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Analyzing Radio-Frequency Coverage for the ISS

The Interactive Coverage Analysis Tool (iCAT) is an interactive desktop computer program serving to (1) support planning of coverage, and management of usage of frequencies, of current and proposed radio communication systems on and near the International Space Station (ISS) and (2) enable definition of requirements for development of future such systems. The iCAT can also be used in design trade studies for other (both outer-space and terrestrial) communication systems. A user can enter the parameters of a communication-system link budget in a table in a worksheet. The nominal (onaxis) link values for the bit-to-noise-energy ratio, received isotropic power (RIP), carrier-to-noise ratio (C/N), power flux density (PFD), and link margin of the system are calculated and displayed in the table. Plots of field gradients for the RIP, C/N, PFD, and link margin are constructed in an ISS coordinate system, at a specified link range, for both the forward and return link parameters, and are displayed in worksheets. The forward and reverse link antenna gain patterns are also constructed and displayed. Line-of-sight (LOS) obstructions can be both incorporated into the gradient plots and displayed on separate plots.

Bolen, Steven M.↗

A New Display Format Relating Azimuth-Scanning Radar Data and All-Sky Images in 3-D

Here we correlate features in a sequence of all-sky images of 630 nm airglow with the three-dimensional (3-D) structure of electron densities in the F region above Arecibo. Pairs of 180 azimuth scans (using the Gregorian and line feeds) of the two-beam incoherent scatter radar (ISR) have been plotted in cone pictorials of the line-of-sight electron densities. The plots include projections of the 630 nm airglow onto the ground using the same spatial scaling as for the ISR data. Selected sequential images from the night of 16-17 June 2004 correlate ionospheric plasma features with scales comparable to the ISR density-cone diameter. The entire set of over 100 images spanning about eight hours is available as a movie. The correlation between the airglow and the electron densities is not unexpected, but the new display format shows the 3-D structures better than separate 2-D plots in latitude and longitude for the airglow and in height and time for the electron densities. Furthermore, the animations help separate the bands of airglow from obscuring clouds and the star field.

Swartz, Wesley E.↗

"One-Stop Shopping" for Ocean Remote-Sensing and Model Data

OurOcean Portal 2.0 (http:// ourocean.jpl.nasa.gov) is a software system designed to enable users to easily gain access to ocean observation data, both remote-sensing and in-situ, configure and run an Ocean Model with observation data assimilated on a remote computer, and visualize both the observation data and the model outputs. At present, the observation data and models focus on the California coastal regions and Prince William Sound in Alaska. This system can be used to perform both real-time and retrospective analyses of remote-sensing data and model outputs. OurOcean Portal 2.0 incorporates state-of-the-art information technologies (IT) such as MySQL database, Java Web Server (Apache/Tomcat), Live Access Server (LAS), interactive graphics with Java Applet at the Client site and MatLab/GMT at the server site, and distributed computing. OurOcean currently serves over 20 real-time or historical ocean data products. The data are served in pre-generated plots or their native data format. For some of the datasets, users can choose different plotting parameters and produce customized graphics. OurOcean also serves 3D Ocean Model outputs generated by ROMS (Regional Ocean Model System) using LAS. The Live Access Server (LAS) software, developed by the Pacific Marine Environmental Laboratory (PMEL) of the National Oceanic and Atmospheric Administration (NOAA), is a configurable Web-server program designed to provide flexible access to geo-referenced scientific data. The model output can be views as plots in horizontal slices, depth profiles or time sequences, or can be downloaded as raw data in different data formats, such as NetCDF, ASCII, Binary, etc. The interactive visualization is provided by graphic software, Ferret, also developed by PMEL. In addition, OurOcean allows users with minimal computing resources to configure and run an Ocean Model with data assimilation on a remote computer. Users may select the forcing input, the data to be assimilated, the simulation period, and the output variables and submit the model to run on a backend parallel computer. When the run is complete, the output will be added to the LAS server for

Li, P. Peggy↗

Summary Report of Mission Acceleration Measurement for STS-87, Launched November 19, 1997

