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NASA NTRS2021

Demonstration of a 1-D Submillimeter-Wave Phased Array with MEMS Phase Shifters

At submillimeter-wave frequencies, due to the nonavailability of low-loss phase shifters, electronic antenna beam scanning is difficult to realize. Traditionally, power-hungry and bulky motors are used to mechanically scan the antenna beam. At lower-frequencies, phased array antennas are most commonly used where low-loss phase shifters are used with the array elements to accomplish beam steering. However, development of similar phased array antennas at submillimeter-waves has been challenging. Recently, we have developed a low-loss microelectromechanical systems (MEMS) based phased shifter in the 500-750 GHz band. In this work, we present a submillimeter-wave phased array antenna system with a cavity-backed double slot antenna architecture using the MEMS-based phase shifters. To demonstrate the concept, we developed two arrays: first one is a 8×1 linear antenna array with a fixed waveguide feeding network that achieved ±20◦ beam scanning, 18 dB directivity, and less than 1 dB scan loss over the design frequency of 500–570 GHz. The second one is a 4 × 1 linear antenna array with integrated MEMS-based phase shifters on each array element, achieving 15 dB directivity and capable of dynamic beam scanning over a range of ±9 ◦ . All the plots presented are simulated results since the parts are currently being fabricated. We hope to have access to our assembly and measurement facilities over the next few months and present measured performances at the conference.

Chattopadhyay, G.↗
NASA NTRS1998

PIMS Data Storage, Access, and Neural Network Processing

The Principal Investigator Microgravity Services (PIMS) project at NASA's Lewis Research Center has supported microgravity science Principal Investigator's (PIs) by processing, analyzing, and storing the acceleration environment data recorded on the NASA Space Shuttles and the Russian Mir space station. The acceleration data recorded in support of the microgravity science investigated on these platforms has been generated in discrete blocks totaling approximately 48 gigabytes for the Orbiter missions and 50 gigabytes for the Mir increments. Based on the anticipated volume of acceleration data resulting from continuous or nearly continuous operations, the International Space Station (ISS) presents a unique set of challenges regarding the storage of and access to microgravity acceleration environment data. This paper presents potential microgravity environment data storage, access, and analysis concepts for the ISS era.

McPherson, Kevin M.↗
NASA NTRS1999

Silicon-Germanium Fast Packet Switch Developed for Communications Satellites

Emerging multimedia applications and future satellite systems will require high-speed switching networks to accommodate high data-rate traffic among thousands of potential users. This will require advanced switching devices to enable communication between satellites. The NASA Lewis Research Center has been working closely with industry to develop a state-of-the-art fast packet switch (FPS) to fulfill this requirement. Recently, the Satellite Industry Task Force identified the need for high-capacity onboard processing switching components as one of the "grand challenges" for the satellite industry in the 21st century. In response to this challenge, future generations of onboard processing satellites will require low power and low mass components to enable transmission of services in the 100 gigabit (1011 bits) per second (Gbps) range.

Quintana, Jorge A.↗
NASA NTRS2010

Radioadaptive Cytoprotective Pathways in the Mouse Retina

Exposure to cosmic radiation implies a risk of tissue degeneration. Radiation retinopathy is a complication of radiotherapy and exhibits common features with other retinopathies and neuropathies. Exposure to a low radiation dose elicits protective cellular events (radioadaptive response), reducing the stress of a subsequent higher dose. To assess the risk of radiation-induced retinal changes and the extent to which a small priming dose reduces this risk, we used a mouse model exposed to a source of Cs-137-gamma radiation. Gene expression profiling of retinas from non-irradiated control C57BL/6J mice (C) were compared to retinas from mice treated with a low 50 mGy dose (LD), a high 6 Gy dose (HD), and a combined treatment of 50 mGy (priming) and 6 Gy (challenge) doses (LHD). Whole retina RNA was isolated and expression analysis for selected genes performed by RTqPCR. Relevant target genes associated with cell death/survival, oxidative stress, cellular stress response and inflammation pathways, were analyzed. Cellular stress response genes were upregulated at 4 hr after the challenge dose in LHD retinas (Sirt1: 1.5 fold, Hsf1: 1.7 fold, Hspa1a: 2.5 fold; Hif1a: 1.8 fold, Bag1: 1.7). A similar trend was observed in LD animals. Most antioxidant enzymes (Hmox1, Sod2, Prdx1, Cygb, Cat1) and inflammatory mediators (NF B, Ptgs2 and Tgfb1) were upregulated in LHD and LD retinas. Expression of the pro-survival gene Bcl2 was upregulated in LD (6-fold) and LHD (4-fold) retinas. In conclusion, cytoprotective gene networks activation in the retina suggests a radioadaptive response to a priming irradiation dose, with mitigation of the deleterious effects of a subsequent high dose exposure. The enhancement of these cytoprotective mechanisms has potential value as a countermeasure to ocular alterations caused by radiation alone or in combination with other factors in spaceflight environments.

