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269 records · Page 15

Eight Metagenome-Assembled Genomes Provide Evidence for Microbial Adaptation in 20,000- to 1,000,000-Year-Old Siberian Permafrost

Permafrost microbes may be metabolically active in microscopic layers of liquid brines, even in ancient soil. Metagenomics can help discern whether permafrost microbes show adaptations to this environment. Thirty-three metagenome-assembled genomes (MAGs) were obtained from six depths (3.5 m to 20 m) of freshly cored permafrost from the Siberian Kolyma-Indigirka Lowland region. These soils have been continuously frozen for ~20,000 to 1,000,000 years. Eight of these MAGs were ≥80% complete with <10% contamination and were taxonomically identified as Aminicenantes, Atribacteria, Chloroflexi, and Actinobacteria within bacteria and Thermoprofundales within archaea. MAGs from these taxa have been obtained previously from nonpermafrost environments and have been suggested to show adaptations to long-term energy starvation, but they have never been explored in ancient permafrost. The permafrost MAGs had greater proportions in the Clusters of Orthologous Groups (COGs) categories of energy production and conversion and carbohydrate transport and metabolism than did their nonpermafrost counterparts. They also contained genes for trehalose synthesis, thymine metabolism, mevalonate biosynthesis, and cellulose degradation, which were less prevalent in nonpermafrost genomes. Furthermore, many of these genes are involved in membrane stabilization and osmotic stress responses, consistent with adaptation to the anoxic, high-ionic-strength, cold environments of permafrost brine films. Our results suggest that this ancient permafrost contains DNA of high enough quality to assemble MAGs from microorganisms with adaptations to survive long-term freezing in this extreme environment.

54 ENVIRONMENTAL SCIENCES↗

Modeling the Absorbing Aerosol Index

We propose a scheme to model the absorbing aerosol index and improve the biomass carbon inventories by optimizing the difference between TOMS aerosol index (AI) and modeled AI with an inverse model. Two absorbing aerosol types are considered, including biomass carbon and mineral dust. A priori biomass carbon source was generated by Liousse et al [1996]. Mineral dust emission is parameterized according to surface wind and soil moisture using the method developed by Ginoux [2000]. In this initial study, the coupled CCM1 and GRANTOUR model was used to determine the aerosol spatial and temporal distribution. With modeled aerosol concentrations and optical properties, we calculate the radiance at the top of the atmosphere at 340 nm and 380 nm with a radiative transfer model. The contrast of radiance at these two wavelengths will be used to calculate AI. Then we compare the modeled AI with TOMS AI. This paper reports our initial modeling for AI and its comparison with TOMS Nimbus 7 AI. For our follow-on project we will model the global AI with aerosol spatial and temporal distribution recomputed from the IMPACT model and DAO GEOS-1 meteorology fields. Then we will build an inverse model, which applies a Bayesian inverse technique to optimize the agreement of between model and observational data. The inverse model will tune the biomass burning source strength to reduce the difference between modelled AI and TOMS AI. Further simulations with a posteriori biomass carbon sources from the inverse model will be carried out. Results will be compared to available observations such as surface concentration and aerosol optical depth.

Penner, Joyce↗

Perspective on Satellite-Based Land Data Assimilation to Estimate Water Cycle Components in an Era of Advanced Data Availability and Model Sophistication

The beginning of the 21st century is marked by a rapid growth of land surface satellite data and model sophistication. This offers new opportunities to estimate multiple components of the water cycle via satellite-based land data assimilation (DA) across multiple scales. By resolving more processes in land surface models and by coupling the land, the atmosphere, and other Earth system compartments, the observed information can be propagated to constrain additional unobserved variables. Furthermore, access to more satellite observations enables the direct constraint of more and more components of the water cycle that are of interest to end users. However, the finer level of detail in models and data is also often accompanied by an increase in dimensions, with more state variables, parameters, or boundary conditions to estimate, and more observations to assimilate. This requires advanced DA methods and efficient solutions. One solution is to target specific observations for assimilation based on a sensitivity study or coupling strength analysis, because not all observations are equally effective in improving subsequent forecasts of hydrological variables, weather, agricultural production, or hazards through DA. This paper offers a perspective on current and future land DA development, and suggestions to optimally exploit advances in observing and modeling systems.

