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At least 991 records · Page 55

Evaluation of MEMS-Based Wireless Accelerometer Sensors in Detecting Gear Tooth Faults in Helicopter Transmissions

The diagnostics capability of micro-electro-mechanical systems (MEMS) based rotating accelerometer sensors in detecting gear tooth crack failures in helicopter main-rotor transmissions was evaluated. MEMS sensors were installed on a pre-notched OH-58C spiral-bevel pinion gear. Endurance tests were performed and the gear was run to tooth fracture failure. Results from the MEMS sensor were compared to conventional accelerometers mounted on the transmission housing. Most of the four stationary accelerometers mounted on the gear box housing and most of the CI's used gave indications of failure at the end of the test. The MEMS system performed well and lasted the entire test. All MEMS accelerometers gave an indication of failure at the end of the test. The MEMS systems performed as well, if not better, than the stationary accelerometers mounted on the gear box housing with regards to gear tooth fault detection. For both the MEMS sensors and stationary sensors, the fault detection time was not much sooner than the actual tooth fracture time. The MEMS sensor spectrum data showed large first order shaft frequency sidebands due to the measurement rotating frame of reference. The method of constructing a pseudo tach signal from periodic characteristics of the vibration data was successful in deriving a TSA signal without an actual tach and proved as an effective way to improve fault detection for the MEMS.

gears↗

Landing Site Dispersion Analysis and Statistical Assessment for the Mars Phoenix Lander

The Mars Phoenix Lander launched on August 4, 2007 and successfully landed on Mars 10 months later on May 25, 2008. Landing ellipse predicts and hazard maps were key in selecting safe surface targets for Phoenix. Hazard maps were based on terrain slopes, geomorphology maps and automated rock counts of MRO's High Resolution Imaging Science Experiment (HiRISE) images. The expected landing dispersion which led to the selection of Phoenix's surface target is discussed as well as the actual landing dispersion predicts determined during operations in the weeks, days, and hours before landing. A statistical assessment of these dispersions is performed, comparing the actual landing-safety probabilities to criteria levied by the project. Also discussed are applications for this statistical analysis which were used by the Phoenix project. These include using the statistical analysis used to verify the effectiveness of a pre-planned maneuver menu and calculating the probability of future maneuvers.

Bonfiglio, Eugene P.↗

Validating and Verifying Biomathematical Models of Human Fatigue

Airline pilots experience acute and chronic sleep deprivation, sleep inertia, and circadian desynchrony due to the need to schedule flight operations around the clock. This sleep loss and circadian desynchrony gives rise to cognitive impairments, reduced vigilance and inconsistent performance. Several biomathematical models, based principally on patterns observed in circadian rhythms and homeostatic drive, have been developed to predict a pilots levels of fatigue or alertness. These models allow for the Federal Aviation Administration (FAA) and commercial airlines to make decisions about pilot capabilities and flight schedules. Although these models have been validated in a laboratory setting, they have not been thoroughly tested in operational environments where uncontrolled factors, such as environmental sleep disrupters, caffeine use and napping, may impact actual pilot alertness and performance. We will compare the predictions of three prominent biomathematical fatigue models (McCauley Model, Harvard Model, and the privately-sold SAFTE-FAST Model) to actual measures of alertness and performance. We collected sleep logs, movement and light recordings, psychomotor vigilance task (PVT), and urinary melatonin (a marker of circadian phase) from 44 pilots in a short-haul commercial airline over one month. We will statistically compare with the model predictions to lapses on the PVT and circadian phase. We will calculate the sensitivity and specificity of each model prediction under different scheduling conditions. Our findings will aid operational decision-makers in determining the reliability of each model under real-world scheduling situations.

fatigue↗

Bayesian Revision of Residual Detection Power

This paper addresses some issues with quality assessment and quality assurance in response surface modeling experiments executed in wind tunnels. The role of data volume on quality assurance for response surface models is reviewed. Specific wind tunnel response surface modeling experiments are considered for which apparent discrepancies exist between fit quality expectations based on implemented quality assurance tactics, and the actual fit quality achieved in those experiments. These discrepancies are resolved by using Bayesian inference to account for certain imperfections in the assessment methodology. Estimates of the fraction of out-of-tolerance model predictions based on traditional frequentist methods are revised to account for uncertainty in the residual assessment process. The number of sites in the design space for which residuals are out of tolerance is seen to exceed the number of sites where the model actually fails to fit the data. A method is presented to estimate how much of the design space in inadequately modeled by low-order polynomial approximations to the true but unknown underlying response function.

