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At least 577 records · Page 32

Inference of the aerosol Angstrom coefficient from SAGE short-wavelength data

SAGE four-channel transmission profiles are inverted to retrieve the extinction profiles from which the aerosol Angstrom coefficient alpha is obtained. The procedure allows one to check the influence of the NO2 absorption profile, which is small below 25 km. The results compare well with those obtained by a completely different procedure at NASA Langley Research Center, and the main features of the alpha profiles seem to be significant, even considering the rather large error bars. The relation between the retrieved Angstrom coefficient, the particle effective radius and the asymmetry factor is considered.

Lenoble, J.↗

Inference of surface power spectra from inversion of multifrequency polarimetric radar data

During the summer of 1988 an intensive field experiment was conducted in the vicinity of Pisgah lava field in the Mojave Desert. As part of the experiment, physical properties such as microtopography, composition, soil moisture, and dielectric constant at five different sites representing surfaces with rms heights varying from less than one centimeter to tens of centimeters were measured. In addition, polarimetric radar images at P-band, L-band and C-band were acquired at three different incidence angles with the NASA/JPL airborne imaging radar polarimeter. Using trihedral corner reflectors deployed in the area prior to imaging, the radar images were calibrated to provide values for each resolution element in each scene. This paper reports on the derivation of the power spectrum of surface microtopography by solution of the small perturbation model for multiple incidence angle and multiple frequency radar data. Power-law fits to the power spectra have exponents that are nearly the same for all surfaces. These values are close to those from measured microtopography profiles.

Van Zyl, Jacob J.↗

Development of methods for inferring cloud thickness and cloud-base height from satellite radiance data

Cloud-top height is a major factor determining the outgoing longwave flux at the top of the atmosphere. The downwelling radiation from the cloud strongly affects the cooling rate within the atmosphere and the longwave radiation incident at the surface. Thus, determination of cloud-base temperature is important for proper calculation of fluxes below the cloud. Cloud-base altitude is also an important factor in aircraft operations. Cloud-top height or temperature can be derived in a straightforward manner using satellite-based infrared data. Cloud-base temperature, however, is not observable from the satellite, but is related to the height, phase, and optical depth of the cloud in addition to other variables. This study uses surface and satellite data taken during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (13 Nov. - 7 Dec. 1991, to improve techniques for deriving cloud-base height from conventional satellite data.

Smith, William L., Jr.↗

Compactly‐Supported Nonstationary Kernels for Computing Exact Gaussian Processes on Big Data

The Gaussian process (GP) is a widely used method for analyzing large-scale data sets, including spatio-temporal measurements of nonlinear processes that are now commonplace in the environmental sciences. Traditional implementations of GPs involve stationary kernels (also termed covariance functions) that limit their flexibility, and exact methods for inference that prevent application to data sets with more than about 10,000 points. Modern approaches to address stationarity assumptions generally fail to accommodate large data sets, while all attempts to address scalability focus on approximating the Gaussian likelihood, which can involve subjectivity and lead to inaccuracies. In this work, we explicitly derive an alternative kernel that can discover and encode both sparsity and nonstationarity. We embed the kernel within a fully Bayesian GP model and leverage high-performance computing resources to enable the analysis of massive data sets. We demonstrate the favorable performance of our novel kernel relative to existing exact and approximate GP methods across a variety of synthetic data examples. Furthermore, we conduct space–time prediction based on more than 1 million measurements of daily maximum temperature and verify that our results outperform state-of-the-art methods in the Earth sciences. More broadly, having access to exact GPs that use ultra-scalable, sparsity-discovering, nonstationary kernels allows GP methods to truly compete with a wide variety of machine learning methods.

