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NASA NTRS2008

Kinetic Temperature and Carbon Dioxide from Broadband Infrared Limb Emission Measurements Taken from the TIMED/SABER Instrument

The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) experiment is one of four instruments on NASA's Thermosphere-Ionosphere-Energetics and Dynamics (TIMED) satellite. SABER measures broadband infrared limb emission and derives vertical profiles of kinetic temperature (Tk) from the lower stratosphere to approximately 120 km, and vertical profiles of carbon dioxide (CO2) volume mixing ratio (vmr) from approximately 70 km to 120 km. In this paper we report on SABER Tk/CO2 data in the mesosphere and lower thermosphere (MLT) region from the version 1.06 dataset. The continuous SABER measurements provide an excellent dataset to understand the evolution and mechanisms responsible for the global two-level structure of the mesopause altitude. SABER MLT Tk comparisons with ground-based sodium lidar and rocket falling sphere Tk measurements are generally in good agreement. However, SABER CO2 data differs significantly from TIME-GCM model simulations. Indirect CO2 validation through SABER-lidar MLT Tk comparisons and SABER-radiation transfer comparisons of nighttime 4.3 micron limb emission suggest the SABER-derived CO2 data is a better representation of the true atmospheric MLT CO2 abundance compared to model simulations of CO2 vmr.

Mertens, Christopher J.↗
NASA NTRS2008

Statistical Evaluation of Combined Daily Gauge Observations and Rainfall Satellite Estimations over Continental South America

This paper describes a comprehensive assessment of a new high-resolution, high-quality gauge-satellite based analysis of daily precipitation over continental South America during 2004. This methodology is based on a combination of additive and multiplicative bias correction schemes in order to get the lowest bias when compared with the observed values. Inter-comparisons and cross-validations tests have been carried out for the control algorithm (TMPA real-time algorithm) and different merging schemes: additive bias correction (ADD), ratio bias correction (RAT) and TMPA research version, for different months belonging to different seasons and for different network densities. All compared merging schemes produce better results than the control algorithm, but when finer temporal (daily) and spatial scale (regional networks) gauge datasets is included in the analysis, the improvement is remarkable. The Combined Scheme (CoSch) presents consistently the best performance among the five techniques. This is also true when a degraded daily gauge network is used instead of full dataset. This technique appears a suitable tool to produce real-time, high-resolution, high-quality gauge-satellite based analyses of daily precipitation over land in regional domains.

Vila, Daniel↗
NASA NTRS2009

New Nd-142 Evidence for a Non-Chondritic Composition of the Moon

The coupled Sm-147,146-Nd-143,142 systematics of lunar samples has been extensively studied for estimating the timescale of lunar differentiation. The published datasets yield consistent ages for Nd isotopic closure within the lunar mantle of approx.200 Myr after CAI formation. Although this time constraint is consistent with estimates derived from Hf-W chronometry of the Moon (>60 Myr after CAI formation), there is debate as to whether this age has chronological significance. Furthermore, there are discrepancies regarding the Nd isotope composition of the bulk Moon. Rankenburg et al. obtained a epsilon Nd-142 vs. Sm-147/Nd-144 correlation for lunar samples passing though the chondritic reference value (Sm-147/Nd-144 = 0.1967, epsilon Nd-142 = -0.21), suggesting that the Moon has a chondritic bulk composition. In contrast, the other datasets define a correlation line that passes approx.10-20 ppm above, suggesting that the Moon has a superchondritic Sm-147/Nd-144 (approx.0.206), close to that of the early depleted Earth (EDM). We present new Sm-Nd data for a high-Ti mare basalt (70135), two low-Ti mare basalt (LAP 02205 and MIL 05035) and a KREEPy low-Ti mare basalt (NWA 2977). These data are used to evaluate the significance of the Sm-Nd systematics for constraining the timescale of lunar differentiation and the bulk Nd isotope composition of the Moon.