Zanello, Susana B.↗
NASA NTRS2012

Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data

This technique enhances the detection capability of the autonomous Real-Nose system from MIT to detect odorants and their concentrations in noisy and transient environments. The lowcost, portable system with low power consumption will operate at high speed and is suited for unmanned and remotely operated long-life applications. A deterministic mathematical model was developed to detect odorants and calculate their concentration in noisy environments. Real data from MIT's NanoNose was examined, from which a signal conditioning technique was proposed to enable robust odorant detection for the RealNose system. Its sensitivity can reach to sub-part-per-billion (sub-ppb). A Space Invariant Independent Component Analysis (SPICA) algorithm was developed to deal with non-linear mixing that is an over-complete case, and it is used as a preprocessing step to recover the original odorant sources for detection. This approach, combined with the Cascade Error Projection (CEP) Neural Network algorithm, was used to perform odorant identification. Signal conditioning is used to identify potential processing windows to enable robust detection for autonomous systems. So far, the software has been developed and evaluated with current data sets provided by the MIT team. However, continuous data streams are made available where even the occurrence of a new odorant is unannounced and needs to be noticed by the system autonomously before its unambiguous detection. The challenge for the software is to be able to separate the potential valid signal from the odorant and from the noisy transition region when the odorant is just introduced.

Duong, Tuan A.↗
NASA NTRS2021

Aerosol and Cloud Detection Using Machine Learning Algorithms and Space-Based Lidar Data

Clouds and aerosols play a significant role in determining the overall atmospheric radiation budget, yet remain a key uncertainty in understanding and predicting the future climate system. In addition to their impact on the Earth’s climate system, aerosols from volcanic eruptions, wildfires, man-made pollution events and dust storms are hazardous to aviation safety and human health. Space-based lidar systems provide critical information about the vertical distributions of clouds and aerosols that greatly improve our understanding of the climate system. However, daytime data from backscatter lidars, such as the Cloud-Aerosol Transport System (CATS) on the International Space Station (ISS), must be averaged during science processing at the expense of spatial resolution to obtain sufficient signal-to-noise ratio (SNR) for accurately detecting atmospheric features. For example, 50% of all atmospheric features reported in daytime operational CATS data products require averaging to 60 km for detection. Furthermore, the single-wavelength nature of the CATS primary operation mode makes accurately typing these features challenging in complex scenes. This paper presents machine learning (ML) techniques that, when applied to CATS data, (1) increased the 1064 nm SNR by 75%, (2) increased the number of layers detected (any resolution) by 30%, and (3) enabled detection of 40% more atmospheric features during daytime operations at a horizontal resolution of 5 km compared to the 60 km horizontal resolution often required for daytime CATS operational data products. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime.

lidar↗
NASA NTRS2011

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykhian, Gholam Ali↗
NASA NTRS2011

Improve Data Mining and Knowledge Discovery through the use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykahian, Gholan Ali↗
NASA NTRS1992

Dome cities for extreme environments

Extreme environments whether they be the frigid nights of the polar regions, the burning sands of the desert, or the harsh environment of space pose interesting challenges to the architect, the engineer, and the constructor in their efforts to create habitats for mankind. In space, the goals are to provide radiation protection while also providing an aesthetic living environment for long duration missions. Because of the need to provide both radiation protection and options for expansion of base facilities, a unique structural system which separates the radiation protection systems from the pressure envelope of the habitats was created. The system uses cable networks in a tensioned structural system, which supports the lunar regolith used for shielding above the facilities. The system is modular, easily expandable, and simple to construct. Additional innovations include the use of rock melting perpetrators for piles and anchoring deadmen, and various sized craters to provide side shielding. The reflective properties of the fabric used in the membrane are utilized to provide diffuse illumination. The use of craters along with the suspended shielding allows the dome to be utilized in fashions similar to those proposed by various designers unaware of the Moon's hostile radiation environment. Additional topics addressed deal with construction techniques for large domes, i.e., on the order of 100's to 1000's of meters, thermal control, the integration of tertiary water treatment schemes with architectural design, human factors, and its implications for the design of habitats for long term use in extreme environments.

