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All sources NASA NTRS DOE OSTI

NASA NTRS2016

Airborne Spectral BRDF of Various Surface Types (Ocean, Vegetation, Snow, Desert, Wetlands, Cloud Decks, Smoke Layers) for Remote Sensing Applications

In this paper we describe measurements of the bidirectional reflectance-distribution function (BRDF) acquired over a 30-year period (1984-2014) by the National Aeronautics and Space Administration's (NASA's) Cloud Absorption Radiometer (CAR). Our BRDF database encompasses various natural surfaces that are representative of many land cover or ecosystem types found throughout the world. CAR's unique measurement geometry allows a comparison of measurements acquired from different satellite instruments with various geometrical configurations, none of which are capable of obtaining such a complete and nearly instantaneous BRDF. This database is therefore of great value in validating many satellite sensors and assessing corrections of reflectances for angular effects. These data can also be used to evaluate the ability of analytical models to reproduce the observed directional signatures, to develop BRDF models that are suitable for sub-kilometer-scale satellite observations over both homogeneous and heterogeneous landscape types, and to test future spaceborne sensors. All of these BRDF data are publicly available and accessible in hierarchical data format (http:car.gsfc.nasa.gov/).

albedo↗

NASA NTRS2012

NASA IMAGESEER: NASA IMAGEs for Science, Education, Experimentation and Research

A number of web-accessible databases, including medical, military or other image data, offer universities and other users the ability to teach or research new Image Processing techniques on relevant and well-documented data. However, NASA images have traditionally been difficult for researchers to find, are often only available in hard-to-use formats, and do not always provide sufficient context and background for a non-NASA Scientist user to understand their content. The new IMAGESEER (IMAGEs for Science, Education, Experimentation and Research) database seeks to address these issues. Through a graphically-rich web site for browsing and downloading all of the selected datasets, benchmarks, and tutorials, IMAGESEER provides a widely accessible database of NASA-centric, easy to read, image data for teaching or validating new Image Processing algorithms. As such, IMAGESEER fosters collaboration between NASA and research organizations while simultaneously encouraging development of new and enhanced Image Processing algorithms. The first prototype includes a representative sampling of NASA multispectral and hyperspectral images from several Earth Science instruments, along with a few small tutorials. Image processing techniques are currently represented with cloud detection, image registration, and map cover/classification. For each technique, corresponding data are selected from four different geographic regions, i.e., mountains, urban, water coastal, and agriculture areas. Satellite images have been collected from several instruments - Landsat-5 and -7 Thematic Mappers, Earth Observing-1 (EO-1) Advanced Land Imager (ALI) and Hyperion, and the Moderate Resolution Imaging Spectroradiometer (MODIS). After geo-registration, these images are available in simple common formats such as GeoTIFF and raw formats, along with associated benchmark data.

Le Moigne, Jacqueline↗

NASA NTRS2011

Atmospheric Composition Change: Climate-Chemistry Interactions

Chemically active climate compounds are either primary compounds such as methane (CH4), removed by oxidation in the atmosphere, or secondary compounds such as ozone (O3), sulfate and organic aerosols, formed and removed in the atmosphere. Man-induced climate-chemistry interaction is a two-way process: Emissions of pollutants change the atmospheric composition contributing to climate change through the aforementioned climate components, and climate change, through changes in temperature, dynamics, the hydrological cycle, atmospheric stability, and biosphere-atmosphere interactions, affects the atmospheric composition and oxidation processes in the troposphere. Here we present progress in our understanding of processes of importance for climate-chemistry interactions, and their contributions to changes in atmospheric composition and climate forcing. A key factor is the oxidation potential involving compounds such as O3 and the hydroxyl radical (OH). Reported studies represent both current and future changes. Reported results include new estimates of radiative forcing based on extensive model studies of chemically active climate compounds such as O3, and of particles inducing both direct and indirect effects. Through EU projects such as ACCENT, QUANTIFY, and the AEROCOM project, extensive studies on regional and sector-wise differences in the impact on atmospheric distribution are performed. Studies have shown that land-based emissions have a different effect on climate than ship and aircraft emissions, and different measures are needed to reduce the climate impact. Several areas where climate change can affect the tropospheric oxidation process and the chemical composition are identified. This can take place through enhanced stratospheric-tropospheric exchange of ozone, more frequent periods with stable conditions favouring pollution build up over industrial areas, enhanced temperature-induced biogenic emissions, methane releases from permafrost thawing, and enhanced concentration through reduced biospheric uptake. During the last 510 years, new observational data have been made available and used for model validation and the study of atmospheric processes. Although there are significant uncertainties in the modelling of composition changes, access to new observational data has improved modelling capability. Emission scenarios for the coming decades have a large uncertainty range, in particular with respect to regional trends, leading to a significant uncertainty range in estimated regional composition changes and climate impact.

