PSD parameters, the mass weighted particle diameter (Dmass) and the normalized intercept parameter NW, have median values of 1.15-1.31 mm and 2.84-3.04 log(mm-1 m-3), respectively. This range arises from the choice of the relationship between the maximum versus equivalent diameter, Dmx-Deq, and the relationship between the Reynolds and Best numbers, Re-X. Normalization of snow water equivalent rate (SWER) and ice water content (W) by NW reduces the range in NW resulting in well fitted power law relationship, between SWER/NW and Dmass and between W/NW and Dmass. The bulk descriptors of snowfall are calculated from PIP observations and from the gamma PSD with values of the shape parameter (μ) ranging from -2 to 10. NASA’s Global Precipitation Measurement (GPM) mission, which adopted the normalized gamma PSD, assumes μ = 2 and μ = 3 in its two separate algorithms. The mean fractional bias (MFB) of the snowfall parameters changes with μ, where the functional dependence on μ depends on the specific snowfall parameter of interest. The MFB of the total concentration was underestimated by 0.23-0.34 when μ = 2 and by 0.29-0.40 when μ = 3, while the MFB of SWER had a much narrower range (-0.03 to 0.04) for the same μ values.

Snowfall↗

NASA NTRS2013

Fuzzy Reasoning to More Accurately Determine Void Areas on Optical Micrographs of Composite Structures

Accomplishing the best-performing composite matrix (resin) requires that not only the processing method but also the cure cycle generate low-void-content structures. If voids are present, the performance of the composite matrix will be significantly reduced. This is usually noticed by significant reductions in matrix-dominated properties, such as compression and shear strength. Voids in composite materials are areas that are absent of the composite components: matrix and fibers. The characteristics of the voids and their accurate estimation are critical to determine for high performance composite structures. One widely used method of performing void analysis on a composite structure sample is acquiring optical micrographs or Scanning Electron Microscope (SEM) images of lateral sides of the sample and retrieving the void areas within the micrographs/images using an image analysis technique. Segmentation for the retrieval and subsequent computation of void areas within the micrographs/images is challenging as the gray-scaled values of the void areas are close to the gray-scaled values of the matrix leading to the need of manually performing the segmentation based on the histogram of the micrographs/images to retrieve the void areas. The use of an algorithm developed by NASA and based on Fuzzy Reasoning (FR) proved to overcome the difficulty of suitably differentiate void and matrix image areas with similar gray-scaled values leading not only to a more accurate estimation of void areas on composite matrix micrographs but also to a faster void analysis process as the algorithm is fully autonomous.

Dominquez, Jesus A.↗

NASA NTRSDate not supplied

Using the Diurnal Variability in GeoNEX TOA Reflectances for Earth Monitoring

Observations from the third-generation geostationary satellite instruments (GOES 16/17 ABI, Himawari 8/9 AHI, and etc.) have spatial resolution and spectral band configurations comparable to flagship LEO sensors (e.g., MODIS/VIIRS). More importantly, these data are acquired at very high temporal resolution, faithfully recording the variations of the full disk of Earth at every 5-10 minutes. They thus provide unique information about Earth’s atmosphere and surface. In order to explore the unique information content of geostationary data, this study systematically analyzes the diurnal variability in the GeoNEX L1G TOA reflectance products and compares them to simulated results by state-of-the-art radiative transfer codes. Our results show that • The smoothness of the TOA reflectance diurnal cycle provides a convenient and reliable way to identify stable atmospheric conditions and filter out passing clouds/shadows. • The diurnal variability of the blue band (0.47µm) reflectance is regulated mainly by atmospheric optical conditions over a majority of land cover types. As such, the diurnal variability of the blue band data allows us to retrieve AOD without invoking the use of spectral band ratios (SRC) as in previous algorithms. • In comparison, the diurnal variability of the short-wave infrared band (2.2µm) BRFs is mainly regulated by surface reflectance and the sun-target-satellite geometry. This information allows us to test and, if suitable, retrieve surface BRDF parameters. • Spectral band ratios, especially those between the 2.2µm and 0.47µm bands, are not constant but vary by locations and sun-target-satellite geometries. Our analysis clearly demonstrates that the information provided in high-frequent geostationary observations is unique and complementary to LEO sensors. Therefore, a synergy of GEO and LEO (and other) sensors has the great potential to improve existing remote sensing models and algorithms for better Earth monitoring.