DeLoach, Richard↗

Thermal Hardware for the Thermal Analyst

The presentation will be given at the 26th Annual Thermal Fluids Analysis Workshop (TFAWS 2015) hosted by the Goddard Space Flight Center (GSFC) Thermal Engineering Branch (Code 545). NCTS 21070-1. Most Thermal analysts do not have a good background into the hardware which thermally controls the spacecraft they design. SINDA and Thermal Desktop models are nice, but knowing how this applies to the actual thermal hardware (heaters, thermostats, thermistors, MLI blanketing, optical coatings, etc...) is just as important. The course will delve into the thermal hardware and their application techniques on actual spacecraft. Knowledge of how thermal hardware is used and applied will make a thermal analyst a better engineer.

0000↗

Simulation and Measurement of Stray Light in the CLASP

We are planning an international rocket experiment Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP) is (2015 planned) that Lyman Alpha line polarization spectroscopic observations from the sun. The purpose of this experiment, detected with high accuracy of the linear polarization of the Ly􀉲 lines to 0.1% by using a Hanle effect is to measure the magnetic field of the chromosphere-transition layer directly. For total flux of the sun visible light overwhelmingly larger and about 200 000 times the Ly􀉲 line wavelength region, also hinder to 0.1% of the polarization photometric accuracy achieved in the stray light of slight visible light. Therefore we were first carried out using the illumination design analysis software called stray light simulation CLASP Light Tools. Feature of this simulation, using optical design file (ZEMAX format) and structural design file (STEP format), to reproduce realistic CLASP as possible to calculate machine is that it was stray study. And, at the stage in the actual equipment that made the provisional set of CLASP, actually put sunlight into CLASP using coelostat of National Astronomical Observatory of Japan, was subjected to measurement of stray light (San test). Pattern was not observed in the simulation is observed in the stray light measurement results need arise that measures. However, thanks to the stray light measurement and simulation was performed by adding, it was found this pattern is due to the diffracted light at the slit. Currently, the simulation results is where you have taken steps to reference. In this presentation, we report the stray light simulation and stray light measurement results that we have implemented

CLASP↗

Sensitivity of Water Scarcity Events to ENSO-Driven Climate Variability at the Global Scale

Globally, freshwater shortage is one of the most dangerous risks for society. Changing hydro-climatic and socioeconomic conditions have aggravated water scarcity over the past decades. A wide range of studies show that water scarcity will intensify in the future, as a result of both increased consumptive water use and, in some regions, climate change. Although it is well-known that El Niño- Southern Oscillation (ENSO) affects patterns of precipitation and drought at global and regional scales, little attention has yet been paid to the impacts of climate variability on water scarcity conditions, despite its importance for adaptation planning. Therefore, we present the first global-scale sensitivity assessment of water scarcity to ENSO, the most dominant signal of climate variability. We show that over the time period 1961-2010, both water availability and water scarcity conditions are significantly correlated with ENSO-driven climate variability over a large proportion of the global land area (> 28.1 %); an area inhabited by more than 31.4% of the global population. We also found, however, that climate variability alone is often not enough to trigger the actual incidence of water scarcity events. The sensitivity of a region to water scarcity events, expressed in terms of land area or population exposed, is determined by both hydro-climatic and socioeconomic conditions. Currently, the population actually impacted by water scarcity events consists of 39.6% (CTA: consumption-to-availability ratio) and 41.1% (WCI: water crowding index) of the global population, whilst only 11.4% (CTA) and 15.9% (WCI) of the global population is at the same time living in areas sensitive to ENSO-driven climate variability. These results are contrasted, however, by differences in growth rates found under changing socioeconomic conditions, which are relatively high in regions exposed to water scarcity events. Given the correlations found between ENSO and water availability and scarcity conditions, and the relative developments of water scarcity impacts under changing socioeconomic conditions, we suggest that there is potential for ENSO-based adaptation and risk reduction that could be facilitated by more research on this emerging topic.