Data Assimilation↗

Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon

The Weather Research and Forecasting (WRF) model can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations but subjected to uncertainties associated with model physical parameterizations. In this study, we propose a framework to quantify and reduce model physical parameterization uncertainties associated with surface fluxes and L-A coupling. An ensemble of WRF simulations with different physical schemes is used to simulate surface fluxes and land-atmosphere coupling strength over the Amazon region. The physical parameterizations investigated include cloud microphysics (MP), land surface processes (LSM), planetary boundary layer (PBL), surface layer (SL), and cumulus (CU). We perform 120 ensemble simulations using the WRF model and different combinations of six MPs, three LSMs, six PBLs and SLs and three CUs. The measurements from the GoAMAZON field campaign and satellite data are used to evaluate model performance. A Multi-way analysis of variance (ANOVA) approach is applied to quantify the relative importance of different physics processes on L-A coupling. The Tukey’s test is used to sort schemes that have no significant differences into one group. The suite of physics that result in the best simulations of the corresponding variables are selected based on the Taylor skill score. Results show that the relative importance of processes and their interaction vary with the variables of interest. For example, CU was the most important process in modulating soil moisture, 2 m-humidity, latent heat, and net radiation. LSM showed dominant effects on 2 m-temperature and also has the largest impact on sensible heat and the lifting condensation level. The best physical parameterization ensembles show much narrower ranges of the variables of interest than the priori ensemble. Results of this study show the roles of different physical processes in modulating L-A interactions, quantify model uncertainties from physical processes, and provide insights for improving the model physics parameterizations.

Wang, Chen↗

Airborne hyperspectral imaging of cover crops through radiative transfer process-guided machine learning

Cover cropping between cash crop growing seasons is a multifunctional conservation practice. Timely and accurate monitoring of cover crop traits, notably aboveground biomass and nutrient content, is beneficial to agricultural stakeholders to improve management and understand outcomes. Currently, there is a scarcity of spatially and temporally resolved information for assessing cover crop growth. Remote sensing has a high potential to fill this need, but conventional empirical regression operated with coarse-resolution multispectral data has large uncertainties. Therefore, this study utilized airborne hyperspectral imaging techniques and developed new process-guided machine learning approaches (PGML) for cover crop monitoring. Specifically, we deployed an airborne hyperspectral system covering visible to shortwave-infrared wavelengths (400–2400 nm) to acquire high spatial (0.5 m) and spectral (3–5 nm) resolution reflectance over 23 cover crop fields across Central Illinois in March and April of 2021. Airborne hyperspectral surface reflectance with high spectral and spatial resolution can be well matched with field data to quantify cover crop traits. Furthermore, the PGML models were pre-trained by synthetic data from soil-vegetation radiative transfer modeling (one million records), and then fine-tuned with field data of cover crop biomass and nutrient content. Results show that airborne hyperspectral data with PGML can achieve high accuracy to predict cover crop aboveground biomass (R 2 = 0.72, relative RMSE = 15.16%) and nitrogen content (R 2 = 0.69, relative RMSE = 16.59%) through leave-one-field-out cross-validation. Unlike the pure data-driven approach (e.g., partial least-squares regression), PGML incorporated radiative transfer knowledge and obtained higher predictive performance with fewer field data. Meanwhile, with field data for model fine-tuning, PGML predicted biomass more accurately than the inversion of radiative transfer models. Here we also found that the red edge has a high contribution in quantifying aboveground biomass and nitrogen content, followed by green and shortwave spectra. This study demonstrated the first attempt of utilizing hyperspectral remote sensing to accurately quantify cover crop traits. We highlight the strength of PGML in exploiting sensing data to quantify ecosystem variables to advance agroecosystem monitoring for sustainable agricultural management.

60 APPLIED LIFE SCIENCES↗

Atmospheric cycles of nitrogen oxides and ammonia

The atmospheric cycles of nitrogenous trace compounds for the Northern and Southern Hemispheres are discussed. Source strengths and destruction rates for the nitrogen oxides: NO, NO2 and HNO3 -(NOX) and ammonia (NH3) are given as a function of latitude over continents and oceans. The global amounts of NOX-N and NH3-N produced annually in the period 1950 to 1975 (34 + 5 x one trillion g NOx-N/yr and 29 + or - 6 x one trillion g NH3-N/yr) are much less than previously assumed. Globally, natural and anthropogenic emissions are of similar magnitude. The NOx emission from anthropogenic sources is 1.5 times that from natural processes in the Northern Hemisphere, whereas in the Southern Hemisphere, it is a factor of 3 or 4 less. More than 80% of atmospheric ammonia seems to be derived from excrements of domestic animals, mostly by bulk deposition: 24 + or - 9 x one trillion g NO3 -N/yr and 21 + or - 9 x one trillion g NH4+-N/yr. Another fraction may be removed by absorption on vegetation and soils.