Gaussian processes↗

Applying Machine Learning and Bayesian Inference to Identify and Locate Moving Anthropogenic Sources Using Distributed Acoustic Sensing Data

Distributed acoustic sensing (DAS) systems, which use existing telecommunication fibers, offer high‐resolution capabilities ideal for recording anthropogenic sources. However, the complexity of urban environments and the large amount of data recorded by DAS require automated methods to efficiently detect and categorize anthropogenic sources. Here, we evaluate how well three machine learning models (k‐nearest neighbor [k‐NN], convolutional neural networks, and recurrent‐convolutional neural networks) can identify various anthropogenic sources recorded by DAS. Our findings reveal that both k‐NN and neural network methods perform well in high signal‐to‐noise ratio (SNR) settings. However, their accuracy decreases at SNRs <4. We also use Kalman filtering, a form of Bayesian inference, on backprojected locations of these sources to recover locations that generally fall within standard smartphone Global Positioning System errors. By combining machine learning and Kalman filter results, we calculate a multidimensional model of moving anthropogenic sources. These results demonstrate the potential of DAS data in urban seismology for accurately identifying and locating such sources. Depending on the research objectives, these sources can be further studied or filtered out to improve the quality of seismic data for earthquake studies. Such methods provide a valuable tool for urban seismology and seismic hazard analysis.

Luckie, Thomas William [Sandia National Laboratori↗

Reconstruction of the 1997/1998 El Nino from TOPEX/POSEIDON and TOGA/TAO Data Using a Massively Parallel Pacific-Ocean Model and Ensemble Kalman Filter

Two massively parallel data assimilation systems in which the model forecast-error covariances are estimated from the distribution of an ensemble of model integrations are applied to the assimilation of 97-98 TOPEX/POSEIDON altimetry and TOGA/TAO temperature data into a Pacific basin version the NASA Seasonal to Interannual Prediction Project (NSIPP)ls quasi-isopycnal ocean general circulation model. in the first system, ensemble of model runs forced by an ensemble of atmospheric model simulations is used to calculate asymptotic error statistics. The data assimilation then occurs in the reduced phase space spanned by the corresponding leading empirical orthogonal functions. The second system is an ensemble Kalman filter in which new error statistics are computed during each assimilation cycle from the time-dependent ensemble distribution. The data assimilation experiments are conducted on NSIPP's 512-processor CRAY T3E. The two data assimilation systems are validated by withholding part of the data and quantifying the extent to which the withheld information can be inferred from the assimilation of the remaining data. The pros and cons of each system are discussed.

Keppenne, C. L.↗

Constraining Hydrological and Cryospheric Mass Flux in Southeastern Alaska using Space-Based Gravity Measurements

Watersheds draining into the Gulf of Alaska (GoA) experience large seasonal and inter-annual variations of water in the form of rain, snow, and ice, but accurate constraints on these variations have been difficult to obtain. Over larger geographic regions, water variations can be inferred directly from the Gravity Recovery and Climate Experiment (GRACE) data. However, because GoA variations occur over such a small region, the inferred average value of water flux increases as the applied smoothing of the GRACE data decreases. We use this observed scaling together with scaling results obtained from forward models to infer a seasonal amplitude of 115 plus or minus 20 cubic kilometers of water and an average contribution to sea level rise over the two years of data of 0.31 plus or minus 0.09 millimeters per year. These results suggest that accelerated melting that began in the late 1990s, as inferred from altimetry, continues unabated.

Tamisiea, M. E.↗

The Martian surface as imaged, sampled, and analyzed by the Viking landers

Data collected by two Viking landers are analyzed. Attention is given to the characteristics of the surface inferred from Lander imaging and meteorology data, physical and magnetic properties experiments, and both inorganic and organic analyses of Martian samples. Viking Lander 1 touched down on Chryse Planitia on July 20, 1976 and continued to operate for 2252 sols, until November 20, 1982. Lander 2 touched down about 6500 km away from Lander 1, on Utopia Planitia on September 3, 1976. The chemical compositions of sediments at the two landing sites are similar, suggesting an aeolian origin. The compositions suggest an iron-rich rock an are matched by various clays and salts.