Diurnal Variability↗

NASA NTRSDate not supplied

Explore Information Content Efficiently from Current and Future Hyperspectral Satellite Missions using a Spectral Fingerprinting Method

Hyperspectral remote sensors from current and future missions provide measurements of the Top of Atmosphere (TOA) radiance or reflectance spectra with high information content. For example, the Atmospheric Infrared Sounder (AIRS), together with the Cross-track Infrared Sounder (CrIS), and the Infrared Atmospheric Sounding Interferometer (IASI) have provided more than 20 years radiance measurements with thousands of spectral channels. These measurements will be continued for the next two decades with the same or more advanced hyperspectral sensors. The upcoming missions such as NASA’s CLARREO Pathfinder (CPF) and ESA’s TRUTHS will provide unprecedented accurate TOA hyperspectral radiance measurements in solar spectral region. Traditional ways to derive Climate Data Records (CDRs) from these measurements are performing spatial and temporal averages of the retrieved Level-2 products. However, it is a time-consuming process to generate decades of Level-2 data from Level-1 data. Furthermore, the differences in Level-2 algorithms used for different satellite sensors will introduce errors in derived CDRs. In this presentation, we will describe a spectral fingerprinting method to generate high-quality CDRs directly from spatiotemporally averaged Level-1 data. By using consistent radiative kernels which contain the spectral information of various atmospheric and surface CDRs, we can reduce the errors due to algorithm inconsistency. Additionally, the spectral fingerprinting method reduces the time needed to generate CDRs by more than three orders of magnitude. This makes it easy to reprocess CDRs once the Level-1 data from different satellites have been improved via either re-calibrations or inter-satellite calibrations. We will present results of applying spectral fingerprinting method to 20-years of AIRS and CrIS data. The resulting CDRs include: 1) vertical profiles of atmospheric temperature and water vapor, 2) cloud properties such as optical depth, effective size, and height, 3) vertical profiles or column amounts for atmospheric trace gases such as O3 and CO, and 4) surface emissivity spectra and skin temperatures. These CDRs will be publicly available at NASA GES DISC in late 2024. The same fingerprinting method is planned to be applied to future CPF and TRUTHS data for solar spectral region.

hyperspectral remote sensing↗

NASA NTRS2006

Proteomic Retrieval from Nucleic Acid Depleted Space-Flown Human Cells

Compared to experiments utilizing humans in microgravity, cell-based approaches to questions about subsystems of the human system afford multiple advantages, such as crew safety and the ability to achieve statistical significance. To maximize the science return from flight samples, an optimized method was developed to recover protein from samples depleted of nucleic acid. This technique allows multiple analyses on a single cellular sample and when applied to future cellular investigations could accelerate solutions to significant biomedical barriers to human space exploration. Cell cultures grown in American Fluoroseal bags were treated with an RNA stabilizing agent (RNAlater - Ambion), which enabled both RNA and immunoreactive protein analyses. RNA was purified using an RNAqueous(registered TradeMark) kit (Ambion) and the remaining RNA free supernatant was precipitated with 5% trichloroacetic acid. The precipitate was dissolved in SDS running buffer and tested for protein content using a bicinchoninic acid assay (1) (Sigma). Equal loads of protein were placed on SDS-PAGE gels and either stained with CyproOrange (Amersham) or transferred using Western Blotting techniques (2,3,4). Protein recovered from RNAlater-treated cells and stained with protein stain, was measured using Imagequant volume measurements for rectangles of equal size. BSA treated in this way gave quantitative data over the protein range used (Fig 1). Human renal cortical epithelial (HRCE) cells (5,6,7) grown onboard the International Space Station (ISS) during Increment 3 and in ground control cultures exhibited similar immunoreactivity profiles for antibodies to the Vitamin D receptor (VDR) (Fig 2), the beta isoform of protein kinase C (PKC ) (Fig 3), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (Fig 4). Parallel immunohistochemical studies on formalin-fixed flight and ground control cultures also showed positive immunostaining for VDR and other biomarkers (Fig 5). These results are consistent with data from additional antigenic recovery experiments performed on human Mullerian tumor cells cultured in microgravity (8).