Atmosphere climate chemistry↗

NASA NTRS2007

The NASA Human Space Flight Supply Chain, Current and Future

The current NASA Human Space Flight transportation system, the Space Shuttle, is scheduled for final flight in 2010. The Exploration initiative will create a new capability with a combination of existing systems and new flight and ground elements. To fully understand and act on the implications of such change it is necessary to understand what, how, when and where such changes occur and more importantly, how all these interact. This paper presents Human Space Flight, with an emphasis on KSC Launch and Landing, as a Supply Chain of both information and materials. A supply chain methodology for understanding the flow of information and materials is presented. Further, modeling and simulation projects funded by the Exploration initiative to understand the NASA Exploration Supply Chain are explained. Key concepts and their purpose, including the Enterprise, Locations, Physical and Organizational Functional Units, Products, and Resources, are explained. It is shown that the art, science and perspective of Supply Chain Management is not only applicable to such a government & contractor operation, it is also an invaluable approach for understanding, focusing improvement and growth. It is shown that such commercial practice applies to Human Space Flight and is invaluable towards one day creating routine, affordable access to and from space.

supply chain managemen↗

NASA NTRS2017

Online Visualization and Value Added Services of MERRA-2 Data at GES DISC

NASA climate reanalysis datasets from MERRA-2, distributed at the Goddard Earth Sciences Data and Information Services Center (GES DISC), have been used in broad research areas, such as climate variations, extreme weather, agriculture, renewable energy, and air quality, etc. The datasets contain numerous variables for atmosphere, land, and ocean, grouped into 95 products. The total archived volume is approximately 337 TB ( approximately 562K files) at the end of October 2017. Due to the large number of products and files, and large data volumes, it may be a challenge for a user to find and download the data of interest. The support team at GES DISC, working closely with the MERRA-2 science team, has created and is continuing to work on value added data services to best meet the needs of a broad user community. This presentation, using aerosol over Asia Monsoon as an example, provides an overview of the MERRA-2 data services at GES DISC, including: How to find the data? How many data access methods are provided? What are the best data access methods for me? How do download the subsetted (parameter, spatial, temporal) data and save in preferred spatial resolution and data format? How to visualize and explore the data online? In addition, we introduce a future online analytic tool designed for supporting application research, focusing on long-term hourly time-series data access and analysis.

Shen, Suhung↗

NASA NTRS2024

Extravehicular Activity and Human Surface Mobility Program (EHP) Exploration EVA (xEVA) System Compatibility Standards

Extravehicular Activity (EVA) is a significant capability for Artemis Systems which includes Gateway Program (modules), Human Landing System (HLS) Program (Integrated Lander and Human Class Delivery Lander), Lunar Terrain Vehicle (LTV), Pressurized Rover (PR), Payloads, and any other future lunar surface assets that will be utilized for exploration or science. The EVA and Human Surface Mobility Program (EHP) will provide the following: Exploration EVA (xEVA) suits, xEVA tools and crew aids along with vehicle integration/support hardware, LTV, and PR. Being a distributed and dynamic capability (moving components), xEVA System hardware will interface with almost all elements of the Artemis architecture. As such, it is important to document a singular set of EVA compatibility standards at the programmatic level to articulate “how to interface with xEVA suit hardware” and “how to design hardware that EVA crewmembers will access and manipulate.”

