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The MSP 2001 Mars Environmental Compatibility Assessment (MECA)

The Mars Environmental Compatibility Assessment (MECA) will evaluate the Martian environment for soil and dust-related hazards to human exploration as part of the Mars Surveyor Program 2001 Lander. Sponsored by the Human Exploration and Development of Space (HEDS) enterprise, MECA's goal is to evaluate potential geochemical and environmental hazards that may confront future Martian explorers, and to guide HEDS scientists in the development of high fidelity Mars soil simulants. The integrated MECA payload contains a wet-chemistry laboratory, a microscopy station, an electrometer to characterize the electrostatics of the soil and its environment, and arrays of material patches to study the abrasive and adhesive properties of soil grains. The instrument will acquire soil samples with a robotic arm equipped with a camera. MECA will examine surface and subsurface soil and dust in order to characterize particle size, shape, hardness, and also physical characteristics that may provide clues to mineralogy. MECA will characterize soil/water mixtures with respect to pH, redox potential, total dissolved ions, and trace toxins. MECA will determine the nature of electrostatic charging associated with excavation of soil, and the influence of ionizing radiation on material properties. It will also observe natural dust accumulation on engineering materials. To accomplish these objectives, MECA is allocated a mass of 10 kg within an enclosure of 35 x 25 x 15 cm. The Wet Chemistry Laboratory (WCL) consists of four identical cells that will accept samples from surface and subsurface regions accessible to the Lander's robotic arm, mix them with water, and perform extensive analysis of the solution. Ion-selective electrodes and related sensors will evaluate total dissolved solids, redox potential, pH, and the concentration of many soluble ions and gases in wet Martian soil. These electrodes can detect potentially dangerous heavy-metal ions, emitted pathogenic gases, and the soil's corrosive potential. Experiments will include cyclic voltammetry and anodic stripping voltammetry. Complementary to the Viking experiments, the chemical laboratory will characterize the water-soil solution rather than emitted gases. Nonetheless, through analysis of dissolved gases it will be able to replicate many of the Viking observations related to oxidants. MECA's microscopy station combines optical and atomic-force microscopy (AFM) in an actively focused, controlled illumination environment to image particles from millimeters to nanometers in size. Careful selection of substrates allows controlled experiments in adhesion, abrasion, hardness, aggregation, magnetic and other properties. Special tools allow primitive manipulation (brushing and scraping) of samples. Soil particle properties including size, shape, color, hardness, adhesive potential (electrostatic and magnetic), will be determined using an array of sample receptacles and collection substrates. The simple, rugged atomic-force microscope will image in the submicron size range and has the capability of performing a particle-by-particle analysis of the dust and soil. On Earth, the earliest forms of life are preserved as microfossils. The atomic-force microscope will have the required resolution to image down to the scale of terrestrial microfossils and beyond. Mounted on the end of the robot arm, MECA's electrometer actually consists of four types of sensors: an electric field meter, several triboelectricity monitors, an ion gauge, and a thermometer. Tempered only by ultraviolet-light-induced ions and a low-voltage breakdown threshold, the dry, cold, dusty martian environment presents an imposing electrostatic hazard to both robots and humans. The field meter will measure the ambient field on nearby objects while the triboelectric sensors, using identical circuitry, will measure the charge accumulated on test substances as they are dragged through the soil by the arm. The ion chamber, open to the environment, will sense both charged dust and free ions in the air. Over and above the potential threat to electronics, the electrostatic environment holds one of the keys to transport of dust and, consequently, Martian meteorology. Viewed with the robot arm camera, the abrasion and adhesion plates are strategically placed to allow direct observation of the interaction between materials and soils on a macroscopic scale. Materials of graded hardness are placed directly under the robot arm scoop to sense wear and soil hardness. A second array, placed on the lander deck, is deployed after the dust plume of landing has settled. It can be manipulated in a primitive fashion by the arm, first having dirt deposited on it from the scoop and subsequently shaken clean. A third array will passively collect dust from the atmosphere. In addition to objectives related to human exploration, the MECA data set will be rich in information relevant to basic geology, paleoclimate, and exobiology issues. To understand both contemporaneous and ancient processes on Mars, the mineralogy, petrology, and reactivity of Martian surface materials should be constrained. The MECA experiment will shed light on these quantities through its combination of chemistry and microscopy. MECA will be capable of measuring the composition of ancient surface water environments, observing microscopic evidence of geological (and biological?) processes, inferring soil and dust transport, comminution and weathering mechanisms, and characterizing soil horizons that might be encountered during excavation.