Two accelerometer systems, the Orbital Acceleration Research Experiment and the Space Acceleration Measurement System, were used to measure and record the microgravity environment of the Orbiter Columbia during the STS-87 mission in November-December 1997. Data from two separate Space Acceleration Measurement System units were telemetered to the ground during the mission and data plots were displayed for investigators of the Fourth United States Microgravity Payload experiments in near real-time using the World Wide Web. Plots generated using Orbital Acceleration Research Experiment data (telemetered to the ground using a tape delay) were provided to the investigators using the World Wide Web approximately twelve hours after data recording. Disturbances in the microgravity environment as recorded by these instruments are grouped by source type: Orbiter systems, on-board activities, payload operations, and unknown sources. The environment related to the Ku-band antenna dither, Orbiter structural modes, attitude deadband collapses, water dump operations, crew sleep, and crew exercise was comparable to the effects of these sources on previous Orbiter missions. Disturbances related to operations of the Isothermal Dendritic Growth Experiment and Space Acceleration Measurement Systems that were not observed on previous missions are detailed. The effects of Orbiter cabin and airlock depressurization and extravehicular activities are also reported for the first time. A set of data plots representing the entire mission is included in the CD-ROM version of this report.

Rogers, Melissa J. B.↗

Characterizing Orbital Debris and Spacecrafts Through a Multi-Analytical Approach

Defining the risks present to both crewed and robotic spacecrafts is part of NASA s mission, and is critical to keep these resources out of harms way. Characterizing orbital debris is an essential part of this mission. We present a proof-of-concept study that employs multiple techniques to demonstrate the efficacy of each approach. The targets of this study are IDCSPs (Initial Defense Communications Satellite Program). 35 of these satellites were launched by the US in the mid-1960s and were the first US communications satellites in the GEO regime. They were emplaced in slightly sub-synchronous orbits. These targets were chosen for this proof-of-concept study for the simplicity of their observable exterior surfaces. The satellites are 26-sided polygons (86cm in diameter), initially spin-stabilized and covered on all sides in solar panels. Data presented here include: (a) visible broadband photometry (Johnson B and Cousins R bands) taken with the University of Michigan s 0.6-m aperture Curtis-Schmidt telescope MODEST (for Michigan Orbital DEbris Survey Telescope) in Chile in November, 2011, (b) laboratory broadband photometry (Johnson BV Cousins RI) of solar cells, obtained using the Optical Measurements Center (OMC) at NASA/JSC (see Cowardin et al., this meeting for more details), (c) visible-band spectra taken using the Magellan 6.5m Baade Telescope at Las Campanas Observatory in Chile in March, 2012 (see also Seitzer et al., this meeting), and (d) visible-band laboratory spectra of solar cells using a Field Spectrometer. Color-color plots using broadband photometry (e.g. B-R vs. R-I) demonstrate that different material types fall into distinct areas on the plots (Cowardin, AMOS 2010). Spectra will be binned in wavelength to compare with photometry results and plotted on the same graph for comparison. This allows us to compare lab data with telescopic data, and photometric results with spectroscopic results. In addition, the spectral response of solar cells in the visible wavelength regime varies from relatively flat (modern black solar cells with uniform albedo as a function of wavelength) to older solar cells whose reflectivity is sharply peaked in the blue (similar to the IDCSP solar cells). With a target like IDCSPs, the material type is known a priori. Therefore, this study will also be used to determine whether laboratory spectra of pre-launch (pristine) solar cells differ from the telescopic spectra of IDCSPs that have been exposed to the harsh environment of space for ~45 years to investigate whether space weathering effects are evident.

Lederer, S. M.↗

SATPLOT for Analysis of SECCHI Heliospheric Imager Data

Determining trajectories of solar transients such as coronal mass ejections is not always easy. White light images from SECCHI's (Sun Earth Connection Coronal and Heliospheric Investigation) heliospheric imagers are difficult to interpret because they represent a line-of-sight projection of optically thin solar wind structures. A structure's image by itself gives no information about its angle of propagation relative to the Sunspacecraft line, and an image may show a superposition of several structures, all propagating at different angles. Analyzing SECCHI heliospheric imager data using plots of elongation (angle from the Sun) versus time at fixed position angle (aka Jplots ) has proved extremely useful in understanding the observed solar wind structures. This technique has been used to study CME (coronal mass ejection) propagation, CIRs (corotating interaction regions), and blobs. SATPLOT software was developed to create and analyze such elongation versus time plots. The tool uses a library of cylindrical maps of the data for each spacecraft s panoramic field-of-view. Each map includes data from three SECCHI white-light telescopes (the COR2 coronagraph and both heliospheric imagers) at one time for one spacecraft. The maps are created using a Plate Carree projection, optimized for creating the elongation versus time plots. The tool can be used to analyze the observed tracks of features seen in the maps, and the tracks are then used to extract information, for example, on the angle of propagation of the feature.