Exploration↗

DOE OSTI2020

SICOPOLIS-AD v1: an open-source adjoint modeling framework for ice sheet simulation enabled by the algorithmic differentiation tool OpenAD

We present a new capability of the ice sheet model SICOPOLIS that enables flexible adjoint code generation via source transformation using the open-source algorithmic differentiation (AD) tool OpenAD.The adjoint code enables efficient calculation of the sensitivities of a scalar-valued objective function or quantity of interest (QoI) to a range of important, often spatially varying and uncertain model input variables, including initial and boundary conditions, as well as model parameters.Compared to earlier work on the adjoint code generation of SICOPOLIS, our work makes several important advances:(i) it is embedded within the up-to-date trunk of the SICOPOLIS repository – accounting for 1.5 decades of code development and improvements – and is readily available to the wider community;(ii) the AD tool used, OpenAD, is an open-source tool;(iii) the adjoint code developed is applicable to both Greenland and Antarctica, including grounded ice as well as floating ice shelves, with an extended choice of thermodynamical representations.A number of code refactorization steps were required. They are discussed in detail in an Appendix as they hold lessons for the application of AD to legacy codes at large.As an example application, we examine the sensitivity of the total Antarctic Ice Sheet volume to changes in initial ice thickness, austral summer precipitation, and basal and surface temperatures across the ice sheet.Simulations of Antarctica with floating ice shelves show that over 100 years of simulation the sensitivity of total ice sheet volume to the initial ice thickness and precipitation is almost uniformly positive, while the sensitivities to surface and basal temperature are almost uniformly negative. Sensitivity to austral summer precipitation is largest on floating ice shelves from Queen Maud to Queen Mary Land. The largest sensitivity to initial ice thickness is at outlet glaciers around Antarctica. Comparison between total ice sheet volume sensitivities to surface and basal temperature shows that surface temperature sensitivities are higher broadly across the floating ice shelves, while basal temperature sensitivities are highest at the grounding lines of floating ice shelves and outlet glaciers. A uniformly perturbed region of East Antarctica reveals that, among the four control variables tested here, total ice sheet volume is the most sensitive to variations in austral summer precipitation as formulated in SICOPOLIS.Comparison between adjoint- and finite-difference-derived sensitivities shows good agreement, lending confidence that the AD tool is producing correct adjoint code.The new modeling infrastructure is freely available at http://www.sicopolis.net (last access: 2 April 2020) under the development trunk.

58 GEOSCIENCES↗

NASA NTRS2015

OSIRIS-REx, Returning the Asteroid Sample

This paper addresses the technical aspects of the sample return system for the upcoming Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer (OSIRIS-REx) asteroid sample return mission. The overall mission design and current implementation are presented as an overview to establish a context for the technical description of the reentry and landing segment of the mission.The prime objective of the OSIRIS-REx mission is to sample a primitive, carbonaceous asteroid and to return that sample to Earth in pristine condition for detailed laboratory analysis. Targeting the near-Earth asteroid Bennu, the mission launches in September 2016 with an Earth reentry date of September 24, 2023.OSIRIS-REx will thoroughly characterize asteroid Bennu providing knowledge of the nature of near-Earth asteroids that is fundamental to understanding planet formation and the origin of life. The return to Earth of pristine samples with known geologic context will enable precise analyses that cannot be duplicated by spacecraft-based instruments, revolutionizing our understanding of the early Solar System. Bennu is both the most accessible carbonaceous asteroid and one of the most potentially Earth-hazardous asteroids known. Study of Bennu addresses multiple NASA objectives to understand the origin of the Solar System and the origin of life and will provide a greater understanding of both the hazards and resources in near-Earth space, serving as a precursor to future human missions to asteroids.This paper focuses on the technical aspects of the Sample Return Capsule (SRC) design and concept of operations, including trajectory design and reentry retrieval. Highlights of the mission are included below.The OSIRIS-REx spacecraft provides the essential functions for an asteroid characterization and sample return mission: attitude control propulsion power thermal control telecommunications command and data handling structural support to ensure successful rendezvous with Bennu characterization of Bennus properties delivery of the sampler to the surface, and return of the spacecraft to the vicinity of the Earth sample collection, performed by the Touch-and-Go Sample Acquisition Mechanism (TAGSAM), to acquire a regolith sample from the surface Earth re-entry and SRC recovery. Following sample collection, OSIRIS-REx drifts away from Bennu until the Asteroid Departure Maneuver is commanded on March 4, 2021, sending OSIRIS-REx on a ballistic return cruise to Earth. No additional large deterministic maneuvers are required to return the SRC to Earth. During the cruise, tracking and trajectory correction maneuvers (TCMs) are performed as necessary to precisely target the entry corridor. As OSIRIS-REx approaches Earth, the reentry plans are reviewed starting about a year before arrival, and preparations begin. The spacecraft is targeted away from the Earth until 7 days before entry. The final two trajectory correction maneuvers bring the spacecraft on target toward the Utah Test and Training Range (UTTR), with sufficient time for contingency resolution. The SRC releases 4 hours prior to atmospheric entry interface and, using the Stardust capsule heritage design, employs a traditional drogue and main parachute descent system for a soft touchdown.