Bottger, A.↗

Constitutive and Stability Behavior of Granular Materials Under Very Low Effective Stresses

The study of the behavior of granular materials such as sand is of great importance to the understanding of the response of foundations resting on surface and near-surface soil deposits. A clear understanding of the behavior of such materials can also provide insights into other related issues where low effective stresses are encountered such as liquefaction. The main sources of the constitutive and stability properties of cohesionless granular materials is interparticle friction, which in turn under low confinement stress levels is strongly affected by gravitational body forces under terrestrial (1 gravity) conditions. Under moderate-to-high stress levels, the influence of gravity on the behavior of experiments may not be pronounced and therefore the test results in a terrestrial environment may be acceptable for engineering purposes. However, the conduct of experiments on granular materials under very low stress levels and under quasi-static conditions can only be performed in a microgravity environment. A series of displacement-controlled cyclic triaxial compression experiments were performed in a SPACEHAB module on the Space Shuttle during the STS-79 mission to Mir in September, 1996, and the STS-89 mission in January, 1998. The experiments were conducted on six right cylindrical specimens 75 mm in diameter and 150 mm long at effective confining pressures of 0.05, 0.52 and 1.30 kPa. The results show very high peak strength friction angles in the range of 47.6 to 70.0 degrees, which are mainly due to overconsolidation and grain interlocking effects. It was observed that the residual strength levels were in the same range as that observed at higher confining stress levels. The dilatancy angles were unusually high in the range of 30 to 31 degrees. All specimens display substantial initial stiffnesses and elastic moduli during unloading and reloading events, which are nearly an order of magnitude higher than conventional theories predict. A periodic instability phenomenon which appears to result from buckling of multiple internal arches and columnar systems, augmented by stick-slips was observed in the experiments. Computed Tomography (CT) measurements revealed valuable data about the internal fabric and the specimens deformation patterns. Uniform diffuse bifurcation with multiple radial shear bands was observed in the specimens tested in a microgravity environment. In the axial direction, two major conical surfaces were developed. Spatial nonsymmetrical deformations were observed in specimens tested in terrestrial laboratory.

Alshibli, Khalid A.↗

Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics

Mounting evidence indicates dryland ecosystems play an important role in driving the interannual variability and trend of the terrestrial carbon sink. Nevertheless, our understanding of the seasonal dynamics of dryland ecosystem carbon uptake through photosynthesis [gross primary productivity (GPP)] remains relatively limited due in part to the limited availability of long-term data and unique challenges associated with satellite remote sensing across dryland ecosystems. Here, we comprehensively evaluated longstanding and emerging satellite vegetation proxies in their ability to capture seasonal dryland GPP dynamics. Specifically, we evaluated: 1) reflectance-based proxies normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), near infrared reflectance index (NIR v ), and kernel NDVI (kNDVI) from the MODerate resolution Imaging Spectroradiometer (MODIS); and 2) newly available physiologically-based proxy solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI). As a performance benchmark, we used GPP estimates from a robust network of 21 western United States eddy covariance tower sites that span representative gradients in dryland ecosystem climate and functional composition. We found that NIR v and SIF were the best performing GPP proxies and captured complementary aspects of seasonal GPP dynamics across dryland ecosystem types. NIR v offered better performance than the other proxies across relatively low-productivity, sparsely non-evergreen vegetated sites (R 2 = 0.59 ± 0.13); whereas SIF best captured seasonal dynamics across relatively high-productivity sites, including evergreen-dominated sites (R 2 = 0.74 ± 0.07). Notably, across grass-dominated sites, all reflectance-based proxies (NDVI, SAVI, NIRv and kNDVI) showed significant seasonal bias (hysteresis) that strengthened with the total fraction of woody vegetation cover, likely due to seasonal patterns in woody vegetation reflectance that are unrelated to or decoupled from GPP. In conclusion, future efforts to fully integrate the complementary strengths of NIR v and SIF could significantly improve our understanding and representation of dryland GPP dynamics in satellite-based models.

