ALBERT

Description: Culture medium from an isolate of the fungus Aspergillus candidus was extracted, fractionated and examined to discover compounds antagonistic to plant-parasitic nematodes that are important pathogens of agricultural crops. Column, thin layer and preparative chromatographies and spectral and elemental analyses, were used to isolate and identify two major constituents of an active fraction (Fraction F) obtained from the medium. Compound 1 was identified as 2-hydroxypropane-1, 2, 3-tricarboxylic acid (citric acid). Compound 2 was identified as 3-hydroxy-5-methoxy-3-(methoxycarbonyl)-5-oxopentanoic acid, an isomer of 1, 2-dimethyl citrate. Compound 1 and a citric acid standard, each tested at 50 mg mL –1 in water, decreased hatch from eggs of the plant-parasitic nematode Meloidogyne incognita by more than 94%, and completely immobilized second-stage juveniles after 4–6 days exposure. Fraction F and Compounds 1 and 2 decreased the mobility of adults of the plant-parasitic nematode Ditylenchus destructor in vitro . Fraction F (25 mg mL –1 ) inhibited mobility 〉99% at 72 hrs. Compounds 1 and 2 (50 mg mL –1 ) each inhibited mobility more than 25% at 24 hr and more than 50% at 72 hr. This is the first assignment of nematode-antagonistic properties to specifically identified A. candidus metabolites.

Description: A new crustal thickness model was used to test the viability of 110 candidate large lunar basins previously identified using older topographic and crustal thickness data as well as photogeologic data. The new model was also used to search for new candidate lunar basins greater than 300 km in diameter. We eliminated 11 of 27 candidates previously identified in the older crustal thickness model, and found strong evidence for at least 8 new candidates.

Description: Topography and crustal thickness data from LOLA altimetry were used to test the validity of 98 candidate large lunar basins derived from photogeologic and earlier topographic and crustal thickness data, and to search for possible new candidates. We eliminate 23 previous candidates but find good evidence for 20 new candidates. The number of basins greater than 300 km diameter on the Moon is almost certainly a factor 2 (maybe 3?) larger than the number of named features having basin-like topography. Unified Lunar Control Net 2005 data [1] and model crustal thickness data [2] were previously used to search for possible previously unrecognized large lunar impact basins [3,4]. An inventory of 98 candidate topographic basins greater than 300 km in diameter was found [5]. This includes 33 named features (only those having basin-like topography) out of the 45 listed by Wilhelms [6], 38 additional Quasi-Circular Depressions (QCDs) found in the ULCN2005 topography, and 27 Circular Thin Areas (CTAs) found in model crustal thickness data [2]. Most named features and additional QCDs have strong CTA signatures, but there may be a class of CTAs that are not easily recognized in the old and low resolution ULCN2005 topography. Lunar Orbiter Laser Altimeter (LOLA) data have recently become publically available. We used these data to (a) refine the center and ring diameters of known basins, (b) test the viability of the candidate basins previously found (as described above), and (c) search for additional candidate basins not revealed by the earlier lower resolution data. We used the LOLA topography directly but also a recent new model crustal thickness data that includes Kaguya gravity data [7]. We repeated a Topographic Expression (TE) and a Crustal Thickness Expression (CTE) scoring exercise originally done with the basins found in ULCN and earlier model crustal thickness data [5]. Each candidate was scored on a scale from 0 (no topographic basin or circular thin area signature) to 5 (strong circular low or strong circular thin area signature). These were combined into a total score used to rank the probability for each candidate basin. We used the same GRIDVIEW software to stretch, contour and profile the LOLA and new crustal thickness data as was done with the ULCN2005 and older model crustal thickness data.

Description: Global satellite-based precipitation products have been widely used in research and applications around the world. Compared to ground-based observations, satellite-based measurements provide data on a global scale, especially in remote continents and over oceans. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to NASA global precipitation product archives including the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), as well as other global and regional precipitation products. Precipitation is one of the top downloaded and accessed parameters in the GES DISC data archive. Meanwhile, users want to easily locate and obtain data quality information at regional and global scales to better understand how precipitation products perform and how reliable they are. As a data service provider, it is necessary to provide easy access to data quality information. However, such information normally is not available, and when it is available, it is not in one place and difficult to locate. In this presentation, we will present such challenges and activities at the GES DISC to address precipitation data (other datasets as well) quality issues.

Description: Precipitation is a key environmental variable. For example, in agriculture, precipitation, temperature, water (soil moisture), solar radiation, NDVI, etc., are key variables.Rainfed agriculture major farming practices that rely on rainfall for water.Rainfed agriculture: 〉95% of farmed land (sub-Saharan Africa); 90% (Latin America); 75% (Near East and North Africa); 65% (East Asia); 60% (South Asia).Droughts and floods can cause severe crop loss. The Goddard Earth Sciences (GES) Data and Information Services Center (DISC), one of 12 NASA data centers, is located in Greenbelt, Maryland, USA. The NASA GES DISC is a major data archive center for global precipitation, water & energy cycles, atmospheric composition, and climate variability.