reentry↗

NASA NTRSDate not supplied

GeoNEX: A Geostationary Earth Observatory

The latest generation of geostationary satellites (Himawari 8/9, GOES-16/17, FY-4, GK-2A) carries sensors that closely mimic the spatial and spectral characteristics of widely used polar-orbiting, global monitoring sensors such as MODIS and VIIRS. When combined, data from various currently operating/planned geostationary platforms provide a geo-ring of hyper-temporal (5-10 minutes), multispectral observations at spatial resolutions as high as 500 m. These high frequency observations offer exciting new possibilities for monitoring our planet, including better retrievals of geophysical variables by overcoming cloud cover, enabling studies of diurnally varying phenomena in the atmosphere, land, and the oceans, and support operational decision-making in agriculture, hydrology and disaster management. The NASA Earth Exchange (NEX) team, in collaboration with scientists from JAXA, KARI, NOAA and other international institutions, created the GeoNEX (www.nasa.gov/geonex) pipeline to integrate data from all available geostationary platforms and produce and distribute spatially, temporally, and radiometrically consistent data for the earth science community. We envision various institutions adapting the Geo component (e.g., GeoNOAA, GeoKARI, GeoChiba, GeoJAXA, GeoCMA) and customizing the pipeline and downstream products to serve the local/regional research and applied science communities. To facilitate collaborative work among the partners, we have established the OpenNEX platform on the public cloud. OpenNEX provides researchers, developers, educators, and ordinary users with easy access to an integrated Earth science computational and data platform, enabling citizen scientists and application developers to realize the full value of GeoNEX data assets and software tools.

GeoNEX↗

NASA NTRS1996

Hypersonic Airbreathing Vehicles/Technologies

Hypersonic airbreathing horizontal takeoff and landing (HTOL) vehicles are highly integrated systems involving many advanced technologies. The design environment is variable rich, intricately networked, and sensitivity intensive; as such, it represents a tremendous challenge. Creating a viable design requires addressing three main elements: (1) an understanding of the 'figures of merit' and their relationship, (2) the development of sophisticated configuration discipline prediction methods and a synthesis procedure, and (3) the synergistic integration of advanced technologies across the discipline spectrum. This paper will focus on the vision for hypersonic airbreathing vehicles and the advanced technologies that forge the designs. Airbreathing hypersonics encompass endoatmospheric (airplanes...missiles are a part of the matrix but will not be included in this paper since they are an air force focus) and space access vehicles with speed from Mach 4 up to Mach 25 (orbital). These vehicles can be divided into two classes...cruisers and accelerators. The cruiser designs reflect high lift-to-drag whereas the accelerators reflect low drag per unit inlet capture; thus, the cross section of the accelerator attributes a much larger percentage to propulsion. One of the more design influencing items is fuel. The hydrogen fueled vehicles must be very volumetric efficient to contain the low density fuel and thus tend to be a bit bulgy (more conducive to lifting bodies or wing bodies) whereas with hydrocarbon fueled vehicles, the concern is loading because of the high density fuel; thus, they may tend to be more towards waveriders which are not usually very volumetric efficient. Hydrocarbon fuels (endothermic) are limited in their engine cooling capacity to below Mach 8.