Hammond, D. K.↗

NASA NTRS1999

Wind Speed Measurement from Bistatically Scattered GPS Signals

Instrumentation and retrieval algorithms are described which use the forward, or bistatically scattered range-coded signals from the Global Positioning System (GPS) radio navigation system for the measurement of sea surface roughness. This roughness is known to be related directly to the surface wind speed. Experiments were conducted from aircraft along the TOPEX ground track, and over experimental surface truth buoys. These flights used a receiver capable of recording the cross correlation power in the reflected signal. The shape of this power distribution was then compared against analytical models derived from geometric optics. Two techniques for matching these functions were studied. The first recognized the most significant information content in the reflected signal is contained in the trailing edge slope of the waveform. The second attempted to match the complete shape of the waveform by approximating it as a series expansion and obtaining the nonlinear least squares estimate. Discussion is also presented on anomalies in the receiver operation and their identification and correction.

Garrison, James L.↗

NASA NTRSDate not supplied

Evaluating Combined Lidar and Polarimeter Measurements of Cloud Top Parameters (Extinction, Scattering Cross Sections, and Droplet Number Density, Liquid Water Content)

We present a new method to derive profiles of extinction from a lidar which is then combined with polarimeter measurements to derive cloud droplet number density (CDNC) in the tops of warm clouds. The method employs polarization-sensitive elastic backscatter lidar measurements to estimate attenuation of the lidar signal within the cloud and polarimeter estimates of cloud droplet size distributions. The measurements used for this demonstration are from NASA Langley Research Center’s High Spectral Resolution Lidar – Generation 2 (HSRL-2) and NASA GISS’s Research Scanning Polarimeter (RSP). The measurements were acquired on NASA’s ACTIVATE mission, during which the instruments were deployed in a down-looking mode from a high-altitude aircraft, which flew in coordination with a low-flying aircraft acquiring coincident in situ measurements of cloud droplet size and number. The high vertical (1.25 m) and horizontal (~50 m) sampling resolution of the HSRL-2 data enabled retrievals of single-scattering extinction profiles to within ~2.5 optical depths of cloud top. Another key feature of the method was the well-calibrated measurement of backscatter at cloud top due to using the HSRL technique. The RSP retrievals of cloud droplet effective radius and variance were accomplished using the “cloud-bow” technique. Overall, the technique provides extinction profile estimates for the top 2.5 optical depths of water clouds that can be used to estimate the cloud droplet number density in various types of warm clouds. The mean extinction values at cloud top (0-1 optical depth) are compared against cloud drop size and number concentration acquired from wing-mounted probes (e.g., DMT Cloud Droplet Probe - CDP, SPEC Fast Cloud Droplet Probe FCDP, and SPEC 2D Stereo Probe - 2DS) that were deployed on the low-flying aircraft. Comparisons between the effective radius and variance from the polarimeter, lidar ratio (extinction to backscatter) from the lidar and polarimeter, and LWC are also presented. All measurements were acquired over the Western North Atlantic over 3 years from 2020 to 2022.

lidar↗

NASA NTRS2010

Comparison of GOES-Retrieved and In Situ Measurements of Deep Convective Anvil Cloud Microphysical Properties During the Tropical Composition, Cloud and Climate Coupling Experiment (TC(sup 4))