Leonard, Raymond S.↗
NASA NTRS1999

El Nino and the Global Ocean Observing System

Until a decade ago, an often-quoted expression in oceanography is that very few observations are recorded throughout the ocean. Now, the sentiment is no longer valid in the uppermost 10% of the tropical Pacific Ocean nor at the surface of the global ocean. One of the remarkable legacies of the 1985-1994 Tropical Oceans Global Atmosphere (TOGA) Program is an in situ marine meteorological and upper oceanographic measurement array throughout the equatorial Pacific to monitor the development and maintenance of El Nino episodes. The TOGA Observing System, which initially consisted of moored- and drifting-buoy arrays, a network of commercial ships, and coastal and island stations, now includes a constellation of satellites and data-assimilating models to simulate subsurface oceanographic conditions. The El Nino and La Nina tropical Pacific Ocean observing system represents the initial phase of an integrated global ocean observing system. Remarkable improvements have been made in ocean model simulation of subsurface currents, but some problems persist. For example, the simulation of the South Equatorial Current (SEC) remains an important challenge in the 2S-2N Pacific equatorial wave guide. During El Nino the SEC at the equator is reduced and sometimes the direction is reversed, becoming eastward. Both conditions allow warm water stored in the western Pacific to invade the eastern region, creating an El Nino episode. Assimilation of data is a tenet of faith to correct simulation errors caused by deficiencies in surface fluxes (especially wind stress) and parameterizations of subgrid-scale physical processes. In the first of two numerical experiments, the Pacific SEC was simulated with and without assimilation of subsurface temperature data. Along the equator, a very weak SEC occurred throughout the eastern Pacific, independent of assimilation of data. However, as displayed in the diagram, in the western Pacific there was no satisfactory agreement between the two simulations. To help determine reliability of the simulated SEC in the western Pacific, current measurements recorded during the 9-19 October 1994 voyage of the French research vessel L'Atalante are also shown in the diagram. With data assimilation, the simulated SEC was in much better agreement with L'Atalante observations. The simulated SEC with data assimilation was far from perfect, in part because of the sparsity of subsurface temperature observations. In the next experiment, TOPEX/POSEIDON sea surface height data in combination with subsurface temperatures will be assimilated to assess further improvement of the simulation of the SEC.

Halpern, David↗
NASA NTRS2019

Building a Knowledge Graph for the Air Traffic Management Community

Historically, most of the focus in the knowledge graph community has been on the support for web, social network, or product search applications. This paper describes some of our experience in developing a large-scale applied knowledge graph for a more technical audience with more specialized information access and analysis needs - the air traffic management community. We describe ATMGRAPH (NASA's Air Traffic Management (ATM) Knowledge Graph), a knowledge graph created by integrating various sources of structured aviation data, provided in large part by US federal agencies. We review some of the practical challenges we faced in creating this knowledge graph.

Air Traffic Information Management↗
NASA NTRS1989

The role of the host in a cooperating mainframe and workstation environment, volumes 1 and 2

In recent years, advancements made in computer systems have prompted a move from centralized computing based on timesharing a large mainframe computer to distributed computing based on a connected set of engineering workstations. A major factor in this advancement is the increased performance and lower cost of engineering workstations. The shift to distributed computing from centralized computing has led to challenges associated with the residency of application programs within the system. In a combined system of multiple engineering workstations attached to a mainframe host, the question arises as to how does a system designer assign applications between the larger mainframe host and the smaller, yet powerful, workstation. The concepts related to real time data processing are analyzed and systems are displayed which use a host mainframe and a number of engineering workstations interconnected by a local area network. In most cases, distributed systems can be classified as having a single function or multiple functions and as executing programs in real time or nonreal time. In a system of multiple computers, the degree of autonomy of the computers is important; a system with one master control computer generally differs in reliability, performance, and complexity from a system in which all computers share the control. This research is concerned with generating general criteria principles for software residency decisions (host or workstation) for a diverse yet coupled group of users (the clustered workstations) which may need the use of a shared resource (the mainframe) to perform their functions.