54 ENVIRONMENTAL SCIENCES↗

A Multi-Satellite Assimilation and Modeling Platform to Construct a Global and Complete view of the Hydrologic Cycle

What captivates me about the research field of satellite remote sensing of the earth system science is the opportunity to help human beings by addressing challenging questions related to the current and future availability of natural resources for domestic, agricultural, and industrial needs. For example, a continuously varying climate poses a threat to the water resource, not only in developing countries, but also in economically well-developed regions, creating the urgent need to characterize and predict its spatial and temporal availability. Specifically, my curiosity is driven by the challenge of merging cutting-edge space technology and earth observations (i.e., remote sensing) with state-of-the-art models for the purpose of improving our scientific knowledge about the variability and the change of the hydrologic cycle.The only practical way to observe the land surface processes (e.g., hydrologic cycle) on continental to global scales is via satellite remote sensing. Though remote sensing can make spatially comprehensive measurements of various components of the land surface system, it cannot provide direct information on the entire system, and the measurements represent only a snapshot in time. Physical based models may be used to continuously predict the temporal and spatial earth processes, but these predictions are often poor, due to model initialization, parameter and meteorological forcing errors, and inadequate model physics and/or resolution. Thus, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses of both) to provide a superior land surface state estimate. This is the goal of land surface data assimilation. Data assimilation provides a better estimate of the environmental states than either models or observations could individually do. The broad concept of data assimilation can be applied to various disciplines such as hydrology, ecology, environmental hazards, agriculture and economy.My research is targeted to integrating multiple satellite information having multi-sensor and multi-resolution assimilation within today's state-of-the-art hydrologic models. Multi-sensor and multi-resolution assimilation techniques represent a necessary milestone in future earth science applications because they offer the capability of comprehensively integrating disparate types of earth observations via deep-learning techniques. A multi-satellite assimilation and modeling platform will ultimately provide a robust and complete dataset to more fully understand earth's dynamics. In fact, the multi-satellite assimilation platforms build a comprehensive description of the earth processes that is geared toward accurately representing the complexity of natural and anthropogenic interactions in land surface processes. Most importantly, these platforms are suitable as decision support tools for applications across different aspects of earth system science.My recent work has focused on recent multi-sensor data assimilation techniques targeted at improving snow, soil moisture, groundwater, and terrestrial water storage hydrological states.

Girotto, Manuela↗

Low-Cost Evaluation of EO-1 Hyperion and ALI for Detection and Biophysical Characterization of Forest Logging in Amazonia (NCC5-481)

Major uncertainties exist regarding the rate and intensity of logging in tropical forests worldwide: these uncertainties severely limit economic, ecological, and biogeochemical analyses of these regions. Recent sawmill surveys in the Amazon region of Brazil show that the area logged is nearly equal to total area deforested annually, but conversion of survey data to forest area, forest structural damage, and biomass estimates requires multiple assumptions about logging practices. Remote sensing could provide an independent means to monitor logging activity and to estimate the biophysical consequences of this land use. Previous studies have demonstrated that the detection of logging in Amazon forests is difficult and no studies have developed either the quantitative physical basis or remote sensing approaches needed to estimate the effects of various logging regimes on forest structure. A major reason for these limitations has been a lack of sufficient, well-calibrated optical satellite data, which in turn, has impeded the development and use of physically-based, quantitative approaches for detection and structural characterization of forest logging regimes. We propose to use data from the EO-1 Hyperion imaging spectrometer to greatly increase our ability to estimate the presence and structural attributes of selective logging in the Amazon Basin. Our approach is based on four "biogeophysical indicators" not yet derived simultaneously from any satellite sensor: 1) green canopy leaf area index; 2) degree of shadowing; 3) presence of exposed soil and; 4) non-photosynthetic vegetation material. Airborne, field and modeling studies have shown that the optical reflectance continuum (400-2500 nm) contains sufficient information to derive estimates of each of these indicators. Our ongoing studies in the eastern Amazon basin also suggest that these four indicators are sensitive to logging intensity. Satellite-based estimates of these indicators should provide a means to quantify both the presence and degree of structural disturbance caused by various logging regimes. Our quantitative assessment of Hyperion hyperspectral and ALI multi-spectral data for the detection and structural characterization of selective logging in Amazonia will benefit from data collected through an ongoing project run by the Tropical Forest Foundation, within which we have developed a study of the canopy and landscape biophysics of conventional and reduced-impact logging. We will add to our base of forest structural information in concert with an EO-1 overpass. Using a photon transport model inversion technique that accounts for non-linear mixing of the four biogeophysical indicators, we will estimate these parameters across a gradient of selective logging intensity provided by conventional and reduced impact logging sites. We will also compare our physical ly-based approach to both conventional (e.g., NDVI) and novel (e.g., SWIR-channel) vegetation indices as well as to linear mixture modeling methods. We will cross-compare these approaches using Hyperion and ALI imagers to determine the strengths and limitations of these two sensors for applications of forest biophysics. This effort will yield the first physical ly-based, quantitative analysis of the detection and intensity of selective logging in Amazonia, comparing hyperspectral and improved multi-spectral approaches as well as inverse modeling, linear mixture modeling, and vegetation index techniques.