One of the main goals of the Tropical Composition, Cloud and Climate Coupling Experiment (TC(sup 4)) during July and August 2007 was to gain a better understanding of the formation and life cycle of cirrus clouds in the upper troposphere and lower stratosphere and how their presence affects the exchange of water vapor between these layers. Additionally, it is important to compare in situ measurements taken by aircraft instruments with products derived from satellite observations and find a meaningful way to interpret the results. In this study, cloud properties derived using radiance measurements from the Geostationary Operational Environmental Satellite (GOES) imagers are compared to similar quantities from aircraft in situ observations and are examined for meaningful relationships. A new method using dual \angle satellite measurements is used to derive the ice water content (IWC) for the top portion of deep convective clouds and anvils. The results show the in situ and remotely sensed mean microphysical properties agree to within approx.10 microns in the top few kilometers of thick anvils despite the vastly different temporal and spatial resolutions of the aircraft and satellite instruments. Mean particle size and IWC are shown to increase with decreasing altitude in the top few kilometers of the cloud. Given these relationships, it may be possible to derive parameterizations for effective particle size and IWC as a function of altitude from satellite observations

Yost, Christoher R.↗

NASA NTRS2008

Air Quality Study Using Satellites - Current Capability and Future Plans

Satellite instruments have had great success in monitoring the stratospheric ozone and in understanding the processes that control its daily to decadal scale variations. This field is now reaching its zenith with a number of satellite instruments from the US, Europe and Canada capping several decades of active research in this field. The primary public policy imperative of this research was to make reliable prediction of increases in biologically active surface UV radiation due to human activity. By contrast retrieval from satellite data of atmospheric constituents and photo-chemically active radiation that affect air quality is a new and growing field that is presenting us with unique challenges in measurement and data interpretation. A key distinction compared to stratospheric sensors is the greatly enhanced role of clouds, aerosols, and surfaces (CAS) in determining the quality and quantity of useful data that is available for air quality research. In our presentation we will use data from several sensors that are currently flying on the A-train satellite constellation, including OMI, MODIS, CLOUDSAT, and CALIPSO, to highlight that CAS can have both positive and negative effects on the information content of satellite measurements. This is in sharp contrast to other fields of remote sensing where CAS are usually considered an interference except in those cases when they are the primary subject of study. Our analysis has revealed that in the reflected wavelengths one often sees much further down into the atmosphere, through most cirrus, than one does in the emitted wavelengths. The lower level clouds provide a nice background against which one can track long-range transport of trace gases and aerosols. In addition, differences in trace gas columns estimated over cloudy and adjacent clear pixels can be used to measure boundary layer trace gases. However, in order to take full advantage of these features it will be necessary to greatly advance our understanding of how CAS affect the radiation at wavelengths that are used to derive the atmospheric constituents that affect air quality as well as the radiation that controls the photolysis of chemically active trace gases. We will discuss how we are using these new insights to design future satellite missions to study air quality.

Bhartia, Pawan K.↗

NASA NTRS2014

Ontology Engineering in Provenance Enablement for the National Climate Assessment

The National Climate Assessment of the U.S. Global Change Research Program (USGCRP) analyzes and presents the impacts of climate change on the United States. The provenance information in the assessment is important because the assessment findings are of great public and academic concern and are used in policy and decision-making. By applying a use case-driven iterative methodology, we developed information models and ontology to represent the content structure of the recent National Climate Assessment draft report and its associated provenance information. We tested the ontology by using it in pilot systems serving information about instances of chapters, scientific findings, figures, tables, images, datasets, references, people, and organizations, etc. in the draft report, as well as interrelationships among those instances. The results successfully help users trace provenance in the draft report, such as finding all the journal articles from which a figure in the report was derived. The provenance information in our work was maintained in the context of the "Web of Data". In addition to the pilot systems we developed, other tools and services are also able to retrieve and utilize the provenance information. Our work is part of a Global Change Information System coordinated by the USGCRP that will eventually cover provenance information for the entire scope of global change research. Such a system will greatly increase understanding, credibility and trust in the global change research and foster reproducibility of scientific results and conclusions.

Ontology engineering↗