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At least 289 records · Page 16

COVID-19 Lockdowns Drive Decline in Active Fires in Southeastern United States

Fire is a common ecosystem process in forests and grasslands worldwide. Increasingly, ignitions are controlled by human activities either through suppression of wildfires or intentional ignition of prescribed fires. The Southeastern United States leads the nation in prescribed fire, burning ca. 80% of the countries extent annually. The COVID-19 pandemic radically changed human behavior as workplaces implemented social-distancing guidelines and provided an opportunity to evaluate relationships between humans and fire as fire management plans were postponed or cancelled. Using active fire data from satellite-based observations, we found that in the Southeastern United States, COVID-19 led to a 21% reduction in fire activity compared to the 2003-2019 average. The reduction was more pronounced for federally managed lands, up to 41% below average compared to the past 20-years (38% below average compared to the past decade). Declines in fire activity were partly affected by an unusually wet February before the COVID-19 shutdown began in mid-March 2020. Despite the wet spring, the predicted number of active fire detections was still lower than expected, confirming a COVID-19 signal on ignitions. In addition, prescribed fire management statistics, reported by US federal agencies, confirmed the satellite observations, and showed that following the wet February and before the mid-March COVID-19 shutdown, cumulative burned area was approaching record highs across the region. With fire return intervals in the Southeastern United States as frequent as 1-2 years, COVID-19 fire impacts will contribute to an increasing backlog in necessary fire management activities, affecting biodiversity and future fire danger.

Biological Sciences↗

Statistical analysis of total ozone and stratospheric Umkehr data for trends and solar cycle relationship

Dobson total ozone data from 1970-1984 and stratospheric Umkehr profile ozone data from 1970-1981 are analyzed. The relationship between ozone and long-term solar cycle activity is examined using 10.7 cm solar flux data. From the Dobson data it is estimated that the overall global trend in total ozone is -0.26 + or -0.92 percent per decade, which indicates no significant overall trend; and for the total ozone-solar flux relationship there is a 1.18 + or - 0.66 percent change in total ozone from solar cycle minimum to maximum that reveals a positive relationship. Analysis of the Umkehr data reveals a negative trend of -0.30 + or - 0.17 percent per year in the layers 7 snd 8. The relationship between Umkehr data and solar flux in layers 6 and 7 is 2.57 + or - 1.25 percent and 3.40 + or - 2.16 percent change from solar cycle minimum to maximum; however, no significant relationship is detected in the higher layers 8 and 9. These estimates are compared with theoretical model calculations. It is noted that the estimated effects of solar cycle activity on total ozone and stratospheric ozone agree with calculations of photochemical models.

Reinsel, Gregory C.↗

GEO Population Estimates using Optical Survey Data

Optical survey data taken using the NASA Michigan Orbital Debris Survey Telescope (MODEST) gives us an opportunity to statistically sample faint object population in the Geosynchronous (GEO) and near-GEO environment. This paper will summarize the MODEST survey work that has been conducted by NASA since 2002, and will outline the techniques employed to arrive at the current population estimates in the GEO environment for dim objects difficult to detect and track using current systems in the Space Surveillance Network (SSN). Some types of orbits have a higher detection rate based on what parts of the GEO belt is being observed, a straightforward statistical technique is used to debias these observations to arrive at an estimate of the total population potentially visible to the telescope. The size and magnitude distributions of these fainter debris objects are markedly different from the catalogued population. GEO debris consists of at least two different populations, one which follows the standard breakup power law and one which has anomalously high Area-to-Mass Ratios (1 to approx. 30 square meters per kilogram; a sheet of paper = approx. 13 square meters per kilogram). The Inter-Agency Space Debris Coordination Committee (IADC) is investigating objects in GEO orbits with anomalously high Area-to-Mass Ratios (AMRs). The ESA Space Debris Telescope discovered this population and has and its properties of inclinations (0 to 30 degrees), changing eccentricities (0 and 0.6), and mean motions (approx. 1 rev), will be presented. The accepted interpretation of this orbital behavior is that solar radiation pressure drives the perturbations causing time varying inclinations and eccentricities. The orbital parameters are unstable for this population and thus difficult to predict. Their dim visual magnitudes and photometric variability make observations a challenge. The IADC has enlisted a series of observatories (participating institutions: University of Michigan/CTIO, Astronomical Institute University of Bern, Boeing LTS / AMOS, Keldysh Institute of Applied Mathematics) at different longitudes. Complete observational coverage over periods of days to months will provide a better understanding of the properties, such as solar radiation pressure effects on orbital elements, size, shape, attitude, color variations, and spectral characteristics. Results from recent observational programs will be summarized, and includes a description of the orbit elements prediction processes, a summary of the metric tracking performance, and some photometric characteristics of this class of debris.