Asner, Gregory P.↗

A season of heat, water vapor, total hydrocarbon, and ozone fluxes at a subarctic fen

High-latitude environments are thought to play several critical roles in the global balance of radiatively active trace gases. Adequate documentation of the source and sink strengths for trace gases requires long time series of detailed measurements, including heat and moisture budgets. A fen near Schefferville, Quebec, was instrumented during the summer of 1990 for the measurement of the surface energy, radiation, and moisture balances as well as for eddy correlation estimates of ozone and methane flux. Despite the limited fetch at this site, analysis of the tower flux 'footprint' indicates that at least 80% of the flux observed originates from sources within the fen. Sensible heat fluxes averaged 25% of the daytime net radiation at the site, while the latent heat flux, determined from the energy balance, was 63%; the Bowen ratio varied from 0.2 to 0.8 from day to day, without a seasonal trend to the variation. The competing effects of rooted macrophyte development (with concomitant effects on roughness and transpiration) and the normal shift in synoptic pattern around day 200 to warm, dry conditions results in a lack of net seasonal effect on the energy partitioning. Over the period from days 170 to 230, the evaporation (167 mm) was double the rainfall, while the decline in water level was 107 mm, leaving a net runoff of 0.44 mm/d. The total hydrocarbon flux was 75-120 mg m(exp -2)/d, following a diurnal pattern similar to heat or moisture flux, while the daytime ozone flux was about -1.11 x 10(exp 11) molecules cm(exp -2)/s. A period near the end of the experiment, during week 30, produced the strongest total hydrocarbon flux, associated with warmer deep (1 m) soil temperatures, lower fen water levels, and the late summer shift in wind direction at that time. An early summer 'flush' of total hydrocarbon was not observed.

Moore, Kathleen E.↗

High-Pressure Lightweight Thrusters

Returning samples of Martian soil and rock to Earth is of great interest to scientists. There were numerous studies to evaluate Mars Sample Return (MSR) mission architectures, technology needs, development plans, and requirements. The largest propulsion risk element of the MSR mission is the Mars Ascent Vehicle (MAV). Along with the baseline solid-propellant vehicle, liquid propellants have been considered. Similar requirements apply to other lander ascent engines and reaction control systems. The performance of current state-ofthe- art liquid propellant engines can be significantly improved by increasing both combustion temperature and pressure. Pump-fed propulsion is suggested for a single-stage bipropellant MAV. Achieving a 90-percent stage propellant fraction is thought to be possible on a 100-kg scale, including sufficient thrust for lifting off Mars. To increase the performance of storable bipropellant rocket engines, a high-pressure, lightweight combustion chamber was designed. Iridium liner electrodeposition was investigated on complex-shaped thrust chamber mandrels. Dense, uniform iridium liners were produced on chamber and cylindrical mandrels. Carbon/carbon composite (C/C) structures were braided over iridium-lined mandrels and densified by chemical vapor infiltration. Niobium deposition was evaluated for forming a metallic attachment flange on the carbon/ carbon structure. The new thrust chamber was designed to exceed state-of-the-art performance, and was manufactured with an 83-percent weight savings. High-performance C/Cs possess a unique set of properties that make them desirable materials for high-temperature structures used in rocket propulsion components, hypersonic vehicles, and aircraft brakes. In particular, more attention is focused on 3D braided C/Cs due to their mesh-work structure. Research on the properties of C/Cs has shown that the strength of composites is strongly affected by the fiber-matrix interfacial bonding, and that weakening interface realizes pseudo-plastic behavior with significant increase in the tensile strength. The investigation of high-temperature strength of C/Cs under high-rate heating (critical for thrust chambers) shows that tensile and compression strength increases from 70 MPa at room temperature to 110 MPa at 1,773 K, and up to 125 MPa at 2,473 K. Despite these unique properties, the use of C/Cs is limited by its high oxidation rate at elevated temperatures. Lining carbon/carbon chambers with a thin layer of iridium or iridium and rhenium is an innovative way to use proven refractory metals and provide the oxidation barrier necessary to enable the use of carbon/ carbon composites. Due to the lower density of C/Cs as compared to SiC/SiC composites, an iridium liner can be added to the C/C structure and still be below the overall thruster weight. Weight calculations show that C/C, C/C with 50 microns of Ir, and C/C with 100 microns of Ir are of less weight than alternative materials for the same construction.