risk↗

Health Monitoring Survey of Bell 412EP Transmissions

Health and usage monitoring systems (HUMS) use vibration-based Condition Indicators (CI) to assess the health of helicopter powertrain components. A fault is detected when a CI exceeds its threshold value. The effectiveness of fault detection can be judged on the basis of assessing the condition of actual components from fleet aircraft. The Bell 412 HUMS-equipped helicopter is chosen for such an evaluation. A sample of 20 aircraft included 12 aircraft with confirmed transmission and gearbox faults (detected by CIs) and eight aircraft with no known faults. The associated CI data is classified into "healthy" and "faulted" populations based on actual condition and these populations are compared against their CI thresholds to quantify the probability of false alarm and the probability of missed detection. Receiver Operator Characteristic analysis is used to optimize thresholds. Based on the results of the analysis, shortcomings in the classification method are identified for slow-moving CI trends. Recommendations for improving classification using time-dependent receiver-operator characteristic methods are put forth. Finally, lessons learned regarding OEM-operator communication are presented.

mechanical components↗

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account system integration risks such as those attributable to manufacturing and assembly. These sources often dominate component level risk. While consequence of failure is often understood, using predicted values in a risk model to estimate the probability of occurrence may underestimate the actual risk. Managers and decision makers use the probability of occurrence to influence the determination whether to accept the risk or require a design modification. The actual risk threshold for acceptance may not be fully understood due to the absence of system level test data or operational data. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.↗

Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

aerosols above clouds↗

Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the “Version 2” validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities.

SMAP L4_SM↗

Key Gaps for Enabling Plant Growth in Future Missions

Growing plants to provide food or psychological benefits to crewmembers is a common vision for the future of human spaceflight, often represented in media and in serious concept studies. The complexity of controlled environment agriculture, and plant growth in microgravity have and continue to be the subject of dedicated scientific research. However, actually implementing these systems in a way that will be cost effective, efficient, and sustainable for future space missions is a complex, multi-disciplinary problem. Key questions exist in many areas: human medical research in nutrition and psychology, horticulture, plant physiology and microbiology, multi-phase microgravity fluid physics, hardware design and technology development, and system design, operations and mission planning. This paper describes key knowledge gaps identified by a multi-disciplinary working group within the National Aeronautics and Space Administration (NASA). It also begins to identify solutions to the simpler questions identified by the group based on work initiated in 2017. Growing plants to provide food or psychological benefits to crewmembers is a common vision for the future of human spaceflight, often represented in media and in serious concept studies. The complexity of controlled environment agriculture, and plant growth in microgravity have and continue to be the subject of dedicated scientific research. However, actually implementing these systems in a way that will be cost effective, efficient, and sustainable for future space missions is a complex, multi-disciplinary problem. Key questions exist in many areas: human medical research in nutrition and psychology, horticulture, plant physiology and microbiology, multi-phase microgravity fluid physics, hardware design and technology development, and system design, operations and mission planning. This paper describes key knowledge gaps identified by a multi-disciplinary working group within the National Aeronautics and Space Administration (NASA). It also begins to identify solutions to the simpler questions identified by the group based on work initiated in 2017.

Anderson, Molly↗

A Method for Obtaining High Frequency, Global, IR-Based Convective Cloud Tops for Studies of the TTL

Models of varying complexity that simulate water vapor and clouds in the Tropical Tropopause Layer (TTL) show that including convection directly is essential to properly simulating the water vapor and cloud distribution. In boreal winter, for example, simulations without convection yield a water vapor distribution that is too uniform with longitude, as well as minimal cloud distributions. Two things are important for convective simulations. First, it is important to get the convective cloud top potential temperature correctly, since unrealistically high values (reaching above the cold point tropopause too frequently) will cause excessive hydration of the stratosphere. Second, one must capture the time variation as well, since hydration by convection depends on the local relative humidity (temperature), which has substantial variation on synoptic time scales in the TTL. This paper describes a method for obtaining high frequency (3-hourly) global convective cloud top distributions which can be used in trajectory models. The method uses rainfall thresholds, standard IR brightness temperatures, meteorological temperature analyses, and physically realistic and documented corrections IR brightness temperature corrections to derive cloud top altitudes and potential temperatures. The cloud top altitudes compare well with combined CLOUDSAT and CALIPSO data, both in time-averaged overall vertical and horizontal distributions and in individual cases (correlations of .65-.7). An important finding is that there is significant uncertainty (nearly .5 km) in evaluating the statistical distribution of convective cloud tops even using lidar. Deep convection whose tops are in regions of high relative humidity (such as much of the TTL), will cause clouds to form above the actual convection. It is often difficult to distinguish these clouds from the actual convective cloud due to the uncertainties of evaluating ice water content from lidar measurements. Comparison with models show that calculated cloud top altitudes are generally higher than those calculated by global analyses (e.g., MERRA). Interannual variability in the distribution of convective cloud top altitudes is also investigated.