Arvidson, Raymond E.↗

Polarization and the envelopes of B(e) supergiants in the Magellanic Clouds

We report optical linear polarization observations of nine B(e) supergiants in the Magellanic Clouds. Several of them have large intrinsic polarizations. The data are consistent with nonspherically symmetric envelopes, around the B(e) stars, that possess a range of intrinsic polarizations. Comparison of the polarimetric data with the viewing aspect, inferred from the spectroscopy of the individual objects, agrees with this interpretation. The polarization correlates best with the infrared excess due to dust, suggesting the latter as the cause of most of the polarization. We cannot find, using the available data, a statistically significant difference between the polarization distributions of Galactic and Magellanic B(e) stars. Comparison of our data with previous polarimetric data, recovered from the literature for four stars, seems to indicate that the envelopes are stable.

Magalhaes, A. M.↗

Block-Structured Operator Inference for Coupled Multiphysics Model Reduction

This work presents a block-structured formulation of Operator Inference as a way to learn structured reduced-order models for multiphysics systems. The approach specifies the governing equation structure for each physics component and the structure of the coupling terms. Once the multiphysics structure is specified, the reduced-order model is learned from snapshot data following the nonintrusive Operator Inference methodology. In addition to preserving physical system structure, which in turn permits preservation of system properties such as stability and second-order structure, the block-structured approach has the advantages of reducing the overall dimensionality of the learning problem and admitting tailored regularization for each physics component. The numerical advantages of the block-structured formulation over a monolithic Operator Inference formulation are demonstrated for aeroelastic analysis, which couples aerodynamic and structural models. For the benchmark test case of the AGARD 445.6 wing, block-structured Operator Inference provides an average 20% online prediction speedup over monolithic Operator Inference across subsonic and supersonic flow conditions in both the stable and fluttering parameter regimes while preserving the accuracy achieved with monolithic Operator Inference.

42 ENGINEERING↗

Geodynamics of crustal deformation and seismotectonic block movements in central Europe

Geological observations reveal the style of neotectonic near-surface stresses and deformations in central Europe. Seismic activity, focal depths and fault plane solutions of earthquakes indicate kinematic reactions within the crust. A crustal deformation model which may account for the Rhine graben systems and the associated seismotectonic block movements in Europe is presented. A computer aided tomography to gravity anomalies is used in determining the crustal stresses in central Europe. Tomographical interpretations of gravity data with respect to seismic stresses are discussed. Kinematics and dynamics are integrated to show that the measured regional stresses in central Europe are derivable from the convection generated traction on the boundary of the elastic spherical shell of the crust as inferred from satellite derived gravity data.

Liu, H. S.↗

An expert system shell for inferring vegetation characteristics

The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. The report describes the extensions that have been made to the first generation version of VEG. An interface to a file of unkown cover type data has been constructed. An interface that allows the results of VEG to be written to a file has been implemented. A learning system that learns class descriptions from a data base of historical cover type data and then uses the learned class descriptions to classify an unknown sample has been built. This system has an interface that integrates it into the rest of VEG. The VEG subgoal PROPORTION.GROUND.COVER has been completed and a number of additional techniques that infer the proportion ground cover of a sample have been implemented.

Harrison, P. Ann↗

Validity of the Temperature Reconstruction from Water Isotopes in Ice Cores

Well-documented present-day distributions of stable water isotopes (HDO and others) show the existence, in middle and high latitudes, of a linear relationship between the mean annual isotope content of precipitation (SD and 51"0) and the mean annual temperature at the precipitation site. Paleoclimatologists have used this relationship, which is particularly well obeyed over Greenland and Antarctica, to infer paleotemperatures from ice core data. There is, however, growing evidence that spatial and temporal isotope/ surface temperature slopes differ, thus complicating the use of stable water isotopes as paleothermometers. In this paper we review empirical estimates of temporal slopes in polar regions and relevant information that can be inferred from isotope models: simple, Rayleigh-type distillation models and (particularly over Greenland) general circulation models (GCMS) fitted with isotope tracer diagnostics. Empirical estimates of temporal slopes appear consistently lower than present-day spatial slopes and are dependent on the timescale considered. This difference is most probably due to changes in the evaporative origins of moisture, changes in the seasonality of the precipitation, changes in the strength of the inversion layer, or some combination of these changes. Isotope models have not yet been used to evaluate the relative influences of these different factors. The apparent disagreement in the temporal and spatial slopes clearly makes calibrating the isotope paleothermometer difficult. Nevertheless, the use of a (calibrated) isotope paleothermometer appears justified; empirical estimates and most (though not all) GCM results support the practice of interpreting ice core isotope records in terms of local temperature changes.