Nyquist, L.↗
NASA NTRS2009

Climate and Lightning: An updated TRMM-LIS Analysis

The TRMM Lightning Imaging Sensor (LIS) has sampled global tropical and sub-tropical lightning flash densities for approximately 11 years. These data were originally processed and results presented by the authors in the 3rd AMS MALD Conference held in 2007 using both pre and post TRMM-boost lightning data. These data were normalized for the orbit boost by scaling the pre-boost data by a fixed constant based on the different swath areas for the pre and post-boost years (post-boost after 2001). Inevitably, one must question this simple approach to accounting for the orbit boost when sampling such a noisy quantity. Hence we are in the process of reprocessing the entire 11-year TRMM LIS dataset to reduce the orbit swath of the post-boost era to that of the pre-boost in order to eliminate sampling bias in the dataset. Study of the diurnal/seasonal/annual sampling suggests that those biases are already minimal and should not contribute to error in examination of annual trends. We will present new analysis of the 11-year annual trends in total lightning flash density for all latitudinal belts and select regions/regimes of the tropics as related to conventional climate signals and precipitation contents in the same period. The results should enable us to address, in some fashion, the sensitivity of the lightning flash density to subtle changes in climate.

Petersen, Walter A.↗
NASA NTRS2010

Experimental Space Shuttle Orbiter Studies to Acquire Data for Code and Flight Heating Model Validation

In an experimental study to obtain detailed heating data over the Space Shuttle Orbiter, CUBRC has completed an extensive matrix of experiments using three distinct models and two unique hypervelocity wind tunnel facilities. This detailed data will be employed to assess heating augmentation due to boundary layer transition on the Orbiter wing leading edge and wind side acreage with comparisons to computational methods and flight data obtained during the Orbiter Entry Boundary Layer Flight Experiment and HYTHIRM during STS-119 reentry. These comparisons will facilitate critical updates to be made to the engineering tools employed to make assessments about natural and tripped boundary layer transition during Orbiter reentry. To achieve the goals of this study data was obtained over a range of Mach numbers from 10 to 18, with flight scaled Reynolds numbers and model attitudes representing key points on the Orbiter reentry trajectory. The first of these studies were performed as an integral part of Return to Flight activities following the accident that occurred during the reentry of the Space Shuttle Columbia (STS-107) in February of 2003. This accident was caused by debris, which originated from the foam covering the external tank bipod fitting ramps, striking and damaging critical wing leading edge heating tiles that reside in the Orbiter bow shock/wing interaction region. During investigation of the accident aeroheating team members discovered that only a limited amount of experimental wing leading edge data existed in this critical peak heating area and a need arose to acquire a detailed dataset of heating in this region. This new dataset was acquired in three phases consisting of a risk mitigation phase employing a 1.8% scale Orbiter model with special temperature sensitive paint covering the wing leading edge, a 0.9% scale Orbiter model with high resolution thin-film instrumentation in the span direction, and the primary 1.8% scale Orbiter model with detailed thin-film resolution in both the span and chord direction in the area of peak heating. Additional objectives of this first study included: obtaining natural or tripped turbulent wing leading edge heating levels, assessing the effectiveness of protuberances and cavities placed at specified locations on the orbiter over a range of Mach numbers and Reynolds numbers to evaluate and compare to existing engineering and computational tools, obtaining cavity floor heating to aid in the verification of cavity heating correlations, acquiring control surface deflection heating data on both the main body flap and elevons, and obtain high speed schlieren videos of the interaction of the orbiter nose bow shock with the wing leading edge. To support these objectives, the stainless steel 1.8% scale orbiter model in addition to the sensors on the wing leading edge was instrumented down the windward centerline, over the wing acreage on the port side, and painted with temperature sensitive paint on the starboard side wing acreage. In all, the stainless steel 1.8% scale Orbiter model was instrumented with over three-hundred highly sensitive thin-film heating sensors, two-hundred of which were located in the wing leading edge shock interaction region. Further experimental studies will also be performed following the successful acquisition of flight data during the Orbiter Entry Boundary Layer Flight Experiment and HYTHIRM on STS-119 at specific data points simulating flight conditions and geometries. Additional instrumentation and a protuberance matching the layout present during the STS-119 boundary layer transition flight experiment were added with testing performed at Mach number and Reynolds number conditions simulating conditions experienced in flight. In addition to the experimental studies, CUBRC also performed a large amount of CFD analysis to confirm and validate not only the tunnel freestream conditions, but also 3D flows over the orbiter acreage, wing leading edge, and controlurfaces to assess data quality, shock interaction locations, and control surface separation regions. This analysis is a standard part of any experimental program at CUBRC, and this information was of key importance for post-test data quality analysis and understanding particular phenomena seen in the data. All work during this effort was sponsored and paid for by the NASA Space Shuttle Program Office at the Johnson Space Center in Houston, Texas.

