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Characterizing diurnal and seasonal cycles in monsoon systems from TRMM and CEOP observations

The CEOP Inter-Monsoon Study (CIMS) is one of the two main science drivers of CEOP that aims to (a) provide better understanding of fundamental physical processes in monsoon regions around the world, and (b) demonstrate the synergy and utility of CEOP data in providing a pathway for model physics evaluation and improvement. As the data collection phase for EOP-3 and EOP-4 is being completed, two full annual cycles (2003-2004) of research-quality data sets from satellites, reference sites, and model output location time series (MOLTS) have been processed and made available for data analyses and model validation studies. This article presents preliminary results of a CIMS study aimed at the characterization and intercomparison of all major monsoon systems. The CEOP reference site data proved its value in such exercises by being a powerful tool to cross-validate the TRMM data, and to intercompare with multi-model results in ongoing work. We use 6 years (1998-2003) of pentad CEOP/TRMM data with 2deg x 2.5deg latitude-longitude grid, over the domain of interests to define the monsoon climatological diurnal and annual cycles for the East Asian Monsoon (EAM), the South Asian Monsoon (SAM), the West Africa Monsoon (WAM), the North America/Mexican Monsoon (NAM), the South American Summer Monsoon (SASM) and the Australian Monsoon (AUM). As noted, the TRMM data used in the study were cross-validated using CEOP reference site data, where applicable. Results show that the observed diurnal cycle of rain peaked around late afternoon over monsoon land, and early morning over the oceans. The diurnal cycles in models tend to peak 2-3 hours earlier than observed. The seasonal cycles of the EAM and SAM show the strongest continentality, i.e, strong control by continental processes away from the ITCZ. The WAM, and the AUM shows the less continentality, i.e, strong control by the oceanic ITCZ.

Lau, William K. M.↗

Characterizing Diurnal and Seasonal Cycles in Monsoon Systems from TRMM and CEOP Observations

The CEOP Inter-Monsoon Study (CIMS) is one of the two main science drivers of CEOP that aims to (a) provide better understanding of fundamental physical processes in monsoon regions around the world, and (b) demonstrate the synergy and utility of CEOP data in providing a pathway for model physics evaluation and improvement. As the data collection phase for EOP-3 and EOP-4 is being completed, two full annual cycles (2003-2004) of research-quality data sets from satellites, reference sites, and model output location time series (MOLTS) have been processed and made available for data analyses and model validation studies. This article presents preliminary results of a CIMS study aimed at the characterization and intercomparison of all major monsoon systems. The CEOP reference site data proved its value in such exercises by being a powerful tool to cross-validate the TRMM data, and to intercompare with multi-model results in ongoing work. We use 6 years (1998-2003) of pentad CEOP/TRMM data with 2 deg x 2.5 deg. latitude-longitude grid, over the domain of interests to define the monsoon climatological diurnal and annual cycles for the East Asian Monsoon (EAM), the South Asian Monsoon (SAM), the West Africa Monsoon (WAM), the North America/Mexican Monsoon (NAM), the South American Summer Monsoon (SASM) and the Australian Monsoon (AUM). As noted, the TRMM data used in the study were cross-validated using CEOP reference site data, where applicable. Results show that the observed diurnal cycle of rain peaked around late afternoon over monsoon land, and early morning over the oceans. The diurnal cycles in models tend to peak 2-3 hours earlier than observed. The seasonal cycles of the EAM and SAM show the strongest continentality, i.e, strong control by continental processes away from the ITCZ. The WAM, and the AUM shows the less continentality, i.e, strong control by the oceanic ITCZ.