Hall, Jeffrey R.↗

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods.

Morton, D. C.↗

An Approximate Solution and Master Curves for Buckling of Symmetrically Laminated Composite Cylinders

Nondimensional linear-bifurcation buckling equations for balanced, symmetrically laminated cylinders with negligible shell-wall anisotropies and subjected to uniform axial compression loads are presented. These equations are solved exactly for the practical case of simply supported ends. Nondimensional quantities are used to characterize the buckling behavior that consist of a stiffness-weighted length-to-radius parameter, a stiffness-weighted shell-thinness parameter, a shell-wall nonhomogeneity parameter, two orthotropy parameters, and a nondimensional buckling load. Ranges for the nondimensional parameters are established that encompass a wide range of laminated-wall constructions and numerous generic plots of nondimensional buckling load versus a stiffness-weighted length-to-radius ratio are presented for various combinations of the other parameters. These plots are expected to include many practical cases of interest to designers. Additionally, these plots show how the parameter values affect the distribution and size of the festoons forming each response curve and how they affect the attenuation of each response curve to the corresponding solution for an infinitely long cylinder. To aid in preliminary design studies, approximate formulas for the nondimensional buckling load are derived, and validated against the corresponding exact solution, that give the attenuated buckling response of an infinitely long cylinder in terms of the nondimensional parameters presented herein. A relatively small number of "master curves" are identified that give a nondimensional measure of the buckling load of an infinitely long cylinder as a function of the orthotropy and wall inhomogeneity parameters. These curves reduce greatly the complexity of the design-variable space as compared to representations that use dimensional quantities as design variables. As a result of their inherent simplicity, these master curves are anticipated to be useful in the ongoing development of buckling-design technology.

Nemeth, Michael P.↗

Combined Use of Airborne Lidar and DBInSAR Data to Estimate LAI in Temperate Mixed Forests

The objective of this study was to determine whether leaf area index (LAI) in temperate mixed forests is best estimated using multiple-return airborne laser scanning (lidar) data or dual-band, single-pass interferometric synthetic aperture radar data (from GeoSAR) alone, or both in combination. In situ measurements of LAI were made using the LiCor LAI-2000 Plant Canopy Analyzer on 61 plots (21 hardwood, 36 pine, 4 mixed pine hardwood; stand age ranging from 12-164 years; mean height ranging from 0.4 to 41.2 m) in the Appomattox-Buckingham State Forest, Virginia, USA. Lidar distributional metrics were calculated for all returns and for ten one meter deep crown density slices (a new metric), five above and five below the mode of the vegetation returns for each plot. GeoSAR metrics were calculated from the X-band backscatter coefficients (four looks) as well as both X- and P-band interferometric heights and magnitudes for each plot. Lidar metrics alone explained 69% of the variability in LAI, while GeoSAR metrics alone explained 52%. However, combining the lidar and GeoSAR metrics increased the R2 to 0.77 with a CV-RMSE of 0.42. This study indicates the clear potential for X-band backscatter and interferometric height (both now available from spaceborne sensors), when combined with small-footprint lidar data, to improve LAI estimation in temperate mixed forests.

leaf area index↗

Cara Status and Upcoming Enhancements

RIC Miss Values in Summary TableTabular presentation of miss vector in Summary Section RIC Uncertainty Values in Details SectionNumerical presentation of miss component uncertainty values in Details SectionGreen Events with Potentially Maneuverable Secondary ObjectsAll potentially maneuverable secondary objects will be reported out to 7-days prior to TCA for LEO events and 10-days for NONLEO events, regardless of risk (relates to MOWG Action Item 1309-11) All green events with potentially active secondary objects included in Summary ReportsAllows more time for contacting other OOBlack Box FixSometimes a black square appeared in the summary report where the ASW RIC time history plot should beAppendix Orbit RegimeMission Name MismatchPc 0 Plotting BugAll Pc points less than 1e-10 (zero) are now plotted as 1e-10 (instead of not at all)Maneuver Indication FixManeuver indicator now present even if maneuver was in the past.