Barker, Edwin S.↗

Performance Evaluation of Fiber Bragg Gratings at Elevated Temperatures

The development of integrated fiber optic sensors for smart propulsion systems demands that the sensors be able to perform in extreme environments. In order to use fiber optic sensors effectively in an extreme environment one must have a thorough understanding of the sensor s limits and how it responds under various environmental conditions. The sensor evaluation currently involves examining the performance of fiber Bragg gratings at elevated temperatures. Fiber Bragg gratings (FBG) are periodic variations of the refractive index of an optical fiber. These periodic variations allow the FBG to act as an embedded optical filter passing the majority of light propagating through a fiber while reflecting back a narrow band of the incident light. The peak reflected wavelength of the FBG is known as the Bragg wavelength. Since the period and width of the refractive index variation in the fiber determines the wavelengths that are transmitted and reflected by the grating, any force acting on the fiber that alters the physical structure of the grating will change what wavelengths are transmitted and what wavelengths are reflected by the grating. Both thermal and mechanical forces acting on the grating will alter its physical characteristics allowing the FBG sensor to detect both temperature variations and physical stresses, strain, placed upon it. This ability to sense multiple physical forces makes the FBG a versatile sensor. This paper reports on test results of the performance of FBGs at elevated temperatures. The gratings looked at thus far have been either embedded in polymer matrix materials or freestanding with the primary focus of this paper being on the freestanding FBGs. Throughout the evaluation process, various parameters of the FBGs performance were monitored and recorded. These parameters include the peak Bragg wavelength, the power of the Bragg wavelength, and total power returned by the FBG. Several test samples were subjected to identical test conditions to allow for statistical analysis of the data. Test procedures, calibrations, and referencing techniques are presented in the paper along with directions for future research.

Juergens, Jeffrey↗

Detection of atmospheric pressure loading using very long baseline interferometry measurements

Loading of the Earth by the temporal redistribution of global atmospheric mass is likely to displace the positions of geodetic monuments by tens of millimeters both vertically and horizontally. Estimates of these displacements are determined by convolving National Meteorological Center (NMC) global values of atmospheric surface pressure with Farrell's elastic Green's functions. An analysis of the distances between radio telescopes determined by very long baseline interferometry (VLBI) between 1984 and 1992 reveals that in many of the cases studied there is a significant contribution to baseline length change due to atmospheric pressure loading. Our analysis covers intersite distances of between 1000 and 10,000 km and is restricted to those baselines measured more than 100 times. Accounting for the load effects (after first removing a best fit slope) reduces the weighted root-mean-square (WRMS) scatter of the baseline length residuals on 11 of the 22 baselines investigated. The slight degradation observed in the WRMS scatter on the remaining baselines is largely consistent with the expected statistical fluctuations when a small correction is applied to a data set having a much larger random noise. The results from all baselines are consistent with approximately 60% of the computed pressure contribution being present in the VLBI length determinations. Site dependent coefficients determined by fitting local pressure to the theoretical radial displacement are found to reproduce the deformation caused by the regional pressure to within 25% for most inland sites. The coefficients are less reliable at near coastal and island stations.