Lau, William K. M.↗

SCDU Testbed Automated In-Situ Alignment, Data Acquisition and Analysis

In the course of fulfilling its mandate, the Spectral Calibration Development Unit (SCDU) testbed for SIM-Lite produces copious amounts of raw data. To effectively spend time attempting to understand the science driving the data, the team devised computerized automations to limit the time spent bringing the testbed to a healthy state and commanding it, and instead focus on analyzing the processed results. We developed a multi-layered scripting language that emphasized the scientific experiments we conducted, which drastically shortened our experiment scripts, improved their readability, and all-but-eliminated testbed operator errors. In addition to scientific experiment functions, we also developed a set of automated alignments that bring the testbed up to a well-aligned state with little more than the push of a button. These scripts were written in the scripting language, and in Matlab via an interface library, allowing all members of the team to augment the existing scripting language with complex analysis scripts. To keep track of these results, we created an easily-parseable state log in which we logged both the state of the testbed and relevant metadata. Finally, we designed a distributed processing system that allowed us to farm lengthy analyses to a collection of client computers which reported their results in a central log. Since these logs were parseable, we wrote query scripts that gave us an effortless way to compare results collected under different conditions. This paper serves as a case-study, detailing the motivating requirements for the decisions we made and explaining the implementation process.

Automation↗

Mars ISRU for Production of Mission Critical Consumables - Options, Recent Studies, and Current State of the Art

In 1978, a ground breaking paper titled, "Feasibility of Rocket Propellant Production on Mars" by Ash, Dowler, and Varsi discussed how ascent propellants could be manufactured on the Mars surface from carbon dioxide collected from the atmosphere to reduce launch mass. Since then, the concept of making mission critical consumables such as propellants, fuel cell reactants, and life support consumables from local resources, commonly known as In-Situ Resource Utilization (ISRU), for robotic and human missions to Mars has been studied many times. In the late 1990's, NASA initiated a series of Mars Human Design Reference Missions (DRMs), the first of which was released in 1997. These studies primarily focused on evaluating the impact of making propellants on Mars for crew ascent to Mars orbit, but creating large caches of life support consumables (water & oxygen) as a backup for regenerative life support systems for long-duration surface stays (>500 days) was also considered in Mars DRM 3.0. Until science data from the Mars Odyssey orbiter and subsequent robotic missions revealed that water may be widely accessable across the surface of Mars, prior Mars ISRU studies were limited to processing Mars atmospheric resources (carbon dioxide, nitrogen, argon, oxygen, and water vapor). In December 2007, NASA completed the Mars Human Design Reference Architecture (DRA) 5.0 study which considered water on Mars as a potential resource for the first time in a human mission architecture. While knowledge of both water resources on Mars and the hardware required to excavate and extract the water were very preliminary, the study concluded that a significant reduction in mass and significant enhancements to the mission architecture were possible if Mars water resources were utilized. Two subsequent Mars ISRU studies aimed at reexamining ISRU technologies, processing options, and advancements in the state-of-the-art since 2007 and to better understand the volume and packaging associated with Mars ISRU systems further substantiated the preliminary results from the Mars DRA 5.0 study. This paper will provide an overview of Mars ISRU consumable production options, the analyses, results, and conclusions from the Mars DRA 5.0 (2007), Mars Collaborative (2013), and Mars ISRU Payload for the Supersonic Retro Propulsion (2014) mission studies, and the current state-of-the-art of Mars ISRU technologies and systems. The paper will also briefly discuss the mission architectural implications associated with Mars resource and ISRU processing options.

Sanders, G. B.↗

Nondestructive Evaluation for Aerospace Composites

Nondestructive evaluation (NDE) techniques are important for enabling NASA's missions in space exploration and aeronautics. The expanded and continued use of composite materials for aerospace components and vehicles leads to a need for advanced NDE techniques capable of quantitatively characterizing damage in composites. Quantitative damage detection techniques help to ensure safety, reliability and durability of space and aeronautic vehicles. This presentation will give a broad outline of NASA's range of technical work and an overview of the NDE research performed in the Nondestructive Evaluation Sciences Branch at NASA Langley Research Center. The presentation will focus on ongoing research in the development of NDE techniques for composite materials and structures, including development of automated data processing tools to turn NDE data into quantitative location and sizing results. Composites focused NDE research in the areas of ultrasonics, thermography, X-ray computed tomography, and NDE modeling will be discussed.