Operations↗

Measuring Polanyi Potentials for Chemsorb 1000 and Chemsorb 3800

Polanyi adsorption potential plots are used to predict the adsorptive capacities of volatile organic compounds onto activated carbons. The design and construction of a test rig for measuring equilibrium adsorption capacities suitable for constructing Polanyi adsorption potential plots for candidate sorbents suitable for use in ECLS systems is presented. The adsorptive capacities of Chemsorb(TradeMark) 1000 and Chemsorb(TradeMark) 800 for ethanol and acetone were measured. The capacities and Polanyi adsorption potential plots for these commercially-available sorbents were compared to that of Barnebey Sutcliffe Type 3032, an acid-impregnated activated carbon utilized aboard the International Space Station.

Chemsorb 3800↗

Automated ISS Flight Utilities

During my internship at NASA Johnson Space Center, I worked in the Space Radiation Analysis Group (SRAG), where I was tasked with a number of projects focused on the automation of tasks and activities related to the operation of the International Space Station (ISS). As I worked on a number of projects, I have written short sections below to give a description for each, followed by more general remarks on the internship experience. My first project is titled "General Exposure Representation EVADOSE", also known as "GEnEVADOSE". This project involved the design and development of a C++/ ROOT framework focused on radiation exposure for extravehicular activity (EVA) planning for the ISS. The utility helps mission managers plan EVAs by displaying information on the cumulative radiation doses that crew will receive during an EVA as a function of the egress time and duration of the activity. SRAG uses a utility called EVADOSE, employing a model of the space radiation environment in low Earth orbit to predict these doses, as while outside the ISS the astronauts will have less shielding from charged particles such as electrons and protons. However, EVADOSE output is cumbersome to work with, and prior to GEnEVADOSE, querying data and producing graphs of ISS trajectories and cumulative doses versus egress time required manual work in Microsoft Excel. GEnEVADOSE automates all this work, reading in EVADOSE output file(s) along with a plaintext file input by the user providing input parameters. GEnEVADOSE will output a text file containing all the necessary dosimetry for each proposed EVA egress time, for each specified EVADOSE file. It also plots cumulative dose versus egress time and the ISS trajectory, and displays all of this information in an auto-generated presentation made in LaTeX. New features have also been added, such as best-case scenarios (egress times corresponding to the least dose), interpolated curves for trajectories, and the ability to query any time in the EVADES output. As mentioned above, GEnEVADOSE makes extensive use of ROOT version 6, the data analysis framework developed at the European Organization for Nuclear Research (CERN), and the code is written to the C++11 standard (as are the other projects). My second project is the Automated Mission Reference Exposure Utility (AMREU).Unlike GEnEVADOSE, AMREU is a combination of three frameworks written in both Python and C++, also making use of ROOT (and PyROOT). Run as a combination of daily and weekly cron jobs, these macros query the SRAG database system to determine the active ISS missions, and query minute-by-minute radiation dose information from ISS-TEPC (Tissue Equivalent Proportional Counter), one of the radiation detectors onboard the ISS. Using this information, AMREU creates a corrected data set of daily radiation doses, addressing situations where TEPC may be offline or locked up by correcting doses for days with less than 95% live time (the total amount time the instrument acquires data) by averaging the past 7 days. As not all errors may be automatically detectable, AMREU also allows for manual corrections, checking an updated plaintext file each time it runs. With the corrected data, AMREU generates cumulative dose plots for each mission, and uses a Python script to generate a flight note file (.docx format) containing these plots, as well as information sections to be filled in and modified by the space weather environment officers with information specific to the week. AMREU is set up to run without requiring any user input, and it automatically archives old flight notes and information files for missions that are no longer active. My other projects involve cleaning up a large data set from the Charged Particle Directional Spectrometer (CPDS), joining together many different data sets in order to clean up information in SRAG SQL databases, and developing other automated utilities for displaying information on active solar regions, that may be used by the space weather environment officers to monitor solar activity. I consulted my mentor Dr. Ryan Rios and Dr. Kerry Lee for project requirements and added features, and ROOT developer Edmond Offermann for advice on using the ROOT library. I also received advice and feedback from Dr. Janet Barzilla of SRAG, who tested my code. Besides these inputs, I worked independently, writing all of the code by myself. The code for all these projects is documented throughout, and I have attempted to write it in a modular format. Assuming that ROOT is updated accordingly, these codes are also Y2038-compliant (and Y10K-compliant). This allows the code to be easily referenced, modified and possibly repurposed for non-ISS missions in the future, should the necessary inputs exist. These projects have taught me a lot about coding and software design - I have become a much more skilled C++ programmer and ROOT user, and I also learned to code in Python and PyROOT (and its advantages and disadvantages compared to C++/ ROOT). Furthermore, I have learned about space radiation and radiation modeling, topics that greatly interest me as I pursue a degree in physics. Working alongside experimental physicists like Dr. Rios, I have developed a greater understanding and appreciation for experimental science, something I have always leaned towards but to which I lacked significant exposure. My work in SRAG has also given me the invaluable opportunity to witness the work environment for physicists at NASA, and what a career in academia may look like at a government laboratory such as NASA Johnson Space Center. As I continue my studies and look forward to graduate school and a future career, this experience at NASA has given me a meaningful and enjoyable opportunity to put my skills to use and see what my future career path might hold.