Vandam, T. M.↗

Atmospheric pressure loading effects on Global Positioning System coordinate determinations

Earth deformation signals caused by atmospheric pressure loading are detected in vertical position estimates at Global Positioning System (GPS) stations. Surface displacements due to changes in atmospheric pressure account for up to 24% of the total variance in the GPS height estimates. The detected loading signals are larger at higher latitudes where pressure variations are greatest; the largest effect is observed at Fairbanks, Alaska (latitude 65 deg), with a signal root mean square (RMS) of 5 mm. Out of 19 continuously operating GPS sites (with a mean of 281 daily solutions per site), 18 show a positive correlation between the GPS vertical estimates and the modeled loading displacements. Accounting for loading reduces the variance of the vertical station positions on 12 of the 19 sites investigated. Removing the modeled pressure loading from GPS determinations of baseline length for baselines longer than 6000 km reduces the variance on 73 of the 117 baselines investigated. The slight increase in variance for some of the sites and baselines is consistent with expected statistical fluctuations. The results from most stations are consistent with approximately 65% of the modeled pressure load being found in the GPS vertical position measurements. Removing an annual signal from both the measured heights and the modeled load time series leaves this value unchanged. The source of the remaining discrepancy between the modeled and observed loading signal may be the result of (1) anisotropic effects in the Earth's loading response, (2) errors in GPS estimates of tropospheric delay, (3) errors in the surface pressure data, or (4) annual signals in the time series of loading and station heights. In addition, we find that using site dependent coefficients, determined by fitting local pressure to the modeled radial displacements, reduces the variance of the measured station heights as well as or better than using the global convolution sum.

Vandam, Tonie M.↗

Climate Change Signal in Atlantic Tropical Cyclones Today and Near Future

This manuscript discusses the challenges in detecting and attributing recently observed trends in the Atlantic tropical cyclone (TC) and the epistemic uncertainty we face in assessing future risk. We use synthetic storms downscaled from five CMIP5 models by the Columbia HAZard model (CHAZ), and directly simulated storms from high-resolution climate models. We examine three aspects of recent TC activity: the upward trend and multi-decadal oscillation of the annual frequency, the increase in storm wind intensity, and the decrease in forward speed. Some data sets suggest that these trends and oscillation are forced while others suggest that they can be explained by natural variability. Projections under warming climate scenarios also show a wide range of possibilities, especially for the annual frequencies, which increase or decrease depending on the choice of moisture variable used in the CHAZ model and on the choice of climate model. The uncertainties in the annual frequency lead to epistemic uncertainties in TC risk assessment. Here, we investigate the potential for reduction of these epistemic uncertainties through a statistical practice, namely likelihood analysis. We find that historical observations are more consistent with the simulations with increasing frequency than those with decreasing frequency, but we are not able to rule out the latter. We argue that the most rational way to treat epistemic uncertainty is to consider all outcomes contained in the results. In the context of risk assessment, since the results contain possible outcomes in which TC risk is increasing, this view implies that the risk is increasing.

54 ENVIRONMENTAL SCIENCES↗

Charles River Watershed Water Resources: Assessing Flooding Vulnerability to Assist High Water Intervention and Urban Planning Programs in the Charles River Watershed

The Charles River watershed intersects 35 municipalities within the Boston Metropolitan Area and has a population of 1.2 million, making it one of the most densely populated watersheds in New England. In recent years, the watershed has observed higher rates of flood inundation, mainly due to increased development, extreme precipitation events, and increased surface runoff. As the frequency of flood events increases and a changing climate poses an ongoing threat to local communities, governments, and organizations in Massachusetts need accurate flood risk assessments. This project partnered with the Charles River Watershed Association, the Town of Natick’s Office of Sustainability, and the Massachusetts Audubon Society to assess the potential for watershed degradation, flood vulnerability, and flood susceptibility in the watershed. The team used Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR), and Sentinel-2 MultiSpectral Instrument (MSI) to assess the feasibility of identifying flood events using remote sensing. After identifying images that overlapped with the reported flood events, the team concluded that it was not feasible to use Earth observation data to detect localized flooding. Instead, the Federal Emergency Management Agency (FEMA) 100-year floodplain was used as a proxy for areas where flooding may occur. The team used statistical analysis and supervised classification to develop a flood susceptibility map, incorporating factors like soil drainage, height above nearest drainage, and topographic wetness index. This was overlaid with demographic and socioeconomic data to create a flood vulnerability map. The flood susceptibility map captured over 2/3 of reported flood events in the watershed, an improvement over the 1/3 of events captured by the FEMA 100-year and 500-year floodplain maps.