Leckey, Cara↗

The Land Surface Data Toolkit (LDT v7.2) - A Data Fusion Environment for Land Data Assimilation Systems

The effective applications of land surface models (LSMs) and hydrologic models pose a varied set of data input and processing needs, ranging from ensuring consistency checks to more derived data processing and analytics. This article describes the development of the Land surface Data Toolkit (LDT), which is an integrated framework designed specifically for processing input data to execute LSMs and hydrological models. LDT not only serves as a preprocessor to the NASA Land Information System (LIS), which is an integrated framework designed for multi-model LSM simulations and data assimilation (DA) integrations, but also as a land-surface-based observation and DA input processor. It offers a variety of user options and inputs to processing datasets for use within LIS and stand-alone models. The LDT design facilitates the use of common data formats and conventions. LDT is also capable of processing LSM initial conditions and meteorological boundary conditions and ensuring data quality for inputs to LSMs and DA routines. The machine learning layer in LDT facilitates the use of modern data science algorithms for developing data-driven predictive models. Through the use of an object-oriented framework design, LDT provides extensible features for the continued development of support for different types of observational datasets and data analytics algorithms to aid land surface modeling and data assimilation.

droughts and floods↗

VIIRS Thermal Emissive Bands L1B Calibration Uncertainty

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key instrument on-board the Suomi National Polar-orbiting Partnership (S-NPP) spacecraft. The S-NPP launched in October 2011 and it has been collecting valuable Earth science data with VIIRS and four other instruments for more than five years. The VIIRS Characterization Support Team (VCST) of the National Aeronautics and Space Administration (NASA) Science Investigator-led Processing Systems (SIPS) is designed to support the VIIRS sensor pre-launch geometric and radiometric characterization and to access on-orbit long-term Level-1B (L1B) calibration and performance. This paper reviews the VIIRS thermal emissive bands (TEB), covering wavelengths from 3.7 to 12.0 μm, L1B radiometric calibration algorithms and presents the calibration uncertainty methodology which will be implanted in the L1B processing software. Discussions will be focused on the key uncertainty parameters and the application in L1B.

S-NPP VIIRS TEB Uncertainty↗

"Sensor Web Evolution - Webs of Webs for NASA Science - Focus on small Uninhabited Aerial Systems (sUAS)"

This paper will describe the evolution of information collection, derivation and delivery mechanisms in webs of NASA sensor webs, with a focus on recent advancements in small Uninhabited Aerial Systems (sUAS). I will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, sUASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary sUASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. I will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing sUASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to sUAS development. This paper will focus on application, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

Sensor Web↗

Exploring the human-nature dynamics of Hunga Tonga Hunga Ha'apai, Earth's newest landmass

This paper examines the human-nature dynamics of volcanic eruptions through a multidisciplinary exploration of the recently-formed Hunga Tonga Hunga Ha‘apai (HTHH) landmass in the Kingdom of Tonga. HTHH was formed in early 2015 in the Ha‘apai island group in southwestern Tonga. This landmass has persisted longer than expected, providing a rare opportunity to examine pathways of erosion and biological colonization, and offering a glimpse into the cultural dynamics of a continuously changing Polynesian seascape. In 2018 and 2019, a collaborative partnership between the Kingdomof Tonga, Sea Education Association (SEA), and the United States National Aeronautics and Space Administration (NASA) ran expeditions to HTHH to calibrate satellite observations via field, ship, and drone-based measurements. In accessing HTHH via SEA's sailing school vessel (SSV) the Robert C. Seamans, a team of scientists and students combined fieldwork in anthropology, oceanography, and physical volcanology to study micro- and macro-scale dynamics of this classical surtseyan eruption site. In this pathfinding paper, we discuss the value of involving students in the process of real-time scientific discovery with on-the-fly adaptive hypothesis testing; this collaborative project provided mutual benefit to initiatives in science and education by offering robust data collection, while expanding environmental and cultural literacy. Additionally, we integrate collaborative research on HTHH with ethnographic research to understand how this ever changing “sea of islands” or intimately interconnected island spaces impact social-cultural relations within Oceania. We emphasize the importance of such multidisciplinary research in understanding the complexity of human-nature relations in a rapidly changing world.