Holmes, Richard↗

Hayabusa Recovery, Curation and Preliminary Sample Analysis: Lessons Learned from Recent Sample Return Mission

I describe lessons learned from my participation on the Hayabusa Mission, which returned regolith grains from asteroid Itokawa in 2010 [1], comparing this with the recently returned Stardust Spacecraft, which sampled the Jupiter Family comet Wild 2. Spacecraft Recovery Operations: The mission Science and Curation teams must actively participate in planning, testing and implementing spacecraft recovery operations. The crash of the Genesis spacecraft underscored the importance of thinking through multiple contingency scenarios and practicing field recovery for these potential circumstances. Having the contingency supplies on-hand was critical, and at least one full year of planning for Stardust and Hayabusa recovery operations was necessary. Care must be taken to coordinate recovery operations with local organizations and inform relevant government bodies well in advance. Recovery plans for both Stardust and Hayabusa had to be adjusted for unexpectedly wet landing site conditions. Documentation of every step of spacecraft recovery and deintegration was necessary, and collection and analysis of launch and landing site soils was critical. We found the operation of the Woomera Text Range (South Australia) to be excellent in the case of Hayabusa, and in many respects this site is superior to the Utah Test and Training Range (used for Stardust) in the USA. Recovery operations for all recovered spacecraft suffered from the lack of a hermetic seal for the samples. Mission engineers should be pushed to provide hermetic seals for returned samples. Sample Curation Issues: More than two full years were required to prepare curation facilities for Stardust and Hayabusa. Despite this seemingly adequate lead time, major changes to curation procedures were required once the actual state of the returned samples became apparent. Sample databases must be fully implemented before sample return for Stardust we did not adequately think through all of the possible sub sampling and analytical activities before settling on a database design - Hayabusa has done a better job of this. Also, analysis teams must not be permitted to devise their own sample naming schemes. The sample handling and storage facilities for Hayabusa are the finest that exist, and we are now modifying Stardust curation to take advantage of the Hayabusa facilities. Remote storage of a sample subset is desirable. Preliminary Examination (PE) of Samples: There must be some determination of the state and quantity of the returned samples, to provide a necessary guide to persons requesting samples and oversight committees tasked with sample curation oversight. Hayabusa s sample PE, which is called HASPET, was designed so that late additions to the analysis protocols were possible, as new analytical techniques became available. A small but representative number of recovered grains are being subjected to in-depth characterization. The bulk of the recovered samples are being left untouched, to limit contamination. The HASPET plan takes maximum advantage of the unique strengths of sample return missions

Zolensky, Michael E.↗

Improved Calibration of Reflectance Data from the LRO Lunar Orbiter Laser Altimeter (LOLA) and Implications for Space Weathering

The Lunar Orbiter Laser Altimeter (LOLA) experiment on Lunar Reconnaissance Orbiter (LRO) is a laser altimeter that also measures the strength of the return pulse from the lunar surface. These data have been used to estimate the reflectance of the lunar surface, including regions lacking direct solar illumination. A new calibration of these data is presented that features lower uncertainties overall and more consistent results in the polar regions. We use these data, along with newly available maps of the distribution of lunar maria, also derived from LRO instrument data, to investigate a newly discovered dependence of the albedo of the lunar maria on latitude (Hemingway et al., [2015]). We confirm that there is an increase in albedo with latitude in the lunar maria, and confirm that this variation is not an artifact arising from the distribution of compositions within the lunar maria, using data from the Lunar Prospector Neutron Spectrometer. Radiative transfer modeling of the albedo dependence within the lunar maria is consistent with the very weak to absent dependence of albedo on latitude in the lunar highlands; the lower abundance of the iron source for space weathering products in the lunar highlands weakens the latitude dependence to the extent that it is only weakly detectable in current data. In addition, photometric mod- els and normalization may take into account the fact that the lunar albedo is latitude dependent, but this dependence can cause errors in normalized reflectance of at most 2% for the majority of near-nadir geometries. We also investigate whether the latitude dependent albedo may have obscured detection of small mare deposits at high latitudes. We find that small regions at high latitudes with low roughness similar to the lunar maria are not mare deposits that may have been misclassified owing to high albedos imposed by the latitude dependence. Finally, we suggest that the only modest correlations among space weathering indicators defined for the lunar samples may be due to mixing of soils from distinct latitudes.