hydration↗

Simulink(Trademark) Controller for a Reluctance Motor With a Four-Pole Rotor and 36-Tooth Stator

NASA Glenn Research Center has developed a Simulink(Trademark) controller logic for driving a room temperature, 36-teeth stator, four-pole rotor reluctance motor. The Simulink logic was extracted from an existing C++ motor controller that was previously employed to achieve a rotor speed of 3000 rpm. The Simulink controller has additional logic refinements that were not available in past C++ controller, such as the per rev logic component and its frequency filter. The filter provides a more accurate reading of the rotor input signals. The controller is versatile, and with slight modifications, can be used to drive other reluctance motor types incorporating dissimilar stator rotor pole combinations. The original C++ controller was designed with the goal (after appropriate modification) of controlling a future superconducting motor. This superconducting motor will be employed as a test bed for developing other superconducting aviation propulsion motors envisioned for future turbo-electric aircrafts. The Simulink results presented in this paper were generated from simulated rotor inputs. However, in an actual application, these simulated inputs are to be replaced by actual proximity probe signals emanating from D-Space hardware inputs.

Motor Controller↗

In-Flight Performance of the Soft X-Ray Spectrometer Detector System on ASTRO-H

The SXS instrument was launched aboard the Astro-H observatory on February 17, 2016. The SXS spectrometer is based on a high sensitivity x-ray calorimeter detector system that has been successfully deployed in many ground and sub-orbital spectrometers. The instrument was to provide essential diagnostics for nearly every class of x-ray emitting objects from the atmosphere of Jupiter to the outskirts of galaxy clusters, without degradation for spatially extended objects. The SXS detector system consisted of a 36-pixel cryogenic microcalorimeter array operated at a heat sink temperature of 50 mK. In pre-flight testing, the detector system demonstrated a resolving power of better than 1300 at 6 keV with a simultaneous band-pass from below 0.3 keV to above 12 keV with a timing precision better than 100 microsecond. In addition, a solid-state anti-coincidence detector was placed directly behind the detector array for background suppression. The detector error budget included the measured interference from the SXS cooling system and the spacecraft. Additional margin for on-orbit gain-stability, and on-orbit spacecraft interference were also included predicting an on-orbit performance that meets or exceeds the 7 eV FWHM at 6 keV requirement. The actual on-orbit spectral resolution was better than 5 eV FWHM at 6 keV, easily satisfying the instrument requirement. Here we discuss the actual on-orbit performance of the SXS detector system and compare this to performance in pre-flight testing and the on-orbit predictions. We will also discuss the on-orbit gain stability, additional on-orbit interference, and measurements of the on-orbit background.

X-ray astrophysics↗

Qualitative Validation of the IMM Model for ISS and STS Programs

To validate and further improve the Integrated Medical Model (IMM), medical event data were obtained from 32 ISS and 122 STS person-missions. Using the crew characteristics from these observed missions, IMM v4.0 was used to forecast medical events and medical resource utilization. The IMM medical condition incidence values were compared to the actual observed medical event incidence values, and the IMM forecasted medical resource utilization was compared to actual observed medical resource utilization. Qualitative comparisons of these parameters were conducted for both the ISS and STS programs. The results of these analyses will provide validation of IMM v4.0 and reveal areas of the model requiring adjustments to improve the overall accuracy of IMM outputs. This validation effort should result in enhanced credibility of the IMM and improved confidence in the use of IMM as a decision support tool for human space flight.