Offermann, Jan Tuzlic↗

Engine Icing Data - An Analytics Approach

Engine icing researchers at the NASA Glenn Research Center use the Escort data acquisition system in the Propulsion Systems Laboratory (PSL) to generate and collect a tremendous amount of data every day. Currently these researchers spend countless hours processing and formatting their data, selecting important variables, and plotting relationships between variables, all by hand, generally analyzing data in a spreadsheet-style program (such as Microsoft Excel). Though spreadsheet-style analysis is familiar and intuitive to many, processing data in spreadsheets is often unreproducible and small mistakes are easily overlooked. Spreadsheet-style analysis is also time inefficient. The same formatting, processing, and plotting procedure has to be repeated for every dataset, which leads to researchers performing the same tedious data munging process over and over instead of making discoveries within their data. This paper documents a data analysis tool written in Python hosted in a Jupyter notebook that vastly simplifies the analysis process. From the file path of any folder containing time series datasets, this tool batch loads every dataset in the folder, processes the datasets in parallel, and ingests them into a widget where users can search for and interactively plot subsets of columns in a number of ways with a click of a button, easily and intuitively comparing their data and discovering interesting dynamics. Furthermore, comparing variables across data sets and integrating video data (while extremely difficult with spreadsheet-style programs) is quite simplified in this tool. This tool has also gathered interest outside the engine icing branch, and will be used by researchers across NASA Glenn Research Center. This project exemplifies the enormous benefit of automating data processing, analysis, and visualization, and will help researchers move from raw data to insight in a much smaller time frame.

Engine Icing↗

Estimating the Relative Water Content of Leaves in a Cotton Canopy

Remotely sensing plant canopy water status remains a long-term goal of remote sensing research. Established approaches to estimating canopy water status the Crop Water Stress Index, the Water Deficit Index and the Equivalent Water Thickness involve measurements in the thermal or reflective infrared. Here we report plant water status estimates based upon analysis of polarized visible imagery of a cotton canopy measured by ground Multi-Spectral Polarization Imager (MSPI). Such estimators potentially provide access to the plant hydrological photochemistry that manifests scattering and absorption effects in the visible spectral region.Twice during one day, +- 3 hours from solar noon, we collected polarized imagery and relative water content data on a cotton test plot located at the Arid Land Agricultural Research Center, United States Department of Agriculture, Maricopa, AZ. The test plot, a small portion of a large cotton field, contained stressed plants ready for irrigation. The evening prior to data collection we irrigated several rows of plants within the test plot. Thus, ground MSPI imagery from both morning and afternoon included cotton plants with a range of water statuses. Data analysis includes classifying the polarized imagery into sunlit reflecting, sunlit transmitting, shaded foliage and bare soil. We estimate the leaf surface reflection and interior reflection based upon the per pixel polarization and sunview directions. We compare our cotton results with our prior polarization results for corn and soybean leaves measured in the lab and corn leaves measured in the field.

Cotton Canopy↗

Description of the TCERT Vetting Reports for Data Release 25

The Q1Q17 DR25 TCERT Vetting Reports are a collection of plots and diagnostics used by the Threshold Crossing Event Review Team (TCERT) to evaluate threshold crossing events (TCEs). While designation of Kepler Objects of Interest (KOIs) and classification of them as Planet Candidates (PCs) or False Positives (FPs) is completely automated via a robotic vetting procedure (the Robovetter) for the Q1Q17 DR25 planet catalog, as described in Thompson et al. (2017), these reports help to visualize the metrics used by the Robovetter and evaluate those robotic decisions for individual objects. For each Q1Q17 DR25 TCE, these reports include the following products: (a) the DV one-page summary, (b) selected pertinent diagnostics and plots from the full DV report, and (c) additional plots and diagnostics not included in the full DV report, including an alternate means of data detrending.