Kusmanoff, Antone↗
NASA NTRS2011

Telemedicine in Space Flight - Summary of a NASA Workshop

The Exploration Medical Capability Element of the Human Research Program at NASA Johnson Space Center hosted the Telemedicine Workshop in January 2011 to discuss the medical operational concept for a crewed mission to a near-Earth asteroid (NEA) and to identify areas for future work and collaboration. With the increased likelihood of a medical incident on a long duration exploration mission to a near-Earth asteroid, as well as the fact that there will likely be limited medical capabilities and resources available to diagnose and treat medical conditions, it is anticipated that a more structured use of telemedicine will become highly desirable. The workshop was convened to solicit expert opinion on current telemedicine practices and on medical care in remote environments. Workshop Objectives: The workshop brought together leaders in telemedicine and remote medicine from The University of Texas Medical Branch, Henry Ford Hospital, Ontario Telemedicine Network, U.S. Army Institute of Surgical Research, University of Miami, American Telemedicine Association, Doctors Without Borders, and the Pan American Health Organization. The primary objectives of the workshop were to document the medical operations concept for a crewed mission to a NEA, to determine gaps between current capabilities and the capabilities outlined in the operations concept, to identify research required to close these gaps, and to discuss potential collaborations with external-to-NASA organizations with similar challenges. Summary of Discussions and Conclusions: The discussions held during the workshop and the conclusions reached by the workshop participants were grouped into seven categories: Crew Medical Officers, Patient Area in Spacecraft, Training, Electronic Medical Records, Intelligent Care Systems, Consultation Protocols, Prophylactic Surgical Procedures, and Data Prioritization. The key points discussed under each category will be presented.

Barsten, K. N.↗
NASA NTRS2016

GPS and Galileo Developments on Board the International Space Station With the Space Communications and Navigation (SCaN) Testbed

The Space Communications and Navigation (SCaN) is a facility developed by NASA and hosted on board the International Space Station (ISS) on an external truss since 2013.It has the objective of testing navigation and communication experimentations with a Software Defined Radio (SDR) approach, which permits software updates for testing new experimentations.NASA has developed the Space Telecommunications Radio System (STRS) architecture standard for SDRs used in space and ground-based platforms to provide commonality among radio developments to provide enhanced capability. The hardware is equipped with both L band front-end radios and the NASA space network communicates with it using S-band, Ku-band and Ka-band links.In May 2016 Qascom started GARISS (GPS and Galileo Receiver for the ISS), an activity of experimentation in collaboration with ESA and NASA that has the objective to develop and validate the acquisition and processing of combined GPS and Galileo signals on board the ISS SCaN testbed. This paper has the objective to present the mission, and provide preliminary details about the challenges in the design, development and verification of the waveform that will be installed on equipment with limited resources. GARISS is also the first attempt to develop a waveform for the ISS as part of an international collaboration between US and Europe. Although the final mission objective is to target dual frequency processing, initial operations will foresee a single frequency processing. Initial results and trade-off between the two options, as well as the final decision will be presented and discussed. The limited resources on board the SCaN with respect to the challenging requirements to acquire and track contemporaneously two satellite navigation systems, with different modulations and data structure, led to the need to assess the possibility of aiding from ground through the S-band. This option would allow assistance to the space receiver in order to provide knowledge of GNSS orbits and reduce the processing on board. Trade off and various options for telemetry and uplink data are presented and discussed. Finally, integration and validation of the waveform are one of the major challenges of GARISS: The Experiment Development System (EDS) and the the Ground Integration Unit (GIU) for VV will be used prior to conducting the experiment on the ISS. The EDS can be used in lab environment and allows prototyping and verification activities with the simulator, but does not include all hardware components. The GIU on the other side is the flight model which replicates the flying equipment, but has limited flexibility for testing.As conclusion, the project is now approaching the Preliminary Design Review (PDR) and indeed only preliminary results are available. This paper is an opportunity to present the GARISS mission as part of an International cooperation between ESA, NASA and Qascom. The preliminary results include GPS and Galileo processing from space signals, the challenges and trade off decisions, the high level STRS architecture and foreseen experimentation campaign. Detailed results from the test campaigns are expected in 2017.

