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At least 1,693 records · Page 94

Leaf Nitrogen, Leaf Mass Area, Leaf Water Content, Seward Peninsula, Alaska, 2017

Nitrogen and carbon content, leaf mass per area and leaf water content of leaves sampled from the NGEE Arctic Teller study site, Seward Peninsula, Alaska in 2017. Data is included for 13 species from the deciduous shrub, forb and graminoid plant functional types. See related dataset for leaf reflective spectra, sample photographs and dGPS locations. This data package includes leaf sample information and trait data (*.csv). Note that leaf nitrogen content analysis was performed on a subset of samples. Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA103_flmd.csv. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Seasonal to Decadal-Scale Variability in Satellite Ocean Color and Sea Surface Temperature for the California Current System

Support for this project was used to develop satellite ocean color and temperature indices (SOCTI) for the California Current System (CCS) using the historic record of CZCS West Coast Time Series (WCTS), OCTS, WiFS and AVHRR SST. The ocean color satellite data have been evaluated in relation to CalCOFI data sets for chlorophyll (CZCS) and ocean spectral reflectance and chlorophyll OCTS and SeaWiFS. New algorithms for the three missions have been implemented based on in-water algorithm data sets, or in the case of CZCS, by comparing retrieved pigments with ship-based observations. New algorithms for absorption coefficients, diffuse attenuation coefficients and primary production have also been evaluated. Satellite retrievals are being evaluated based on our large data set of pigments and optics from CalCOFI.

Mitchell, B. Greg↗

ACIX-Aqua: A Global Assessment of Atmospheric Correction Methods for Landsat-8 and Sentinel-2 Over Lakes, Rivers, and Coastal Waters

Atmospheric correction over inland and coastal waters is one of the major remaining challenges in aquatic remote sensing, often hindering the quantitative retrieval of biogeochemical variables and analysis of their spatial and temporal variability within aquatic environments. The Atmospheric Correction Intercomparison Exercise (ACIX-Aqua), a joint NASA – ESA activity, was initiated to enable a thorough evaluation of eight state-of-the-art atmospheric correction (AC) processors available for Landsat-8 and Sentinel-2 data processing. Over 1000 radiometric matchups from both freshwaters (rivers, lakes, reservoirs) and coastal waters were utilized to examine the quality of derived aquatic reflectances (ρ̂w). This dataset originated from two sources: Data gathered from the international scientific community (henceforth called Community Validation Database, CVD), which captured predominantly inland water observations, and the Ocean Color component of AERONET measurements (AERONET-OC), representing primarily coastal ocean environments. This volume of data permitted the evaluation of the AC processors individually (using all the matchups) and comparatively (across seven different Optical Water Types, OWTs) using common matchups. We found that the performance of the AC processors differed for CVD and AERONET-OC matchups, likely reflecting inherent variability in aquatic and atmospheric properties between the two datasets. For the former, the median errors in ρ̂w560 and ρ̂w664 were found to range from 20 to 30% for best-performing processors. Using the AERONET-OC matchups, our performance assessments showed that median errors within the 15–30% range in these spectral bands may be achieved. The largest uncertainties were associated with the blue bands (25 to 60%) for best-performing processors considering both CVD and AERONET-OC assessments. We further assessed uncertainty propagation to the downstream products such as near-surface concentration of chlorophyll-a (Chla) and Total Suspended Solids (TSS). Using satellite matchups from the CVD along with in situ Chla and TSS, we found that 20–30% uncertainties in ρ̂w490≤λ≤743nm yielded 25–70% uncertainties in derived Chla and TSS products for top-performing AC processors. We summarize our results using performance matrices guiding the satellite user community through the OWT-specific relative performance of AC processors. Our analysis stresses the need for better representation of aerosols, particularly absorbing ones, and improvements in corrections for sky- (or sun-) glint and adjacency effects, in order to achieve higher quality downstream products in freshwater and coastal ecosystems.