DEVELOP Project Summary↗

RU Net for Automatic Characterization of TRISO Fuel Cross Sections

TRistructural ISOtropic (TRISO) particle fuel is a type of nuclear fuel known for its high-temperature and high-burnup performance. Each sub-millimeter diameter TRISO particle consists of uranium-oxycarbide (UCO) or UO2 fuel kernel, coated with buffer, inner pyrolytic carbon (IPyC), silicon carbide (SiC), and outer pyrolytic carbon (OPyC) layers. The SiC layer acts as the main containment barrier for the TRISO particle to retain the fission products, while the IPyC and OPyC layers provide additional barriers to the release of fission products, especially fission gases. During irradiation, phenomena like kernel swelling, buffer densification, and IPyC fracture may impact fuel performance. Post-irradiation microscopy on entire compact cross sections or samples of individual particles deconsolidated from compacts is often used to identify these irradiation-induced changes in morphology. However, each fuel compact generally contains thousands of TRISO particles. To get statistical information on these phenomena, it is cumbersome work if done manually. For example, to get information about swelling/densification behaviors of different layers or kernels after irradiation, researchers previously manually measured the perimeter of each TRISO layer in hundreds of particles after four rounds of iterative grinding and polishing encompassing more than 2000 cross-section images for a total of four fuel compacts. To attempt to reduce the subjectivity inherent in that process and accelerate data analysis, we conducted a study on the automatic TRISO layer segmentation on cross-sectional microscopic images using Convolutional Neural Networks (CNNs). CNNs are a class of machine learning algorithms specifically designed for processing structured grid data that have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we have generated the large irradiated TRISO layer dataset with more than 2000 cross-section TRISO microscopic images and the corresponding annotated images. Based on these annotated images, we have employed different CNNs for automatic segmentation of different TRISO layers. These include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net has the best performance in terms of intersection-over-union (IoU). Through the aid of these CNN models, we can expedite the analysis of TRISO particle cross-sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

Convolutional Neural Networks↗

A Terrestrial Validation of ICESat Elevation Measurements and Implications for Global Reanalyses

The primary goal of NASA's Ice, Cloud, and land Elevation Satellite (ICESat) mission was to detect centimeter-level changes in global ice sheet elevations at the spatial scale of individual ice streams. Confidence in detecting these small signals requires careful validation over time to characterize the uncertainty and stability of measured elevations. A common validation approach compares altimeter elevations to an independently characterized and stable reference surface. Using a digital elevation model (DEM) from geodetic surveys of one such surface, the salar de Uyuni in Bolivia, we show that ICESat elevations at this location have a 0.0-centimeter bias relative to the WGS84 ellipsoid, 4.0-centimeter (1-sigma) uncertainty overall, and 1.8-centimeter uncertainty under ideal conditions over short (50 kilometer) profiles. We observe no elevation bias between ascending and descending orbits, but we do find that elevations measured immediately after transitions from low to high surface albedo may be negatively biased. Previous studies have reported intercampaign biases (ICBs) between various ICESat observation campaigns, but we find no statistically significant ICBs or ICB trends in our data. We do find a previously unreported 3.1-centimeter bias between ICESat's Laser 2 and Laser 3, and we find even larger interlaser biases in reanalyzed data from other studies. For an altimeter with an exact repeat orbit like ICESat, we also demonstrate that validation results with respect to averaged elevation profiles along a single ground track are comparable to results obtained using reference elevations from an in situ survey.

Laser Ranging↗

Assessing Flooding Vulnerability to Assist High Water Intervention and Urban Planning Programs in the Charles River Watershed with NASA DEVELOP