space navigation↗
NASA NTRS2022

Embedding Climate Change in Urban Planning and Urban Design in New York City

Confronting the challenges of a rapidly urbanizing world threatened by climate change requires expanding the traditional influence and capabilities of urban planning and urban design, integrating climate science, natural systems and compact urban form to configure dynamic, desirable and healthy communities. Cost-effective planning and design measures that help mitigate emissions while bringing adaptive benefits should be prioritized. The chapter draws from the publication Climate Change and Cities (Cambridge University Press 2018) by the Urban Climate Change Research Network (UCCRN). The two-phase New York City case study by the Urban Design Climate Lab at the New York Institute of Technology and a team of international urban design climate experts illustrates how this emerging expertise can be replicated and implemented worldwide. Its focus on configuring people-centered public spaces that enhance energy efficiency and improve public health draws from four urban climate factors: improving efficiency of urban systems, both in energy and transportation; optimizing the form and layout of urban districts to enhance ventilation; promoting appropriate building materials with high reflectivity; and increasing green and blue urban infrastructure. The chapter highlights a set of tools and methods to measure success.

Resiliency↗
NASA NTRS2008

Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

Hong, Yang↗
NASA NTRS2008

Forecasting Cool Season Daily Peak Winds at Kennedy Space Center and Cape Canaveral Air Force Station

The expected peak wind speed for the day is an important element in the daily 24-Hour and Weekly Planning Forecasts issued by the 45th Weather Squadron (45 WS) for planning operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The morning outlook for peak speeds also begins the warning decision process for gusts ^ 35 kt, ^ 50 kt, and ^ 60 kt from the surface to 300 ft. The 45 WS forecasters have indicated that peak wind speeds are a challenging parameter to forecast during the cool season (October-April). The 45 WS requested that the Applied Meteorology Unit (AMU) develop a tool to help them forecast the speed and timing of the daily peak and average wind, from the surface to 300 ft on KSC/CCAFS during the cool season. The tool must only use data available by 1200 UTC to support the issue time of the Planning Forecasts. Based on observations from the KSC/CCAFS wind tower network, surface observations from the Shuttle Landing Facility (SLF), and CCAFS upper-air soundings from the cool season months of October 2002 to February 2007, the AMU created multiple linear regression equations to predict the timing and speed of the daily peak wind speed, as well as the background average wind speed. Several possible predictors were evaluated, including persistence, the temperature inversion depth, strength, and wind speed at the top of the inversion, wind gust factor (ratio of peak wind speed to average wind speed), synoptic weather pattern, occurrence of precipitation at the SLF, and strongest wind in the lowest 3000 ft, 4000 ft, or 5000 ft. Six synoptic patterns were identified: 1) surface high near or over FL, 2) surface high north or east of FL, 3) surface high south or west of FL, 4) surface front approaching FL, 5) surface front across central FL, and 6) surface front across south FL. The following six predictors were selected: 1) inversion depth, 2) inversion strength, 3) wind gust factor, 4) synoptic weather pattern, 5) occurrence of precipitation at the SLF, and 6) strongest wind in the lowest 3000 ft. The forecast tool was developed as a graphical user interface with Microsoft Excel to help the forecaster enter the variables, and run the appropriate regression equations. Based on the forecaster's input and regression equations, a forecast of the day's peak and average wind is generated and displayed. The application also outputs the probability that the peak wind speed will be ^ 35 kt, 50 kt, and 60 kt.

Barrett, Joe, III↗
NASA NTRS2012

Science Traverses in the Canadian High Arctic

The presentation is divided into three parts. Part I is an overview of early expeditions to the High Arctic, and their political consequences at the time. The focus then shifts to the Geological Survey of Canada s mapping program in the North (Operation Franklin), and to the Polar Continental Shelf Project (PCSP), a unique organization that resides within the Government of Canada s Department of Natural Resources, and supports mapping projects and science investigations. PCSP is highlighted throughout the presentation so a description of mandate, budgets, and support infrastructure is warranted. In Part II, the presenter describes the planning required in advance of scientific deployments carried out in the Canadian High Arctic from the perspective of government and university investigators. Field operations and challenges encountered while leading arctic field teams in fly camps are also described in this part of the presentation, with particular emphasis on the 2008 field season. Part III is a summary of preliminary results obtained from a Polar Survey questionnaire sent out to members of the Arctic research community in anticipation of the workshop. The last part of the talk is an update on the analog program at the Canadian Space Agency, specifically, the Canadian Analog Research Network (CARN) and current activities related to Analog missions, 2009-2010.

Williamson, Marie-Claude↗