Nima Pahlevan↗

Identification and spectral characteristics of hydrothermal alteration on Landsat TM imagery of north Chile

This study examines the application of Landsat TM data to the identification of hydrothermal alteration in the arid terrain of the El Salvador region of north Chile. Numerical reflectance values were extracted from the digital Landsat TM data for a variety of rock surfaces, including four parts of the El Salvador gossan, for each of six spectral bands. These reflectance values were analyzed statistically in order to select the three spectral bands, combined as a color composite image, that are most efficient in discriminating different varieties of alteration and for general geological interpretation. The most cost effective composite image for this area is a combination of bands 1, 4 and 7 as the blue, green and red components respectively, with simple contrast enhancement. This image is superior to some much more expensive enhancement techniques and allows unambiguous identification of areas of hydrothermal alteration larger than about 50 m. The display includes a practical guide to the use of Landsat TM imagery for volcanic gold exploration.

Baker, Michael C. W.↗

Investigation of Cloud Interior Structure Using a Tomographic Technique Based on Radon Transform. Application to the Measurements Made by the Research Scanning Polarimeter During CAMP2Ex

The Research Scanning Polarimeter (RSP) is an airborne along-track scanner measuring the polarized and total reflectances in 9 spectral channels. The RSP's uniquely high angular resolution coupled with the high frequency of measurements allows for characterization of liquid-water cloud droplet sizes using the rainbow structure observed in the polarized reflectance measurements. The RSP observations also provide for derivation of 2D field of extinction coefficient inside the cloud using a tomographic technique. This technique utilizes the family of cloud shapes derived using "cutout" technique and corresponding to a number of thresholds in total reflectance (separating bright cloud from its darker background). These shapes can be interpreted as level curves of an abstract "reflectance density", which is then used for derivation of the directional cloud optical thickness (dCOT) tomogram. The latter is a collection of dCOTs parameterized by the angles and offsets of the corresponding view rays (chords) relative to the cloud center. After this, the inverse Radon Transform (the mathematical basis of the X-ray com-puter tomography) is applied to the dCOT tomogram yielding 2D spatial distribution of the extinction coefficient. The later can be converted into droplet number concentration using the droplet size profiles derived from the RSP's polarized reflectance measurements. After tests on synthetic data this technique was applied to real RSP measurements from NASA's Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) conducted in the vicinity of the Philippines during the Southwest Monsoon (August–September 2019). We have investigated the interiors of a number of clouds observed during CAMP2Ex focusing on Cu and CuCg (Tcu) cases. Our retrievals were routinely compared with the correlative measurements by lidar (HSRL-2) and cloud radar (APR-3) that were deployed on the same airborne platform (NASA P-3B) during this field experiment.

Research Scanning Polarimeter↗

A Web-based application for the collection, management and release of Alignment and Calibration configurations used in data processing at the Compact Muon Solenoid experiment

The Compact Muon Solenoid (CMS) experiment makes a vast use of alignment and calibration measurements in several data processing workflows: in the High Level Trigger, in the processing of the recorded collisions and in the production of simulated events for data analysis and studies of detector upgrades. A complete alignment and calibration scenario is factored in approximately three-hundred records, which are updated independently and can have a time-dependent content, to reflect the evolution of the detector and data taking conditions. Given the complexity of the CMS condition scenarios and the large number (50) of experts who actively measure and release calibration data, in 2015 a novel web-based service has been developed to structure and streamline their management. The cmsDbBrowser provides an intuitive and easily accessible entry point for the navigation of existing conditions by any CMS member, for the bookkeeping of record updates and for the actual composition of complete calibration scenarios. This paper describes the design, choice of technologies and the first year of usage in production of the cmsDbBrowser.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Game Based Learning For Earth Science Applications Training