Hecht, M. H.↗

NASA Advanced Explorations Systems: Advancements in Life Support Systems

The NASA Advanced Exploration Systems (AES) Life Support Systems (LSS) project strives to develop reliable, energy-efficient, and low-mass spacecraft systems to provide environmental control and life support systems (ECLSS) critical to enabling long duration human missions beyond low Earth orbit (LEO). Highly reliable, closed-loop life support systems are among the capabilities required for the longer duration human space exploration missions assessed by NASA's Habitability Architecture Team (HAT). The LSS project is focused on four areas: architecture and systems engineering for life support systems, environmental monitoring, air revitalization, and wastewater processing and water management. Starting with the international space station (ISS) LSS systems as a point of departure (where applicable), the mission of the LSS project is three-fold: 1. Address discrete LSS technology gaps 2. Improve the reliability of LSS systems 3. Advance LSS systems towards integrated testing on the ISS. This paper summarized the work being done in the four areas listed above to meet these objectives. Details will be given on the following focus areas: Systems Engineering and Architecture- With so many complex systems comprising life support in space, it is important to understand the overall system requirements to define life support system architectures for different space mission classes, ensure that all the components integrate well together and verify that testing is as representative of destination environments as possible. Environmental Monitoring- In an enclosed spacecraft that is constantly operating complex machinery for its own basic functionality as well as science experiments and technology demonstrations, it's possible for the environment to become compromised. While current environmental monitors aboard the ISS will alert crew members and mission control if there is an emergency, long-duration environmental monitoring cannot be done in-orbit as current methodologies rely largely on sending environmental samples back to Earth. The LSS project is developing onboard analysis capabilities that will replace the need to return air and water samples from space for ground analysis. Air Revitalization- The air revitalization task is comprised of work in carbon dioxide removal, oxygen generation and recovery and trace contamination and particulate control. The CO2 Removal and associated air drying development efforts under the LSS project are focused both on improving the current SOA technology on the ISS and assessing and examining the viability of other sorbents and technologies available in academia and industry. The Oxygen Generation and Recovery technology development area encompasses several sub-tasks in an effort to supply O2 to the crew at the required conditions, to recover O2 from metabolic CO2, and to recycle recovered O2 back to the cabin environment. Current state-of-the-art oxygen generation systems aboard space station are capable of generating or recovering approximately 40% of required oxygen; for exploration missions this percentage needs to be greatly increased. A spacecraft cabin trace contaminant and particulate control system serves to keep the environment below the spacecraft maximum allowable concentration (SMAC) for chemicals and particulates. Both passive (filters) and active (scrubbers) methods contribute to the overall TC & PC design. Work in the area of trace contamination and particulate control under the LSS project is focused on making improvements to the SOA TC & PC systems on ISS to improve performance and reduce consumables. Wastewater Processing and Water Management- A major goal of the LSS project is the development of water recovery systems to support long duration human exploration beyond LEO. Current space station wastewater processing and water management systems distill urine and wastewater to recover water from urine and humidity condensate in the spacecraft at a approximately 74% recovery rate. For longer, farther missions into deep space, that recovery rate must be greatly increased so that astronauts can journey for months without resupply cargo ships from Earth.

Shull, Sarah A.↗

Leveraging Pre-storm Soil Moisture Estimates for Enhanced Land Surface Model Calibration in Ungauged Hydrologic Basins

Despite long-standing efforts, hydrologists still lack robust tools for calibrating land surface model (LSM) streamflow estimates within ungauged basins. Using surface soil moisture estimates from the Soil Moisture Active Passive Level 4 Soil Moisture (L4_SM) product, precipitation observations, and streamflow gauge measurements for 617 medium-scale (200-10,000 km2) basins in the contiguous United States, we measure the temporal (Spearman) rank correlation between antecedent (i.e., pre-storm) surface soil moisture (ASM) and the storm-scale runoff coefficient (RC; the fraction of storm-scale precipitation accumulation converted into streamflow). In humid and semi-humid basins, this rank correlation is shown to be sufficiently strong to allow for the substitution of storm-scale RC observations (available only in basins that are both lightly regulated and gauged) with high-quality ASM values (available quasi-globally from L4_SM) in streamflow calibration procedures. Using this principle, we define a new, basin-wise LSM streamflow calibration approach based on L4_SM alone and successfully apply it to identify LSM configurations that produce a high rank correlation with observed RC. However, since the approach cannot detect RC bias, it is less successful in identifying LSM configurations with low mean-absolute error. Plain Text Summary Accurately forecasting the fraction of rainfall that runs off into streams, as opposed to infiltrates into the soil, is critical for flash-flood prediction, water-resource monitoring, and tracking the transport of nutrients from agricultural fields into local waterways. Such forecasting is typically performed by hydrologic models that attempt to represent the physical processes responsible for surface runoff generation. However, to provide accurate streamflow forecasts, these models typically need to be calibrated against actual streamflow observations. This is problematic given the relatively poor, and declining, global availability of stream gauges. This paper presents a novel model calibration strategy that uses soil moisture from remote sensing and numerical modeling in place of streamflow observations during calibration. This transition has significant practical advantages because, unlike streamflow observations, the soil moisture data are continuously available across space. Our results demonstrate that this new approach can significantly improve hydrologic models within humid and semi-humid basins lacking sufficient ground-based instrumentation for traditional streamflow calibration.