Jouzel, J.↗

Far-Infrared Spectroscopy of Planetary Nebulae with the KAO

We present new far-infrared line observations of the planetary nebulae (PNs) NGC 7027, NGC 7009, and NGC 6210 obtained with the Kuiper Airborne Observatory (KAO). The bulk of our data are for NGC 7027 and NGC 7009, including [Ne(V)] 24 micrometers, [O(IV)] 26 micrometers, [O(III)] (52, 88) micrometers, and [N(III)] 57 micrometers. Our data for [O(III)] (52, 88) and [N(III)] 57 in NGC 7027 represent the first measurements of these lines in this source. The large [O(III)] 52/88-micrometer flux ratio implies an electron density (cubic cm) of log N(sub e)[O(III)] = 4.19, the largest Ne ever inferred from these lines. We derive N(++)/O(++) = 0.394 +/- 0.062 for NGC 7027 and 0.179 +/- 0.043 for NGC 6210. We are able to infer the O(+3)/O(++) ionic ratio from our data. As gauged by this ionic ratio, NGC 7027 is substantially higher ionization than is NGC 7009 - consistent with our observation that the former produces copious [Ne(V)] emission while the latter does not. These data help characterize the stellar ionizing radiation field. From our [O(IV)] and [O(III)] fluxes, we are able to show that O(++) is by far the dominant oxygen ion in NGC 7009. As a result, the O/H abundance inferred using these data tends to corroborate the value found from UV/optical, collisionally excited lines. We determined accurate rest wavelengths for the [Ne(V)] 2s(2)2p(2)P(sub 1) to 2s(2)2p(2)3P(sub 0) (lambda(sub rest) = 24.316 +/- 0.008 micrometers) and [O(IV)] 2s(2)2p(2)P(sup 0, sub 3/2) to 2s(2)2p(2)P(sup 0, sub 1/2) (lambda(sub rest) = 25.887 +/- 0.007 micrometers) transitions from observations of one or both of the bright PNs NGC 7027 and NGC 7009. Our [O(IV)] value, to the best of our knowledge, is the most accurate direct determination of this lambda(sub rest). These new KAO data will be beneficial for comparison with ISO observations of these PNs.

Rubin, Robert H.↗

Microwave remote sensing of sea ice

The long term objectives are: (1) to understand the physics of the multispectral microwave radiative characteristics of sea ice as it goes through different phases; (2) to improve characterization of sea ice cover using satellite microwave sensors; and (3) to study ice/ocean physical and biological processes associated with polynya formations and variability of the marginal sea ice region. Two field experiments were conducted to pursue these objectives. One involved measurements of radiative and physical characteristics of sea ice from a ship during a 3-month long cruise through the Weddell Sea ice pack during the Austral winter of 1986. The other involved similar measurements from two aircrafts and a submarine over the Central Arctic and Greenland Sea region. Preliminary results have already led to an enhanced understanding of the microwave signatures of pancake ice, nilas, first year ice, multiyear ice and effects of snow cover. Coastal and deep ocean polynyas and their role in bottom water formation and ocean circulation were studied using a time series of ice images from SMMR. An unsupervised cluster analysis of Arctic sea ice using SMMR and THIR emissivity and brightness temperature data was implemented. The analysis indicates the existence of several unique and persistent clusters in the Central Arctic region during winter and that the sum of the area of these clusters excluding those of first year ice is about 20 percent less than minimum ice cover area inferred from a previous summer data. This result is consistent with saline surface for some multiyear ice floes as observed during MIZEZ and suggests that a significant fraction of multiyear ice floes in the Arctic have first year ice signatures.

Comiso, J. C.↗