Hunt, James L.↗

NASA NTRS1985

Activities of the Pilot Land Data System project

The University of Maryland's Remote Sensing Systems Laboratory submitted to NASA/Goddard an interim progress report on the work being conducted within its Pilot Land Data System IPLDS project. The Remote Sensing Systems Laboratory addressed the following tasks: (1) identify data types and data sources needed to describe the selected test sites in collaboration with Goddard's Hydrological Sciences Branch; (2) define the procedures necessary to access/acquire this data; (3) conduct meetings with the PLDS Systems Engineering Group to identify functional specification priorities for PLDS development; (4) assemble documentation on historical remotely sensed imagery and transfer of such information to the PLDS Data Management Group; (5) collect data identified by Goodard's Hydrological Sciences Branch for data set inventory in PLD; (6) develop a Workstation-PLDS system interface over high speed lines, (7) develop and test through a Phase 1 demonstration of a micro workstation to access PLDS; and (8) establish interdepartmental agreement of development of computer link for electronic access of water resources data from USGS.

Sircar, J. K.↗

NASA NTRS1998

NASA's Earth Observing System: The Transition from Climate Monitoring to Climate Change Prediction

Earth's 4.5 billion year history is a study in change. Natural geological forces have been rearranging the surface features and climatic conditions of our planet since its beginning. There is scientific evidence that some of these natural changes have not only led to mass extinctions of species (e.g., dinosaurs), but have also severely impacted human civilizations. For instance, there is evidence that a relatively sudden climate change caused a 300-year drought that contributed to the downfall of Akkadia, one of the most powerful empires in the Middle-East region around 2200 BC. More recently, the "little ice age" from 1200-1400 AD forced the Vikings to abandon Greenland when temperatures there dropped by about 1.5 C, rendering it too difficult to grow enough crops to sustain the population. Today, there is compelling scientific evidence that human activities have attained the magnitude of a geological force and are speeding up the rate of global change. For example, carbon dioxide levels have risen 30 percent since the industrial revolution and about 40 percent of the world's land surface has been transformed by humans. We don't understand the cause-and-effect relationships among Earth's land, ocean, and atmosphere well enough to predict what, if any, impacts these rapid changes will have on future climate conditions. We need to make many measurements all over the world, over a long period of time, in order to assemble the information needed to construct accurate computer models that will enable us to forecast climate change. In 1988, the Earth System Sciences Committee, sponsored by NASA, issued a report calling for an integrated, long-term strategy for measuring the vital signs of Earth's climate system. The report urged that the measurements must all be intimately coupled with focused process studies, they must facilitate development of Earth system models, and they must be stored in an information system that ensures open access to consistent, long-term data. This committee emphasized that the only feasible way to collect these consistent, long-term data is through the use of space-based Earth "remote sensors" (instruments that can measure from a distance things like temperature).

King, Michael D.↗

DOE OSTI2021

Elucidating and predicting the dynamic evolution of water and land systems due to natural and energy-related forcings

Focal Area(s): 3. Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI; & 1. Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Science Challenge: Interactions between water, land, and energy systems are complex and occur on a variety of scales, ranging from local to basinal to regional. Accurately predicting the behavior of ground water and surface water systems for 5-10 years and beyond requires an understanding of the current system and the ability to model both the natural system at scale and human-induced forcings related to energy and other activities. Artificial intelligence and machine learning (AI/ML) combined with modern compilation and integration efforts for U.S. groundwater and surface water systems present potential solutions to bolstering detailed physics-based models of these systems. Big data tied with ML and physics-based modeling can drive breakthroughs in understanding the earth system, but research is often impeded by data access (e.g., privacy issues), quality, formats, gaps, multi-source, multi-scale, integration, and spatiotemporal challenges. Effective integration of real data and simulated (synthetic) data that fill gaps is critical. Overcoming these complex data and model integration challenges will enable a transformational approach to acquiring enhanced understanding of environmental systems.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