risk assessment↗

Landsat at 45: How it Changed the Way We See the Earth

On October 24, 1946, more than 10 years before the launch of the first artificial satellite Sputnik, scientists at the White Sands Missile Range in New Mexico placed a camera on top of a captured German V-2 ballistic missile. As the rocket flew to an altitude of about 65 miles - just above the generally recognized border of outer space - the 35-millimeter motion picture camera snapped a frame every one and a half seconds. Minutes later, the missile came crashing back down and slammed into the ground at more than 340 mph, but the film survived and gave us our first glimpse of Earth from space. Earth Resources Technology Satellite aka Landsat It was images like those first grainy black and white pictures and later those taken by America's first astronauts in the 1960's that inspired the development of the Earth Resources Technology Satellite (ERTS). From the unique vantage point of space, we could now observe Earth using a variety of different instruments to monitor changes over time. The ERTS-1 satellite, wisely renamed Landsat-1, was launched aboard a Delta rocket on July 23, 1972, into a Sun-synchronous polar orbit at an altitude of about 560 miles. In this unique orbit, Landsat could observe the same point on the Earth every 18 days, always with the same solar illumination, allowing for precise monitoring of changes on the ground over time. Landsat-1, derived from the highly successful Nimbus weather satellites, carried two instruments that allowed it to take images not only in visible light but also in infrared, well-suited to track changes in vegetation over time. Designed to last only one year, Landsat-1 actually operated for nearly three years, by which time it had been joined in space by Landsat-2, a near identical copy of the original. Since then, ever more sophisticated instruments were flown aboard Landsat-3 through -8, with Landsat-9 planned for launch in 2020, acquiring millions of images of Earth over more than four decades. At first, images from Landsat were processed by NASA and hardcopies sold to users for a fee, a somewhat tedious process. Since 2008, images have been made available to all interested users by the US Geological Survey (USGS) at no cost via the Internet in near real time. So, how can Landsat help? In short, Landsat looks. And looks. And proves Yogi right. Space-based images from Landsat and other similar satellites offer a unique and critical capability to observe land use over time by providing repetitive observations of the Earth otherwise unavailable. The data provided by the images can be used by scientists and politicians to inform wise decisions in areas such as agriculture, climate, ecosystems and biodiversity, energy, forest management, human health, fire, natural disasters, urban growth and water management. This overview article doesn't allow for examples from each of these disciplines, but details can be found at the following website: https://landsat.gsfc.nasa.gov/how_landsat_helps/. One third of the US economy is influenced by climate, weather and natural hazards, providing strong economic incentives to sustain a healthy space-based Earth observation program. One example, however, may be illustrative of how Landsat and other space-based observations can be helpful in monitoring and documenting some effects of global climate change. It had been noted since the 1970's that permafrost in subarctic areas like Siberia was melting at an accelerating rate. It also became apparent that this led to the formation of hundreds of melt lakes and the liberation of large quantities of methane, a gas that in the short-term has more potent greenhouse effects than carbon dioxide. The methane turned the water in these lakes blue, making them easy to track over time by satellite. Additionally, the newly released methane has been carbon dated to tens of thousands of years ago, meaning that it had remained frozen since the last Ice Age and therefore hadn't been accounted for in models of the Earth's overall carbon balance. Release of sufficient methane by an increasingly warming climate could actually cause a positive feedback loop in global warming, melting more permafrost and releasing yet more methane. Further monitoring by Landsat and other platforms will reveal whether this process is reversible or whether we've passed the tipping point. In addition to the highly successful Landsat series of satellites, NASA and other agencies such as the National Oceanic and Atmospheric Administration (NOAA) operate a fleet of other Earth observing platforms, many with more specific research goals such as monitoring sea ice levels or atmospheric carbon content. Several instruments aboard the International Space Station also contribute to this overall effort to better understand short- and long-term changes to the Earth. Many of these missions are guided by the 2009 Decadal Survey published by the National Research Council of the National Academy of Sciences. Europe, Russia and China all see the value of space-based Earth observation by deploying their own fleet of satellites.