Current NASA Earth capacity development programs employ mechanisms ranging from online resource sharing, and virtual and in-person trainings to share knowledge. While these programs are highly successful at engaging individuals around the world – in 2018, over 8000 individuals and over 2000 institutions from all 50 US states and over 140 countries were engaged through over 150 projects and trainings – user feedback has highlighted the desire for expanded hands-on, practical experiences in incorporating NASA EO insights with localized data and actions. We aim to address this gap by leveraging the benefits of game-based learning to build user skills in integrating NASA and local EO data to guide decisions for climate resiliency and hazard planning. This project is being executed as a two-phase crowdsourced challenge: 1) Phase 1 will require a well-researched product concept that reflects an understanding of NASA’s Earth data and tools and user needs, and proposes an innovative and interactive game or extended reality experience to train users in identifying relevant NASA data and applying insights to their climate resiliency decisions; 2) Winners of Phase 1 will be provided seed funding to develop a working prototype of the product. We aim to award 1-3 final winners to support the development of more than one game, thereby ensuring that NASA's diverse audiences around the world can access training games that best suit their needs and capabilities. This EO training game project fits in the NASA Earth Science Applied Sciences Program’s Capacity Development Program, contributing to the program mission of “helping people around the world better understand [NASA’s Earth] data and find ways to use them” (https://appliedsciences.nasa.gov/what-we-do/capacity-building). The final training game will complement existing programmatic activities of workforce development, trainings, and collaborative projects, while providing the unique value of providing interactive experiences to users and collecting real-time data and feedback to improve NASA’s Earth applications’ products and services related to climate resilience.

Human centered design↗

Impeller flow field characterization with a laser two-focus velocimeter

Use of Computational Fluid Dynamics (CFD) codes, prevalent in the rocket engine turbomachinery industry, necessitates data of sufficient quality and quantity to benchmark computational codes. Existing data bases for typical rocket engine configurations, in particular impellers, are limited. In addition, traditional data acquisition methods have several limitations: typically transducer uncertainties are 0.5% of transducer full scale and traditional pressure probes are unable to provide flow characteristics in the circumferential (blade-to-blade) direction. Laser velocimetry circumvents these limitations by providing +0.5% uncertainty in flow velocity and +0.5% uncertainty in flow angle. The percent of uncertainty in flow velocity is based on the measured value, not full range capability. The laser electronics multiple partitioning capability allows data acquired between blades as the impeller rotates, to be analyzed separately, thus providing blade-to-blade flow characterization. Unlike some probes, the non-intrusive measurements made with the laser velocimeter does not disturb the flow. To this end,, and under Contract (NAS8-38864) to the National Aeronautics and Space Administration (NASA) at Marshall Space Flight Center (MSFC), an extensive test program was undertaken at Rocketdyne. Impellers from two different generic rocket engine pump configurations were examined. The impellers represent different spectrums of pump design: the Space Shuttle Main Engine (SSME) high pressure fuel turbopump (HPFTP) impeller was designed in the 1 1970's the Consortium for CFD application in Propulsion Technology Pump Stage Technology Team (Pump Consortium) optimized impeller was designed with the aid of modern computing techniques. The tester configuration for each of the impellers consisted of an axial inlet, an inducer, a diffuser, and a crossover discharge. While the tested configurations were carefully chosen to be representative of generic rocket engine pumps, several features of both testers were intentionally atypical. A crossover discharge, downstream of the impeller, rather than a volute discharge was used to minimize asymmetric flow conditions that might be reflected in the impeller discharge flow data. Impeller shroud wear ring radial clearances were purposely close to minimize leakage flow, thus increasing confidence in using the inlet data as an input to CFD programs. The empirical study extensively examined the flow fields of the two impellers via performance of laser two-focus velocimeter surveys in an axial plane upstream of the impellers and in multiple radial planes downstream of the impellers. Both studies were performed at the impeller design flow coefficients. Inlet laser surveys that provide CFD code inlet boundary conditions were performed in one axial plane, with ten radial locations surveyed. Three wall static pressures, positioned circumferentially around the impeller inlet, were used to identify asymmetrical pressure distributions in the inlet survey plane. The impeller discharge flow characterization consisted of three radial planes for the SSME HPFTP impeller and two radial planes for the Pump Consortium optimized impeller. Housing wall static pressures were placed to correspond to the radial locations surveyed with the laser velocimeter. Between five and thirteen axial stations across the discharge channel width were examined in each radial plane during the extensive flow mapping. The largely successful empirical flow characterization of two different impellers resulted in a substantial contribution to the limited existing data base, and yielded accurate data for CFD code benchmarking.