The Charles River watershed intersects 35 municipalities within the Boston Metropolitan Area and has a total population of 1.2 million, making it one of the most densely populated watersheds in New England. In recent years, the watershed has observed higher rates of flood inundation, mainly due to increased development, extreme precipitation events, and increased surface runoff. As the frequency of flooding events increases and a changing climate poses an ongoing threat to local communities, governments and organizations in Massachusetts are in need of accurate flood risk assessments. NASA DEVELOP partnered with the Charles River Watershed Association, the Town of Natick’s Office of Sustainability, and the Massachusetts Audubon Society to assess flood vulnerability and susceptibility in the watershed. The team used Landsat 5 Thematic Mapper, Landsat 8 Operational Land Imager, Sentinel-1 C-Band Synthetic Aperture Radar, and Sentinel-2 MultiSpectral Instrument to assess the feasibility of identifying the extent of past flood events using remote sensing. After identifying images that overlapped with reported flood events, the team concluded that it was not feasible to use Earth observation data to detect localized flooding in the time available for this study. Instead, the Federal Emergency Management Agency (FEMA) 100-year floodplain was used as a proxy for areas where flooding may occur. The team used statistical regression analysis and validation and supervised classification to develop a flood susceptibility map, incorporating several flood conditioning factors. The susceptibility maps were calibrated to various thresholds, including two that highlight hypothetical flooding under more liberal and more conservative planning scenarios. These were overlaid with demographic and socioeconomic data to create flood vulnerability maps. The team’s flood susceptibility maps showed an improvement in capturing known flood events over the FEMA 100-year and 500-year floodplain maps. These results will be improved with the addition of stormwater drainage mapping and precipitation data. Results can be used to fill in the gaps to help the stakeholders understand their communities’ vulnerability and susceptibility to flooding and improve their preparedness plans.

Trista Brophy↗

Global CALIPSO Observations of Aerosol Changes Near Clouds

Several recent studies have found that clouds are surrounded by a transition zone of rapidly changing aerosol optical properties and particle size. Characterizing this transition zone is important for better understanding aerosol-cloud interactions and aerosol radiative effects, and also for improving satellite retrievals of aerosol properties. This letter presents a statistical analysis of a monthlong global data set of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar observations over oceans. The results show that the transition zone is ubiquitous over all oceans and extends up to 15 km away from clouds. They also show that near-cloud enhancements in backscatter and particle size are strongest at low altitudes, slightly below the top of the nearest clouds. Also, the enhancements are similar near illuminated and shadowy cloud sides, which confirms that the asymmetry of Moderate Resolution Imaging Spectroradiometer reflectances found in an earlier study comes from 3-D radiative processes and not from differences in aerosol properties. Finally, the effects of CALIPSO aerosol detection and cloud identification uncertainties are discussed. The findings underline the importance of accounting for the transition zone to avoid potential biases in studies of satellite aerosol products, aerosol-cloud interactions, and aerosol direct radiative effects.

Varnai, Tamas↗

AstroBiology Explorer Mission Concepts (ABE/ASPIRE)

The AstroBiology Explorer (ABE) and the Astrobiology Space InfraRed Explorer (ASPIRE) Mission Concepts are two missions designed to address the questions (1) Where do we come from? and (2) Are we alone? as outlined in NASA s Origins Program using infrared spectroscopy to explore the identity, abundance, and distribution of molecules of astrobiological importance throughout the Universe. The ABE mission s observational program is focused on six tasks to: (1) Investigate the evolution of ice and organics in dense clouds and star formation regions, and the young stellar/planetary systems that form in them; (2) Measure the evolution of complex organic molecules in stellar outflows; (3) Study the organic composition of a wide variety of solar system objects including asteroids, comets, and the planets and their satellites; (4) Identify organic compounds in the diffuse interstellar medium and determine their distribution , abundance, and change with environment; (5) Detect and identify organic compounds in other galaxies and determine their dependence on galactic type; and (6) Measure deuterium enrichments in interstellar organics and use them as tracers of chemical processes. The ASPIRE mission s observational program expands upon ABE's core mission and adds tasks that (7) Address the role of silicates in interstellar organic chemistry; and (8) Use different resolution spectra to assess the relative roles and abundances of gas- and solid-state materials. ABE (ASPIRE) achieves these goals using a highly sensitive, cryogenically-cooled telescope in an Earth drift-away heliocentric orbit, armed with a suite of infrared spectrometers that cover the 2.5-20(40) micron spectral region at moderate spectral resolution (R>2000). ASPIRE's spectrometer complement also includes a high-resolution (R>25,000) module over the 4-8 micron spectral region. Both missions target lists are chosen to observe a statistically significant sample of a large number of objects of varied types in support of the tasks outline above. The ABE and ASPIRE mission lifetimes are designed to be 14 months and 3 years, respectively, both with significant cryogen and propellant lifetime margins to support an extended observing campaign. The ABE/ASPIRE mission concepts and their supporting Science Teams are led by Principal Investigator Dr. Scott Sandford of NASA s Ames Research Center, with industry partner Ball Aerospace Technologies Ltd., and managed by Jet Propulsion Laboratory. The ABE/ASPIRE Science Operations will be carried out at NASA s Ames Research Center, and the ABE/ASPIRE database will be archived at Caltech/IPAC.