hydrologic models↗

NASA Tech Briefs, June 2011

Topics covered include: Wind and Temperature Spectrometry of the Upper Atmosphere in Low-Earth Orbit; Health Monitor for Multitasking, Safety-Critical, Real-Time Software; Stereo Imaging Miniature Endoscope; Early Oscillation Detection Technique for Hybrid DC/DC Converters; Parallel Wavefront Analysis for a 4D Interferometer; Schottky Heterodyne Receivers With Full Waveguide Bandwidth; Carbon Nanofiber-Based, High-Frequency, High-Q, Miniaturized Mechanical Resonators; Ultracapacitor-Based Uninterrupted Power Supply System; Coaxial Cables for Martian Extreme Temperature Environments; Using Spare Logic Resources To Create Dynamic Test Points; Autonomous Coordination of Science Observations Using Multiple Spacecraft; Autonomous Phase Retrieval Calibration; EOS MLS Level 1B Data Processing Software, Version 3; Cassini Tour Atlas Automated Generation; Software Development Standard Processes (SDSP); Graphite Composite Panel Polishing Fixture; Material Gradients in Oxygen System Components Improve Safety; Ridge Waveguide Structures in Magnesium-Doped Lithium Niobate; Modifying Matrix Materials to Increase Wetting and Adhesion; Lightweight Magnetic Cooler With a Reversible Circulator; The Invasive Species Forecasting System; Method for Cleanly and Precisely Breaking Off a Rock Core Using a Radial Compressive Force; Praying Mantis Bending Core Breakoff and Retention Mechanism; Scoring Dawg Core Breakoff and Retention Mechanism; Rolling-Tooth Core Breakoff and Retention Mechanism; Vibration Isolation and Stabilization System for Spacecraft Exercise Treadmill Devices; Microgravity-Enhanced Stem Cell Selection; Diagnosis and Treatment of Neurological Disorders by Millimeter-Wave Stimulation; Passive Vaporizing Heat Sink; Remote Sensing and Quantization of Analog Sensors; Phase Retrieval for Radio Telescope and Antenna Control; Helium-Cooled Black Shroud for Subscale Cryogenic Testing; Receive Mode Analysis and Design of Microstrip Reflectarrays; and Chance-Constrained Guidance With Non-Convex Constraints.

Source record↗

Remote sensing of earth terrain

In remote sensing, the encountered geophysical media such as agricultural canopy, forest, snow, or ice are inhomogeneous and contain scatters in a random manner. Furthermore, weather conditions such as fog, mist, or snow cover can intervene the electromagnetic observation of the remotely sensed media. In the modelling of such media accounting for the weather effects, a multi-layer random medium model has been developed. The scattering effects of the random media are described by three-dimensional correlation functions with variances and correlation lengths corresponding to the fluctuation strengths and the physical geometry of the inhomogeneities, respectively. With proper consideration of the dyadic Green's function and its singularities, the strong fluctuation theory is used to calculate the effective permittivities which account for the modification of the wave speed and attenuation in the presence of the scatters. The distorted Born approximation is then applied to obtain the correlations of the scattered fields. From the correlation of the scattered field, calculated is the complete set of scattering coefficients for polarimetric radar observation or brightness temperature in passive radiometer applications. In the remote sensing of terrestrial ecosystems, the development of microwave remote sensing technology and the potential of SAR to measure vegetation structure and biomass have increased effort to conduct experimental and theoretical researches on the interactions between microwave and vegetation canopies. The overall objective is to develop inversion algorithms to retrieve biophysical parameters from radar data. In this perspective, theoretical models and experimental data are methodically interconnected in the following manner: Due to the complexity of the interactions involved, all theoretical models have limited domains of validity; the proposed solution is to use theoretical models, which is validated by experiments, to establish the region in which the radar response is most sensitive to the parameters of interest; theoretically simulated data will be used to generate simple invertible models over the region. For applications to the remote sensing of sea ice, the developed theoretical models need to be tested with experimental measurements. With measured ground truth such as ice thickness, temperature, salinity, and structure, input parameters to the theoretical models can be obtained to calculate the polarimetric scattering coefficients for radars or brightness temperature for radiometers and then compare theoretical results with experimental data. Validated models will play an important role in the interpretation and classification of ice in monitoring global ice cover from space borne remote sensors in the future. We present an inversion algorithm based on a recently developed inversion method referred to as the Renormalized Source-Type Integral Equation approach. The objective of this method is to overcome some of the limitations and difficulties of the iterative Born technique. It recasts the inversion, which is nonlinear in nature, in terms of the solution of a set of linear equations; however, the final inversion equation is still nonlinear. The derived inversion equation is an exact equation which sums up the iterative Neuman (or Born) series in a closed form and, thus, is a valid representation even in the case when the Born series diverges; hence, the name Renormalized Source-Type Integral Equation Approach.