Wadhams, T. P.↗
NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗
NASA NTRS2009

TASS Model Application for Testing the TDWAP Model

One of the operational modes of the Terminal Area Simulation System (TASS) model simulates the three-dimensional interaction of wake vortices within turbulent domains in the presence of thermal stratification. The model allows the investigation of turbulence and stratification on vortex transport and decay. The model simulations for this work all assumed fully-periodic boundary conditions to remove the effects from any surface interaction. During the Base Period of this contract, NWRA completed generation of these datasets but only presented analysis for the neutral stratification runs of that set (Task 3.4.1). Phase 1 work began with the analysis of the remaining stratification datasets, and in the analysis we discovered discrepancies with the vortex time to link predictions. This finding necessitated investigating the source of the anomaly, and we found a problem with the background turbulence. Using the most up to date version TASS with some important defect fixes, we regenerated a larger turbulence domain, and verified the vortex time to link with a few cases before proceeding to regenerate the entire 25 case set (Task 3.4.2). The effort of Phase 2 (Task 3.4.3) concentrated on analysis of several scenarios investigating the effects of closely spaced aircraft. The objective was to quantify the minimum aircraft separations necessary to avoid vortex interactions between neighboring aircraft. The results consist of spreadsheets of wake data and presentation figures prepared for NASA technical exchanges. For these formation cases, NASA carried out the actual TASS simulations and NWRA performed the analysis of the results by making animations, line plots, and other presentation figures. This report contains the description of the work performed during this final phase of the contract, the analysis procedures adopted, and sample plots of the results from the analysis performed.

Switzer, George F.↗
NASA NTRS2009

Approach to Managing MeaSURES Data at the GSFC Earth Science Data and Information Services Center (GES DISC)

A major need stated by the NASA Earth science research strategy is to develop long-term, consistent, and calibrated data and products that are valid across multiple missions and satellite sensors. (NASA Solicitation for Making Earth System data records for Use in Research Environments (MEaSUREs) 2006-2010) Selected projects create long term records of a given parameter, called Earth Science Data Records (ESDRs), based on mature algorithms that bring together continuous multi-sensor data. ESDRs, associated algorithms, vetted by the appropriate community, are archived at a NASA affiliated data center for archive, stewardship, and distribution. See http://measures-projects.gsfc.nasa.gov/ for more details. This presentation describes the NASA GSFC Earth Science Data and Information Services Center (GES DISC) approach to managing the MEaSUREs ESDR datasets assigned to GES DISC. (Energy/water cycle related and atmospheric composition ESDRs) GES DISC will utilize its experience to integrate existing and proven reusable data management components to accommodate the new ESDRs. Components include a data archive system (S4PA), a data discovery and access system (Mirador), and various web services for data access. In addition, if determined to be useful to the user community, the Giovanni data exploration tool will be made available to ESDRs. The GES DISC data integration methodology to be used for the MEaSUREs datasets is presented. The goals of this presentation are to share an approach to ESDR integration, and initiate discussions amongst the data centers, data managers and data providers for the purpose of gaining efficiencies in data management for MEaSUREs projects.

Vollmer, Bruce↗
NASA NTRS2009

Lunar Geologic Mapping: A Preliminary Map of a Portion of the LQ-10 ("Marius") Quadrangle

Since the first lunar mapping program ended in the 1970s, new topographical, multispectral, elemental and albedo imaging datasets have become available (e.g., Clementine, Lunar Prospector, Galileo). Lunar science has also advanced within the intervening time period. A new systematic lunar geologic mapping effort endeavors to build on the success of earlier mapping programs by fully integrating the many disparate datasets using GIS software and bringing to bear the most current understanding of lunar geologic history. As part of this program, we report on a 1:2,500,000-scale preliminary map of a subset of Lunar Quadrangle 10 ("LQ-10" or the "Marius Quadrangle," see Figures 1 and 2), and discuss the first-order science results. By generating a geologic map of this region, we can constrain the stratigraphic and geologic relationships between features, revealing information about the Moon s chemical and thermal evolution.