Sandford, Scott↗

Major episodes of geologic change - Correlations, time structure and possible causes

Published data sets of major geologic events of the past about 250 Myr (extinction events, sea-level lows, continental flood-basalt eruptions, mountain-building events, abrupt changes in sea-floor spreading, ocean-anoxic and blackshale events and the largest evaporite deposits) have been synthesized (with estimated errors). These events show evidence for a statistically significant periodic component with an underlying periodicity, formally equal to 26.6 Myr, and a recent maximum, close to the present time. The cycle may not be strictly periodic, but a periodicity of about 30 Myr is robust to probable errors in dating of the geologic events. The intervals of geologic change seem to involve jumps in sea-floor spreading associated with episodic continental rifting, volcanism, enhanced orogeny, global sea-level changes and fluctuations in climate. The period may represent a purely internal earth-pulsation, but evidence of planetesimal impacts at several extinction boundaries, and a possible underlying cycle of 28-36 Myr in crater ages, suggests that highly energetic impacts may be affecting global tectonics. A cyclic increase in the flux of planetesimals might result from the passage of the Solar System through the central plane of the Milky Way Galaxy - an event with a periodicity and mean phasing similar to that detected in the geologic changes.

Rampino, Michael R.↗

Regime-oriented causal model evaluation of Atlantic–Pacific teleconnections in CMIP6

The climate system and its spatio-temporal changes are strongly affected by modes of long-term internal variability, like the Pacific decadal variability (PDV) and the Atlantic multidecadal variability (AMV). As they alternate between warm and cold phases, the interplay between PDV and AMV varies over decadal to multidecadal timescales. Here, we use a causal discovery method to derive fingerprints in the Atlantic–Pacific interactions and to investigate their phase-dependent changes. Dependent on the phases of PDV and AMV, different regimes with characteristic causal fingerprints are identified in reanalyses in a first step. In a second step, a regime-oriented causal model evaluation is performed to evaluate the ability of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in representing the observed changing interactions between PDV, AMV and their extra-tropical teleconnections. The causal graphs obtained from reanalyses detect a direct opposite-sign response from AMV to PDV when analyzing the complete 1900–2014 period and during several defined regimes within that period, for example, when AMV is going through its negative (cold) phase. Reanalyses also demonstrate a same-sign response from PDV to AMV during the cold phase of PDV. Historical CMIP6 simulations exhibit varying skill in simulating the observed causal patterns. Generally, large-ensemble (LE) simulations showed better network similarity when PDV and AMV were out of phase compared to other regimes. Also, the two largest ensembles (in terms of number of members) were found to contain realizations with similar causal fingerprints to observations. For most regimes, these same models showed higher network similarity when compared to each other. This work shows how causal discovery on LEs complements the available diagnostics and statistical metrics of climate variability to provide a powerful tool for climate model evaluation.

54 ENVIRONMENTAL SCIENCES↗

Acute stress reduces population-level metabolic and proteomic variation

Abstract Background Variation in omics data due to intrinsic biological stochasticity is often viewed as a challenging and undesirable feature of complex systems analyses. In fact, numerous statistical methods are utilized to minimize the variation among biological replicates. Results We demonstrate that the common statistics relative standard deviation (RSD) and coefficient of variation (CV), which are often used for quality control or part of a larger pipeline in omics analyses, can also be used as a metric of a physiological stress response. Using an approach we term Replicate Variation Analysis (RVA), we demonstrate that acute physiological stress leads to feature-wide canalization of CV profiles of metabolomes and proteomes across biological replicates. Canalization is the repression of variation between replicates, which increases phenotypic similarity. Multiple in-house mass spectrometry omics datasets in addition to publicly available data were analyzed to assess changes in CV profiles in plants, animals, and microorganisms. In addition, proteomics data sets were evaluated utilizing RVA to identify functionality of reduced CV proteins. Conclusions RVA provides a foundation for understanding omics level shifts that occur in response to cellular stress. This approach to data analysis helps characterize stress response and recovery, and could be deployed to detect populations under stress, monitor health status, and conduct environmental monitoring.