Yueh, Herng-Aung↗

How Well Do Satellite AOD Observations Represent the Spatial and Temporal Variability of PM2.5 Concentration for the United States?

Due to their extensive spatial coverage, satellite Aerosol Optical Depth (AOD) observations have been widely used to estimate and predict surface PM2.5 concentrations. While most previous studies have focused on establishing relationships between collocated, hourly or daily AOD and PM2.5 measurements, in this study, we instead focus on the comparison of the large-scale spatial and temporal variability between satellite AOD and PM2.5 using monthly mean measurements. A newly developed spectral analysis technique e Combined Maximum Covariance Analysis (CMCA) is applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Ozone Monitoring Instrument (OMI) AOD datasets and Environmental Protection Agency (EPA) PM2.5 data, in order to extract and compare the dominant modes of variability. Results indicate that AOD and PM2.5 agree well in terms of interannual variability. An overall decrease is found in both AOD and PM2.5 across the United States, with the strongest signal over the eastern US. With respect to seasonality, good agreement is found only for Eastern US, while for Central and Western US, AOD and PM2.5 seasonal cycles are largely different or even reversed. These results are verified using Aerosol Robotic Network (AERONET) AOD observations and differences between satellite and AERONET are also examined. MODIS and MISR appear to have the best agreement with AERONET. In order to explain the disagreement between AOD and PM2.5 seasonality, we further use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) extinction profile data to investigate the effect of two possible contributing factors, namely aerosol vertical distribution and cloud-free sampling. We find that seasonal changes in aerosol vertical distribution, due to the seasonally varying mixing height, is the primary cause for the AOD and PM2.5 seasonal discrepancy, in particular, the low AOD but high PM2.5 observed during the winter season for Central and Western US. In addition, cloud-free sampling by passive sensors also induces some bias in AOD seasonality, especially for the Western US, where the largest seasonal change in cloud fraction is found. The seasonal agreement between low level (below 500 m AGL), all sky CALIOP AOD and PM2.5 is significantly better than column AOD from MODIS, MISR, SeaWiFS and OMI. In particular, the correlation between low level, all sky AOD and PM2.5 seasonal cycles increases to above 0.7 for Central and Western US, as opposed to near zero or negative correlation for column, clear sky AOD. This result highlights the importance of accounting for the seasonally varying aerosol profiles and cloud-free sampling bias when using column AOD measurements to infer surface PM2.5 concentrations.

MODIS (radiometry)↗

4.4 Development of a 30-Year Soil Moisture Climatology for Situational Awareness and Public Health Applications

This paper provided a brief background on the work being done at NASA SPoRT and the CDC to create a soil moisture climatology over the CONUS at high spatial resolution, and to provide a valuable source of soil moisture information to the CDC for monitoring conditions that could favor the development of Valley Fever. The soil moisture climatology has multi-faceted applications for both the NOAA/NWS situational awareness in the areas of drought and flooding, and for the Public Health community. SPoRT plans to increase its interaction with the drought monitoring and Public Health communities by enhancing this testbed soil moisture anomaly product. This soil moisture climatology run will also serve as a foundation for upgrading the real-time (currently southeastern CONUS) SPoRT-LIS to a full CONUS domain based on LIS version 7 and incorporating real-time GVF data from the Suomi-NPP Visible Infrared Imaging Radiometer Suite (Vargas et al. 2013) into LIS-Noah. The upgraded SPoRT-LIS run will serve as a testbed proof-of-concept of a higher-resolution NLDAS-2 modeling member. The climatology run will be extended to near real-time using the NLDAS-2 meteorological forcing from 2011 to present. The fixed 1981-2010 climatology shall provide the soil moisture "normals" for the production of real-time soil moisture anomalies. SPoRT also envisions a web-mapping type of service in which an end-user could put in a request for either an historical or real-time soil moisture anomaly graph for a specified county (as exemplified by Figure 2) and/or for local and regional maps of soil moisture proxy percentiles. Finally, SPoRT seeks to assimilate satellite soil moisture data from the current Soil Moisture Ocean Salinity (SMOS; Blankenship et al. 2014) and the recently-launched NASA Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010) missions, using the EnKF capability within LIS. The 9-km combined active radar and passive microwave retrieval product from SMAP (Das et al. 2011) has the potential to provide valuable information about the near-surface soil moisture state for improving land surface modeling output.