Emily B. Hite↗

UASs in the VOG/Edge/FOG Sensor Web Environment

This paper will describe the evolution of information collection, derivation and delivery mechanisms in sensor webs utilizing Uninhabited Aerial Systems (UAS).We will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, UASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary UASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. The Author will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing UASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to other UAS development This paper will focus on applications, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

UAS↗

The CheMin X-ray Diffractometer on MSL Curiosity: A Decade of Mineralogical Observations from Gale Crater, Mars

For more than a decade, the CheMin X-ray Diffraction instrument on the Mars Science Laboratory rover Curiosity has been returning quantitative mineralogical data from Gale crater, Mars. CheMin receives and analyzes sieved soil and powdered rock samples from Curiosity’s Sample Acquisition / Sample Processing and Handling (SA/SPaH) system. To date, 38 samples have been analyzed over the course of a 28 km transit. These samples document more than 600 vertical meters of flat-lying lacustrine, fluvial and aeolian sediments that comprise the lower part of the central mound of Gale crater (commonly called Mt. Sharp).The principal mineralogy of the sediments is basaltic, with evidence of early and late-stage diagenetic overprinting. The rocks in many cases preserve most of their primary mineralogy and sedimentary features, suggesting that they were never strongly heated or deformed. Using aeolian soil composition as a proxy for the composition of the deposited and lithified sediment, it appears that in many cases the diagenetic changes observed are principally isochemical. Exceptions to this include secondary nodules, calcium sulfate veining and rare alteration halos. A striking hematite-rich feature in lower Mt. Sharp called Vera Rubin Ridge is interpreted to be lake sediment diagenetically altered by silica-poor fluids. A surprising and as yet poorly understood observation is that nearly all of the 3.7 Gyr old sedimentary rocks analyzed to date are comprised of 25-50% X-ray amorphous material. Overall, this 600 m vertical section of sedimentary rock explored in lower Mt. Sharp documents a perennial shallow lake environment grading upward into alternating lacustrine/fluvial and aeolian environments. The mineralogical changes observed going up-section include a transition from trioctahedral to dioctahedral clay minerals and a transition from magnetite to hematite. More recently, in the last 150 m of section, CheMin has documented an overall decrease in clay minerals and increase in Fe3+ oxides and oxyhydroxides. The mineralogical changes observed in Gale crater may document the gradual drying out and oxidation of the martian hydrosphere.

CHEMIN↗

What is LAADS DAAC? How to Download Data from NASA's Source for Cloud and Aerosol Data

The Level-1 and Atmosphere Archive Distribution System (LAADS) Distributed Active Archive Center (DAAC) primarily archives and distributes data on clouds and aerosols in Earth’s atmosphere in addition to providing Level 0 and 1 Moderate Imaging Radiometer Suite (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS) and airborne data as well as data from the European Space Agency’s Sea and Land Surface Temperature Radiometer (SLSTR) and the Ocean and Land Colour Instrument (OLCI). Secondarily, LAADS DAAC serves as a backup source for MODIS and VIIRS land products. As one of twelve DAACS supported by NASA’s Earth Science Data and Information System (ESDIS), LAADS DAAC provides a gateway to data through multiple tools. The newest, View Data, allows users to preview data sets before downloading or applying any post-processing transformations. Learn about how to access LAADS DAAC data, get up-to-date information about LAADS DAAC's migration to hosting data in the cloud, and discover how to use the View Data tool.

Tassia Owen↗

High Performance Access to Archival Data Stored in HDF4 and HDF5 on Cloud Object Stores Without Reformatting the Files