Description: Accessing and using NASA Earth science data has commonly presented a challenge to many educators and students, due to issues such as heterogeneous data formats, complex data structures, large volumes of data storage, special programming requirements, and diverse analytical software options that often require a significant investment in time and resources, especially for novices. By facilitating data access and evaluation, as well as promoting open access to create a more level playing field for non-funded scientists, NASA Earth observation data can be more readily used for scientific discovery and societal benefits. To advance this goal, the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) developed the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni). To date, Giovanni has assisted researchers around the world publish over 1300 peer-reviewed papers in a wide range of Earth science disciplines. In this presentation, we will demonstrate how easy it is to use Giovanni for the rapid creation of many different analyses of both weather and climate events.

Description: It is the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) mission statement to facilitate data access and evaluation, as well as scientific exploration and discovery. Recently, GES DISC has been evolving and improving our data management and services in order to promote GES DISC data to be easily discovered, improve usage and made more interoperable with common tools. As a result, we will present a brief review of our recent data services at the GES DISC including our new science-data driven website, subsetting and resampling services across multitude of satellite processing levels, visualization services, and how we utilize social media tools to interact with user communities.

Description: Recently, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has released global land 3-hourly Potential Evapotranspiration and Supporting Forcing Data Version-1 (PET_PU_3H025.001), at 0.25x0.25 degree spatial resolution, spanning the 23 year period from 1984 to 2006. The Version-2 will be released in the near future, covering longer time period. This dataset was generated by Professor Justin Sheffield through NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) project. Potential evapotranspiration (PET) is a representation of the environmental demand for evapotranspiration (ET). ET and PET are important part of the global water cycle estimation, and are also critical to advance our understanding of the climate system. NASA GES DISC archives and distributes various global and regional ET datasets from several projects, for example, Land Data Assimilation System (LDAS), Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), other MEaSUREs Projects, such as Land Surface Atmospheric Boundary Interaction Product by William Rossow; and SRB/GEWEX evapotranspiration (Penman-Monteith) by Eric F. Wood. In this presentation, we will overview all available PET and ET datasets and services at GES DISC. As examples, climatology and some seasonal characteristics of PET and selected ET will be shown. The data can be accessed from NASA GES DISC (https://disc.gsfc.nasa.gov/) by searching keyword "evapotranspiration".

Description: We report oxygen isotopic compositions for 14 zircon grains from a sample of sawdust from lunar breccia 14321. The zircons range in age from approx.4.4 to 3.9 Ga and in U and Th content from a few to several hundred ppm. As such these grains represent a range of possible source rocks, from granophyric to mafic composition, and cover the total age range of the major initial lunar bombardment. Nevertheless, results show that the oxygen isotopic compositions of the zircons fall within a narrow range of (delta18)O of about 1 per mil and have (delta18)O values indistinguishable from those observed for terrestrial mid-ocean ridge basalts confirming the coincidence of lunar and Earth oxygen isotopic compositions. In the (delta17)O vs. (delta18)O, coordinates data form a tight group with a limited trend on the terrestrial fractionation line. The zircon oxygen isotopes show minimal evidence of the extreme and variable mineral differentiation and element fractionation that have contributed to the formation of their parent rocks.

Description: NASA Earth science data collected from satellites, model assimilation, airborne missions, and field campaigns, are large, complex and evolving. Such characteristics pose great challenges for end users (e.g., Earth science and applied science users, students, citizen scientists), particularly for those who are unfamiliar with NASA's EOSDIS and thus unable to access and utilize datasets effectively. For example, a novice user may simply ask: what is the total rainfall for a flooding event in my county yesterday? For an experienced user (e.g., algorithm developer), a question can be: how did my rainfall product perform, compared to ground observations, during a flooding event? Nonetheless, with rapid information technology development such as natural language processing, it is possible to develop simplified Web interfaces and back-end processing components to handle such questions and deliver answers in terms of text, data, or graphic results directly to users.In this presentation, we describe the main challenges for end users with different levels of expertise in accessing and utilizing NASA Earth science data. Surveys reveal that most non-professional users normally do not want to download and handle raw data as well as conduct heavy-duty data processing tasks. Often they just want some simple graphics or data for various purposes. To them, simple and intuitive user interfaces are sufficient because complicated ones can be difficult and time-consuming to learn. Professionals also want such interfaces to answer many questions from datasets. One solution is to develop a natural language based search box like Google and the search results can be text, data, graphics and more. Now the challenge is, with natural language processing, can we design a system to process a scientific question typed in by a user? In this presentation, we describe our plan for such a prototype. The workflow is: 1) extract needed information (e.g., variables, spatial and temporal information, processing methods, etc.) from the input, 2) process the data in the backend, and 3) deliver the results (data or graphics) to the user.