land surface modeling↗

Assimilation of SMAP and ASCAT Soil Moisture Retrievals into the JULES Land Surface Model Using the Local Ensemble Transform Kalman Filter

A land data assimilation system is developed to merge satellite soil moisture retrievals into the Joint U.K. Land Environment Simulator (JULES) land surface model (LSM) using the Local Ensemble Transform Kalman Filter (LETKF). The system assimilates microwave soil moisture retrievals from the Soil Moisture Active Passive (SMAP) radiometer and the Advanced Scatterometer (ASCAT) after bias correction based on cumulative distribution function fitting. The soil moisture assimilation estimates are evaluated with ground-based soil moisture measurements over the continental U.S. for five consecutive warm seasons (May–September of 2015–2019). The result shows that both SMAP and ASCAT retrievals improve the accuracy of soil moisture estimates. Especially, the SMAP single-sensor assimilation experiment shows the best performance with the increase of temporal anomaly correlation by ΔR ~ 0.05 for surface soil moisture and ΔR ~ 0.03 for root-zone soil moisture compared with the LSM simulation without satellite data assimilation. SMAP assimilation is more skillful than ASCAT assimilation primarily because of the greater skill of the assimilated SMAP retrievals compared to the ASCAT retrievals. The skill improvement also depends significantly on the region; the higher skill improvement in the western U.S. compared to the eastern U.S. is explained by the Kalman gain in the two experiments. Additionally, the regional skill differences in the single-sensor assimilation experiments are attributed to the number of assimilated observations. Finally, the soil moisture assimilation estimates provide more realistic land surface information than model-only simulations for the 2015 and the 2016 western U.S. droughts, suggesting the advantage of using satellite soil moisture retrievals in the current drought monitoring system.

SMAP↗

Mapping Boreal Forest Spruce Beetle Health Status at the Individual Crown Scale Using Fused Spectral and Structural Data

The frequency and severity of spruce bark beetle outbreaks are increasing in boreal forests leading to widespread tree mortality and fuel conditions promoting extreme wildfire. Detection of beetle infestation is a forest health monitoring (FHM) priority but is hampered by the challenges of detecting early stage (“green”) attack from the air. There is indication that green stage might be detected from vertical gradients of spectral data or from shortwave infrared information distributed within a single crown. To evaluate the efficacy of discriminating “non-infested”, “green”, and “dead” health statuses at the landscape scale in Alaska, USA, this study conducted spectral and structural fusion of data from: (1) Unoccupied aerial vehicle (UAV) multispectral (6 cm) + structure from motion point clouds (~700 pts per sq. m); and (2) Goddard Lidar Hyperspectral Thermal (G-LiHT) hyperspectral (400 to 1000 nm, 0.5 m) + SWIR-band lidar (~32 pts per sq.m). We achieved 78% accuracy for all three health statuses using spectral + structural fusion from either UAV or G-LiHT and 97% accuracy for non-infested/dead using G-LiHT. We confirm that UAV 3D spectral (e.g., greenness above versus below median height in crown) and lidar apparent reflectance metrics (e.g., mean reflectance at 99th percentile height in crown), are of high value, perhaps capturing the vertical gradient of needle degradation. In most classification exercises, UAV accuracy was lower than G-LiHT indicating that collecting ultra-high spatial resolution data might be less important than high spectral resolution information. While the value of passive optical spectral information was largely confined to the discrimination of non-infested versus dead crowns, G-LiHT hyperspectral band selection (~400, 675, 755, and 940 nm) could inform future FHM mission planning regarding optimal wavelengths for this task. Interestingly, the selected regions mostly did not align with the band designations for our UAV multispectral data but do correspond to, e.g., Sentinel-2 red edge bands, suggesting a path forward for moderate scale bark beetle detection when paired with suitable structural data.