Brozowski, L. A.↗

Evaluation of Electrical Resistivity Tomography to Monitor the Transport of Past Releases Beneath Tank Farms

Underground storage tanks at the Hanford Site, in southeastern Washington State, hold radioactive waste generated from four decades of plutonium production. The 149 single-shell tanks and the 28 double-shell tanks have all exceeded their initial design life of approximately 25 years. At least 67 tanks are assumed to have leaked in the past, resulting in radioactive releases into the vadose zone. Gamma ray logging within dry monitoring wells is currently the primary method for tracking the migration of leaked tank waste through the vadose zone. While this approach provides an accurate assessment of radioactive contamination, that information is only provided near (within ~1m) the borehole, leaving most of the vadose zone unmonitored, particularly the important region directly beneath the tank. This report describes a numerical study that investigates the feasibility and performance of time-lapse 3D electrical resistivity tomography (ERT) for long-term monitoring of a hypothetical tank waste location and migration through the vadose zone. ERT is a method of remotely imaging the bulk electrical conductivity (EC) of the subsurface, which is significantly impacted by the presence of conductive solid and liquid tank waste. The release of liquid tank wastes increases subsurface fluid conductivity and saturation over time, creating a target to use time-lapse ERT for long-term monitoring. Although the presence of metallic infrastructure can cause ERT interference, recent advancements in ERT data processing enable the deleterious effects of buried metallic infrastructure (e.g. pipes, wellbore casings, tanks) to be removed to better determine the liquid tank waste migration over time. Three hypothetical realistic scenarios were simulated in the ERT evaluation. The first two scenarios assume the same leak amount and rate (i.e., between 1/1/1951 and 12/31/1951 at the rate of 347 m 3 per year) but different leaky tanks. Scenario 1 assumes leaks under tank B-102, which is located on the edge of the B-tank farm and surrounded by a few metallic infrastructure including cased pipes/wells/tanks. Scenario 2 assumes leaks under tank B-108, which is located near the center of the B-tank farm and surrounded by larger amount of metallic infrastructure than B-102. Scenario 3 assumes the same metallic infrastructure as B-102, with a more recent contaminant leak that was simulated to have occurred between 1/1/2018 and 12/31/2023 at a rate of 1.89 m 3 per year. The leak time in Scenarios 1 and 2 corresponds to a historical overfill event in 1951 and Scenario 3 corresponds to a recent found tank leak in 2019. In each scenario, a “true” bulk EC model vs. time reflecting contaminant migration was generated. ERT data was simulated from these “true” bulk EC models and a time-lapse ERT inversion produced “imaged” bulk EC vs. time. Three electrode configurations in two, four and eight boreholes surrounding the leak tank were used in the ERT simulations in each scenario. These borehole configurations were considered logistically feasible and cost-effective for monitoring. The hypothetical ERT boreholes are assumed to have non-metallic casing. By comparing the “imaged” bulk EC with the “true” bulk EC, it was demonstrated that the three configurations of wells used (two, four, and eight wells) were able to successfully monitor the migration of tank leaks through the vadose zone, with bulk EC resolution increasing with the number of down borehole ERT arrays for all scenarios. Therefore, the use of eight boreholes to perform ERT monitoring beneath the tanks provided the best spatiotemporal information.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

HTESP (High-throughput electronic structure package): A package for high-throughput ab initio calculations

High-throughput ab initio calculations are the indispensable parts of data-driven discovery of new materials with desirable properties, as reflected in the establishment of several online material databases. The accumulation of extensive theoretical data through computations enables data-driven discovery by constructing machine learning and artificial intelligence models to predict novel compounds and forecast their properties. Efficient usage and extraction of data from these existing online material databases can accelerate the next stage materials discovery that targets different and more advanced properties, such as electron–phonon coupling for phonon-mediated superconductivity. However, extracting data from these databases, generating tailored input files for different ab initio calculations, performing such calculations, and analyzing new results can be demanding tasks. Here, in this work, we introduce a software package named “HTESP” (High-Throughput Electronic Structure Package) written in Python and Bash languages, which automates the entire workflow including data extraction, input file generation, calculation submission, result collection and plotting. Our HTESP will help speed up future computational materials discovery processes.