Gregg, T. K. P.↗
NASA NTRS2009

New Geologic Map of the Scandia Region of Mars

We have begun work on a sophisti-cated digital geologic map of the Scandia region (Fig. 1) at 1:3,000,000 scale based on post-Viking image and to-pographic datasets. Through application of GIS tools, we will produce a map product that will consist of (1) a printed photogeologic map displaying geologic units and relevant modificational landforms produced by tectonism, erosion, and collapse/mass wasting; (2) a landform geoda-tabase including sublayers of key landform types, attributed with direct measurements of their planform and to-pography using Mars Orbiter Laser Altimeter (MOLA) altimetry data and High-Resolution Stereo Camera (HRSC) digital elevation models (DEMs) and various image datasets; and (3) a series of digital, reconstructed paleostratigraphic and paleotopographic maps showing the inferred distribution and topographic form of materi-als and features during past ages

Tanaka, K. L.↗
NASA NTRS2009

Mars Global Geologic Mapping: About Half Way Done

We are in the third year of a five-year effort to map the geology of Mars using mainly Mars Global Surveyor, Mars Express, and Mars Odyssey imaging and altimetry datasets. Previously, we have reported on details of project management, mapping datasets (local and regional), initial and anticipated mapping approaches, and tactics of map unit delineation and description [1-2]. For example, we have seen how the multiple types and huge quantity of image data as well as more accurate and detailed altimetry data now available allow for broader and deeper geologic perspectives, based largely on improved landform perception, characterization, and analysis. Here, we describe mapping and unit delineation results thus far, a new unit identified in the northern plains, and remaining steps to complete the map.

Tanaka, K. L.↗
NASA NTRS2009

A Look at Seasonal Snow Cover and Snow Mass in the Southern Hemisphere from 1979-2006 Using SMMR and SSM/I Passive Microwave Data

Seasonal snow cover in extra-tropical areas of South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and from the Special Sensor Microwave Imagers (SSM/I) on board the Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow mass were estimated for the months of May-September. Most of the seasonal snow in South America occurs in the Patagonia region of Argentina. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 sq km. The seasonal (May-September) 2 average snow cover extent was greatest in 1984 (464,250 sq km) and least in 1990 (69,875 sq km). In terms of snow mass, 1984 was also the biggest year (1.19 x 10(exp 13) kg) and 1990 was the smallest year (0.12 X 10(exp 13) kg). A strong relationship exists between the snow cover area and snow mass, correlated at 0.95, though no significant trend was found over the 28 year record for either snow cover extent or snow mass. For this long term climatology, snow mass and snow cover extent are shown to vary considerably from month to month and season to season. This analysis presents a consistent approach to mapping and measuring snow in South America utilizing an appropriate and readily available long term snow satellite dataset. This is the optimal dataset available, thus far, for deriving seasonal snow cover and snow mass in this region. Nonetheless, shallow snow, wet snow, snow beneath forests, as well as snow along coastal areas all may confound interpretation using passive microwave approaches. More work needs to be done to reduce the uncertainties in the data and hence, increase the confidence of the interpretation

Foster, James↗
NASA NTRS2010

An Examination of the Hadley Sea-Surface Temperature Time Series for the Nino 3.4 Region

The Hadley sea-surface temperature (HadSST) dataset is investigated for the interval 1871-2008. The purpose of this investigation is to determine the degree of success in identifying and characterizing El Nino (EN) southern (ENSO) extreme events, both EN and La Nina (LN) events. Comparisons are made against both the Southern Oscillation Index for the same time interval and with published values of the Oceanic Nino Index for the interval since 1950. Some 60 ENSO extreme events are identified in the HadSST dataset, consisting of 33 EN and 27 LN events. Also, preferential associations are found to exist between the duration of ENSO extreme events and their maximum anomalous excursion temperatures and between the recurrence rate for an EN event and the duration of the last known EN event. Because the present ongoing EN is a strong event, it should persist 11 months or longer, inferring that the next EN event should not be expected until June 2012 or later. Furthermore, the decadal sum of EN-related months is found to have increased somewhat steadily since the decade of 1920-1929, suggesting that the present decade (2010-2019) possibly will see about 3-4 EN events, totaling about 37 +/- 3 EN-related months (i.e., months that meet the definition for the occurrence of an EN event).