Janice Cessna↗

The Global L-Band Observatory for Water Cycle Studies (Glows)– SMAP continuity Mission

SMOS and SMAP radiometers have demonstrated the ability to monitor soil moisture and sea surface salinity and continue to provide high quality radiometric measurements to this day in extended mission operations. It is important to maintain data continuity for these science measurements. The proposed instrument concept (Global L-band active/passive Observatory for Water cycle Studies - GLOWS) will enable low-cost L-band data continuity (that includes both L-band radar and radiometer measurements). The objective of this project is to develop key instrument technology to enable L-band observations using an Earth Venture class satellite. Specifically, a new deployable reflectarray lens antenna is being developed that will enable a smaller EELV Secondary Payload Adapter (ESPA) Grande-class satellite mission to continue the L-band observations at SMAP and SMOS resolution and accuracy at substantially lower cost, size, and weight

SMAP↗

Three-Dimensional Vibration Isolator for Suppressing High-Frequency Responses for Sage III Contamination Monitoring Package (CMP)

The Stratospheric Aerosol and Gas Experiment (SAGE) III - International Space Station (ISS) instrument will be used to study ozone, providing global, long-term measurements of key components of the Earth's atmosphere for the continued health of Earth and its inhabitants. SAGE III is launched into orbit in an inverted configuration on SpaceX;s Falcon 9 launch vehicle. As one of its four supporting elements, a Contamination Monitoring Package (CMP) mounted to the top panel of the Interface Adapter Module (IAM) box experiences high-frequency response due to structural coupling between the two structures during the SpaceX launch. These vibrations, which were initially observed in the IAM Engineering Development Unit (EDU) test and later verified through finite element analysis (FEA) for the SpaceX launch loads, may damage the internal electronic cards and the Thermoelectric Quartz Crystal Microbalance (TQCM) sensors mounted on the CMP. Three-dimensional (3D) vibration isolators were required to be inserted between the CMP and IAM interface in order to attenuate the high frequency vibrations without resulting in any major changes to the existing system. Wire rope isolators were proposed as the isolation system between the CMP and IAM due to the low impact to design. Most 3D isolation systems are designed for compression and roll, therefore little dynamic data was available for using wire rope isolators in an inverted or tension configuration. From the isolator FEA and test results, it is shown that by using the 3D wire rope isolators, the CMP high-frequency responses have been suppressed by several orders of magnitude over a wide excitation frequency range. Consequently, the TQCM sensor responses are well below their qualification environments. It is indicated that these high-frequency responses due to the typical instrument structural coupling can be significantly suppressed by a vibration passive control using the 3D vibration isolator. Thermal and contamination issues were also examined during the isolator selection period for meeting the SAGE III-ISS instrument requirements.

Li, Y.↗

Cryogenic systems for the large deployable reflector

There are five technologies which may have application for Large Deployable Reflector (LDR), one passive and four active. In order of maturity, they are passive stored cryogen systems, and mechanical, sorption, magnetic, and pulse-tube refrigerators. In addition, deep space radiators will be required to reject the heat of the active systems, and may be useful as auxiliary coolers for the stored cryogen systems. Hybrid combinations of these technologies may well be more efficient than any one alone, and extensive system studies will be required to determine the best trade-offs. Stored cryogen systems were flown on a number of missions. The systems are capable of meeting the temperature requirements of LDR. The size and weight of stored cryogen systems are proportional to heat load and, as a result, are applicable only if the low-temperature heat load can be kept small. Systems using chemisorption and physical adsorption for compressors and pumps have received considerable attention in the past few years. Systems based on adiabatic demagnetization of paramagnetic salts were used for refrigeration for many years. Pulse-tube refrigerators were recently proposed which show relatively high efficiency for temperatures in the 60 to 80 K range. The instrument heat loads and operating temperatures are critical to the selection and design of the cryogenic system. Every effort should be made to minimize heat loads, raise operating temperatures, and to define these precisely. No one technology is now ready for application to LDR. Substantial development efforts are underway in all of the technologies and should be monitored and advocated. Magnetic and pulse-tube refrigerators have high potential.

Mason, Peter V.↗

Advancements in Lunar Dust Mitigation and Leveraging the Contamination Control Community