59 BASIC BIOLOGICAL SCIENCES↗

EGRET observations of the Vela pulsar, PSR0833-45

During the all sky survey (May 1991 to November 1992) of the Compton Gamma Ray Observatory, the Vela pulsar PSR0833-45 was in the field of view of the Energetic Gamma Ray Experiment Telescope (EGRET) in ten separate viewing periods. The pulsar was detected in each one. The average intensity from 100 MeV to 2GeV was (7.8 +/- 1.0) x 10(exp -6) photons /sq cm/s, which indicates that the pulsar in the years 1991/92 was in a state comparable to the low fluxes observed in 1977-1980. No significant changes in intensity were detected during the EGRET observations. The total spectrum of PSR0833-45 measured by EGRET can be described by a power-law with index -1.70 +/- 0.02 over the range 30 MeV to 2 GeV. The extrapolation of this spectrum into the 3-30 MeV range agrees with the observations by COMPTEL. Above 2-4 GeV EGRET detects a strong spectral break. The lightcurves obtained show a familiar structure in the phase histogram: two peaks separated by 0.424 +/- 0.002 in phase with considerable emission in the phase interval between the peaks. The first gamma ray peak maximum trails the single radio peak maximum by 10.54 +/- 0.09 ms (= 0.118 +/- 0.001 in phase). The widths of the emission peaks (FWHM) are 2.7 ms for the first peak (0.03 phase) and 4.1 ms for the second peak (0.05 phase). The widths are approximately constant below a GeV, but show a tendency to become narrower at higher energies. The statistics available for the Vela observations allow for a division of the lightcurve into eight phase intervals. The emission peak cores (central FWHM) with leading and trailing wings and two interval regions were defined and spectra were derived for all parts of the lightcurve. The energy spectra for the eight phase intervals show significant differences: the first peak (approximately E(exp -1.81 +/- 0.04)) is somewhat softer than the second peak (approximately E(exp -1.71 +/- 0.03)); the wings attached to each peak show softer spectra than the core of the peaks; the interval emission has the hardest spectrum (approximately E(exp -1.52 +/- 0.03)).

Kanbach, G.↗

Preliminary Optical And Electric Field Pulse Statistics From Storm Overflights During The Altus Cumulus Electrification Study

The Altus Cumulus Electrification Study (ACES) was conducted during the month of August, 2002 in an area near Key West, Florida. One of the goals of this uninhabited aerial vehicle (UAV) study was to collect high resolution optical pulse and electric field data from thunderstorms. During the month long campaign, we acquired 5294 lightning generated optical pulses with associated electric field changes. Most of these observations were made while close to the top of the storms. We found filtered mean and median 10-10% optical pulse widths of 875 and 830 microns respectively while the 50-50% mean and median optical pulse widths are 422 and 365 microns respectively. These values are similar to previous results as are the 10-90% mean and median rise times of 327 and 265 microns. The peak electrical to optical pulse delay mean and median were 209 and 145 microns which is longer than one would expect from theoretical results. The results of the pulse analysis will contribute to further validation of the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS) satellites. Pre-launch estimates of the flash detection efficiency were based on a small sample of optical pulse measurements associated with less than 350 lightning discharges collected by NASA U-2 aircraft in the early 1980s. Preliminary analyses of the ACES measurements show that we have greatly increased the number of optical pulses available for validation of the LIS and other orbital lightning optical sensors. Since the Altus was often close to the cloud tops, many of the optical pulses are from low-energy pulses. From these low-energy pulses, we can determine the fraction of optical lightning pulses below the thresholds of LIS, OTD, and any future satellite-based optical sensors such as the geostationary Lightning Mapping Sensor.

Mach, D. A.↗