Understanding Fire Through Improved Technology

Aztec(TradeMark) is the commercial name for Southwest Sciences laser. The laser has coarse tuning ranges of 10 nanometers (nm) to 30 nm at wavelengths ranging from 630 nm to 2,300 nm, making it the only commercially available external cavity diode laser with wavelengths beyond 1,650 nm. The laser's high-speed tuning in both coarse and fine wavelength regimes allows for increased trace gas detection. With the automated coarse tuning option, the Aztec sweeps through its wavelength range in less than 1 millisecond. While some diode lasers can only detect one type, or species, of a trace gas, the Aztec's broad wavelength tuning provides access to multiple trace gas species. The Aztec has a wide range of applications for both NASA and commercial users, from protecting astronauts in space to improving combustion processes on Earth. It may serve as a new tool for planetary exploration, as it can detect a wide range of multiple gas species in planetary atmospheres. The laser could optically detect gaseous indicators of incipient fires on the International Space Station and Space Shuttle, as well as detect low concentrations of potentially toxic gases in spacecraft crew habitats. The laser could also provide more accurate fire detection in aircraft cargo compartments. Since the Aztec can detect several gases that only evolve during an actual fire, its implementation could reduce the large number of commercial aircraft landings that currently occur due to false alarms. Other applications include environmental and industrial process monitoring.

Source record↗

NASA NTRS2018

Robotic Infrastructure for Mars Outpost Water Supply

Intercontinental rovers servicing automated solar-powered Rodriguez Wells can supply water for Human Exploration on Mars. This paper describes a solar-powered multivehicle concept that can turn water resources obtained from mid-latitude glacier ice into a sustained water supply. A robotic drilling platform is proposed that can access relatively pure water ice in mid-latitude Martian glaciers through 1-10m of loose regolith, whereupon longdistance tanker rovers continually traverse terrain between the drilling operation and human outposts located in Mars equatorial zones. Robotically deployed solar-thermal panels will be able to passively heat warm water that is delivered into a Rodriguez Well (a melted cavity in an expanse of water ice such as a glacier). Newly melted water will be pumped up out of the well and cycled through the solar panels to fill tankers. The tankers will consist of multiple four-wheeled linked cars in a tram-like configuration that can overcome steep terrain and obstacles. The system will be able to deliver its own landed mass of water to the human explorers every ~74 Mars days. The resources, power, vehicle configurations, and detailed functions are described.

Howe, Scott A.↗

NASA NTRSDate not supplied

Climate Information and Lessons Learned from the NASA Earth eXchange (NEX), Short-term Prediction Research and Transition Center (NASA SPoRT), and the NASA Regional Climate Model Evaluation System (RCMES)

Climate resilience can emerge from a combination of (1) climate projections that enable future-oriented planning and (2) contemporary observations that can be used for adaptation in the face of realized climate. NASA is uniquely positioned to provide global climate projections and satellite-based observations to users who must take a global perspective on climate risk (e.g., supply chain managers). Here, we will share the capabilities and experiences of three NASA projects. The first project, the NASA Earth eXchange (NEX) provides two downscaled climate projections, NEX-GDDP-CMIP6, a global 25 km resolution product, and NEX-DCP30-CMIP6, an 800 m resolution product covering the coterminous U.S. specifically designed for U.S. National Climate Assessment (NCA). NEX also offers land surface products that mirror the twice-daily products provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) but are derived from operational geostationary weather satellite data collected at 5-10 minutes intervals. The second project, the Short-term Prediction Research and Transition Center (SPoRT), was established in 2002 to transition unique NASA satellite products and capabilities to stakeholders to improve decision-making that benefits society. SPoRT provides products and capabilities derived from NASA observations and models to end users in government, academia, and the private sector. SPoRT translates NASA Earth science into actionable solutions reaching over 400 stakeholders across 80 organizations. Finally, the Regional Climate Model Evaluation System (RCMES) is designed to facilitate regional-scale evaluations of climate models by providing standardized access to a vast and comprehensive set of observations, such as satellite, in-situ, and reanalyses, and modeling resources such as CMIP & CORDEX. These three projects form part of the core capabilities at the NASA Centers deliver climate information under the new NASA Earth Science to Action (ES2A) strategy.