Kepler Objects of Interest↗

Detection of Vegetation Trends in Highly Variable Environments After Grazing Exclusion in Mongolia

Aims: Environmental variability (e.g. in precipitation) has a large effect on vegetation dynamics, and this often makes it difficult to assess the recovery of vegetation after a disturbance. In this study, we assessed vegetation recovery trends in response to grazing exclusion while considering for the annual environmental variability. Location: Two regions with highly variable precipitation: a steppe near Mandalgobi, in Mongolia's Central Gobi province, and a desert steppe near Bulgan, in Mongolia's South Gobi province. Methods: Changes in vegetation were observed along grazing gradients at the above two sites, and vegetation thresholds were identified. We established reference plots in pre-threshold areas along the grazing gradients. We removed the impact of livestock grazing at various locations along the grazing gradients by establishing exclosures, and investigated vegetation from 2005 to 2013. We developed a smoothed hierarchical model within a Bayesian framework, and examined the effect of grazing exclusion on vegetation, focusing especially on the extent of grass cover recovery. In addition, we compared soil nutrient conditions in the reference plots and inside and outside each exclosure along the grazing gradients. Results: Temporal trends in the cover of perennial grass in each plot inside and outside of the exclosures largely coincided, irrespective of grazing intensity, and exclosure had no effect (Bulgan) or a negative effect (Mandalgobi) on vegetation recovery. Soil nutrient content was not significantly affected by exclosure at a given distance from the grazing source, but decreased significantly with decreasing grazing intensity. Thus, recovery of the land from a post-threshold state may not be apparent even after 9 yr of grazing exclusion in environments with highly variable precipitation. Conclusion: The effect of exclosure duration on perennial grass cover was limited, even after controlling for environmental variability. Once a vegetation threshold has been crossed, merely removing livestock from the landscape may not be sufficient for that area to recover.

Bayesian statistics;Drought;Environmental variabil↗

Remote Sensing of Evapotranspiration over the Central Arizona Irrigation and Drainage District, USA

Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm (millimeters) for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6-8 mm per day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm per day, METRIC 6 mm per day, and VISW 8 mm per day. For alfalfa, the ET values from TSEB were 8.0 mm per day, METRIC 5 mm per day, and VISW 6 mm per day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from minus 10 percent to plus 18 percent, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators - potential ET (ET (sub 0)), FAO-56 ET, and USDA-SW gravimetric-ET - showed still greater deviations, up to 35 percent of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation.

Alfalfa↗

Creating Calibration Curves to Determine Shock Pressure in Clinopyroxene

Impact cratering is an important geological process that occurs on every rocky body in the solar system. It alters the texture and mineralogy of rocks via shock metamorphism. The peak shock pressures experienced by a rock are traditionally evaluated using qualitative optical methods however, quantitative methods do exist. One such method was developed by Uchizono et al., who used X-ray Diffraction (XRD) to measure lattice strain (ε) in several artificially shocked olivine grains using XRD peak broadening as a function of tan θ, where θ is the diffraction angle. They plotted the ε values against the known peak shock pressures experienced by the olivine grains. Using this calibration curve, the precise shock pressure experienced by a grain of olivine can be determined using its measured ε value. Another method was developed by McCausland et al. and Izawa et al., who used in situ XRD to measure strain-related mosaicity (SRM) of olivine in several ordinary chondrites and enstatite in enstatite chondrites, respectively. They plotted these results against the shock stage estimates for these meteorites. Using these plots, meteorites can be assigned to shock stage bins by measuring the SRM of olivine and/or enstatite. Both methods are useful for evaluating shock metamorphism, however, they have limitations. Uchizono et al.’s calibration curve has been successfully applied to martian meteorites, however it can only be applied to olivine-bearing rocks. McCausland et al.’s and Izawa et al.’s SRM method is uncalibrated and is limited to binning meteorites by shock stage. This work aims to expand on both methods by creating calibration curves for clinopyroxene (CPX): one for ε, similar to Uchizono et al.’s calibration curve for olivine, and one for SRM. This will extend the application of shock calibration methods to a greater variety of rock types. Preliminary results are presented herein.

Jenkins, Laura E.↗