Lemelin, M.↗

Kennedy Space Center: Swamp Works

When I began my internship with the Granular Mechanics and Regolith Operations laboratory (GMRO), also known as Swamp Works, I was given the unique opportunity to shadow many teams working on various projects, and decide what projects I wanted to take part in. Before I go into details of my experiences at Swamp Works, I would like to take a moment to explain what I discovered Swamp Works to be. Swamp Works is a family of hardworking, dedicated, and driven people from various backgrounds and skill sets. These people all work to advance technologies and make science fiction science fact through means of rapid prototyping. They support and encourage failure as an option when learning new things, as long as lesson learned from said failure. In fact, their motto states "Fail, Fast, Forward." What this means is, not if but when one fails he or she must do so quickly and spring forward from the failure so that his or her progress is not delayed. With this acceptance, it provided me the confidence to dive into a multitude of projects working in various fields and with a wide range of skill sets. The first project I joined was Badger. My motivation for taking on this project was the opportunity I would have to obtain valuable experience working with 3D modeling and 3D printing technologies. Badger was a digging apparatus to be used in a highly dusty environment in a material known as Regolith. Regolith is a scientific term for the dirt or top soil found on planetary bodies. Regolith contains a large quantity of sediments less than lOppm and as a result poses a challenge of keeping it out of any cracks and crevices. Furthermore, regolith can create high levels of electrostatic energy, which can prove damaging to sensitive electrical hardware. With these characteristics in mind, I decided to take on the task of designing and manufacturing a dust proof cover for the sensitive electrical hardware. When I began this project, I did not have the slightest idea as to how to use 3D modeling software or a means of manufacturing a viable product. As I went along with variants of the design, I became very proficient with a 3D modeling program known as CREO 2.0. Upon completion of my 3D design, I then had the task of manufacturing and having, in my hands, a usable model. To do this I had to work with additive printing technologies also known as 3D printing. Through my experiences working with Badger, I realized that 3D modeling is the focal point in much of engineering. With this in mind, I have embraced this fact and decided to further my experience with this software so that I may become a more valuable asset to any firm later in my career. Mid-way through work with Badger, I picked up another project in which I found much interest. I ha~ the opportunity to work side by side with a materials and composites guru in manufacturing carbon composite coupons (test strips) for performing stress, strain, and sheer analysis on. Being from a surfing, kiteboarding, and other water sport background I have always been interested in board design. With this in mind, it is no wonder why I found interest in such a project. I had the opportunity to refine Mold preparatory, composite layup, and composite curing techniques. Following manufacturing of these composite strips, I then performed various stress tests and logged my results. With these results, future teams could create lighter, stronger, and more cost effective composite structures for use in varieties of applications. After my experiences with materials and composites testing, I have obtained crucial appreciation for detailed documentation and analysis that material sciences involve. However, as interesting as composite materials testing has been, I do not feel this is where my future career lies. Another, more on the side, project I have been involved in is building a 626 cubic foot regolith containment chamber for doing full scale testing of robotic systems. This chamber is built of high strength aluminum scaffold materials, 80/20, and massive panels of Lexan. Once the chamber is completed, it is be filled with 120 tons of regolith and dubbed the largest regolith test chamber in the world. Through my experiences with building "Big Bin" as we called it, I discovered my demand for engaging and hands on activities. Through all of my incredible experiences working with the Swamp Works at Kennedy Space Center; I have obtained crucial knowledge, insights, and experiences that have fuelled, shaped, and will continue to drive me toward my ultimate goal of obtaining not only a degree in Engineering, but obtaining a job that I can call a career. I want to give much thanks to all of those who mentored me along my journey, and to all who made this opportunity a reality.