Lunar Dust Contamination: As we get closer to putting landers, rovers, payloads, and astronauts on the Moon, dust mitigation is becoming more critical than ever. To address the many challenges of dust mitigation on the surface, engineers and scientists are looking at various technologies that may have relevance for the contamination control community. This includes active, passive, architectural, and operational solutions. There have been advances in coatings for dust mitigation at NASA and through commercial partnerships (see Wiesner, Wohl, et al). There have been advancements to previous solutions as well as novel solutions to address dust mitigation on the surface and on-orbit. There have been several efforts to better understand the effectiveness of various terrestrial and dust mitigation solutions with much of this data published in recent years. In the area of dust mitigation, dust contamination or infiltration refers to the impingement or contact of planetary dust with items not normally dusty and whose operation may therefore be compromised. Recent Advancements in Dust Mitigation: Dust mitigation strategies are becoming more common for hardware heading to the Moon, with most major programs implementing lunar dust contamination requirements for human health and equipment. In the last couple of years, NASA has created more guidance to assist hardware developers with dust mitigation. This includes NASA-STD-1008 (Classifications and Requirements for Testing Systems and Hardware to be Exposed to Dust in Planetary) and NASA TP 20220018746 (Lunar Dust Mitigation Guide and Reference). Several projects are testing hardware in relevant dusty environments to understand their tolerance to lunar dust. There has been a significant increase in the amount of testing with lunar simulants, with the NASA Simulant Advisory Committee serving a resource for NASA and our partners. There are new solutions for detecting and monitoring the dust internally and externally. Learning from the contamination control community: In addition to sharing potentially relevant solutions at the workshop, the dust mitigation community is also interested in learning from the contamination control community on ways to address lunar dust. For instance, a major aspect of managing the dust is monitoring and detection. This is critical for understanding when maintenance is needed and to inform future missions. Another challenge of working with lunar dust is quantifying and characterizing the smallest of particles. There are also challenges in modeling lunar dust and its behavior. The dust mitigation community can also leverage lessons learned from the planetary protection community.

dust mitagation↗

Studies of the Interactions Between Vestibular Function and Tactual Orientation Display Systems

When humans experience conditions in which internal vestibular cues to movement or spatial location are challenged or contradicted by external visual information, the result can be spatial disorientation, often leading to motion sickness. Spatial disorientation can occur in any situation in which the individual is passively moved in the environment, but is most common in automotive, aircraft, or undersea travel. Significantly, the incidence of motion sickness in space travel is great: The majority of individuals in Shuttle operations suffer from the syndrome. Even after the space-sickness-producing influences of spatial disorientation dissipate, usually within several days, there are other situations in which, because of the absence of reliable or familiar vestibular cues, individuals in space still experience disorientation, resulting in a reliance on the already preoccupied sense of vision. One possible technique to minimize the deleterious effects of spatial disorientation might be to present attitude information (including orientation, direction, and motion) through another less-used sensory modality - the sense of touch. Data from experiences with deaf and blind persons indicate that this channel can provide useful communication and mobility information on a real-time basis. More recently, technologies have developed to present effective attitude information to pilots in situations in which dangerously ambiguous and conflicting visual and vestibular sensations occur. This summers project at NASA-Johnson Space Center will evaluate the influence of motion-based spatial disorientation on the perception of tactual stimuli representing veridical position and orientation information, presented by new dynamic vibrotactile array display technologies. In addition, the possibility will be explored that tactile presentations of motion and direction from this alternative modality might be useful in mitigating or alleviating spatial disorientation produced by multi-axis rotatory systems, monitored by physiological recording techniques developed at JSC.

Cholewiak, Roger W.↗

Optical Reflectance and Fluorescence for Detecting Nitrogen Needs in Zea mays L.

Nitrogen (N) status in field grown corn (Zea mays L.) was assessed using spectral techniques. Passive reflectance remote sensing and, both passive and active fluorescence sensing methods were investigated. Reflectance and fluorescence methods are reported to detect changes in the primary plant pigments (chlorophylls a and b; carotenoids) in higher plant species. As a general rule, foliar chlorophyll a (Chl a) and chlorophyll b (Chl b) usually exist in approx.3:l ratio. In plants under stress, Chl b content is affected before Chl a reductions occur. For reflectance, a version of the chlorophyll absorption in reflectance index (CARI) method was tested with narrow bands from the Airborne Imaging Spectroradiometer for Applications (ASIA). CARI minimizes the effects of soil background on the signal from green canopies. A modified CARI (MCARI) was used to track total Chl a levels in the red dip of the spectrum from the corn canopy. A second MCARI was used to track the auxiliary plant pigments (Chl b and the carotenoids) in the yellow/orange/red edge part of the reflectance spectrum. The difference between these two MCARI indices detected variations in N levels across the field plot canopies using ASIA data. At the leaf level, ratios of fluorescence emissions in the blue, green, red and far-red wavelengths sensed responses that were associated with the plant pigments, and were indicative of energy transfer in the photosynthetic process. N stressed corn stands could be distinguish from those with optimally applied N with fluorescence emission spectra obtained from individual corn leaves. Both reflectance and fluorescence methods are sensitive in detecting corn N needs and may be especially powerful in monitoring crop conditions if both types of information can be combined.