Wilson, Robert M.↗
NASA NTRS2010

Weighting Statistical Inputs for Data Used to Support Effective Decision Making During Severe Emergency Weather and Environmental Events

National Aeronautical and Space Administration (NASA) weather and atmospheric environmental organizations are insatiable consumers of geophysical, hydrometeorological and solar weather statistics. The expanding array of internet-worked sensors producing targeted physical measurements has generated an almost factorial explosion of near real-time inputs to topical statistical datasets. Normalizing and value-based parsing of such statistical datasets in support of time-constrained weather and environmental alerts and warnings is essential, even with dedicated high-performance computational capabilities. What are the optimal indicators for advanced decision making? How do we recognize the line between sufficient statistical sampling and excessive, mission destructive sampling ? How do we assure that the normalization and parsing process, when interpolated through numerical models, yields accurate and actionable alerts and warnings? This presentation will address the integrated means and methods to achieve desired outputs for NASA and consumers of its data.

Gardner, Adrian↗
NASA NTRS2010

Large Scale Covariability in the Aerosol-SST-Precipitation Relation: A Satellite Perspective

Although large scale aerosol effects on precipitation have attracted increasing attention in recent years, significant uncertainties still remain in the current understanding of'such effects. One of the factors contributing to these uncertainties is the availability of aerosol data sets that are sufficiently long, stable, and comprehensive to be used for climate analysis. Such data sets are crucial for any long-term studies that are needed to demonstrate the statistical significance of large scale aerosol effects on precipitation when compared to the effects from other climate factors, such as remote or local sea surface temperature (SST) variability (ENSO. etc.). A longterm consistent aerosol product that complements the existing MODIS and AVHRR aerosol products is therefore needed to minimize aerosol data uncertainty issues for such Studies. The SeaWiFS instrument was primarily designed to measure ocean color, and it has been the mayor source for providing a comprehensive global data set of such measurements since its launch in 1997. Besides being used in this capacity, however, the well-calibrated set of radiances measured in the wavelength range from the visible (0.41 m) to the near infrared (0.87 m) is also well suited to creating long-term climate data records of aerosols. Recently, a new 13-year SeaWiFS aerosol optical depth dataset has been developed that expands its capacity to be used for such atmospheric studies. This SeaWiFS aerosol product provides us with an unprecedented opportunity to examine the covariability of aerosol, SST and precipitation on both a regional and global scale. We also use concurrent independent SST (NOAA Optimum Interpolation, OI, SST V2) and precipitation (GPCP V2) datasets for this study. We will present and discuss results from this study over several aerosol hot spot regions ( -,North Atlantic. South Atlantic, Western Pacific, Indian Ocean etc.) during the SeaWIFS data period (1997 -- current) from this study will be presented and discussed. These results will highlight the value and impact of this unique product to climate studies