Cloud computing offers numerous advantages for users of extensive Earth science data collections. These benefits encompass direct online access to data files and granules from any location, scalable access supporting parallel computing workflows, and flexible computing tools enabling innovative experimentation with processing techniques. However, older archival file formats designed for distinct computing systems hinder efficient access to decade-long time-series data when compared to data stored in modern cloud-optimized formats like Web Object Stores (WOS), exemplified by Amazon Web Services’ Simple Storage Service (S3). We describe DMR++ (Dataset Metadata Response plus plus), a technology facilitating efficient access to HDF5 (Hierarchical Data Format, version 5) and HDF4 files stored on WOS systems without requiring data reformatting. DMR++ achieves performance comparable to technologies like Zarr while preserving the original file structure, a substantial benefit considering the vast quantity of archival files held by organizations such as NASA. Moreover, DMR++ typically outperforms cloud-optimized versions of HDF5. Essentially an XML (Extensible Markup Language) document usually stored alongside the described data, DMR++ can also be generated on-the-fly but is generally created during data staging to the WOS. Archival files that use HDF4/5 often store large arrays of numerical data. The data in these files is often compressed, typically reducing their size by a factor of four or more. To achieve efficient access to portions of those arrays, they are 'chunked' into smaller sub-arrays, each individually compressed. The chunk size is a compromise, where spinning disks can efficiently access data in smaller chunks while S3 favors larger chunks. A simple optimization of aggregating smaller chunks that are stored adjacently, transferring them in a single access and then individually decompressing them will improve performance. NASA data pose an additional challenge: special Application Programmer Interface (API) libraries are often needed to compute some variables. These libraries are incompatible with WOS environments. Our solution involves storing computed values in the DMR++ document or a companion file, making them accessible like other variables and eliminating the need for specialized APIs. We outline specific optimizations for both satellite grid and swath data stored in HDF4-EOS2 (Earth Observing System).

James Gallagher↗

CESDIS

CESDIS, the Center of Excellence in Space Data and Information Sciences was developed jointly by NASA, Universities Space Research Association (USRA), and the University of Maryland in 1988 to focus on the design of advanced computing techniques and data systems to support NASA Earth and space science research programs. CESDIS is operated by USRA under contract to NASA. The Director, Associate Director, Staff Scientists, and administrative staff are located on-site at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The primary CESDIS mission is to increase the connection between computer science and engineering research programs at colleges and universities and NASA groups working with computer applications in Earth and space science. Research areas of primary interest at CESDIS include: 1) High performance computing, especially software design and performance evaluation for massively parallel machines; 2) Parallel input/output and data storage systems for high performance parallel computers; 3) Data base and intelligent data management systems for parallel computers; 4) Image processing; 5) Digital libraries; and 6) Data compression. CESDIS funds multiyear projects at U. S. universities and colleges. Proposals are accepted in response to calls for proposals and are selected on the basis of peer reviews. Funds are provided to support faculty and graduate students working at their home institutions. Project personnel visit Goddard during academic recess periods to attend workshops, present seminars, and collaborate with NASA scientists on research projects. Additionally, CESDIS takes on specific research tasks of shorter duration for computer science research requested by NASA Goddard scientists.

Source record↗

FluxSat: Long-term Earth Science Data Record (ESDR) for Terrestrial Gross Primary Production (GPP) based on satellite data calibrated with eddy covariance data

Gross primary production (GPP), the amount of carbon dioxide (CO 2 ) assimilated by plants through photosynthesis, is one of the most variable and uncertain components of the global carbon cycle. Global GPP has been estimated with a number of process-based models, data-driven, and hybrid approaches. Dynamic global vegetation models (DGVMs), driven by observed environmental changes, are used for global carbon budget assessments and long-term (climate) prediction. Benchmarking these and other models globally with data-driven GPP estimates is critical for understanding the land sink and ensuring accurate forecasts of the carbon cycle. In addition, global data-driven GPP estimates are crucial for studies of interannual variability, including trends that are linked to mechanisms with large uncertainties, such as the indirect CO 2 fertilization effect related to greening. In response to a community need for a GPP data set that well captures spatio-temporal variability, we developed FluxSat, a data-driven approach that optimizes the use of satellite reflectance data from the NASA MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites, calibrated using ground-based eddy covariance (EC) data. We are enhancing (spatially, higher resolution) and extending FluxSat (in time, with additional sensors) to create a high quality long term GPP Earth System Data Record (ESDR) for use in model benchmarking, carbon cycle modeling, and studies of trends and interannual variability. Our team’s objectives are to: 1. Update and document the current MODIS FluxSat GPP (daily, 0.05o and 0.5o resolutions) products with latest available MODIS and EC data sets; 2. Extend FluxSat GPP record forward in time with the Visible Infrared Imaging Radiometer Suite (VIIRS) on operational weather satellites going forward; 3. Extend FluxSat GPP record backward in time using the Advanced Very High Resolution Radiometer (AVHRR) on weather satellites dating back to 1981; 4. Provide higher spatial resolution MODIS and VIIRS GPP (0.0083o). 5. Thoroughly evaluate all FluxSat products with independent data; and 6. Create a homogenized long-term GPP record spanning 40+ years. We will discuss plans for this long-term data set that is supported through the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program.