DeFilippo, Anthony Robert↗

Digital Beamforming Scatterometer

This paper discusses scatterometer measurements collected with multi-mode Digital Beamforming Synthetic Aperture Radar (DBSAR) during the SMAP-VEX 2008 campaign. The 2008 SMAP Validation Experiment was conducted to address a number of specific questions related to the soil moisture retrieval algorithms. SMAP-VEX 2008 consisted on a series of aircraft-based.flights conducted on the Eastern Shore of Maryland and Delaware in the fall of 2008. Several other instruments participated in the campaign including the Passive Active L-Band System (PALS), the Marshall Airborne Polarimetric Imaging Radiometer (MAPIR), and the Global Positioning System Reflectometer (GPSR). This campaign was the first SMAP Validation Experiment. DBSAR is a multimode radar system developed at NASA/Goddard Space Flight Center that combines state-of-the-art radar technologies, on-board processing, and advances in signal processing techniques in order to enable new remote sensing capabilities applicable to Earth science and planetary applications [l]. The instrument can be configured to operate in scatterometer, Synthetic Aperture Radar (SAR), or altimeter mode. The system builds upon the L-band Imaging Scatterometer (LIS) developed as part of the RadSTAR program. The radar is a phased array system designed to fly on the NASA P3 aircraft. The instrument consists of a programmable waveform generator, eight transmit/receive (T/R) channels, a microstrip antenna, and a reconfigurable data acquisition and processor system. Each transmit channel incorporates a digital attenuator, and digital phase shifter that enables amplitude and phase modulation on transmit. The attenuators, phase shifters, and calibration switches are digitally controlled by the radar control card (RCC) on a pulse by pulse basis. The antenna is a corporate fed microstrip patch-array centered at 1.26 GHz with a 20 MHz bandwidth. Although only one feed is used with the present configuration, a provision was made for separate corporate feeds for vertical and horizontal polarization. System upgrades to dual polarization are currently under way. The DBSAR processor is a reconfigurable data acquisition and processor system capable of real-time, high-speed data processing. DBSAR uses an FPGA-based architecture to implement digitally down-conversion, in-phase and quadrature (I/Q) demodulation, and subsequent radar specific algorithms. The core of the processor board consists of an analog-to-digital (AID) section, three Altera Stratix field programmable gate arrays (FPGAs), an ARM microcontroller, several memory devices, and an Ethernet interface. The processor also interfaces with a navigation board consisting of a GPS and a MEMS gyro. The processor has been configured to operate in scatterometer, Synthetic Aperture Radar (SAR), and altimeter modes. All the modes are based on digital beamforming which is a digital process that generates the far-field beam patterns at various scan angles from voltages sampled in the antenna array. This technique allows steering the received beam and controlling its beam-width and side-lobe. Several beamforming techniques can be implemented each characterized by unique strengths and weaknesses, and each applicable to different measurement scenarios. In Scatterometer mode, the radar is capable to.generate a wide beam or scan a narrow beam on transmit, and to steer the received beam on processing while controlling its beamwidth and side-lobe level. Table I lists some important radar characteristics

Rincon, Rafael F.↗

Local adaptation of both plant and pathogen: an arms‐race compromise in switchgrass rust

In coevolving species, parasites locally adapt to host populations as hosts locally adapt to resist parasites. Parasites often outpace host local adaptation since they have rapid life cycles, but host diversity, the strength of selection, and external environmental influence can result in complex outcomes. To better understand local adaptation in host–parasite systems, we examined locally adapted switchgrass (Panicum virgatum), and its leaf rust pathogen (Puccinia novopanici) across a latitudinal range in North America. We grew switchgrass genotypes in 10 replicated multiyear common gardens, measuring rust severity from natural infection in a ‘host reciprocal transplant’ framework for testing local adaptation. We conducted genome-wide association mapping to identify genetic loci associated with rust severity. Genetically differentiated rust populations were locally adapted to northern and southern switchgrass, despite host local adaptation to environmental conditions in the same regions. Rust resistance was polygenic, and distinct loci were associated with rust severity in the north and south. We narrowed a previously identified large-effect quantitative trait locus for rust severity to a candidate YELLOW STRIPE-LIKE gene and linked numerous other loci to defense-related genes. Overall, our results suggest that both hosts and parasites can be simultaneously locally adapted, especially when parasites impose less selection than other environmental factors.

59 BASIC BIOLOGICAL SCIENCES↗