McMurtrey, J. E.↗

Assessing Global Surface Water Inundation Dynamics Using Combined Satellite Information from SMAP, AMSR2 and Landsat

A method to assess global land surface water (fw) inundation dynamics was developed by exploiting the enhanced fw sensitivity of L-band (1.4 GHz) passive microwave observations from the Soil Moisture Active Passive (SMAP) mission. The L-band fw (fw(sub LBand)) retrievals were derived using SMAP H-polarization brightness temperature (Tb) observations and predefined L-band reference microwave emissivities for water and land endmembers. Potential soil moisture and vegetation contributions to the microwave signal were represented from overlapping higher frequency (Tb) observations from AMSR2. The resulting (fw(sub LBand)) global record has high temporal sampling (1-3 days) and 36-km spatial resolution. The (fw(sub LBand)) annual averages corresponded favourably (R=0.84, p<0.001) with a 250-m resolution static global water map (MOD44W) aggregated at the same spatial scale, while capturing significant inundation variations worldwide. The monthly (fw(sub LBand)) averages also showed seasonal inundation changes consistent with river discharge records within six major US river basins. An uncertainty analysis indicated generally reliable (fw(sub LBand)) performance for major land cover areas and under low to moderate vegetation cover, but with lower accuracy for detecting water bodies covered by dense vegetation. Finer resolution (30-m) (fw(sub LBand)) results were obtained for three sub-regions in North America using an empirical downscaling approach and ancillary global Water Occurrence Dataset (WOD) derived from the historical Landsat record. The resulting 30-m (fw(sub LBand)) retrievals showed favourable spatial accuracy for water (70.71%) and land (98.99%) classifications and seasonal wet and dry periods when compared to independent water maps derived from Landsat-8 imagery. The new (fw(sub LBand)) algorithms and continuing SMAP and AMSR2 operations provide for near real-time, multi-scale monitoring of global surface water inundation dynamics and potential flood risk.

WOD↗

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC)

On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following: 1. Level-1 GPM Microwave Imager (GMI) and partner radiometer products. 2. Goddard Profiling Algorithm (GPROF) GMI and partner products. 3. Integrated Multi-satellitE Retrievals for GPM (IMERG) products. (early, late, and final)A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http:disc.sci.gsfc.nasa.govgpm). Data services that are currently and to-be available include Google-like Mirador (http:mirador.gsfc.nasa.gov) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http:giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data version control and provenance; documentation; science support for proper data usage, FAQ, help desk; monitoring services (e.g. Current Conditions) for applications.In this presentation, we will present GPM data products and services with examples.

NASA GES DISC↗

Machine Learning Algorithms for Aerosol and Cloud Detection Using CATS on the ISS

Clouds and aerosols are one of the largest uncertainties in understanding and forecasting the Earth’s changing climate system. The type and height of aerosols are important factors in determining the top-of-atmosphere (TOA) radiation budget, either direct reflection of solar radiation back to space and/or absorption of solar radiation. In addition to their impact on the Earth’s climate system, aerosols near the surface from wildfires, man-made pollution events, and dust storms are hazardous to human health. The phase and height of clouds also play a critical role in determining the role of clouds in the Earth’s climate system. Cirrus clouds in the upper troposphere can induce a significant daytime TOA warming effect, while liquid water clouds near the surface cause a large corresponding cooling effect. Lidar measurements provide accurate vertically resolved information about clouds and aerosols, including complex multi-layer scenes where passive sensors are challenged and at night, when passive sensors are unable to measure cloud and aerosol properties. The Cloud-Aerosol Transport System (CATS) is a lidar instrument that operated for 33 months on the International Space Station (ISS) at the 1064 nm wavelength to measure attenuated total backscatter and depolarization ratio. These fundamental measurements are used to derive “vertical feature mask” cloud and aerosol products, including layer top/base heights, layer geometrical thickness, aerosol type, and cloud phase. While space-based lidar systems like CATS provide cloud and aerosol vertical distributions that improve our understanding of the climate system, averaging of the daytime data from these sensors is required, at the expense of spatial resolution, to improve the daytime signal-to noise (SNR) and thus atmospheric layer detection. This presentation shows results from machine learning (ML) techniques that, when applied to CATS data: 1. improve the 1064 nm SNR 2. enable detection of atmospheric features during daytime with a horizontal resolution of 350 m or 5 km (compared to the 60 km required for standard CATS data products) 3. increase the number of atmospheric layers detected in the CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination, cloud phase, and aerosol typing compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime. The ML tools described in this paper can facilitate the development of smaller, low-cost lidar systems in the future and enable real-time accessibility of lidar data products from future lidar systems for monitoring and forecasting of hazardous events.

John Yorks↗