36 MATERIALS SCIENCE↗

Imaging Systems Provide Maps for U.S. Soldiers

Spanning nearly four decades, the remarkable Landsat program has continuously provided data about the Earth s surface, including detailed maps of vegetation, land use, forest extent and health, surface water, population distribution, as well as how these features have changed over time. Managed by NASA and the U.S. Geological Survey, Landsat s series of satellites obtain data through passive remote sensing, or the use of sensors to read the energy reflected or emitted from the Earth s surface. After the data from the sensors is processed and analyzed, it can be applied to create information-rich images of the planet. While the Landsat program has launched seven satellites since 1972, only Landsat 5 and 7 are currently operating. The next spacecraft in line to ensure continuity of data for years to come is the Landsat Data Continuity Mission (LDCM). Planned for launch in 2012, LDCM will take measurements of the Earth in visible, nearinfrared, shortwave infrared, and thermal infrared bands. In addition to widespread use for land use planning and monitoring on local to regional scales, support for disaster response and evaluations, as well as water use monitoring, LDCM measurements will directly serve NASA s research in the areas of climate, the carbon cycle, ecosystems, the water cycle, biogeochemistry, and Earth s surface and interior.

Source record↗

Geonex: A NASA-NOAA Collaboration for Producing Land Surface Products from Geostationary Sensors Using Cloud Computing

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement.Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. We estimate the cost of deploying GEONEX to be $400 - 750 a month for processing data (every 30 minutes) and producing products over the conterminous US. For products such as Fire, latency can be as little as 10 minutes from the time of data acquisition.

Geostationary↗

GEONEX: Webpage to Display NASA-NOAA Collaboration of Producing Land Surface Products from Geostationary Sensors

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement.In order to better introduce the GEONEX products to the science community, we set up a simple webpage (www.geonex.org) to describe the background and the motivation of the project, the algorithms used in deriving the products, and user manuals to the data files. We will also update the status of the data processing, in particular the near-real-time products, on the website and provide links (in text or json files) to the latest datasets.

geostationary↗

Geonex: Land Surface Monitoring from a New Generation of Geostationary Sensors

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

Nemani, Ramakrishna R.↗

Earth Observations from Geostationary Satellites

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GeoNEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GeoNEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GeoNEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

Earth↗

GeoNEX: Land Monitoring from a New Generation of Geostationary Sensors

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

GeoNEX↗

Influence of dissolved organic materials on turbid water optical properties and remote-sensing reflectance

The effects of dissolved organic materials on turbid-water optical properties are assessed, by means of field measurements and laboratory simulations in which upwelled reflectance, attenuation, absorption, and backscatter spectral properties at wavelengths from 450 to 800 nm are examined in relation to water chemistry. The data show that dissolved organic materials decrease upwelled reflectance from turbid waters, and that the decrease in reflectance is a nonlinear function of concentration with the largest gradients at low carbon concentrations, depending on wavelength. Upwelled reflectance is found to be highly correlated with two backscatter-absorption parameters used in some optical models, which are nonlinear with dissolved organic material concentration change.

Witte, W. G.↗

Bistatic radar measurements of the surface of Mars with Mariner 1969.

The detection of echoes produced by oblique reflection of the RF (2300 MHz) spacecraft carrier from the Martian surface as Mariner 6 and 7 flew behind Mars in 1969, is described. Changes in echo center frequency and bandwidth are utilized to study the radius and roughness of the surface along a quasi-specular radar track that led from an optically dark and densely cratered region of Meridiani Sinus over into a smoother and brighter looking area of Thymiamata. A 3 to 1 decrease in surface roughness of large size compared to the wavelength (13 cm) was observed as the reflecting zone moved across the boundary between these two regions. The average radius obtained along the track was 3393 plus or minus 3 km. Due to large angles of incidence (86 to 90 deg), and surface shadowing, the data are not suitable for mapping the reflection coefficient of the surface material.

Fjeldbo, G.↗