Uri, John↗

40 Years of Collecting Martian Meteorites

This year marks the 40th anniversary of the first Martian meteorite found in Antarctica by ANSMET, ALH 77005. Since then, an additional 14 Martian meteorites have been found by the ANSMET team making for a total of 15 Martian meteorites in the Antarctic collection at Johnson Space Center. Of the 15 meteorites, some have been paired so the 15 meteorites actually represent a total of approximately 9 separate meteorites. The first Martian meteorite found by ANSMET was ALH 77005 (482.500 g), a lherzolitic shergottite. When collected, this meteorite was split as a part of the joint expedition with the National Institute of Polar Research (NIPR) Japan. Originally classified as an "achondrite-unique", it was re-classified as a Martian lherzolitic shergottites in 1982 [1]. This meteorite has been allocated to ~125 scientists for research and there are 181.964 g remaining at Johnson Space Center (JSC). Two years later, one of the most significant Martian meteorites of the collection at JSC was found at Elephant Moraine, EET 79001 (7942.000 g), a shergottite. This meteorite is the largest in the Martian collection at JSC and was the largest stony meteorite sample collected during the 1979 season. In addition to its size, this meteorite is of particular interest because it contains a linear contact separating two different igneous lithologies, basaltic and olivine-phyric. EET 79001 has glass inclusions that contain chemical compositions that are proportionally identical to the Martian atmosphere, as measured by the Viking spacecraft [2]. This discovery helped scientists to identify where the "SNC" meteorite suite had originated, and that we actually possessed Martian samples. This meteorite has been allocated to ~195 scientists for research and there are 5304.770 g of sample is available. Five years later, ANSMET found ALH 84001 (1930.900 g), the only Martian orthopyroxenite. This meteorite was initially classified as a diogenite but was reclassified as being a Martian meteorite in 1993 [3,4]. ALH 84001 is known as the "Life on Mars" meteorite, sparked debate about whether it contained evidence of Martian life [5] and significantly influenced the field of astrobiol-ogy. This sample has been allocated to 173 scientists for research and has 1426.694 g remaining at JSC. In 1988, another lherzolitic shergottite was found, LEW 88516, (13.203 g). This meteorite wasn't recognized in the field as an achondrite until it was broken during processing 2 years later. LEW 88516 has been allocated to 43 scientists for research and 5.351 g of this meteorite remains at JSC. Six years later a basaltic shergottite was found in the Queen Alexandra Range, QUE 94201 (12.020 g). This meteorite was believed to be of terrestrial origin until maskelynite was seen in a thin section. QUE 94201 has been allocated to 57 scientists for research and there are 3.629 g of this meteorite left at JSC. In 2003, the NASA Mars Exploration Program joined the ANSMET team with the hopes of finding another Martian mete-orite. During this expedition, MIL 03346 (715.200 g) was found. This meteorite is a nakhlite. MIL 03346 has been allocated to 98 scientists for research and there are 579.046 g of this sample remaining at JSC. Six years later, 3 more meteorites that have been paired with MIL 03346 were found, MIL 090030 (452.630 g), 090032 (532.190 g ) and 090136 (170.980 g). MIL 090030 has been allocated to 21 scientists for research and has 434.420 g remaining at JSC, MIL 090032 has been allocated to 21 scientists for re-search and has 508.710 g remaining at JSC and MIL 090136 has been allocated to 14 scientists for research and has 156.790 g remaining at JSC. During the 2004 expedition, 2 identical meteorites where found together on the ice, RBT 04261 (78.763 g) and RBT 04262 (204.600 g). These paired meteorites are olivine-phyric shergottites. RBT 04261 has been allocated to 33 scientists for research and has 32.335 g remaining at JSC. RBT 04262 has been allocated to 46 scientists for research and has 171.886 g remaining. In 2006, another olivine-phyric shergottite was found, LAR 06319 (78.572 g). This meteorite has 61.414 g remaining at JSC and has been allocated to 39 scientists for research. During the 2012 season, 3 more olivine-phyric shergottites were found at Larkman Nunatak, LAR 12011 (701.170 g), LAR 12095 (133.132 g) and LAR 12240 (57.596 g). LAR 12011 is paired with LAR 06319 and LAR 12095 and LAR 12240 are paired with each other. LAR 12011 has been allocated to 43 scientists for research and there are 685.778 g of LAR 12011 remaining at JSC. LAR 12095 has been allocated to 18 scientists for research and has 119.744 g remaining at JSC. LAR 12240 has been allocated to 10 scientists for research and has 52.231 g remaining at JSC. Martian meteorites are the only samples available from Mars because no mission has returned samples from there to date. All Martian meteorites are crustal rocks with most of them being crystallized magmas, so they are an important source for under-standing Martian geological history and volcanism. The ANSMET program has greatly contributed to the scientific community by collecting these meteorites

Funk, R. C.↗