NEX↗

NASA NTRS2008

The NASA NEESPI Data Portal to Support Studies of Climate and Environmental Changes in Non-Boreal Europe

NASA NEESPI (Northern Eurasia Earth Science Partnership Initiative) data portal is a NASA funded project that focuses on collecting satellite remote sensing data, providing tools, information, and services in support of NEESPI scientific objectives (Leptoukh, et al., 2007). The data can be accessed online through anonymous ftp, through an advanced data searching and ordering system Mirador that uses keywords to find data quickly in a Google-like interface, and through the Goddard Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni). The portal provides preprocessed data from different satellite sensors and numerical models to the same spatial and temporal resolution and the same projection so that the data can be used easily to perform inter-comparison or relationship studies. In addition, it provides parameter and spatially subsetted data for regional studies. Studies of regional carbon, hydrology, aerosols in non-boreal Europe and their interactions with global climate are very challenging research topics. The NASA NEESPI data portal makes many satellite data available for such studies, including information on land cover types, fire, vegetation index, aerosols, land surface temperature, soil moisture, precipitation, snow/ice, and other parameters. This paper will introduce the features and products available in the system, focusing on the online data 1 tool, Giovanni NEESPI. An example that explores different data through Giovanni NEESPI in temperate region of non-boreal Europe will be presented.

Shen, Suhung↗

NASA NTRS2016

A Quantum Annealing Computer Team Addresses Climate Change Predictability

The near confluence of the successful launch of the Orbiting Carbon Observatory2 on July 2, 2014 and the acceptance on August 20, 2015 by Google, NASA Ames Research Center and USRA of a 1152 qubit D-Wave 2X Quantum Annealing Computer (QAC), offered an exceptional opportunity to explore the potential of this technology to address the scientific prediction of global annual carbon uptake by land surface processes. At UMBC,we have collected and processed 20 months of global Level 2 light CO2 data as well as fluorescence data. In addition we have collected ARM data at 2sites in the US and Ameriflux data at more than 20 stations. J. Dorband has developed and implemented a multi-hidden layer Boltzmann Machine (BM) algorithm on the QAC. Employing the BM, we are calculating CO2 fluxes by training collocated OCO-2 level 2 CO2 data with ARM ground station tower data to infer to infer measured CO2 flux data. We generate CO2 fluxes with a regression analysis using these BM derived weights on the level 2 CO2 data for three Ameriflux sites distinct from the ARM stations. P. Gentine has negotiated for the access of K34 Ameriflux data in the Amazon and is applying a neural net to infer the CO2 fluxes. N. Talik validated the accuracy of the BM performance on the QAC against a restricted BM implementation on the IBM Softlayer Cloud with the Nvidia co-processors utilizing the same data sets. G. Nearing and K. Harrison have extended the GSFC LIS model with the NCAR Noah photosynthetic parameterization and have run a 10 year global prediction of the net ecosystem exchange. C. Pellisier is preparing a BM implementation of the Kalman filter data assimilation of CO2 fluxes. At UMBC, R. Prouty is conducting OSSE experiments with the LISNoah model on the IBM iDataPlex to simulate the impact of CO2 fluxes to improve the prediction of global annual carbon uptake. J. LeMoigne and D. Simpson have developed a neural net image registration system that will be used for MODIS ENVI and will be converted to a BM algorithm implementation on the QAC. The first integer adder has been implemented on the D-Wave 2X by A. Shehab that will perform HAAR wavelets for image compression of MODIS scenes. Finally, based on the next generations of QACs, we are preparing a 5-year performance road map on the scalability of the current QAC algorithms.

Science Data Processing↗