gross Primary Production↗

Decadal Seasonal Shifts of Precipitation and Temperature in TRMM and AIRS Data

We present results from an analysis of seasonal phase shifts in the global precipitation and surface temperatures. We use data from the TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Algorithm (TMPA), and the Atmospheric Infrared Sounder (AIRS) on Aqua satellite, all hosted at NASA Goddard Earth Science Data and Information Services Center (GES DISC). We explore the information content and data usability by first aggregating daily grids from the entire records of both missions to pentad (5-day) series which are then processed using Singular Value Decomposition approach. A strength of this approach is the normalized principal components that can then be easily converted from real to complex time series. Thus, we can separate the most informative, the seasonal, components and analyze unambiguously for potential seasonal phase drifts. TMPA and AIRS records represent correspondingly 20 and 15 years of data, which allows us to run simple “phase learning†from the first 5 years of records and use it as reference. The most recent 5 years are then phase-compared with the reference. We demonstrate that the seasonal phase of global precipitation and surface temperatures has been stable in the past two decades. However, a small global trend of delayed precipitation, and earlier arrival of surface temperatures seasons, are detectable at 95% confidence level. Larger phase shifts are detectable at regional level, in regions recognizable from the Eigen vectors to having strong seasonal patterns. For instance, in Central North America, including the North American Monsoon region, confident phase shifts of 1-2 days per decade are detected at 95% confidence level. While seemingly symbolic, these shifts are indicative of larger changes in the Earth Climate System. We thus also demonstrate a potential usability scenario of Earth Science Data Records curated at the NASA GES DISC in partnership with Earth Science Missions.

surface temperatures↗

Fine-tuning of process conditions to improve product uniformity of polystyrene particles used for wind tunnel velocimetry

Monodisperse polymer particles (having uniform diameter) were used for the last two decades in physical, biological, and chemical sciences. In NASA Langley Research Center monodisperse polystyrene particles are used in wind tunnel laser velocimeters. These polystyrene (PS) particles in latex form were formulated at the Engineering Laboratory of FENGD using emulsion-free emulsion polymerization. Monodisperse PS latices particles having different particle diameters were formulated and useful experimental data involving effects of process conditions on particle size were accumulated. However, similar process conditions and chemical recipes for polymerization of styrene monomer have often yielded monodisperse particles having varying diameters. The purpose was to improve the PS latex product uniformity by fine-tuning the process parameters based on the knowledge of suspension and emulsion polymerization.

Ray, Asit K.↗

Chemical and Mineralogical Characterization of a Hematite-bearing Ridge on Mauna Kea, Hawaii: A Potential Mineralogical Process Analog for the Mount Sharp Hematite Ridge

The Mars Science Laboratory (MSL) rover Curiosity landed in Gale Crater in August 2012 and is currently roving towards the layered central mound known as Mount Sharp [1]. Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) hyperspectral data indicate Mount Sharp contains an ~5 km stratigraphic sequence including Fe-Mg smectites, hematite, and hydrated sulfates in the lower layers separated by an unconformity from the overlying anhydrous strata [1,2,3]. Hematite was initially detected in CRISM data to occur in the lower sulfate layers on the north side of the mound [2]. [3] further mapped a distinct hematite detection occurring as part of a ~200 m wide ridge that extends ~6.5 km NE-SW, approximately parallel with the base of Mount Sharp. It is likely a target for in-situ analyses by Curiosity. We document here the occurrence of a stratum of hematite-bearing breccia that is exposed on the Puu Poliahu cinder cone near the summit of Mauna Kea volcano (Hawaii) (Fig.1). The stratum is more resistant to weathering than surrounding material, giving it the appearance of a ridge. The Mauna Kea hematite ridge is thus arguably a potential terrestrial mineralogical and process analog for the Gale Crater hematite ridge. We are acquiring a variety of chemical and mineralogical data on the Mauna Kea samples, with a focus on the chemical and mineralogical information already available or planned for the Gale hematite ridge.

Graff, T. G.↗