Hsu, N. Christina↗
NASA NTRS2010

Remote Characterization of Biomass Measurements: Case Study of Mangrove Forests

Accurately quantifying forest biomass is of crucial importance for climate change studies. By quantifying the amount of above and below ground biomass and consequently carbon stored in forest ecosystems, we are able to derive estimates of carbon sequestration, emission and storage and help close the carbon budget. Mangrove forests, in addition to providing habitat and nursery grounds for over 1300 animal species, are also an important sink of biomass. Although they only constitute about 3% of the total forested area globally, their carbon storage capacity -- in forested biomass and soil carbon -- is greater than that of tropical forests (Lucas et al, 2007). In addition, the amount of mangrove carbon -- in the form of litter and leaves exported into offshore areas is immense, resulting in over 10% of the ocean's dissolved organic carbon originating from mangroves (Dittmar et al, 2006) The measurement of forest above ground biomass is carried out on two major scales: on the plot scale, biomass can be measured using field measurements through allometric equation derivation and measurements of forest plots. On the larger scale, the field data are used to calibrate remotely sensed data to obtain stand-wide or even regional estimates of biomass. Currently, biomass can be calculated using average stand biomass values and optical data, such as aerial photography or satellite images (Landsat, Modis, Ikonos, SPOT, etc.). More recent studies have concentrated on deriving forest biomass values using radar (JERS, SIR-C, SRTM, Airsar) and/or lidar (ICEsat/GLAS, LVIS) active remote sensing to retrieve more accurate and detailed measurements of forest biomass. The implementation of a generation of new active sensors (UAVSar, DesdynI, Alos/Palsar, TerraX) has prompted the development of new tecm'liques of biomass estimation that use the combination of multiple sensors and datasets, to quantify past, current and future biomass stocks. Focusing on mangrove forest biomass estimation, this book chapter has 3 main objectives: a) To describe in detail the field methodologies used to derive accurate estimates of biomass in mangrove forests b) To explain how mangrove forest biomass can be measured using several remote sensing techniques and datasets c) To give a detailed explanation of the measurement challenges and errors that arise in each estimate of forest biomass

Fatoyinbo, Temilola E.↗
NASA NTRS2010

High-Contrast 3.8 Micron Imaging of the Brown Dwarf/Planet-Mass Companion to GJ 758

We present L' band (3.8 Micron) MMT/Clio high-contrast imaging data for the nearby star GJ 758, which was recently reported by Thalmann et al. (2009) to have one -- possibly two-- faint comoving companions (GJ 7588 and "C", respectively). GJ 758B is detected in two distinct datasets. Additionally, we report a \textit(possible) detection of the object identified by Thalmann et al as "GJ 758C" in our more sensitive dataset, though it is likely a residual speckle. However, if it is the same object as that reported by Thalmann et al. it cannot be a companion in a bound orbit. GJ 758B has a H-L'color redder than nearly all known L--T8 dwarfs. Based on comparisons with the COND evolutionary models, GJ 758B has Te approx. 560 K (+150 K, -90 K) and a mass ranging from approx. 10-20 Mj if it is approx. 1 Gyr old to approx. 25-40 Mj if it is 8.7 Gyr old. GJ 758B is likely in a highly eccentric orbit, e approx. 0.73 (+0.12,-0.21), with a semimajor axis of approx. 44 AU (+32 AU, -14 AU). Though GJ 758B is sometimes discussed within the context of exoplanet direct imaging, its mass is likely greater than the deuterium-burning limit and its formation may resemble that of binary stars rather than that of jovian-mass planets.

Currie, Thayne↗
NASA NTRS2010

Fast and Flexible Multivariate Time Series Subsequence Search

Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical monitoring, and financial systems. Domain experts are often interested in searching for interesting multivariate patterns from these MTS databases which often contain several gigabytes of data. Surprisingly, research on MTS search is very limited. Most of the existing work only supports queries with the same length of data, or queries on a fixed set of variables. In this paper, we propose an efficient and flexible subsequence search framework for massive MTS databases, that, for the first time, enables querying on any subset of variables with arbitrary time delays between them. We propose two algorithms to solve this problem (1) a List Based Search (LBS) algorithm which uses sorted lists for indexing, and (2) a R*-tree Based Search (RBS) which uses Minimum Bounding Rectangles (MBR) to organize the subsequences. Both algorithms guarantee that all matching patterns within the specified thresholds will be returned (no false dismissals). The very few false alarms can be removed by a post-processing step. Since our framework is also capable of Univariate Time-Series (UTS) subsequence search, we first demonstrate the efficiency of our algorithms on several UTS datasets previously used in the literature. We follow this up with experiments using two large MTS databases from the aviation domain, each containing several millions of observations. Both these tests show that our algorithms have very high prune rates (>99%) thus needing actual disk access for only less than 1% of the observations. To the best of our knowledge, MTS subsequence search has never been attempted on datasets of the size we have used in this paper.

Bhaduri, Kanishka↗